20210129Morehouse Exhibit 14 Schedules 1.pdf

DAVID J. MEYER
VICE PRESIDENT AND CHIEF COUNSEL FOR
REGULATORY & GOVERNMENTAL AFFAIRS
AVISTA CORPORATION
P.O. BOX 3727
1411 EAST MISSION AVENUE
SPOKANE, WASHINGTON 99220-3727
TELEPHONE: [phone]
FACSIMILE: [phone]
[e-mail]

BEFORE THE IDAHO PUBLIC UTILITIES COMMISSION

IN THE MATTER OF THE APPLICATION ) CASE NO. AVU-G-21-01
OF AVISTA CORPORATION FOR THE )
AUTHORITY TO INCREASE ITS RATES )
AND CHARGES FOR ELECTRIC AND )
NATURAL GAS SERVICE TO ELECTRIC ) Exhibit No. 14
AND NATURAL GAS CUSTOMERS IN THE )
STATE OF IDAHO ) JODY MOREHOUSE
)

FOR AVISTA CORPORATION

(NATURAL GAS ONLY)

DAVID J. MEYER
VICE PRESIDENT AND CHIEF COUNSEL FOR
REGULATORY & GOVERNMENTAL AFFAIRS
AVISTA CORPORATION
P.O. BOX 3727
1411 EAST MISSION AVENUE
SPOKANE, WASHINGTON 99220-3727
TELEPHONE: [phone]
FACSIMILE: [phone]
[e-mail]

BEFORE THE IDAHO PUBLIC UTILITIES COMMISSION

IN THE MATTER OF THE APPLICATION ) CASE NO. AVU-G-21-01
OF AVISTA CORPORATION FOR THE )
AUTHORITY TO INCREASE ITS RATES )
AND CHARGES FOR ELECTRIC AND )
NATURAL GAS SERVICE TO ELECTRIC ) Exhibit No. 14
AND NATURAL GAS CUSTOMERS IN THE )
STATE OF IDAHO ) JODY MOREHOUSE
)

FOR AVISTA CORPORATION

(NATURAL GAS ONLY)

2018
Natural Gas
Integrated Resource Plan
August 31, 2018
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 1 of 190

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 2 of 190
Safe Harbor Statement

This document contains forward-looking statements. Such statements are subject to a
variety of risks, uncertainties and other factors, most of which are beyond the Company’s
control, and many of which could have a significant impact on the Company’s operations,
results of operations and financial condition, and could cause actual results to differ
materially from those anticipated.
For a further discussion of these factors and other important factors, please refer to the
Company’s reports filed with the Securities and Exchange Commission. The forward-
looking statements contained in this document speak only as of the date hereof. The
Company undertakes no obligation to update any forward-looking statement or statements to reflect events or circumstances that occur after the date on which such
statement is made or to reflect the occurrence of unanticipated events. New risks,
uncertainties and other factors emerge from time to time, and it is not possible for
management to predict all of such factors, nor can it assess the impact of each such factor
on the Company’s business or the extent to which any such factor, or combination of factors, may cause actual results to differ materially from those contained in any forward-
looking statement.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 3 of 190

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 4 of 190
TABLE OF CONTENTS
0 Executive Summary………………………………………………..Page 1
1 Introduction………………………………………………………….Page 15
2 Demand Forecasts…………………………………………………Page 27
3 Demand Side Resources………………………………………….Page 47
4 Supply Side Resources……………………………………………Page 87
5 Policy Considerations……………………………………………...Page 113
6 Integrated Resource Portfolio…………………………………….Page 121
7 Alternate Scenarios, Portfolios, and Stochastic Analysis……..Page 151
8 Distribution Planning………………………………………………Page 169
9 Action Plan…………………………………………………………Page 179

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 5 of 190
Executive Summary
Avista’s 2018 Natural Gas Integrated Resource
Plan (IRP) identifies a strategic natural gas
resource portfolio to meet customer demand
requirements over the next 20 years. While the
primary focus of the IRP is meeting customers’
needs under peak weather conditions, this process
also evaluates customer needs under normal or
average conditions. The formal exercise of
bringing together customer demand forecasts with
comprehensive analyses of resource options,
including supply-side resources and demand-side
measures, is valuable to Avista, its customers,
regulatory agencies, and other stakeholders for
long-range planning.
IRP Process and Stakeholder
Involvement
The IRP is a coordinated effort by several Avista departments with input from our
Technical Advisory Committee (TAC), which includes Commission Staff, peer utilities,
customers, and other stakeholders. The TAC is a vital component of our IRP process that
provides a forum for discussing multiple perspectives, identifies issues and risks, and
improves analytical planning methods. TAC topics include natural gas demand forecasts,
price forecasts, demand-side management (DSM), supply-side resources, modeling
tools, distribution planning, and policy issues. The IRP process produces a resource
portfolio designed to serve our customers’ natural gas needs while balancing cost and
risk.
Planning Environment
A long-term resource plan addresses the uncertainties inherent in any planning exercise.
Natural gas is an abundant North American resource with expectations for sufficient
supplies for many decades because of continuing technological advancements in
extraction. The use of natural gas in liquefied natural gas (LNG) exports, natural gas
vehicles, power generation and exports to Mexico will add demand for natural gas. We
model various sensitivities and scenarios to account for the uncertainties surrounding
supply and demand.
Chapter
Highlights
•An increase in customer
forecast over 20 years
versus the 2016 IRP
•Lower use per customer
•Higher DSM potential
•RNG and Hydrogen
considered in the
available resource stack
for the first time
•Landfill RNG is a chosen
resource in the High
Growth & Low Prices
scenario
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Demand Forecasts
Avista defines eleven distinct demand areas in this IRP structured around the pipeline
transportation and storage resources that serve them. Demand areas include Avista’s
service territories (Washington; Idaho; Medford/Roseburg, Oregon; Klamath Falls,
Oregon and La Grande, Oregon) and then disaggregated by the pipelines serving them.
The Washington and Idaho service territories include areas served only by Northwest
Pipeline (NWP), only by Gas Transmission Northwest (GTN), and by both pipelines. The
Medford service territory includes an area served by NWP and GTN.
Weather, customer growth and use-per-customer are the most significant demand
influencing factors. Other demand influencing factors include population, employment,
age and income demographics, construction levels, conservation technology, new uses
(e.g. natural gas vehicles), and use-per-customer trends.
Customers may adjust consumption in response to price, so Avista analyzed factors that
could influence natural gas prices and demand through price elasticity. These factors
include:
•Supply: shale gas, industrial use, and exports to Mexico and of LNG.
•Infrastructure: regional pipeline projects, national pipeline projects, and
storage.
•Regulatory: subsidies, market transparency/speculation, and carbon
regulation.
•Other: drilling innovations, thermal generation and energy correlations (i.e.
oil/gas, coal/gas, and liquids/gas).
Avista developed a historical-based reference case and conducted sensitivity analysis on
key demand drivers by varying assumptions to understand how demand changes. Using
this information, and incorporating input from the TAC, Avista created alternate demand
scenarios for detailed analysis. Table 1 summarizes these demand scenarios, which
represent a broad range of potential scenarios for planning purposes. The Average Case
represents Avista’s demand forecast for normal planning purposes. The Expected Case
is the most likely scenario for peak day planning purposes.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Table 1: Demand Scenarios
2018 IRP Demand Scenarios
The IRP process defines the methodology for the development of two primary types of
demand forecasts – annual average daily and peak day. The annual average daily
demand forecast is useful for preparing revenue budgets, developing natural gas
procurement plans, and preparing purchased gas adjustment filings. Forecasts of peak
day demand are critical for determining the adequacy of existing resources or the timing
for new resource acquisitions to meet our customers’ natural gas needs in extreme
weather conditions. Table 2 shows the Average and Expected Case demand forecasts:
Table 2: Annual Average and Peak Day Demand Cases (Dth/day)
Year Annual Average Daily
Demand
Peak Day Demand Non-coincidental
Peak Day Demand
Annual Average Daily Demand – Expected average day, system-wide core demand
increases from an average of 93,900 dekatherms per day (Dth/day) in 2018 to 94,205
Dth/day in 2037. This is an annual average growth rate of 0.02 percent and is net of
projected conservation savings from DSM programs. Appendix 3.1 shows gross demand,
conservation savings and net demand.
Peak Day Demand – The peak day demand for the Washington, Idaho and La Grande
service territories is modeled on and around February 15 of each year. For the
southwestern Oregon service territories (Medford, Roseburg, Klamath Falls), the model
assumes this event on and around December 20 each year. Expected coincidental peak
day, or the sum of demand from each territories modeled peak, the system-wide core
demand increases from a peak of 377,206 Dth/day in 2018 to 427,852 Dth/day in 2037.
Forecasted non-coincidental peak day demand, or the sum of demand from the highest
single day including all forecasted territories, peaks at 347,228 Dth/day in 2018 and
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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increases to 392,601 Dth/day in 2037, a 0.71 percent average annual growth rate in peak
day requirements. This is also net of projected conservation savings from DSM programs.
Figure 1 shows forecasted average daily demand for the six demand scenarios modeled
over the IRP planning horizon.
Figure 1: Average Daily Demand (Net of DSM Savings)
Figure 2 shows forecasted system-wide peak day demand for the six demand scenarios
modeled over the IRP planning horizon.
40
50
60
70
80
90
100
110
120MDth/d
Expected Case 80 % Below 1990 Emissions High Growth & Low Prices
Low Growth & High Prices Cold Day 20yr Weather Std Average Case
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 9 of 190
Figure 2: Peak Day Demand Scenarios (Net of DSM Savings)
Natural Gas Price Forecasts
Natural gas prices are a fundamental component of integrated resource planning as the
commodity price is a significant element to the total cost of a resource option. Price
forecasts affect the avoided cost threshold for determining cost-effectiveness of
conservation measures. The price of natural gas also influences the consumption of
natural gas by customers. A price elasticity adjustment to use-per-customer reflects
customer responses to changing natural gas prices.
As more information surfaces about the costs and volumes produced by shale gas there
appears to be market consensus that production costs will remain low for quite some time.
Avista expects continued low prices even with increased incremental demand for LNG,
exports to Mexico, transportation fuels, and increased industrial consumption.
Avista expects carbon legislation at the state level through a cap and trade (Oregon) or a
tax mechanism (Washington). Current IRP price forecasts include a considerably higher
carbon adder in Oregon and Washington, but no carbon cost in Idaho. Avista analyzed
100
150
200
250
300
350
400
450MDth/d
Expected Case 80 % Below 1990 Emissions High Growth & Low Prices
Low Growth & High Prices Cold Day 20yr Weather Std Average Case
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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three carbon sensitivities and their impact on demand forecasts to address the uncertainty
about carbon legislation.
Avista combined forward prices with two fundamental price forecasts from credible
industry sources for an expected price strip at the Henry Hub. A high and low price were
developed to vary the price in a symmetrical fashion based off of the expected price curve.
These three price curves represent a reasonable range of pricing possibilities for this IRP
analysis. The array of prices provides necessary variation for addressing uncertainty of
future prices. Figure 3 depicts the price forecasts used in this IRP.
Figure 3: Low/Medium/High Henry Hub Forecasts (Nominal $/Dth)
Historical statistical analysis shows a long run consumption response to price changes.
In order to model consumption response to these price curves, Avista utilized an expected
elasticity response factor of -0.10, for every 10% of price movement, as found in our
Medford/Roseburg service territory, and applied it under various scenarios and
sensitivities.
Existing and Potential Resources
Avista has a diversified portfolio of natural gas supply resources, including access to and
contracts for the purchase of natural gas from several supply basins; owned and
$- $1.00 $2.00 $3.00 $4.00 $5.00 $6.00 $7.00 $8.00 $9.00 $10.00 $11.00 $12.00
$- $1.00 $2.00 $3.00 $4.00 $5.00 $6.00 $7.00 $8.00 $9.00 $10.00 $11.00 $12.00
$
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D
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High Price Low Price Expected Price
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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contracted storage providing supply source flexibility; and firm capacity rights on six
pipelines. For potential resource additions, Avista considers incremental pipeline
transportation, storage options, distribution enhancements, and various forms of LNG
storage or service. Beginning in Avista’s 2020 IRP and all future planning documents and
analysis thereafter, Avista intends to include conservation as a potential resource
addition.
Avista models aggregated conservation potential that reduces demand if the conservation
programs are cost-effective over the planning horizon. The identification and
incorporation of conservation savings into the SENDOUT® model utilizes projected
natural gas prices and the estimated cost of alternative supply resources. The operational
business planning process starts with IRP identified savings and ultimately determines
the near-term program offerings. Avista actively promotes cost-effective DSM measures
to our customers as one component of a comprehensive strategy to arrive at a mix of best
cost/risk adjusted resources.
Resource NeedsIn all cases, except for the High Growth and Low price scenario, the analysis showed no
resource deficiencies in the 20-year planning horizon given Avista’s existing supply
resources. Avista is not resource deficient in the Expected Case in the 20-year planning
horizon.
Figures 5 through 8 illustrate Avista’s peak day demand by service territory for both this
and the prior IRP. These charts compare existing peak day resources to expected peak
day demand by year and show the timing and extent of resource deficiencies, if any, for
the Expected Case. Based on this information, and more specifically where a resource
deficiency is nearly present as shown in Figure 6 & 8, Avista has time to carefully monitor,
plan and take action on potential resource additions as described in the Ongoing Activities
section of Chapter 9 – Action Plan. Any underutilized resources will be optimized to
mitigate the costs incurred by customers until the resource is required to meet demand.
This management of long- and short-term resources provides the flexibility to meet firm
customer demand in a reliable and cost-effective manner as described in Supply Side
Resources – Chapter 4.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Figure 5: Expected Case – WA & ID Existing Resources vs. Peak Day Demand (Net of DSM)
Figure 6: Expected Case – Medford/Roseburg Existing Resources vs. Peak Day Demand
(Net of DSM)
0
50,000
100,000
150,000
200,000
250,000
300,000
350,000
400,000
Dth
Existing GTN Existing NWP JP TF-2
Spokane Supply Peak Day Demand Prior IRP Peak Day Demand
0
20,000
40,000
60,000
80,000
100,000
120,000
Dth
Existing GTN Existing NWP JP TF-2 Peak Day Demand Prior IRP Peak Day Demand
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Figure 7: Expected Case – Klamath Falls Existing Resources vs. Peak Day Demand (Net of DSM)
Figure 8: Expected Case – La Grande Existing Resources vs. Peak Day Demand (Net of DSM)
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
18,000
20,000
22,000
Dth
Klamath Lateral Peak Day Demand Prior IRP Peak Day Demand
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
10,000Dth
Existing NWP JP TF-2 Peak Day Demand Prior IRP Peak Day Demand
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 14 of 190
A critical risk remains in the slope of forecasted demand growth, which although
increasing continues to be almost flat in Avista’s current projections. This outlook implies
that existing resources will be sufficient within the planning horizon to meet demand.
However, if demand growth accelerates, the steeper demand curve could quickly
accelerate resource shortages by several years. Figure 9 conceptually illustrates this risk.
In this hypothetical example, a resource shortage does not occur until year eight in the
initial demand case. However, the shortage accelerates by five years under the revised
demand case to year three. This “flat demand risk” requires close monitoring of
accelerating demand, as well as careful evaluation of lead times to acquire the preferred
incremental resource.
Figure 9: Hypothetical Flat Demand Risk Example
Alternate Demand Scenarios
Avista performed the same analysis for five other demand scenarios: Average, High
Growth/Low Price, 80 Percent Below 1990 Emissions, Low Growth/High Price, and
Coldest in 20 Years. As expected, the High Growth/Low Price scenario has the most rapid
growth and is the only scenario with unserved demand. This “steeper” demand lessens
the “flat demand risk” discussed above, yet resource deficiencies occur late in the
planning horizon. Figure 10 shows first year resource deficiencies under each scenario.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Figure 10: Scenario Comparisons of First Year Peak Demand Not Met with Existing Resources
Issues and Challenges
Even with the planning, analysis, and conclusions reached in this IRP, there is still
uncertainty requiring diligent monitoring of the following issues.
Demand Issues
Although the future customer growth trajectory in Avista’s service territory has slightly
increased compared to the 2016 IRP, the need in considering a range of demand
scenarios provides insight into how quickly resource needs can change if demand varies
from the Expected Case.
With a rise in natural gas supply and subsequent low costs, there is increasing interest in
using natural gas. Avista does not anticipate traditional residential and commercial
customers will provide increased growth in demand. Power generation from natural gas
is increasingly being used to back up solar and wind technology as well as replacing
retired coal plants. Exports of LNG and to Mexico currently have a demand of over 7
Bcf/day. With additional LNG plants forecasted to come online in the next few years
combined with additional pipeline infrastructure build into Mexico increases demand from
these areas to nearly 13.5 Bcf. There is already a higher demand for exports to Mexico
and more LNG plants have come online and are now looking for 4 Bcf per day on average.
20182019202020212022202320242025202620272028202920302031203220332034203520362037
WA/ID Medford/Roseburg Klamath La Grande
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Expected Case 80 % Below 1990 Emissions High Growth & Low PricesLow Growth & High Prices Cold Day 20yr Weather Std Average Case
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 16 of 190
Most of these emerging markets will not be core customers of the LDC, but could affect
regional natural gas infrastructure and natural gas pricing if an LNG export facility is built
in the area.
Price Issues
Shale oil and gas drilling technology is adding an abundant amount of supply at low cost.
This is primarily due to increasingly efficient drilling technology and the rapid
advancement in understanding of drilling shale wells. In areas such as the eastern United
States, shale production is so prolific the entire flow of gas on the pipeline infrastructure
has changed and is now flowing out of the highest demand areas in the US. This supply
also flows into Canada and across the U.S. In western Canada there are some large and
very capital intensive oil sands projects where production will continue regardless of the
price of natural gas. In the past, this natural gas would commonly find its home in the U.S.
Canadian natural gas has become somewhat stranded within the western half of North
America and is creating a very low price environment. This new paradigm, benefits
Northwest consumers as the prices for Canadian gas have deep discounts as compared
to the Henry Hub.
LNG Exports
Liquefied natural gas is a process of chilling natural gas to -260 degrees Fahrenheit to
create a condensed version, 1/600 the volume, of natural gas. This process acts as a
virtual pipeline taking domestic production to nearly any location in the world. For years
the U.S. was expected to be an importer of LNG. This is a stark contrast to reality as in
2017 the export of LNG from the U.S. has quadrupled led by two projects, Sabine Pass
in Louisiana and Cove Point in Maryland. In recent history, this market dynamic has
changed from fixed price gas contracts to more spot purchases of LNG. The three largest
countries for U.S. LNG exports are Mexico, South Korea and China. Waiting in the wings
to provide more LNG supply are four additional export facilities located mostly in the gulf
coast region of the U.S. and will bring the total export capacity to nearly 10 Bcf per day
by 2019. In 2020, the U.S. is expected to become the third largest exporter of LNG in the
world. Canadian LNG is on a slower construction pace, but has a new ray of light in the
LNG Canada project. Though as a whole and when compared to the U.S., environmental
concerns and policies are having a larger impact on investment decisions in these
projects. If and when LNG plants are constructed, exporting LNG can alter the price,
constrain existing pipeline networks, stimulate development of new pipeline resources,
and change flows of natural gas across North America.
Action Plan Avista’s 2019-2020 Action Plan outlines activities for study, development and preparation
for the 2020 IRP. The purpose of the Action Plan is to position Avista to provide the best
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 17 of 190
cost/risk resource portfolio and to support and improve IRP planning. The Action Plan
identifies needed supply and demand side resources and highlights key analytical needs
in the near term. It also highlights essential ongoing planning initiatives and natural gas
industry trends Avista will monitor as a part of its ongoing planning processes (Chapter 9
– Action Plan).

Key ongoing components of the Action Plan include:
1. Avista’s 2020 IRP will contain an individual measure level for dynamic DSM
program structure in its analytics. In prior IRP’s, it was a deterministic method
based on based on Expected Case assumptions. In the 2020 IRP, each portfolio
will have the ability to select conservation to meet unserved customer demand.
Avista will explore methods to enable a dynamic analytical process for the
evaluation of conservation potential within individual portfolios.
2. Work with Staff to get clarification on types of natural gas distribution system
analyses for possible inclusion in the 2020 IRP.
3. Work with Staff to clarify types of distribution system costs for possible inclusion in
our avoided cost calculation.
4. Revisit coldest on record planning standard and discuss with TAC for prudency.
5. Provide additional information on resource optimization benefits and analyze risk
exposure
6. DSM—Integration of ETO and AEG/CPA data. Discuss the integration of ETO and
AEG/CPA data as well as past program(s) experience, knowledge of current and
developing markets, and future codes and standards.
7. Carbon Costs – consult Washington State Commission’s Acknowledgement Letter
Attachment in its 2017 Electric IRP (Docket UE-161036), where emissions price
modelling is discussed, including the cost of risk of future greenhouse gas
regulation, in addition to known regulations.
8. Avista will ensure Energy Trust (ETO) has sufficient funding to acquire therm
savings of the amount identified and approved by the Energy Trust Board.
9. Regarding high pressure distribution or city gate station capital work, Avista does
not expect any supply side or distribution resource additions to be needed in our
Oregon territory for the next four years, based on current projections. However,
should conditions warrant that capital work is needed on a high pressure
distribution line or city gate station in order to deliver safe and reliable services to
our customers, the Company is not precluded from doing such work. Examples of
these necessary capital investments include the following:
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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•Natural gas infrastructure investment not included as discrete projects in IRP
–Consistent with the preceding update, these could include system
investment to respond to mandates, safety needs, and/or maintenance
of system associated with reliability
•Including, but not limited to Aldyl A replacement, capacity
reinforcements, cathodic protection, isolated steel replacement,
etc.
–Anticipated PHMSA guidance or rules related to 49 CFR Part §192
that will likely requires additional capital to comply
•Officials from both PHMSA and the AGA have indicated it is not
prudent for operators to wait for the federal rules to become final
before improving their systems to address these expected rules.
–Construction of gas infrastructure associated with growth
–Other special contract projects not known at the time the IRP was
published
•Other non-IRP investments common to all jurisdictions that are ongoing, for
example:
–Enterprise technology projects & programs
–Corporate facilities capital maintenance and improvements
Ongoing Activities
Meet regularly with Commission Staff to provide information on market activities and
significant changes in assumptions and/or status of Avista activities related to the IRP or
natural gas procurement practices.
Appropriate management of existing resources including optimizing underutilized
resources to help reduce costs to customers.
Conclusion
Slightly higher customer growth continues to be offset by lower use-per-customer and an
increased amount of DSM. This has eliminated the need for Avista to acquire additional
supply-side resources, therefore appropriate management of underutilized resources to
reduce costs until resources are needed is essential. The combination of low priced
natural gas in addition to carbon taxes or other programs has led to a higher potential for
DSM measures as compared to the previous three IRP’s. The IRP has many objectives,
but foremost is to ensure that proper planning enables Avista to continue delivering safe,
reliable, and economic natural gas service to our customers.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 19 of 190
1: Introduction
Avista is involved in the production, transmission
and distribution of natural gas and electricity, as
well as other energy-related businesses. Avista,
founded in 1889 as Washington Water Power,
has been providing reliable, efficient and
reasonably priced energy to customers for over
130 years.
Avista entered the natural gas business with the
purchase of Spokane Natural Gas Company in
1958. In 1970, it expanded into natural gas
storage with Washington Natural Gas (now Puget
Sound Energy) and El Paso Natural Gas (its
interest subsequently purchased by NWP) to
develop the Jackson Prairie natural gas
underground storage facility in Chehalis,
Washington. In 1991, Avista added 63,000 customers with the acquisition of CP
National Corporation’s Oregon and California properties. Avista sold the California
properties and its 18,000 South Lake Tahoe customers to Southwest Gas in 2005.
Figure 1.1 shows where Avista currently provides natural gas service to approximately
348,000 customers in eastern Washington, northern Idaho and several communities in
northeast and southwest Oregon. Figure 1.2 shows the number of natural gas
customers by state.
Highlights
•High amount of
uncertainty in long-term
forecasting
•Sensitivities help to
understand risk of
uncertainty
•Seasonal demand
•348,000 natural gas
customers
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 20 of 190
Figure 1.1: Avista’s Natural Gas Service Territory
Figure 1.2: Avista’s Natural Gas Customer Counts
Washington
163,000
Oregon 102,000
Idaho 83,000
Total 348,000
Washington Oregon Idaho
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 21 of 190
Avista’s natural gas operations covers 30,000 square miles in eastern Washington,
northern Idaho and portions of southern and eastern Oregon, with a population of 1.6
million. The company manages its natural gas operation through the North and South
operating divisions:
• The North Division includes Avista’s eastern Washington and northern Idaho
service area which is home to over 800,000 people. It includes urban areas, farms,
timberlands, and the Coeur d’Alene mining district. Spokane is the largest
metropolitan area with a regional population of approximately 490,000 followed
by the Lewiston, Idaho/Clarkston, Washington, and Coeur d’Alene, Idaho, areas.
The North Division has about 75 miles of natural gas transmission pipeline and
5,400 miles in the distribution system. The North Division receives natural gas at
more than 40 points along interstate pipelines for distribution to over 246,000
customers.
• The South Division serves four counties in southern Oregon and one county in
eastern Oregon. The combined population of these areas is over 500,000
residents. The South Division includes urban areas, farms and timberlands. The
Medford, Ashland and Grants Pass areas, located in Jackson and Josephine
Counties, is the largest single area served by Avista in this division with a regional
population of approximately 297,000. The South Division consists of about 15
miles of natural gas transmission main and 2,400 miles of distribution pipelines.
Avista receives natural gas at more than 20 points along interstate pipelines and
distributes it to more than 102,000 customers.

Customers
Avista provides natural gas services to both core and transportation-only customer
classes. Core or retail customers purchase natural gas directly from Avista with delivery
to their home or business under a bundled rate. Core customers on firm rate schedules
are entitled to receive any volume of natural gas they require. Some core customers are
on interruptible rate schedules. These customers pay a lower rate than firm customers
because their service can be interrupted. Interruptible customers are not considered in
peak day IRP planning.
Transportation-only customers purchase natural gas from third parties who deliver the
purchased gas to our distribution system. Avista delivers this natural gas to their
business charging a distribution rate only. Avista can interrupt the delivery service when
following the priority of service tariff. The long-term resource planning exercise excludes
transportation-only customers because they purchase their own natural gas and utilize
their own interstate pipeline transportation contracts. However, distribution planning
includes these customers.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 22 of 190
Avista’s core or retail customers include residential, commercial and industrial
categories. Most of Avista’s customers are residential, followed by commercial and
relatively few industrial accounts (Figure 1.3).
Figure 1.3: Firm Customer Mix
Res
90.23%
Com
9.68%
Ind
0.09%
WA/ID
Customer
Make up
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 23 of 190
The customer mix is more balanced between residential and commercial accounts on
an annual volume basis (Figure 1.4). Volume consumed by core industrial customers is
not significant to the total, partly because most industrial customers in Avista’s service
territories are transportation-only customers.

Figure 1.4 Therms by Class

Oregon
Customer

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 24 of 190
Core customer demand is seasonal, especially residential accounts in Avista’s service
territories with colder winters (Figure 1.5). Industrial demand, which is typically not
weather sensitive, has very little seasonality. However, the La Grande service territory
has several industrially classified agricultural processing facilities that produce a late
summer seasonal demand spike.
Figure 1.5: Customer Demand by Service Territory
Integrated Resource Planning
Avista’s IRP involves a comprehensive analytical process to ensure that core firm
customers receive long-term reliable natural gas service at a reasonable price. The IRP
evaluates, identifies, and plans for the acquisition of an optimal combination of existing
and future resources using expected costs and associated risks to meet average daily
and peak-day demand delivery requirements over a 20-year planning horizon.
Purpose of the IRP
Avista’s 2018 Natural Gas IRP:
•Provides a comprehensive long-range planning tool;
•Fully integrates forecasted requirements with existing and potential resources;
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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•Determines the most cost-effective, risk-adjusted means for meeting future
demand requirements; and
•Meets Washington, Idaho and Oregon regulations, commission orders, and other
applicable guidelines.
Avista’s IRP Process
The natural gas IRP process considers:
•Customer growth and usage;
•Weather planning standard;
•Conservation opportunities;
•Existing and potential supply-side resource options;
•Current and potential legislation/regulation;
•Risk; and
•Least cost mix of supply and conservation.
Public Participation
Avista’s TAC members play a key role and have a significant impact in developing the
IRP. TAC members included Commission Staff, peer utilities, government agencies,
and other interested parties. TAC members provide input on modeling, planning
assumptions, and the general direction of the planning process.
Avista sponsored four TAC meetings to facilitate stakeholder involvement in the 2018
IRP. The first meeting convened on January 25, 2018 and the last meeting occurred on
May 10, 2018. Meetings are at a variety of locations convenient for stakeholders and
are electronically available for those unable to attend in person. Each meeting included
a broad spectrum of stakeholders. The meetings focused on specific planning topics,
reviewing the progress of planning activities, and soliciting input on IRP development
and results. TAC members received a draft of this IRP on July 2, 2018 for their review.
Avista appreciates all of the time and effort TAC members contributed to the IRP
process; they provided valuable input through their participation in the TAC process. A
list of these organizations can be found below (Table 1.1).
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Table 1.1: TAC Member Participation
Cascade Natural Gas Northwest Industrial Gas
Users Commission
Commission Pipeline
Transportation Commission
Preparation of the IRP is a coordinated endeavor by several departments within Avista
with involvement and guidance from management. We are grateful for their efforts and
contributions.

Regulatory Requirements
Avista submits a natural gas IRP to the public utility commissions in Idaho, Oregon and
Washington on or before August 31 every two years as required by state regulation. There
is a statutory obligation to provide reliable natural gas service to customers at rates, terms
and conditions that are fair, just, reasonable and sufficient. Avista regards the IRP as a
means for identifying and evaluating potential resource options and as a process to
establish an Action Plan for resource decisions. Ongoing investigation, analysis and
research may cause Avista to determine that alternative resources are more cost effective
than resources reviewed and selected in this IRP. Avista will continue to review and refine
our understanding of resource options and will act to secure these risk-adjusted, least-
cost options when appropriate.

Planning Model
Consistent with prior IRPs, Avista used the SENDOUT planning model to perform
comprehensive natural gas supply planning and analysis for this IRP. SENDOUT is a
linear programming-based model that is widely used to solve natural gas supply,
storage and transportation optimization problems. This model uses present value
revenue requirement (PVRR) methodology to perform least-cost optimization based on
daily, monthly, seasonal and annual assumptions related to the following:

• Customer growth and customer natural gas usage to form demand forecasts;
• Existing and potential transportation and storage options and associated costs;
• Existing and potential natural gas supply availability and pricing;
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 27 of 190
•Revenue requirements on all new asset additions;
•Weather assumptions; and
•Conservation.
Avista incorporated stochastic modeling by utilizing a SENDOUT module to simulate
weather and price uncertainty. The module generates Monte Carlo weather and price
simulations, running concurrently to account for events and to provide a probability
distribution of results that aid resource decisions. Some examples of the types of
stochastic analysis provided include:
•Price and weather probability distributions;
•Probability distributions of costs (i.e. system costs, storage costs, commodity
costs); and
•Resource mix (optimally sizing a contract or asset level of competing resources).
These computer-based planning tools were used to develop the 20-year best cost/risk
resource portfolio plan to serve customers.
Planning Environment
Even though Avista publishes an IRP every two years, the process is ongoing with new
information and industry related developments. In normal circumstances, the process can
become complex as underlying assumptions evolve, impacting previously completed
analyses. Widespread agreement on the availability of shale gas and the ability to
produce it at lower prices has increased interest in the use of natural gas for LNG and
Mexico exports and industrial uses. One of the most prominent risks in the IRP involves
policies meant to decrease the use of natural gas as outlined in Chapter 5. These policies
are becoming more frequent in Oregon and Washington with of goal of reducing the
amount of direct use natural gas. However, there is uncertainty about the timing and size
of those policy decisions.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 28 of 190
IRP Planning Strategy
Planning for an uncertain future requires robust analysis encompassing a wide range of
possibilities. Avista has determined that the planning approach needs to:
•Recognize historical trends may be fundamentally altered;
•Critically review all modeling assumptions;
•Stress test assumptions via sensitivity analysis;
•Pursue a spectrum of scenarios;
•Develop a flexible analytical framework to accommodate changes; and
•Maintain a long-term perspective.
With these objectives in mind, Avista developed a strategy encompassing all required
planning criteria. This produced an IRP that effectively analyzes risks and resource
options, which sufficiently ensures customers will receive safe and reliable energy
delivery services with the best-risk, lease-cost, long-term solutions. The following chart
summarizes significant changes from the 2016 IRP (Table 1.2).
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Table 1.2: Summary of changes from the 2016 IRP
Expected
Customer Growth –growth is slightly higher at growth is 1.1% compounded
DSM
conservation potential as a
system.
Cumulative Savings over 20
years:
ID: 21.1 Million Therms
OR: 17.2 Million Therms
WA: 41.4 Million Therms
the conservation potential-
downward.
Environmental
Issues
Carbon Dioxide
Emission (Carbon) out by state allowing for
different policy considerations
across jurisdictions.
ID: No federal or State
initiatives ($0)
OR: HB 4001 & SB 1507
($17.86 – $51.58)
WA – SSB 6203 ($10 - $30)
*Prices are in dollars per
MTCO2e
carbon tax ($/ton) were
compared. The expected
case has a probability of 2
sigma of the likely policy.
The remainder of probability
equally assumed to Low and
Washington State’s I-732
were used to represent the
tails in a normal distribution.
The base carbon case is the
expected case. The high and
low cases help bracket the
Prices
slightly higher conservation
potential.
the conservation potential-
downward.
Supply Side
Resources
Supply Side
Scenarios resource deficiency is the High
Growth/Low Price scenario.
Avista solved this case by
using existing resources plus
added contracted capacity on
GTN. Landfill RNG is also
selected as a resource in ,
Idaho. Also selected is the
upsized compressor on the
Medford lateral.
a resource deficiency is the
High Growth/Low Price
scenario. Avista solved this
case by using existing
resources plus added
contracted capacity on GTN
for WA/ID. In Klamath Falls,
Medford and Roseburg an
upsized compressor would
be added on the Medford
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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2: Demand Forecasts
Overview
The integrated resource planning process begins
with the development of forecasted demand.
Understanding and analyzing key demand drivers
and their potential impact on forecasts is vital to the
planning process. Utilization of historical data
provides a reliable baseline, however past trends
may not be indicative of future trends. This IRP
mitigates the uncertainty by considering a range of
scenarios to evaluate and prepare for a broad
spectrum of outcomes.
Demand Areas
Avista defined eleven demand areas, structured
around the pipeline transportation resources that serve them, within the SENDOUT
model (Table 2.1). These demand areas are aggregated into five service territories and
further summarized as North or South divisions for presentation throughout this IRP.
Table 2.1 Geographic Demand Classifications
Demand Area Service Territory Division
Washington NWP Spokane North
Washington GTN Spokane North
Washington Both Spokane North
Idaho NWP Coeur D' Alene North
Idaho GTN Coeur D' Alene North
Idaho Both Coeur D' Alene North
Medford NWP Medford/Roseburg South
Medford GTN Medford/Roseburg South
Roseburg Medford/Roseburg South
Klamath Falls Klamath Falls South
La Grande La Grande South
Chapter
Highlights
•An increase in customer
forecast over 20 years
versus the 2016 IRP
•Lower use per customer
•Geographic demand
areas are now broken up
by state and territory
•Weather analysis points
to sustained risk of peak
weather, compared to a
base period, in most
areas
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 32 of 190
Demand Forecast Methodology
Avista uses the IRP process to develop two types of demand forecasts – annual and peak
day. Annual average demand forecasts are useful for preparing revenue budgets,
developing natural gas procurement plans, and preparing purchased gas adjustment
filings. Peak day demand forecasts are critical for determining the adequacy of existing
resources or the timing for acquiring new resources to meet customers’ natural gas needs
in extreme weather conditions.
In general, if existing resources are sufficient to meet peak day demand, they will be
sufficient to meet annual average day demand. Developing annual average demand first
and evaluating it against existing resources is an important step in understanding the
performance of the portfolio under normal circumstances. It also facilitates
synchronization of modeling processes and assumptions for planning purposes.
Peak weather analysis aids in assessing resource adequacy and any differences in
resource utilization. For example, storage may be dispatched differently under peak
weather scenarios.

Demand Modeling Equation
Developing daily demand forecasts is essential because natural gas demand can vary
widely from day-to-day, especially in winter months when heating demand is at its highest.
In its most basic form, natural gas demand is a function of customer base usage (non-
weather sensitive usage) plus customer weather sensitive usage. Basic demand takes
the formula in Table 2.2:

Table 2.2: Basic Demand Formula

SENDOUT® requires inputs as expressed in the Table 2.3 format to compute daily
demand in dekatherms.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 33 of 190
Table 2.3: SENDOUT® Demand Formula

Customer Forecasts
Avista’s customer base includes firm residential, commercial and industrial categories.
For each of the customer categories, Avista develops customer forecasts incorporating
national economic forecasts and then drilling down into regional economies. U.S. GDP
growth, national and regional employment growth, and regional population growth
expectations are key drivers in regional economic forecasts and are useful in estimating
the number of natural gas customers. A detailed description of the customer forecast is
found in Appendix 2.1 – Economic Outlook and Customer Count Forecast. Avista
combines this data with local knowledge about sub-regional construction activity, age and
other demographic trends, and historical data to develop the 20-year customer forecasts.
Several Avista departments’ use these forecasts including Finance, Accounting, Rates,
and Gas Supply. The natural gas distribution engineering group utilizes the forecast data
for system optimization and planning purposes (see discussion in Chapter 8 – Distribution
Planning).
Forecasting customer growth is an inexact science, so it is important to consider different
forecasts. Two alternative growth forecasts were developed for this IRP. Avista developed
High and Low Growth forecasts to provide potential paths and test resource adequacy.
Appendix 2.1 contains a description of how these alternatives were developed.
Figure 2.1 shows the three customer growth forecasts. The expected case customer
counts are higher than the last IRP. This has impacted forecasted demand from both the
average and peak day perspective. Detailed customer count data by region and class for
all three scenarios is in Appendix. 2.2 – Customer Forecasts by Region. In comparison
to Avista’s 2016 IRP, the base forecast for customer growth increases by nearly 12,000
new customers converting from electric to natural gas. This emerging natural gas demand
is attributed to both the Line Excess Allowance Program (LEAP) 1 and Fuel Efficiency
programs. Since conversion costs can be expensive, it is common for customers who
participate in the LEAP program to also apply for a fuel conversion rebate resulting in a
large overlap in participation between the two programs. It was estimated that in 2017
1 https://www.myavista.com/about-us/services-and-resources/natural-gas
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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approximately 77% of LEAP participants also participated in the fuel conversion program
offerings.

Figure 2.1: Customer Growth Scenarios

Use-per-Customer Forecast
The goal for a use-per-customer forecast is to develop base and weather sensitive
demand coefficients that can be combined and applied to heating degree day (HDD)
weather parameters to reflect average use-per-customer. This produces a reliable
forecast because of the high correlation between usage and temperature as depicted in
the example scatter plot in Figure 2.2.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Figure 2.2: Example Demand vs. Average Temperature – WA/ID

The first step in developing demand coefficients was gathering daily historical gas flow
data for all of Avista’s city gates. The use of city gate data over revenue data is due to
the tight correlation between weather and demand. The revenue system does not capture
data on a daily basis and, therefore, makes a statistical analysis with tight correlations on
a daily basis virtually impossible. Avista reconciles city gate flow data to revenue data to
ensure that total demand is properly captured.
The historical city gate data was gathered, sorted by service territory/temperature zone,
and then by month. As in the last IRP, Avista used three years of historical data to derive
the use-per-customer coefficients, but also considered varying the number of years of
historical data as sensitivities. When comparing five years of historical use-per-customer
to three years of data, the five-year data had slightly higher use-per-customer, which may
overstate use as efficiency and use-per-customer-per-HDD have been on a downward
trend since 2006. The two-year use-per-customer was much more pronounced for
demand, likely based off of some cold weather in Avista’s territories and a shorter
timeframe for weather to impact the overall use-per-customer. Three years struck a
balance between historical and current customer usage patterns. Figure 2.3 illustrates
the annual demand differences between the three and five-year use-per-customer with
normal and peak weather conditions.
0
50,000
100,000
150,000
200,000
250,000
300,000
-20020406080100
DT
H
2006-2017 AVERAGE TEMP (ºF)
Daily Demand Profile
Washington and Idaho
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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You can see the three year and 5 year coefficients are very close, with the two year
coefficient clearly higher.

Figure 2.3: Annual Demand – Demand Sensitivities 2-Year, 3-Year and 5-Year Use-per-
Customer

The base usage calculation used three years of July and August data to derive
coefficients. Average usage in these months divided by the average number of customers
provides the base usage coefficient input into SENDOUT. This calculation is done for
each area and customer class based on customer billing data demand ratios.
To derive weather sensitive demand coefficients for each monthly data subset, Avista
removed base demand from the total and plotted usage by HDD in a scatter plot chart to
verify correlation visually. The process included the application of a linear regression to
the data by month to capture the linear relationship of usage to HDD. The slopes of the
resulting lines are the monthly weather sensitive demand coefficients input into
SENDOUT. Again, this calculation is done by area and by customer class using
allocations based on customer billing data demand ratios.
30,000
32,000
34,000
36,000
38,000
40,000
42,000
44,000
46,000
MD
t
h
3 year UPC Alternate Historical 2-Year UPC
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 37 of 190
Weather Forecast
The last input in the demand modeling equation is weather (specifically HDDs). The most
current 20 years of daily weather data (minimums and maximums) from the National
Oceanic Atmospheric Administration (NOAA) is used to compute an average for each
day; this 20-year daily average is used as a basis for the normal weather forecast. NOAA
data is obtained from five weather stations, corresponding to the areas where Avista
provides natural gas services (four in Oregon and one for Washington and Idaho), where
this same 20-year daily average weather computation is completed for all five areas. The
HDD weather patterns between the Oregon areas are uncorrelated, while the HDD
weather patterns amongst eastern Washington and northern Idaho portions of the service
area are correlated. Thus, Spokane Airport weather data is used for all Washington and
Idaho demand areas.
The NOAA 20-year average weather serves as the base weather forecast to prepare the
annual average demand forecast. The peak day demand forecast includes adjustments
to average weather to reflect a five-day cold weather event. This consists of adjusting the
middle day of the five-day cold weather event to the coldest temperature on record for a
service territory, as well as adjusting the two days on either side of the coldest day to
temperatures slightly warmer than the coldest day. For the Washington, Idaho and La
Grande service territories, the model assumes this event on and around February 15 each
year. For the southwestern Oregon service territories (Medford, Roseburg, Klamath
Falls), the model assumes this event on and around December 20 each year. The
following section provides details about the coldest days on record for each service
territory.
For, Washington and Idaho service areas, the coldest day on record observed in Spokane
was an 82 HDD that occurred on December 30, 1968. This is equal to an average daily
temperature of -17 degrees Fahrenheit. Only one 82 HDD has been experienced in the
last 51 years for this area; however, within that same time period, 80, 79 and 78 HDD
events occurred on December 29, 1968, December 31,1978 and December 30, 1978,
respectively.
Medford experienced the coldest day on record, a 61 HDD, on December 9, 1972. This
is equal to an average daily temperature of 4 degrees Fahrenheit. Medford has
experienced only one 61 HDD in the last 47 years; however, it has also experienced 59
and 58 HDD events on December 8, 1972 and December 21, 1990, respectively.
The other three areas in Oregon have similar weather data. For Klamath Falls, a 72 HDD
occurred on three separate occasions: December 21, 1990, December 8, 2013 and most
recently on January 6, 2017; in La Grande a 75 HDD occurred on January 31, 1996; and
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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a 55 HDD occurred in Roseburg on December 22, 1990. As with Washington, Idaho and
Medford, these days are the peak day weather standard for modeling purposes.
Utilizing a peak planning standard of the coldest temperature on record may seem
aggressive given a temperature experienced rarely, or only once. Given the potential
impacts of an extreme weather event on customers’ personal safety and property damage
to customer appliances and Avista’s infrastructure, it is a prudent regionally accepted
planning standard. While remote, peak days do occur, as on January 6, 2017, when
Avista matched the previous peak HDD in Klamath Falls.
Avista analyzes an alternate planning standard using the coldest temperature in the last
twenty years. Washington and Idaho service area use a 76 HDD, which is equal to an
average daily temperature of -11 degrees Fahrenheit. In Medford, the coldest day in 20
years is a 52 HDD, equivalent to an average daily temperature of 13 degrees Fahrenheit.
In Roseburg, the coldest day in 20 years is a 48 HDD, equivalent to an average daily
temperature of 17 degrees Fahrenheit. In Klamath Falls, the coldest day in 20 years is a
72 HDD, equivalent to an average daily temperature of -7 degree Fahrenheit. In La
Grande, the coldest day in 20 years is a 66 HDD, equivalent to an average daily
temperature of -1 degree Fahrenheit. The HDDs by area, class and day entered into
SENDOUT® are in Appendix 2.4 – Heating Degree Day Data.
Average rolling 20 year weather is the current methodology used in Avista’s planning in
this IRP. Unlike many peer utilities, Avista has some extreme weather that can have
deadly consequences to both persons and property if observed. If taken into
consideration, wind chill has the potential to drastically change our planning standard.
During Spokane’s coldest on record weather event the average temperature was -17
degrees Fahrenheit or 82HDD2; if combined with a 7mph wind chill, would create a
temperature of -33 Fahrenheit3. This would add an additional 16 HDD’s to Avista’s
planning standard, consequently increasing our new planning standard to 99 HDD. The
coldest in the past 20 years occurred on January 5, 2004 as Spokane International
Airport’s observed mean temperature of -10 Fahrenheit combined with an average wind
speed of 3 mph. The average temperature converts to 75 HDDs and when paired with
the wind-chill factor -18 Fahrenheit, would be 83 HDDs or 1 degree colder than our
planning standard. With the wind chill included, these temperatures appear to be
reasonable as these extreme events have been experienced in recent history. In Oregon
territories, specifically Klamath Falls and La Grande, the coldest on record has occurred
multiple times in the past 30 years.
2 Weather Underground: www.wunderground.com/history
3 http://www.wpc.ncep.noaa.gov/html/windchillbody_txt.html
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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As discussed in TAC 2, warming trends are beginning to emerge in Roseburg and
Medford, though the volatility surrounding the peak is still present as seen in Figures 2.5
and 2.8. This indicates that although temperatures specifically in the Roseburg and
Medford areas are deviating from the base years of 1950-1981, the peaking potential
remains the same. The following figures show this same analysis for all weather areas.

Figure 2.4: Spokane

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Figure 2.5: Medford

Figure 2.6: La Grande

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Figure 2.7: Klamath Falls

Figure 2.8: Roseburg

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Developing a Reference Case
To adjust for uncertainty, Avista developed a dynamic demand forecasting methodology
that is flexible to changing assumptions. To understand how various alternative
assumptions influence forecasted demand Avista needed a reference point for
comparative analysis. For this, Avista defined the reference case demand forecast shown
in Figure 2.4. This case is only a starting point to compare other cases.

Figure 2.4: Reference Case Assumptions
1. Customer Compound Annual Growth Rates
Area Residential Commercial Industrial
Washington/ Idaho 1.1% 0.6% 0.0%
Klamath Falls 1.3% 0.9% 0.0%
La Grande 0.6% 0.4% 0.1%
Medford 1.3% 1.0% 0.0%
Roseburg 1.1% 0.2% 0.0%
2. Use-Per-Customer Coefficients
Flat Across All Classes
3-year Average Use per Customer per HDD by Area/Class
3. Weather 20-year Normal – NOAA (1998-2017)
4. Elasticity
None
5. Conservation
None
Dynamic Demand Methodology

The dynamic demand planning strategy examines a range of potential outcomes. The
approach consists of:
• Identifying key demand drivers behind natural gas consumption;
• Performing sensitivity analysis on each demand driver;
• Combining demand drivers under various scenarios to develop alternative
potential outcomes for forecasted demand; and
• Matching demand scenarios with supply scenarios to identify unserved demand.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Figure 2.5 represents Avista’s methodology of starting with sensitivities, progressing to
portfolios, and ultimately selecting a preferred portfolio.

Figure 2.5: Sensitivities and Preferred Portfolio Selection

Sensitivity Analysis
In analyzing demand drivers, Avista grouped them into two categories based on:
• Demand Influencing Factors directly influencing the volume of natural gas
consumed by core customers.
• Price Influencing Factors indirectly influencing the volume of natural gas consumed
by core customers through a price elasticity response.
After identifying demand and price influencing factors, Avista developed sensitivities to
focus on the analysis of a specific natural gas demand driver and its impact on forecasted
demand relative to the Reference Case when modifying the underlying input
assumptions.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Sensitivity assumptions reflect incremental adjustments not captured in the underlying
Reference Case forecast. Avista analyzed 18 demand sensitivities to determine the
results relative to the Reference Case. Table 2.4 lists these sensitivities. Detailed
information about these sensitivities is in Appendix 2.6 – Demand Forecast Sensitivities
and Scenarios Descriptions.
Table 2.4: Demand Sensitivities

Figure 2.6 shows the annual demand from each of the sensitivities modeled for this IRP.

Figure 2.6: 2018 IRP Demand Sensitivities

10,000
15,000
20,000
25,000
30,000
35,000
40,000
45,000
50,000
MD
t
h
High Prices Low Prices Carbon Legislation-LowCarbon Legislation-Expected Carbon Legislation-High High Cust GrowthLow Cust Growth Expected Elasticity Alternate Historical 2-Year UPCAlternate Historical 5-Year UPC Alternate Weather Std 80% below 1990 emissions80% below 1990 emissions Ref Plus Peak Reference Case - Plus Peak Peak Plus DSM CaseReference Case DSM Case
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Scenario Analysis
After testing the sensitivities, Avista grouped them into meaningful combinations of
demand drivers to develop demand forecasts representing scenarios. Table 2.5 identifies
the scenarios developed for this IRP. The Average Case represents the case used for
normal planning purposes, such as corporate budgeting, procurement planning, and
PGA/General Rate Cases. The Expected Case reflects the demand forecast Avista
believes is most likely given peak weather conditions. The High Growth/Low Price and
Low Growth/High Price cases represent a range of possibilities for customer growth and
future prices. The Alternate Weather Standard case utilizes the coldest day in Avista’s
service territories in the last 20 years. The 80% below 1990 emissions scenario is
intended to show a progressive loss of demand in the areas of Oregon and Washington
(Idaho is unaffected) from policies targeting methane and carbon dioxide emissions to an
estimated emissions levels. It makes no assumptions as to how the reduction in
emissions are obtained just the levelized trend of overall use based on 2050 targets.
Each of these scenarios provides a “what if” analysis given the volatile nature of key
assumptions, including weather and price. Appendix 2.6 lists the specific assumptions
within the scenarios while Appendix 2.7 contains a detailed description of each scenario.

Table 2.5: Demand Scenarios
2018 IRP Demand Scenarios

Price Elasticity
The economic theory of price elasticity states that the quantity demanded for a good or
service will change with its price. Price elasticity is a numerical factor that identifies the
relationship of a customer’s consumption change in response to a price change. Typically,
the factor is a negative number as customers normally reduce their consumption in
response to higher prices or will increase their consumption in response to lower prices.
For example, a price elasticity factor of negative 0.15 for a particular good or service
means a 10 percent price increase will prompt a 1.5 percent consumption decrease and
a 10 percent price decrease will prompt a 1.5 percent consumption increase.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Complex relationships influence price elasticity and given the current economic
environment, Avista questions whether current behavior will become normal or if
customers will return to historic usage patterns. Furthermore, complex regulatory pricing
mechanisms shield customers from price volatility, thereby dampening price signals and
affecting price elastic responses. For example, budget billing averages a customer’s bills
into equal payments throughout the year. This popular program helps customers manage
household budgets, but does not send a timely price signal. Additionally, natural gas cost
adjustments, such as the Purchased Gas Adjustment (PGA), annually adjusts the
commodity cost which shields customers from daily gas price volatility. These
mechanisms do not completely remove price signals, but they can significantly dampen
the potential demand impact.
When considering a variety of studies on energy price elasticity, a range of potential
outcomes was identified, including the existence of positive price elastic adjustments to
demand. One study looking at the regional differences in price elasticity of demand for
energy found that the statistical significance of price becomes more uncertain as the
geographic area of measurement shrinks.4 This is particularly important given Avista’s
geographically diverse and relatively small service territories.
Avista acknowledges changing price levels can and do influence natural gas usage. This
IRP includes a price elasticity of demand factor of -0.10 for every 10% change in price as
measured in the Roseburg and Medford service territories. We assume the same
elasticity for all service areas in this study. When putting this elasticity into our model, it
allows the use-per-customer to vary as the natural gas price forecast changes.
Recent usage data indicates that even with declines in the retail rate for natural gas, long
run use-per-customer continues to decline. This likely includes a confluence of factors
including increased investments in energy DSM measures, building code improvements,
behavioral changes, and heightened focus of consumers’ household budgets.

Results
During 2018, the Average Case demand forecast indicates Avista will serve an average
of 348,000 core natural gas customers with 33,219,431 Dth of natural gas. By 2037,
Avista projects 412,000 core natural gas customers with an annual demand of over
36,154,721 Dth. In Washington/Idaho, the projected number of customers increases at
an average annual rate of 1.30 percent, with demand growing at a compounded average
4 Bernstein, M.A. and J. Griffin (2005). Regional Differences in Price-Elasticity of Demand for Energy, Rand Corporation.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 47 of 190
annual rate of 0.36 percent. In Oregon, the projected number of customers increases at
an average annual rate of 0.9 percent, with demand growing 0.70 percent per year.
During 2018, the Expected Case demand forecast indicates Avista will serve an average
of 348,000 core natural gas customers with 34,369,993 Dth of natural gas. By 2037,
Avista projects 412,000 core natural gas customers with an annual demand of 37,536,603
Dth.
Figure 2.7 shows system forecasted demand for the demand scenarios on an average
daily basis for each year.5

Figure 2.7: Average Daily Demand – 2018 IRP Scenarios

5 Appendix 2.1 shows gross demand, conservation savings and net demand.
01020304050
60
708090100110
120
MD
t
h
High Growth & Low Prices Expected Case
80 % Below 1990 Emissions Cold Day 20yr Weather Std
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 48 of 190
Figure 2.8 shows system forecasted demand for the Expected, High and Low Demand
cases on a peak day basis for each year relative to the Average Case average daily winter
demand. Detailed data for all demand scenarios is in Appendix 2.8 – Demand Before and
After DSM.

Figure 2.8: February 15th – Peak Day – 2016 IRP Demand Scenarios

The IRP balances forecasted demand with existing and new supply alternatives. Since
new supply sources include conservation resources, which act as a demand reduction,
the demand forecasts prepared and described in this section include existing DSM
standards and normal market acceptance levels. The methodology for modeling DSM
initiatives is in Chapter 3 – Demand-Side Resources.

Alternative Forecasting Methodologies
There are many forecasting methods available and used throughout different industries.
Avista uses methods that enhance forecast accuracy, facilitate meaningful variance
analysis, and allows for modeling flexibility to incorporate different assumptions. Avista
believes the IRP statistical methodology to be sound and provides a robust range of
demand considerations. The methodology allows for the analysis of different statistical
0
100
200
300
400
MD
t
h
High and Low Expected Case
80 % Below 1990 Emissions Cold Day 20yr Weather Std
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 49 of 190
inputs by considering both qualitative and quantitative factors. These factors come from
data, surveys of market information, fundamental forecasts, and industry experts. Avista
is always open to new methods of forecasting natural gas demand and will continue to
assess which, if any, alternative methodologies to include in the dynamic demand
forecasting methodology.

Key Issues
Demand forecasting is a critical component of the IRP requiring careful evaluation of the
current methodology and use of scenario planning to understand how changes to the
underlying assumptions will affect the results. The evolution of demand forecasting over
recent years has been dramatic, causing a heightened focus on variance analysis and
trend monitoring. Current techniques have provided sound forecasts with appropriate
variance capabilities. However, Avista is mindful of the importance of the assumptions
driving current forecasts and understands that these can and will change over time.
Therefore, monitoring key assumptions driving the demand forecast is an ongoing effort
that will be shared with the TAC as they develop.

Flat Demand Risk
Forecasting customer usage is a complex process because of the number of underlying
assumptions and the relative uncertainty of future patterns of usage with a goal of
increasing forecast accuracy. There are many factors that can be incorporated into these
models, assessing which ones are significant and improving the accuracy are key. Avista
continues to evaluate economic and non-economic drivers to determine which factors
improve forecasting accuracy. The forecasting process will continue to review research
on climate change and the best way to incorporate the results of that research into the
forecasting process.
For the last few planning cycles, the TAC has discussed the changing slope of forecasted
demand. Growth has slowed due to a declining use-per-customer. Use-per-customer
seems to have stabilized, though it is still on a downward trajectory.
This reduced demand pushes the need for resources beyond the planning horizon, which
means no new investment in resources is necessary. However, should assumptions
about lower customer growth prove to be inaccurate and there is a rebound in demand,
new resource needs will occur sooner than expected. Therefore, careful monitoring of
demand trends in order to identify signposts of accelerated demand growth is critical to
the identification of new resource needs coming earlier than expected.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 50 of 190
Emerging Natural Gas Demand
The shale gas revolution has fundamentally changed the long-term availability and price
of natural gas. An ever growing demand for natural gas-fired generation to integrate
variable wind and solar resources along with an increasing demand from coal retirements
and fuel switching has developed over the last few years. This demand is expected to
increase due to the availability of natural gas combined with its lower carbon emissions.
Other areas of emerging demand include everything from methanol plants to food
processors, and interest in industrial processes using natural gas as a feedstock is
growing.

Conclusion
Avista’s 20 year outlook for customer growth has increased as a whole by nearly 12,000
customers, as compared to Avista’s 2016 IRP. Much of this demand is from a conversion
program offered in Washington and Idaho helping electric customer’s assistance in
converting to natural gas. With an increased amount of energy efficiency, known as DSM,
measures going into new construction and purchased through Avista’s programs, homes
are becoming better equipped to keep the heat in. This in turn leads to a decreasing
amount of natural gas usage. Until a point is reached where maximum efficiency is found,
these trends will likely continue to decline in nature.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 51 of 190
3: Energy Efficiency & Demand-
Side Resources

Overview
Avista is committed to offering natural gas Energy
Efficiency portfolios to residential, low income,
commercial and industrial customer segments when
it is feasible to do so in a cost-effective manner as
prescribed within each jurisdiction. Avista began
offering natural gas energy efficiency programs to its
customers in 1995. Program delivery includes both
prescriptive and site-specific offerings. Prescriptive
programs, or standard offerings, provide cash
incentives for standardized products such as the
installation of qualifying high-efficiency heating
equipment. Delivering programs through a
prescriptive approach works in situations where uniform products or offerings are applicable
for large groups of homogeneous customers and primarily occur in programs for residential
and small commercial customers. Site specific is the most comprehensive offering of the
nonresidential segment. Avista’s Account Executives work with nonresidential customers to
provide assistance in identifying energy efficiency opportunities. Customers receive technical
assistance in determining potential energy and cost savings as well as identifying and
estimating incentives for participation. Other delivery methods build off these approaches and
may include upstream buy downs of low cost measures, free-to-customer direct install
programs, and coordination with regional entities for market transformation efforts.
Recently, programs with the highest impacts on natural gas energy savings include the
residential prescriptive HVAC measures, residential water heat measures, and nonresidential
prescriptive and site-specific HVAC. In the 2017 program year, conservation programs
exceeded the IRP savings targets in both Washington and Idaho.
Improved drilling and extraction techniques of natural gas has led to declines in natural gas
prices in recent years which has made offering cost-effective DSM programs challenging
using the Total Resource Cost Test (TRC) to test cost-effectiveness. Since January 1, 2016,
Washington and Idaho programs utilize the Utility Cost Test (UCT). Effective January 1, 2017,
all Oregon DSM programs, with the exception of low-income conservation, are delivered and
administered by the Energy Trust of Oregon (ETO)1.
1 As part of the settlement for the Avista 2015 Oregon General Rate case
Chapter
Highlights
•Increased DSM potential
•ETO manages Avista’s
DSM programs in Oregon
•In future IRP’s we will visit
new methodology to look at
DSM by scenario
•Distribution will be a
primary area of research for
potential integration in
avoided costs and as a
supply side resource
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 52 of 190
In Washington, a $10/MTCO2e ($0.53/Dth) carbon cost starting July 2019 was included to
account for the potential carbon reduction approaches currently occurring in the state. Idaho
has no assumed carbon costs.
Conservation Potential Assessment Methodology Overview
During 2017, Avista issued an RFP and chose Applied Energy Group (AEG) to perform an
external independent evaluation of Avista’s conservation potential. Included with this
evaluation was the technical, economic and achievable conservation potential for each of
Avista’s three jurisdictions over a 20-year planning horizon (2018-2037). As potential for 2038
was also estimated for reference purposes but not utilized within the IRP, the remainder of
this chapter will refer only to the 20-year planning horizon. This process involves indexing
AEG’s existing nationally recognized Conservation Potential Assessment (CPA) tool,
LoadMAPTM, to the Avista service territory load forecast, housing stock, end-use saturations,
recent conservation accomplishments, and other key characteristics. Additional consideration
of the impact of energy codes and appliance standards for end-use equipment at both the
state and national level are incorporated into the projection of energy use and the baseline
for the evaluation of efficiency options. The modeling process also utilizes ramp rates for the
acquisition of efficiency resources over time in a manner generally consistent with the
assumptions used by the Northwest Power and Conservation Council (NPCC), adapted for
use in modeling natural gas DSM programs.
The process described above results in an Avista-specific supply curve for conservation
resources. Simultaneously, the avoided cost of natural gas consistent with serving the full
forecasted demand was defined as part of the SENDOUT® modeling of the Avista system.
The preliminary cost-effective conservation potential is determined by applying the stream of
annual natural gas avoided costs to the Avista-specific supply curve for conservation
resources. This quantity of conservation acquisition is then decremented from the load which
the utility must serve and the SENDOUT® model is rerun against the modified (reduced) load
requirements. The resulting avoided costs are compared to those obtained from the previous
iteration of SENDOUT® avoided costs. This process continues until the differential between
the avoided cost streams of the most recent and the immediately previous iteration becomes
immaterial. The resulting avoided costs were provided to AEG to use in selecting cost-
effective potential within Avista’s Washington and Idaho service territories. The cost-
effectiveness test used for Washington and Idaho was the UCT.
Integrating the DSM portfolio into the IRP process by equilibrating the avoided costs in this
iterative process is useful since Avista’s DSM acquisition is small relative to the total western
natural gas market used to establish the commodity prices driving the avoided cost stream.
Therefore, few iterations are necessary to reach a stable avoided cost. Additionally, it provides
some assurance, at least at the aggregate level, that the quantity of DSM resource selected
will be cost-effective when the final avoided cost stream is used in retrospective portfolio
evaluation.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 53 of 190
Conservation Potential Assessment Methodology
Prior to the development of potential conservation estimates, AEG created a baseline end-
use projection to quantify the use of natural gas by end use in the base year (2015), and
projections of consumption in the future in the absence of future utility programs and naturally
occurring conservation (through 2038). The end-use forecast includes the relatively certain
impacts of codes and standards that will unfold over the study timeframe. All such mandates
defined as of February 2018 are included in the baseline. The baseline forecast is the
foundation for the analysis of savings from future DSM programs as well as the metric against
which potential savings are measured.
Inputs to the baseline forecast include current economic growth forecasts (e.g. customer
growth and income growth), natural gas price forecasts, trends in fuel shares and equipment
saturations developed by AEG, existing and approved changes to building codes and
equipment standards, and Avista’s internally developed load forecast. Since actual billing data
was available for 2016 and 2017, AEG calibrated the model to reflect recent consumption
trends and weather-actual consumption before aligning with Avista’s weather-normal load
forecast in 2018.
According to the CPA, the residential sector natural gas consumption for all end uses and
technologies increases primarily due to the projected 1.3 percent annual growth in the number
of households for Washington, and 1.5 percent annual growth for Idaho. This projection aligns
well with Avista’s official forecast, diverging in the later years due to two end-use modeling
assumptions. The first is the projected impact of the AFUE 92% federal furnace standard
being phased in over time (starting in 2021), resulting in slower primary space heating growth
compared to the other end uses. Furthermore, impacts of the 2015 Washington State Energy
Code (2015 WSEC) further reduce space heating consumption in Washington, where very
efficient building shell requirements reduce the annual runtime requirements on primary
heating systems.
For the commercial sector, natural gas use grows slowly over the 20-year planning horizon
as new construction increases the overall square footage in this sector. Growth in the heating
end use mirrors overall sector growth while food preparation and miscellaneous consumption
outpace it. Food preparation, though a small percentage of total usage, grows at a higher rate
than the other end uses. Consumption by miscellaneous equipment and process heating are
also projected to increase.
Growth in the industrial sector is tied closely to historical trend and planned facility closures.
This is observed in Washington, where consumption drops by 0.3% annually between 2018
and 2037. In Idaho, consumption between 2018 and 2037 remains quite flat for all end uses.
Table 3.1 illustrates the baseline consumption broken out by state and sector for selected
years over the 20-year planning horizon. The overall baseline consumption is expected to
increase 14 percent over the 20-year planning horizon corresponding to an annualized growth
of 0.7 percent. The forecast projects steady growth over the next 20 years with growth in the Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 54 of 190
residential sector making up for the flat or declining sales in the industrial sector. Idaho is
projected to experience a higher level of growth than Washington due to less stringent energy
codes and a flat industrial baseline.

Table 3.1: Baseline Forecast Summary (Dth)
End Use 2016 2018 2019 2020 2027 2037 % Change ('18-'37) Avg. Growth
Residential
Commercial
Industrial --
Total

Washington
Idaho
Total

The next step in the study is the development of three types of potential: technical, achievable
technical, and achievable economic. Technical potential is the theoretical upper limit of
conservation potential. This assumes that all customers replace equipment with the efficient
option available and adopt the most efficient energy use practices possible at every
opportunity without regard to cost-effectiveness.
Achievable technical potential refines technical potential by applying customer participation
rates that account for market barriers, customer awareness and attitudes, program maturity,
and other factors that affect market penetration of conservation measures. The Seventh
Electric Power Plan’s ramp rates, which also include potential realized from delivery
mechanisms outside utility DSM programs, were used as a starting point when developing
these factors.
Achievable economic potential further refines achievable technical potential by applying an
economic screen, measured by the utility cost test (UCT), which assesses cost-effectiveness
from the utility’s perspective. Please note that while AEG estimated potential under a
balanced total resource cost (TRC) test as a secondary test, results from this sensitivity were
not used for IRP modeling and are excluded from this discussion.
DSM measures that achieve generally uniform year-round energy savings independent of
weather are considered base load measures. Examples include high-efficiency water heaters,
cooking equipment and front-loading clothes washers. Weather-sensitive measures are those
which are influenced by heating degree day factors and include higher efficiency furnaces,
ceiling/wall/floor insulation, weather stripping, insulated windows, duct work improvements
(tighter sealing to reduce leaks) and ventilation heat recovery systems (capturing chimney Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 55 of 190
heat). Weather-sensitive measures are often referred to as winter load shape measures and
were valued using a higher avoided cost (due to summer-to-winter natural gas pricing
differentials) while base-load measures, often called annual load shape measures, are valued
at a lower, year-round avoided cost.
Conservation measures are offered to residential, non-residential and low-income2
customers. Measures offered to residential customers are almost universally on a prescriptive
basis, meaning they have a fixed incentive for all customers and do not require individual pre-
project analysis by the utility. Low-income customers are treated with a more flexible approach
through cooperative arrangements with participating Community Action Agencies. Non-
residential customers have access to various prescriptive and site-specific conservation
measures. Site-specific measures are customized to specific applications and have cost and
therm savings that are unique to the individual facility.
See Table 3.2 for residential, commercial, and industrial measures evaluated in this study
for both states.
Table 3.2: Conservation Measures

Residential Measures Commercial and Industrial Measures
Furnace - Direct Fuel Furnace - Efficient Heating
Boiler - Direct Fuel Boiler - Efficient Heating
Fireplace Unit Heater - Efficient Heating
Water Heating - Efficient Heating Water Heater - Efficient Water Heating
Appliances - Clothes Dryer Food Preparation - Oven
Appliances - Stove/Oven Food Preparation - Conveyor Oven
Pool Heater - Efficient Water Heating Food Preparation - Double Rack Oven
Insulation - Ceiling, Installation Food Preparation - Fryer
Insulation - Ceiling, Upgrade Food Preparation - Broiler
Insulation - Slab Foundation Food Preparation - Griddle
Insulation - Basement Sidewall Food Preparation - Range
Insulation – Ducting Food Preparation - Steamer
Insulation - Infiltration Control (Air Sealing) Food Preparation - Other Food Prep
Insulation - Floor/Crawlspace Pool Heater - Efficient Heater
Insulation - Wall Cavity, Upgrade Insulation - Roof/Ceiling
Insulation - Wall Cavity, Installation Insulation - Wall Cavity
Insulation - Wall Sheathing Insulation - Ducting
Ducting - Repair and Sealing HVAC - Duct Repair and Sealing
Doors - Storm and Thermal Windows - High Efficiency
Windows - High Efficiency Gas Boiler - Maintenance
Thermostat – Programmable Gas Furnace - Maintenance
2 For purposes of tables, figures and targets, low income is a subset of residential class.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 56 of 190
Residential Measures Commercial and Industrial Measures
Thermostat - Wi-Fi/Interactive Gas Boiler - Hot Water Reset
Gas Furnace - Maintenance Steam Trap Maintenance
Gas Boiler - Hot Water Reset Gas Boiler - High Turndown
Gas Boiler - Steam Trap Maintenance Gas Boiler - Burner Control Optimization
Gas Boiler - Maintenance HVAC - Shut Off Damper
Gas Boiler - Pipe Insulation HVAC - Demand Controlled Ventilation
Water Heater - Drainwater Heat Recovery Gas Boiler - Stack Economizer
Water Heater - Faucet Aerators Gas Furnace Tube Inserts
Water Heater - Low Flow Showerhead (2.0 GPM) Gas Boiler - Insulate Steam Lines/Condensate Tank
Water Heater - Low Flow Showerhead (1.5 GPM) Gas Boiler - Insulate Hot Water Lines
Water Heater - Temperature Setback Space Heating - Heat Recovery Ventilator
Water Heater - Thermostatic Shower Restriction Valve Thermostat - Programmable
Water Heater - Pipe Insulation Thermostat - WiFi Enabled
Water Heater - Solar System Water Heater - Ozone Laundry
Pool Heater - Solar System Water Heater - High MEF Commercial Laundry Washers
ENERGY STAR Dishwashers Water Heater - Motion Control Faucet
ENERGY STAR Clothes Washers Water Heater - Faucet Aerator
ENERGY STAR Homes Water Heater - Drainwater Heat Recovery
Combined Boiler + DHW System (Storage Tank) Water Heater - Efficient Dishwasher
Combined Boiler + DHW System (Tankless) Water Heater - Pre-Rinse Spray Valve
Water Heater - Central Controls
Water Heater - Solar System
Destratification Fans (HVLS)
Kitchen Hood - DCV/MUA
Pool Heater - Night Covers
Building Automation System
Steam System Efficiency Improvements
Commissioning - HVAC
Retrocommissioning - HVAC
Strategic Energy Management
Process - Insulate Heated Process Fluids
Process Heat Recovery
Commissioning
Retrocommissioning

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 57 of 190
Conservation Potential Assessment Results
Based upon the previously described methodology and baseline forecasts, AEG developed
technical, achievable technical, and achievable economic potentials by state and segment
over a full 20-year horizon. Although early-year potential differs by state due to maturity of
DSM programs3, 20-year steady-state potential is quite similar between the two states since
ramp rates reach 85% for all non-emerging measures.
The technical potential for the overall Avista service territory for the full 20-year IRP horizon
period ultimately reaches 29.5 percent of the baseline end-use forecast.
Achievable technical potential applies customer participation and market penetration factors
to the technical potential. By the end of the 20-year timeframe, cumulative savings, including
non-utility delivery mechanisms, reach 24.7 percent of the baseline energy forecast.
Achievable economic potential applies the cost-effectiveness metric from the utility’s
perspective to DSM measures identified within the achievable technical potential and quantify
the impact of the adoption of only those DSM measures that are cost-effective. By the end of
the 20-year timeframe this represents 20.6 percent of the baseline energy forecast. Although
falling natural gas avoided costs would significantly affect potential from a TRC perspective,
the UCT is quite similar to achievable technical in all years. This is because utility incentives
were developed using existing, approved Avista tariffs for current measures and incentives
for similar measures for identified new measures.
Tables 3.3 and 3.4 summarize cumulative conservation for each potential type for selected
years across the 20-year CPA and IRP horizon. As the largest sector in both states, the
residential sector accounts for a majority of both early and late-year potential. Industrial
includes only Avista’s core customers (e.g. customers that consume gas rather than transport
it), making the sector a small contributor to overall consumption and potential. For more
specific detail, please refer to the natural gas CPA provided in Appendix 3.1.

3 In May 2012, Avista proposed to suspend its Washington and Idaho natural gas DSM programs due to decreased natural
gas prices. The WUTC guided utilities to continue natural gas programs using the Utility Cost Test (UCT). Avista
requested and was given approval to suspend Avista’s Idaho natural gas DSM programs under the TRC and did not have
programs in 2013, 2014 and 2015 (2013 saw some activity due to prior commitments). After the review of Avista’s avoided
cost methodology and with an IPUC ruling that allows companies to emphasize the UCT when seeking prudence for their
DSM programs, Avista filed for and was approved to reinstate its Idaho Natural Gas DSM programs January 1, 2016.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 58 of 190
Table 3.3: Summary of Cumulative Technical, Achievable Technical, and Achievable
Economic Conservation Potential (Dth)
Washington 2018 2019 2020 2027 2037
17,221,900 17,
Potential Forecasts (Dth)
Achievable Economic 17,160,621 17,
Achievable Technical 17,188,007 17,
Technical 17,135,511 1
Cumulative Savings (Dth)
Achievable Economic 61,279
Achievable Technical 33,893
Technical 86,389
Energy Savings (% of Baseline)
Achievable Economic 1.3
Achievable Technical 1.8
Technical 3.8

Idaho 2018 2019 2020 2027 2037
Baseline Forecast (Dth) 8,557,178 8,667,149 8,765,347 9,288,224 9,917,115
Potential Forecasts (Dth)
Achievable Economic 8,530,838 8,608,797 8,665,006 8,480,677 7,879,230
Achievable Technical 8,547,332 8,644,716 8,627,624 8,261,653 7,466,149
Technical 8,519,855 8,585,623 8,450,043 7,851,146 6,976,401
Cumulative Savings (Dth)
Achievable Economic 26,340 58,352 100,341 807,547 2,037,885
Achievable Technical 9,846 22,432 137,724 1,026,571 2,450,966
Technical 37,324 81,526 315,305 1,437,078 2,940,714
Energy Savings (% of Baseline)
Achievable Economic 0.3% 0.7% 1.1% 8.7% 20.5%
Achievable Technical 0.1% 0.3% 1.6% 11.1% 24.7%
Technical 0.4% 0.9% 3.6% 15.5% 29.7%
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 59 of 190
The overall achievable potential is presented first by state and by sector in the following table.

Table 3.4: Summary of Cumulative Achievable Economic Potential by State and Sector (Dth)
Cumulative Savings (Dth) 2018 2019 2020 2027 2037
Washington 61,279 133,576 226,777 1,613,635 4,008,500
Idaho 26,340 58,352 100,341 807,547 2,037,885
Total 87,619 191,927 327,118 2,421,181 6,046,385
Cumulative Savings (Dth) 2018 2019 2020 2027 2037
Residential 58,333 129,227 223,729 1,727,462 4,565,013
Commercial 28,148 60,428 99,963 681,712 1,461,531
Industrial 1,138 2,272 3,427 12,007 19,840
Total 87,619 191,927 327,118 2,421,181 6,046,385

Figure 3.1 illustrates the impact of the conservation potential forecast upon the end-use
baseline absent of any conservation acquisition.

Figure 3.1 - Conservation Potential Energy Forecast (Dth)

Potential Results – Residential
Single-family homes represent 61 percent of Avista’s residential natural gas customers, but
account for 65 percent of the sector’s consumption in 2018. In the current IRP, residential
provides the largest opportunity for cumulative savings over the next 20 years. Table 3.5
provides a distribution of achievable economic potential by state for the residential sector.
Although potential as a percent of baseline is similar between the two states, there is one
notable difference. The less strict energy codes in Idaho should result in higher residential
potential, but this effect is counteracted by the recent “re-start” of DSM programs in the state
of Idaho, which lowers early-year potential as the programs “ramp” up.
-
5,000,000
10,000,000
15,000,000
20,000,000
25,000,000
30,000,000
35,000,000
2015 2017 2019 2021 2023 2025 2027 2029 2031 2033 2035 2037
Dth
Baseline Forecast
Achievable Economic Potential
Achievable Technical Potential
Technical Potential
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 60 of 190
Table 3.5 Residential Cumulative Achievable Economic Potential by State, Selected Years
Cumulative Savings (Dth) 2018 2019 2020 2027 2037
Baseline Projection (Dth)
Washington 10,773,426 10,971,347 11,144,590 11,877,363 12,636,101
Idaho 5,266,179 5,379,047 5,479,126 5,984,940 6,490,095
Total 16,039,605 16,350,394 16,623,717 17,862,303 19,126,196
Natural Gas Cumulative Savings (Dth)
Washington 39,979 88,051 151,815 1,131,013 3,003,789
Idaho 18,354 41,176 71,914 596,450 1,561,225
Total 58,333 129,227 223,729 1,727,462 4,565,013
% of Total Residential Savings
Washington 69% 68% 68% 65% 66%
Idaho 31% 32% 32% 35% 34%

Table 3.6 identifies the top 10 residential measures by cumulative 2020 savings. Furnaces,
windows, tankless water heaters, and learning thermostats are the top measures. These are
ranked by their combined contribution to Washington and Idaho savings.
Table 3.6 Residential Top Measures, 2020
Rank Measure / Technology WA ID Total % of Total
1 Furnace - Direct Fuel - AFUE 95% 69,659 40,893 110,552 49%
2 Windows - High Efficiency - Double Pane LowE CL22 28,074 4,076 32,150 14%
3 Water Heater <= 55 gal. - Instantaneous - ENERGY STAR 18,893 8,936 27,829 12%
4 Insulation - Floor/Crawlspace - R-30 5,646 3,861 9,507 4%
5 Thermostat - Wi-Fi/Interactive - Interactive/learning thermostat 6,147 3,040 9,187 4%
6 Insulation - Ceiling, Installation - R-38 (Retro only) 3,286 1,638 4,923 2%
7 Insulation - Wall Cavity, Installation - R-11 2,850 1,426 4,276 2%
8 ENERGY STAR Homes - Built Green spec (NC Only) 2,480 1,229 3,709 2%
9 Boiler - Direct Fuel - AFUE 96% 2,175 1,069 3,244 1%
10 Water Heater - Low Flow Showerhead (1.5 GPM) 1,853 922 2,775 1%
Subtotal 141,063 67,090 208,153 93%
Total Savings in Year 151,815 71,914 223,729 100%

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 61 of 190
The bulk of the residential potential exists in space heating end-uses followed by water
heating applications. Appliances and miscellaneous end-use loads contribute a small
percentage of potential. Based on measure-by-measure findings of the potential study the
greatest sources of residential achievable potential across both jurisdictions are:
• High-efficiency furnaces;
• High-efficiency tankless water heaters;
• Low-emissivity windows;
• Shell measures and insulation;
• Thermostats and home energy monitoring systems;
• Water-saving devices (low-flow showerheads and faucet aerators); and
• ENERGY STAR/Built Green Washington new homes.
Avista does not capture end-use savings that are attributable to new construction
homes through “New Homes pathways” as the Energy Trust of Oregon (ETO) does.
The New Homes pathways are packages of savings in new construction homes that
span several end-uses. ETO assigns an end-use to each of the offered New Homes
pathways based on the most significant saving end-use of the package4.
Conservation Potential Results – Commercial and
Industrial
The commercial sector provides the next biggest opportunities for savings. Compared to their
portion of baseline consumption, early-year potential in Idaho is significantly lower than in
Washington. Similar to the residential sector, this is a result of the recent “re-start” of DSM
programs in the state of Idaho.
As seen in Table 3.4 above, Avista’s core industrial customers represent a low fraction of the
load, and correspondingly comprise a small percentage of overall potential. Additionally, since
early-year consumption in the industrial sector is very similar between Washington and Idaho,
potential is split roughly in half.
Table 3.7 and Table 3.8 below details the achievable economic conservation potential by
sector for selected years.
4 Avista 2018 IRP Draft DSM Chapter - Energy Trust of Oregon
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 62 of 190
Table 3.7 Commercial Achievable Economic Potential by Selected Years

Cumulative Savings (Dth) 2018 2019 2020 2027 2037
Baseline Projection (Dth)
Washington 6,197,173 6,197,918 6,202,429 6,303,022 6,553,728
Idaho 3,050,738 3,045,031 3,041,291 3,059,255 3,183,220
Total 9,247,911 9,242,949 9,243,720 9,362,277 9,736,948
Natural Gas Cumulative Savings (Dth)
Washington 20,731 44,393 73,253 476,648 994,795
Idaho 7,417 16,035 26,709 205,064 466,736
Total 28,148 60,428 99,963 681,712 1,461,531
% of Total Residential Savings
Washington 74% 73% 73% 70% 68%
Idaho 26% 27% 27% 30% 32%

Table 3.8 Industrial Cumulative Achievable Economic Potential by Selected Years

Cumulative Savings (Dth) 2018 2019 2020 2027 2037
Baseline Projection (Dth)
Washington 251,300 248,912 247,626 233,229 216,423
Idaho 240,261 243,071 244,930 244,029 243,799
Total 491,562 491,983 492,546 477,257 460,222
Natural Gas Cumulative Savings (Dth)
Washington 569 1,132 1,709 5,974 9,916
Idaho 569 1,140 1,718 6,034 9,924
Total 1,138 2,272 3,427 12,007 19,840
% of Total Residential Savings
Washington 50% 50% 50% 50% 50%
Idaho 50% 50% 50% 50% 50%

Table 3.9 identifies the top 20 commercial measures by cumulative savings in 2020. Boilers
are the top measure, followed food preparation and custom HVAC measures. These are
ranked by their combined contribution to Washington and Idaho savings.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 63 of 190
Table 3.9 C&I Top Measures, 2020
Rank Measure / Technology WA ID Total % of Total
1 Boiler - AFUE 97% 22,515 5,909 28,423 27%
2 Fryer - ENERGY STAR 5,648 1,887 7,535 7%
3 Insulation - Roof/Ceiling - R-38 4,061 2,288 6,349 6%
4 Insulation - Wall Cavity - R-21 3,638 1,993 5,631 5%
5 Gas Boiler - Insulate Steam Lines/Condensate Tank - Lines and 3,331 1,975 5,306 5%
6 HVAC - Demand Controlled Ventilation - DCV enabled 2,985 1,679 4,664 5%
7 Water Heater - TE 0.94 3,559 975 4,534 4%
8 Gas Boiler - Hot Water Reset - Reset control installed 3,936 532 4,468 4%
9 Steam Trap Maintenance - Cleaning and maintenance 2,546 1,334 3,880 4%
10 Gas Boiler - Insulate Hot Water Lines - Insulated water lines 2,224 1,318 3,542 3%
Subtotal 54,442 19,890 74,332 72%
Total Savings in Year 74,962 28,427 103,389 100%

Most of the commercial and industrial conservation potential exists within space heating and
water heating applications. Food preparation, process and miscellaneous represents a
smaller proportion of potential. One large measure that is not represented in the achievable
economic potential is commercial HVAC retrocommissioning. For this measure, AEG updated
the savings assumption from the Seventh Plan’s value of roughly 15% of heating load to 7%
to reflect space heating’s higher end-use share of consumption. For further details on this
adjustment and other top measures, please refer to the natural gas CPA provided in Appendix
3.1. Primary sources of commercial and industrial sector achievable savings are:
• Equipment upgrades for furnaces, boilers and unit heaters;
• High R-value roof/ceiling and wall insulation
• Energy management systems and programmable thermostats:
• High thermal efficiency water heaters
• Boiler operating measures such as maintenance;
• Hot water reset and efficient circulation; and
• Food service equipment.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 64 of 190
Achievable Economic Conservation Potential Results
Tables 3.10 and 3.11 provide the 2018-2020 CPA identified conservation opportunity for
Washington and Idaho, respectively.
Table 3.10: Washington Natural Gas Target (2018-2020)9
Incremental Annual Savings (Dth) 2018 2019 2020
Residential 39,979 48,188 63,970
Commercial & Industrial 21,300 24,330 29,665
Total 61,279 72,518 93,635
Table 3.11: Idaho Natural Gas Target (2018-2020)
Incremental Annual Savings (Dth) 2018 2019 2020
Residential 18,354 22,851 30,784
Commercial & Industrial 7,986 9,232 11,343
Total 26,340 32,083 42,127

Figure 3.2 presents the cumulative energy savings for the 2018 to 2020 period by end use,
for each sector and state. Space heating makes a majority of the potential, followed by
water heating. Food preparation equipment upgrades provide savings in the Commercial
sector.

Figure 3.2 – Conservation Potential by End Use, 2020 (Dth)

0
20,000
40,000
60,000
80,000
100,000
120,000
140,000
160,000
Washington Idaho Washington Idaho
Residential C&I
Dt
h
Space Heating
Secondary Heating
Water Heating
Appliances
Commercial Food Prep
Industrial Process
Miscellaneous
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 65 of 190
Achievable Potential Factor Application
The development of achievable potential factors is an important step when estimating
achievable levels of potential. As part of the CPA, AEG took steps to more closely align with
the NPCC’s Seventh Electric Power Plan Methodology. As part of the Plan, the NPCC
developed a suite of achievable “ramp rates” based on accomplishment data for various
electric EE measures and programs. They then projected them forward on a diffusion curve,
capping achievability at 85% of technical potential by the end of the 20-year planning period
for non-emerging measures.
As a starting point for the CPA, AEG applied these ramp rates to similar natural gas measures
where an electric analog was available. Since these were developed with electric DSM
programs in mind, AEG then adjusted the ramp rates following a similar course of action. AEG
reviewed Avista’s recent program accomplishment data and either 1) reassigned ramp rates
or 2) accelerated/decelerated the mapped ramp rates to align with actual participation in
Avista’s natural gas DSM programs. Remapping was used primarily when a measure’s actual
performance was significantly different than the electric ramp rate suggested while
acceleration/deceleration was used for more moderate adjustments. The result of this step
was a remapping of heating and food preparation equipment measures to faster ramp rates
and deceleration of weatherization measure installations to reflect lower program
participation. This process was conducted for the Washington and Idaho territories
separately, resulting in lower early-year potential in Idaho to reflect the DSM program re-start
referenced in the sections above.
In the longer-term, all of the Seventh Plan’s non-emerging ramp rates reach a steady-state
achievability of 85% of technical potential. This value is intended to represent both potential
realized within utility DSM programs and potential through non-utility delivery mechanisms
such as naturally occurring efficiency, market transformation, and new future codes and
standards. Using this methodology, potential captured after the first year or two of the CPA
includes a portion of additional potential outside Avista’s direct control. To account for this
and provide Avista with the utility-specific targets in Table 3.8 and Table 3.9, AEG slowed the
“ramp-up” of these measures by 50% in years two and three then re-accelerated the ramp
rates, so they re-align after year six. This adjustment is intended to estimate utility-specific
goals for the program planning process yet capture all achievable, cost-effective potential
(even potential realized through non-utility DSM mechanisms) in the later years of the study
period.
Natural Gas IRP Target - Historical Trends 2014-2020
Figure 3.3 and 3.4 below illustrate the historical trend in natural gas IRP targets since 2014.
2018 targets were selected by the 2016 IRP and align well, but are not an exact match with
the CPA results for 2018.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 66 of 190
Figure 3.3: Washington Natural Gas IRP Targets
Figure 3.4: Idaho Natural Gas IRP Targets5

5 Avista’s Idaho natural gas DSM programs were suspended in 2013, 2014 and 2015 (2013 saw some activity due to prior
commitments). Avista filed for and was approved to reinstate its Idaho Natural Gas DSM programs January 1, 2016.
131,000 128,700
73,700
48,911
61,283
72,518
93,635
2014 2015 2016 2017 2018 PRELIM
2019
PRELIM
2020
Dt
h

S
a
v
i
n
g
s
45,600
22,800
11,400
19,764
24,644
32,083
42,127
2014 2015 2016 2017 2018 PRELIM
2019
PRELIM
2020
Dt
h

S
a
v
i
n
g
s
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 67 of 190
Uses and Applications of the CPA
It is useful to place the IRP process and the CPA component of that process into the larger
perspective of Avista’s efforts to acquire all available cost-effective conservation resources.
Activities outside the immediate scope of the IRP process include the formal annual
conservation planning and annual cost-effectiveness and acquisition reporting processes in
addition to the ongoing management of the DSM portfolio.
The IRP leads to the establishment of a 20-year avoided cost stream that is essential to
determining the quantity of DSM resources that are cost-effective when compared to the CPA-
identified conservation supply curve and the management of the DSM portfolio between the
two-year IRP cycles. The many related and coordinated processes all contribute to the
planning and management of the DSM portfolio towards meeting its cost-effectiveness and
acquisition goals.
The relationship between the CPA and the annual conservation planning process is of
particular note. The CPA is regarded as a high-level tool that is useful for establishing
aggregate targets and identifying general target markets and target measures. However, the
CPA of necessity must make certain broad assumptions regarding key characteristics that
are fine-tuned as part of the creation of an operational business plan. Some of the
assumptions that are most frequently modified include market segmentation, customer
eligibility, measure definition, incentive level, interaction between measures and the
opportunities for packaging measures or coordinating the delivery of measures.
One issue that inevitably arises as part of moving from the CPA analysis to the annual
conservation planning process is the treatment of market segments. The CPA defines market
segments (e.g. by residential building type or vintage) to appropriately define the cost-
effective potential for efficiency options and to ensure consistency with system loads and load
forecasts. However, it is often infeasible to recognize these distinctions on an operational
basis. This may result in aggregations of market segments into programs that could lead to
more or less operationally achievable savings.
A second issue that often arises is the “clumpiness” that often occurs with large commercial
and industrial projects. Large natural gas conservation projects typically have long lead times
with multiple years between the original customer contact and design of a project to the final
completion with any required measurement and verification. These projects can lead to over
or underperforming targets in individual years but typically average out over the 20-year time
frame of an IRP.
Conservation Action Plan
The analytical process for the CPA is based on a deterministic model as compared to the
assumptions within the Expected Case. In order to further enhance the Company’s analytical
methodology, Avista will focus on the following:
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 68 of 190
• Recreate the Sendout model and inputs into a new Excel based methodology. This
methodology will allow flexibility to model DSM and other potential supply side
resources on a case by case basis.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 69 of 190
Energy Trust of Oregon:
Background
Energy Trust of Oregon, Inc. (Energy Trust) is an independent nonprofit organization
dedicated to helping utility customers in Oregon and southwest Washington benefit from
saving energy and generating renewable power. Energy Trust funding comes exclusively
from utility customers and is invested on their behalf in lowest-cost energy efficiency and
clean, renewable energy. In 1999, Oregon energy restructuring legislation (SB 1149)
required Oregon’s two largest electric utilities—PGE and Pacific Power—to collect a public
purpose charge from their customers to support energy conservation in K-12 schools, low-
income housing energy assistance, and energy efficiency and renewable energy programs
for residential and business customers.6

In 2001, Energy Trust entered into a grant agreement with the Oregon Public Utility
Commission (OPUC) to invest the majority of revenue from the 3 percent public purpose
charge in energy efficiency and renewable energy programs. Every dollar invested in energy
efficiency by Energy Trust will save residential, commercial and industrial customers nearly
$3 in deferred utility investment in generation, transmission, fuel purchase and other costs.
Appreciating these benefits, natural gas companies asked Energy Trust to provide service
to their customers—NW Natural in 2003, Cascade Natural Gas in 2006 and Avista in 2017.
These arrangements stemmed from settlement agreements reached in Oregon Public Utility
Commission processes.

Energy Trust’s model of delivering energy efficiency programs unilaterally across the service
territories of the five gas and electric utilities they serve has experienced a great deal of
success. Since the inception of the organization in 2002, Energy Trust has saved more than
607 aMW of electricity and 52 million annual therms. This equates to more than 20 million
tons of CO2 emissions avoided and is a significant factor relatively flat or lower energy sales
observed by both gas and electric utilities from 2007 to 2016, as shown in OPUC utility
statistic books.7

6 In 2007, Oregon’s Renewable Energy Act (SB 838) allowed the electric utilities to capture additional, cost-effective electric efficiency
above what could be obtained through the 3 percent charge, thereby avoiding the need to purchase more expensive electricity. This
new supplemental funding, combined with revenues from natural gas utility customers, increased Energy Trust revenues from about
$30 million in 2002 to $148.9 million in 2016.
7 OPUC 2016 Stat book – 10 Year Summary Tables: http://www.puc.state.or.us/docs/statbook2016WEB.pdf
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 70 of 190
Energy Trust serves residential, commercial and firm industrial customers in Avista’s natural
gas service territory in the areas of Medford, Klamath Falls, and La Grande, Oregon. 2017
was the first full year of Energy Trust’s service to Avista customers and programs achieved
107% of goal – 341K therms achieved of the 318K therms goal, as shown in 3.5.

Figure 3.5 – 2017 Achieved Savings vs. Goals for Avista Service Territory

In addition to administering energy efficiency programs on behalf of the utilities, Energy
Trust also provides each utility with a 20-year DSM resource forecast to identify cost-
effective savings potential. This forecast also examines how much of that potential is
estimated to be achieved by Energy Trust over the 20-year period. The results are used by
Avista and other utilities in Integrated Resource Plans (IRP) to inform the resource potential
in their territory and reduce their load forecast over the IRP period to meet their customer’s
projected load.
Energy Trust 20-Year Forecast Methodology

20-Year Forecast Overview
Energy Trust developed a 20-year DSM resource forecast for Avista using Energy Trust’s
DSM resource assessment modeling tool (hereinafter ‘RA Model’) to identify the total 20-
year cost-effective modeled savings potential, which is ‘deployed’ exogenously of the model
to estimate the final savings forecast. There are four types of potential that are calculated to
develop the final savings potential estimate, which are shown in 3.6 and discussed in
greater detail in the sections below.

0
50,000
100,000
150,000
200,000
250,000
300,000
350,000
400,000
Residential Commercial Industrial Avista Total
Annual Goal (therms)Actuals (therms)
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 71 of 190
Figure 3.6: Types of Potential Calculated in 20-year Forecast Determination
Not
Technically
Feasible
Technical Potential
Calculated within RA
Model
Market
Barriers
Achievable Potential (85% of Technical Potential)
Not Cost-
Effective
Cost-Effective Achiev.
Potential
Program
Design &
Market
Penetration
Final Program
Savings Potential
Developed
with
Other
Market
The RA Model utilizes the modeling platform Analytica®8, an object-flow based modeling
platform that is designed to visually show how different objects and parts of the model
interrelate and flow throughout the modeling process. The model utilizes multidimensional
tables and arrays to compute large, complex datasets in a relatively simple user interface.
Energy Trust then deploys this cost-effective potential exogenously to the RA model into an
annual savings projection based on past program experience, knowledge of current and
developing markets, and future codes and standards. This final 20-year savings projection
is provided to Avista for inclusion in in their SENDOUT® Model as a reduction to demand on
the system.

20-Year Forecast Detailed Methodology
Energy Trust’s 20-year forecast for DSM savings follows six overarching steps from initial
calculations to deployed savings, as shown in Figure 1.7. The first five steps in the varying
shades of blue nodes - Data Collection and Measure Characterization to Cost-Effective
Achievable Energy Efficiency Potential - are calculated within Energy Trust’s RA Model.
This results in the total cost-effective potential that is achievable over the 20-year forecast.
The actual deployment of these savings (the acquisition percentage of the total potential
each year, represented in the green node of the flow chart) is done exogenously of the RA
model. The remainder of this section provides further detail each of the steps shown below.

8 http://www.lumina.com/why-analytica/what-is-analytica1/
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 72 of 190
Figure 3.7: Energy Trust’s 20-Year DSM Forecast Determination Flow Chart

1. Data Collection and Measure Characterization
The first step of the modeling process is to identify and characterize a list of measures to
include in the model, as well as receive and format utility ‘global’ inputs for use in the model.
Energy Trust compiles and loads a list of commercially available and emerging technology
measures for residential, commercial, industrial and agricultural applications installed in new
or existing structures. The list of measures is meant to reflect the full suite of measures
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 73 of 190
offered by Energy Trust, plus a spectrum of emerging technologies.9 Simultaneous to this
effort, Energy Trust collects necessary data from the utility to run the model and scale the
measure level savings to a given service territory (known as ‘global inputs’).
• Measure Level Inputs:
Once the measures to include in the model have been identified, they must be
characterized in order to determine their savings potential and cost-effectiveness.
The characterization inputs are determined through a combination of Energy Trust
primary data analysis, regional secondary sources10, and engineering analysis.
There are over 30 measure level inputs that feed into the model, but on a high
level, the inputs are put into the following categories:
1. Measure Definition and Equipment Identification: This is the
definition of the efficient equipment and the baseline equipment it is
replacing (e.g. a 95% EF furnace replacing an 80% EF baseline furnace).
A measure’s replacement type is also determined in this step – Retrofit
(RET), Replace on Burnout (ROB), or New Construction (NEW).
2. Measure Savings: the kWh or therms savings associated with an
efficient measure calculated by comparing the baseline and efficient
measure consumptions.
3. Incremental Costs: The incremental cost of an efficient measure over
the baseline. The definition of incremental cost depends upon the
replacement type of the measure. If a measure is a RET measure, the
incremental cost of a measure is the full cost of the equipment and
installation. If the measure is a ROB or NEW measure, the incremental
cost of the measure is the difference between the cost of the efficient
measure and the cost of the baseline measure.
4. Market Data: Market data of a measure includes the density,
saturation, and suitability of a measure. A density is the number of
measure units that can be installed per scaling basis (e.g. the average
9 An emerging technology is defined as technology that is not yet commercially available, but is in some stage of
development with a reasonable chance of becoming commercially available within a 20-year timeframe. The model is
capable of quantifying costs, potential, and risks associated with uncertain, but high-saving emerging technology
measures. The savings from emerging technology measures are reduced by a risk-adjustment factor based on what
stage of development the technology is in. The working concept is that the incremental risk-adjusted savings from
emerging technology measures will result in a reasonable amount of savings over standard measures for those few
technologies that eventually come to market without having to try and pick winners and losers.
10 Secondary Regional Data sources include: The Northwest Power Planning Council (NWPPC), the Regional Technical
Forum (the technical arm of the NWPPC), and market reports such as NEEA’s Residential and Commercial Building Stock
Assessments (RBSA and CBSA)
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 74 of 190
number of showers per home for showerhead measures). The saturation is
the average saturation of the density that is already efficient (e.g. 50% of
the showers already have a low flow showerhead). Suitability of a measure
is a percentage input to represent the percent of the density that the
efficient measure is actually suitable to be installed in. These data inputs
are all generally derived from regional market data sources such as
NEEA’s Residential and Commercial Building Stock Assessments (RBSA
and CBSA).
• Utility Global Inputs:
The RA Model requires several utility level inputs to create the DSM forecast.
These inputs include:
1. Customer and Load Forecasts: These inputs are essential to scale the
measure level savings to a utility service territory. For example, residential
measures are characterized on a scaling basis ‘per home’, so the measure
densities are calculated as the number of measures per home. The model
then takes the number of homes that Avista serves currently and the
forecasted number of homes to scale the measure level potential to their entire
service territory.
2. Customer Stock Demographics: These data points are utility specific and
identify the percentage of stock that utilize different heating fuels for both
space heating and water heating. The RA Model uses these inputs to segment
the total stocks to the stocks that are applicable to a measure (e.g. gas
storage water heaters are only applicable to customers that have gas water
heat).
3. Utility Avoided Costs: Avoided costs are the net present value of avoided
energy purchases and delivery costs associated with energy efficiency savings
represented as $s per therm saved. These values are provided by Avista and
the components are discussed in other sections of this IRP. Avoided costs are
the primary ‘benefit’ of energy efficiency in the cost-effectiveness screen.

2. Calculate Technical Energy Efficiency Potential
Once measures have been characterized and utility data loaded into the model, the next
step is to determine the technical potential of energy that could be saved. Technical
potential is defined as the total potential of a measure in the service territory that could
be achieved regardless of market barriers, representing the maximum potential energy
savings available. The model calculates technical potential by multiplying the number of
applicable units for a measure in the service territory by the measure’s savings. The Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 75 of 190
model determines the total number of applicable units for a measure utilizing several of
the measure level and utility inputs referenced above:

Total applicable units = Measure Density * Baseline Saturation * Suitability Factor * Heat Fuel
Multipliers (if applicable) * Total Utility Stock (e.g. # of homes)
Technical Potential =Total Applicable Units * Measure Savings

The measure level technical potential is then summed up to show the total technical
potential across all sectors. This savings potential does not take into account the various
market barriers that will limit a 100 percent adoption rate.
3. Calculate Achievable Energy Efficiency Potential
Achievable potential is simply a reduction to the technical potential by 15 percent, to
account for market barriers that prevent total adoption of all cost-effective measures.
Defining the achievable potential as 85 percent of the technical potential is the generally
accepted method employed by many industry experts, including the Northwest Power
and Conservation Council (NWPCC) and National Renewable Energy Lab (NREL).

Achievable Potential =Technical Potential * 85%

4. Determine Cost-effectiveness of Measure using TRC Screen
The RA Model screens all DSM measures in every year of the forecast horizon using the
Total Resource Cost (TRC) test, a benefit-cost ratio (BCR) that measures the cost-
effectiveness of the investment being made in an efficiency measure. This test evaluates
the total present value of benefits attributable to the measure divided by the total present
value of all costs. A TRC test value equal to or greater than 1.0 means the value of
benefits is equal to or exceeds the costs of the measure, and is therefore cost-effective
and contributes to the total amount of cost-effective potential. The TRC is expressed
formulaically as follows:

TRC = Present Value of Benefits / Present Value of Costs

Where the Present Value of Benefits includes the sum of the following two
components:
a) Avoided Costs: The present value of natural gas energy saved over the life of the
measure, as determined by the total therms saved multiplied by Avista’s avoided
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 76 of 190
cost per therm. The net present-value of these benefits is calculated based on the
measure’s expected lifespan using the company’s discount rate.
b) Non-energy benefits are also included when present and quantifiable by a
reasonable and practical method (e.g. water savings from low-flow showerheads,
operations and maintenance (O&M) cost reductions from advanced controls).

Where the Present Value of Costs includes:
Incentives paid to the participant; and
a) The participant’s remaining out-of-pocket costs for the installed cost of the
measures after incentives, minus state and federal tax credits.
b) The cost-effectiveness screen is a critical component for Energy Trust modeling
and program planning because Energy Trust is only allowed to incentivize cost-
effective measures, unless an exception has been granted by the OPUC.

5. Quantify the Cost-Effective Achievable Energy Efficiency Potential
The RA Model’s final output of potential is the quantified cost-effective achievable potential.
If a measure passes the TRC test described above, then achievable savings (85% of
technical potential) from a measure is included in this potential. If the measure does not
pass the TRC test above, the measure is not included in cost-effective achievable potential.
However, the cost-effectiveness screen is overridden for some measures under two specific
conditions:
1. The OPUC has granted an exception to offer non-cost-effective measures under
strict conditions or,
2. When the measure isn’t cost-effective using utility specific avoided costs but the
measure is cost-effective when using blended gas avoided costs for all of the gas
utilities Energy Trust serves and is therefore offered by Energy Trust programs.

6. Deployment of Cost-Effective Achievable Energy Efficiency Potential
After determining the 20-year cost-effective achievable modeled potential, Energy Trust
develops a savings projection based on past program experience, knowledge of current
and developing markets, and future codes and standards. The savings projection is a
20-year forecast of energy savings that will result in a reduction of load on Avista’s
system. This savings forecast includes savings from program activity for existing
measures and emerging technologies, expected savings from market transformation
efforts that drive improvements in codes and standards, and a forecast of what Energy
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 77 of 190
Trust is describing as a ‘megaproject adder’. The ‘megaproject adder’ is characterized as
savings that account for large unidentified projects that consistently appear in Energy
Trust’s historic savings record and have been a source of overachievement against IRP
targets in prior years for other utilities that Energy Trust serves.

3.8 below reiterates the types of potential shown in 3.6, and how the steps described
above and in the flow chart fit together.
Figure 3.8 - The Progression to Program Savings Projections
Data Collection and Measure Characterization Step 1
Not
Technically
Feasible
Technical Potential Step 2
Market
Barriers
Achievable Potential
(85% of Technical Potential) Step 3
Not Cost- Effective
Cost-Effective Achiev.
Potential Steps 4 & 5
Design &
Market
Final Program
Savings Potential
Step 6

Forecast Results
The results will be shown in several different sections, as the RA model and the final
savings projections have different output capabilities. The RA model provides outputs in a
variety of different ways, including by segment, end use, and supply curves. The final
savings projection is provided by segment and program delivery type.

RA Model Results – Technical, Achievable and Cost-Effective Achievable Potential
The RA Model produces results by potential type, as well as several other useful outputs,
including a supply curve based on the levelized cost of energy efficiency measures. This
section discusses the overall model results by potential type and provides an overview of
the supply curve.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 78 of 190
Forecasted Savings by Sector
Table summarizes the technical, achievable, and cost-effective potential for Avista’s system
in Oregon. These savings represent the total 20-year cumulative savings potential identified
in the RA Model by the three types identified in Figure and Figure . Modeled savings
represent the full spectrum of potential identified in Energy Trust’s resource assessment
model through time, prior to deployment of these savings into the final annual savings
projection.
Table 3.12 - Summary of Cumulative Modeled Savings Potential - 2018–2037
Sector Technical Potential
(Million Therms)
Achievable Potential
(Million Therms)
Achievable Potential
(Million Therms)
20.0 17.0 10.6
Commercial 13.3 11.3 6.3
Industrial 0.3 0.3 0.3
Total 33.5 28.5 17.2
Figure 3.9 shows cumulative forecasted savings potential across the three sectors Energy
Trust serves, as well as the type of potential identified in Avista’s service territory.
Residential sales make up the majority of Avista’s service in Oregon, which is reflected in
the potential. Firm industrial sales represent a low percentage of the total sales in Oregon
for Avista, and subsequently shows very little savings potential (Avista’s interruptible and
transport customers are not eligible to participate in Energy Trust programs). 83% of the
industrial technical potential is cost-effective, while the residential and commercial sectors
cost-effective achievable potential are 53% and 47% of technical potential respectively.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 79 of 190
Figure 3.9 - Savings Potential by Sector – Cumulative 2018–2037 (Millions of
Therms)

Cost-Effective Achievable Savings by End-Use
Figure 3.10 below provides a breakdown of Avista’s 20-year cost-effective DSM savings
potential by end use.

Figure 3.10: 20-year Cost-Effective Cumulative Potential by End Use

-
5
10
15
20
25
Residential Commercial Industrial
Mi
l
l
i
o
n
s

o
f

T
h
e
r
m
s
Technical Achievable Cost-effective achievable
Appliance
0.4%Behavioral
14%
Cooking
4%
Water Heating
31%
Other
2%
Process Heating
1%
Weatherization
20%
HVAC
28%
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 80 of 190
As expected for a gas utility, the top saving end uses are water heating, HVAC and
weatherization. A large portion of the water heating end-use is attributable to new
construction homes due to how Energy Trust assigns end uses to the offered New Homes
pathways. The New Home pathways are packages of savings in new construction homes
that span several end-uses. Energy Trust assigns an end-use to each of the offered New
Homes pathways based on the most significant saving end-use of the package. For
example, the most cost-effective New Home pathway that was identified by the model
(because it achieves the most savings for the least cost) was designated as a water heating
end-use, though the package includes several other efficient gas equipment measures.

In addition to the New Homes pathway savings, the water heating end-use includes water
heating equipment from all sectors, as well as showerheads and aerators. Weatherization
and HVAC end uses represent the savings associated with space heating equipment,
retrofit add-ons, and new construction packages. Behavioral consists primarily of potential
from Energy Trust’s commercial strategic energy management measure, a service where
Energy Trust energy experts provide training to facilities teams and staff to identify
operations and maintenance changes that make a difference in a building’s energy use.

Contribution of Emerging Technologies
As mentioned earlier in this report, Energy Trust includes a suite of emerging technologies
(ETs) in its model. The emerging technologies included in the model are listed in 3.13.
Table 3.13 - Emerging Technologies Included in the Model
• Path 5 Emerging Super
Efficient Whole Home
• Window Replacement (U<.20)
• Window Attachments
• Absorption Gas Heat Pump
Water Heaters
• Advanced Insulation
• Behavior Competitions
Controls
• DOAS/HRV
• DHW Circulation Pump
• Gas-fired HP HW
• Gas-fired HP, Heating
• Zero Net Energy Path
• AC Heat Recovery, HW
Heater
• Wall Insulation- VIP,
R0-R35

Energy Trust recognizes that emerging technologies are inherently uncertain, and utilizes a
risk factor to hedge against that risk. The risk factor for each emerging technology is used to
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 81 of 190
characterize the inherent uncertainty in the ability for ETs to produce reliable future savings.
This risk factor was determined based on qualitative metrics of:
• Market risk
• Technical risk
• Data source risk

The framework for assigning the risk factor is shown in Table 3.14.14. Each ET was
assessed within each risk category; a total weighted score was then calculated. Well-
established and well-studied technologies have lower risk factors while nascent,
unevaluated technologies (e.g., gas absorption heat pump water heaters) have higher risk
factors. This risk factor was then used as a multiplier of the incremental savings potential of
the measure.

Table 3.14 - Emerging Technology Risk Factor Score Card ET Risk Factor
Category
Risk
(25%
weighting)
• Requires new/changed business model • Start-up, or small manufacturer • Significant changes to infrastructure • Requires training of contractors. Consumer acceptance barriers
Low Risk:
• Trained contractors • Established business models • Already in U.S. Market • Manufacturer committed to
commercialization
Risk
(25%
weighting)

Prototype in first
field tests.
A single or
unknown
approach
manufacturer.
Limited experience
broad commercial
appeal
in different
application or
different region
Low Risk:
Proven
technology in
target
application.
Multiple
potentially
viable
approaches.
Data
Source
Risk
(50%
weighting)
Based
only on
manufacturer
claims
studies assessment or lab
test
study (real world
installation)
Low Risk:
Evaluation
results or
multiple third
party case
studies

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 82 of 190
Figure 3.11 below shows the amount of emerging technology savings within each type of
DSM cumulative potential. While emerging technologies make up a relatively large
percentage of the technical and achievable potential, nearly 25%, once the cost-
effectiveness screen is applied, the relative share of emerging technologies drops
significantly to about 5% of total cost-effective achievable potential. This is due to the fact
that many of these technologies are still in early stages of development and are quite
expensive. Though Energy Trust includes factors to account for forecasted decreases in
cost and increased savings from these technologies over time, some are still never cost-
effective over the planning horizon or do not become cost-effective until later years.

Figure 3.11 – Cumulative Contribution of Emerging Technologies by Potential Type

Cost-Effective Override Effect
3.15 shows the savings potential in the RA model that was added by employing the cost-
effectiveness override option in the model. As discussed in the methodology section, the
cost-effectiveness override option forces non-cost-effective potential into the cost-effective
potential results and is used when a measure meets one of the following two criteria:
1. A measure is offered under an OPUC exception.
2. When the measure isn’t cost-effective using Avista-specific avoided costs but the
measure is cost-effective when using blended gas avoided costs for all of the gas
utilities Energy Trust serves and is therefore offered by Energy Trust programs.
23%
23%
5%
-
5
10
15
20
25
30
35
40
Technical Achievable Cost-Effective Achievable
Mi
l
l
i
o
n
s

o
f

T
h
e
r
m
s
Conventional Emerging
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 83 of 190
Table 3.15 - Cumulative Cost-Effective Potential (2018-2037) due to Cost-effectiveness override (millions of therms)
Sector Override Override Difference
10.63 8.33 2.30
6.32 6.32 -
0.26 0.26 -

In this IRP, 13% of the cost-effective potential identified by the model is due to the use of
the cost-effective override for measures with exceptions. The measures that had this option
applied to them included 0.67-0.69 Efficiency factor (EF) gas storage water heaters and
attic, floor, and wall insulation in the Residential Sector.

Supply Curves and Levelized Cost Outputs
An additional output of the RA Model is a resource supply curve developed from the
levelized cost of energy of each measure. The supply curve graphically depicts the total
potential therms that could be saved at various costs for all measures. The levelized cost for
each measure is determined by calculating the present value of the total cost of the
measure over its economic life, per therm of energy savings ($/therm saved). The levelized
cost calculation starts with the customer’s incremental TRC of a given measure. The total
cost is amortized over an estimated measure lifetime using the Avista’s discount rate
provided to Energy Trust. The annualized measure cost is then divided by the annual
therms savings. Some measures have negative levelized costs because non-energy
benefits amortized over the life of the measure are greater than the total cost of the
measure over the same period.

Figure 3.12 below shows the supply curve developed for this IRP that can be used for
comparing demand-side and supply-side resources. The cost threshold shown with a star
on the supply curve line represents the approximate levelized cost cutoff that corresponds
with the amount of TRC determined cost-effective DSM potential identified by the RA Model
in the 2018, when ordering all measures based on their levelized cost.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 84 of 190
Figure 3.12 – Gas Supply Curve ($ per therm saved)

Deployed Results – Final Savings Projection
The results of the final savings projection show that Energy Trust can save 1.65 million
therms across Avista’s system in Oregon in the next five years from 2018 to 2022 and over
8.5 million therms by 2037. This represents an 8.7 percent cumulative load reduction by
2037 and is an average of just under a 0.5 percent incremental annual load reduction. The
cumulative final savings projection is shown in Table 3.16 compared to the technical,
achievable and cost –effective achievable potential.

-
5.00
10.00
15.00
20.00
25.00
30.00
35.00
-$
3
.
5
4
-$
2
.
0
1
$0
.
0
0
$0
.
0
0
$0
.
0
2
$0
.
0
3
$0
.
0
5
$0
.
1
0
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.
1
7
$0
.
2
1
$0
.
2
6
$0
.
2
7
$0
.
3
8
$0
.
4
0
$0
.
4
8
$0
.
6
6
$1
.
0
0
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.
3
0
$1
.
5
7
$1
.
8
6
$3
.
1
6
$5
.
2
5
$6
.
3
5
$9
.
6
4
$1
4
.
4
8
$8
5
.
1
8
Mi
l
l
i
o
n
s

o
f

T
h
e
r
m
s
Levelized Total Resouce Cost of Measures $/Therm
Approximate Cost-
Effective Cutoff
(~$0.97/therm)
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 85 of 190
Table 3.16: 20-Year Cumulative savings potential by type, including final savings projection (Millions of Therms)
Technical
Potential
Achievable
Potential
Cost-
Effective
Potential
Deployed
Savings
Projection
20.0 17.0 10.6 5.2
13.3 11.3 6.3 3.3
0.3 0.3 0.3 0.2
33.5 28.5 17.2 8.8

The final deployed savings projection is just over half of the modeled cost-effective
achievable potential. There are several reasons for this additional step down in savings:
1. “Lost Opportunity Measures” – Measures that are meant to replace failed equipment
(ROB) or new construction measures (NEW) are considered lost opportunity
measures because programs have one opportunity to influence the installation of
efficient equipment over code baseline when the existing equipment fails or when the
new building is built. This is because these measures must be installed at that
specific point in time, and if a program administrator misses the opportunity to
influence the installation of more efficient equipment, the opportunity is lost until the
equipment fails again. Energy Trust expects that most of these opportunities will be
met in later years as efficient equipment becomes more readily adopted. However, in
early years, the level of acquisition for these opportunities is smaller and ramps
higher as time progresses.
2. “Hard to Reach Measures” – some measures that show high savings potential are
notoriously hard to reach and are capped at 67% of total retrofit potential. These
measures include insulation and windows.
3. New service territory – Avista is a new service territory for Energy Trust as of 2016
and it takes a few years for Energy Trust trade ally networks and systems become
established in new areas, which is reflected in this deployment. In territories where
programs are already established, Energy Trust expects to achieve 100% penetration
of all cost-effective retrofit potential and ramp to 100% penetration of lost opportunity
measure potential in the later years of the 20-year forecast. For this forecast, these
metrics have been reduced to 85% to reflect that Energy Trust programs are not yet
fully established in Avista territory.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 86 of 190
Figure 3.13 below shows the annual savings projection by sector and measure type. The
initial drop in savings from 2018 to 2019 is due to the expiration of market transformation
savings being claimed by the Residential New Homes program from past building code
changes. Most other sector and measure types ramp up over the forecast period, reflecting
the NWPCC ramp rates and methodology to achieve as much cost-effective potential as
possible.
Figure 3.13 – Annual Deployed Final Savings Potential by Sector and Measure Type (Millions
of Therms)

Finally, Figure 3.14 shows the annual and cumulative savings as a percentage of Avista’s
load forecast in Oregon. Annually, the savings as a percentage of load varies from about
0.35% at its lowest to 0.53% at its highest, as represented on the left Y-axis of the graph
and the blue line. Cumulatively, the savings as a percentage of load builds to 8.7% by 2037,
shown on the right Y-axis and the gold line.

-
0.10
0.20
0.30
0.40
0.50
0.60
Mega-Project Adder
RES-ROB
RES-RET
RES-NEW
Ind-ROB
Ind-RET
Com-SEM
Com-ROB
Com-RET
Com-NEW
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 87 of 190
Figure 3.14 – Annual and Cumulated Forecasted Savings as a Percentage of Annual and Cumulative Load Forecasts

Deployed Results – Peak Day Results
In the state of Oregon and around the region, there is an increased focus on peak day
savings contributions of energy efficiency and their impact on capacity investments. This
new focus has led some utilities to embark on targeted load management efforts for
avoiding or delaying distribution system reinforcements. Additionally, the OPUC is
recommending that all investor-owned gas utilities review and consider the DSM capacity
contribution analysis that NW Natural developed in recent years. Therefore, Avista and
Energy Trust have collaborated to develop estimates of peak day contributions from the
energy efficiency measures that Energy Trust forecasts to install.

Peak day coincident factors are the percentage of annual savings that occur on a peak day
over the total year, which are shown in Table 3.17 below. As mentioned, Avista is still
reviewing this methodology and for the purpose of this analysis, Energy Trust utilized the
peak day factors that are currently being used in Energy Trust’s avoided costs. These
include residential and commercial space heating factors developed by NW Natural in
2016and hot water, process load (flat) and clothes washer factors sourced from the
Northwest Power and Conservation Council for electric measures that are analogous to gas
equipment. The peak day factors are the highest for the space heating load shapes, which
0.00%
1.00%
2.00%
3.00%
4.00%
5.00%
6.00%
7.00%
8.00%
9.00%
10.00%
0.00%
0.10%
0.20%
0.30%
0.40%
0.50%
0.60%
%
o
f

C
u
m
u
l
a
t
i
v
e

L
o
a
d
%
o
f

A
n
n
u
a
l

L
o
a
d
Annual % of Load Savings Cumulative % of Load Savings
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 88 of 190
aligns with a typical winter system peak of natural gas utilities. These peak day factors will
be reviewed and updated by Avista to be specific to Avista’s Oregon service territory in the
next IRP.
Table 3.17 - Peak Day Coincident Factors by Load Profile
Residential Space Heating 2.10% NW Natural
Commercial Space Heating 1.80% NW Natural
Water Heating 0.40% NWPCC
Clothes Washer 0.20% NWPCC
Process Load 0.30% NWPCC

Figure 3.15 below shows the annual, deployed peak day savings potential based upon the
results of the 20-year forecast. Each measure analyzed is assigned a load shape and the
appropriate peak day factor is applied to the annual savings to calculate the overall DSM
contribution to peak day capacity. Cumulatively, this is equal to 110,551 therms, or 1.3% of
the total deployed savings potential in Avista’s Oregon service territory over the 20-year
forecast, as shown in Table 3.18 below.

Figure 3.15: Annual Deployed Peak Day DSM Savings Contribution by Sector (Therms)

-
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
2018 201920202021 2022 2023 202420252026 2027 2028 2029 203020312032 2033 2034 203520362037
Commercial Residential Industrial
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 89 of 190
Table 3.18: Cumulative Deployed Peak Day DSM Savings Contribution by Sector (Therms)
Sector Cumulative Peak Day Savings
(Therms) % of Overall Sector Savings
Commercial 35,263 0.7%
Residential 73,749 2.2%
Industrial 1,538 0.7%
Total 110,551 1.3%

Conclusion
Avista has a long-term commitment to responsibly pursuing all available and cost-effective
efficiency options as an important means to reduce its customer’s energy cost. Cost-effective
demand-side management options are a key element in the Company’s strategy to meet
those commitments. Falling avoided costs and lower growth in customer demand have led to
a reduced role for conservation in the overall natural gas portfolio compared with IRPs done
prior to 2012, however, a regulatory shift to utilizing the UCT in Washington and Idaho DSM
programs will continue to provide a vital role in offsetting future natural gas load growth. The
company transitioned its Oregon DSM regular income, commercial, and industrial customer
programs to the Energy Trust of Oregon (ETO), with the ETO being the sole administrator
effective January 1, 2017. Avista is continuing to adaptively manage its DSM programs in
response to the ever-shifting economic climate.
Perhaps of most importance in the long-term are the Company’s ongoing efforts to work with
key regional players to develop a regional natural gas market transformation organization and
portfolio. The Northwest Energy Efficiency Alliance (NEEA) has been executing the first
stages of their 2015 - 2019 Natural Gas Market Transformation Business Plan. While there
has not yet been any savings realized, there has been many studies and efforts towards
meeting their goals. NEEA is currently working to develop their 2020 – 2024 Business Plan
and we look forward to the conservation opportunities that arise out of their work in the coming
years.
Market transformation is not itself called out within the CPA since the CPA focuses upon
conservation potential without regard to how that potential is achieved. The prospect for a
regional market transformation entity will potentially bring a valuable tool to bear in working
towards the achievement of the cost-effective conservation opportunities identified within the
natural gas CPA.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 90 of 190

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 91 of 190
4: Supply-Side Resources
Overview
Avista analyzed a range of future demand
scenarios and possible cost-effective conservation
measures to reduce demand. This chapter
discusses supply options to meet net demand.
Avista’s objective is to provide reliable natural gas
to customers with an appropriate balance of price
stability and prudent cost under changing market
conditions. To achieve this objective, Avista
evaluates a variety of supply-side resources and
attempts to build a diversified natural gas supply
portfolio. The resource acquisition and commodity
procurement programs resulting from the
evaluation consider physical and financial risks,
market-related risks, and procurement execution
risks; and identifies methods to mitigate these
risks.
Avista manages natural gas procurement and related activities on a system-wide basis
with several regional supply options available to serve core customers. Supply options
include firm and non-firm supplies, firm and interruptible transportation on six interstate
pipelines, and storage. Because Avista’s core customers span three states, the diversity
of delivery points and demand requirements adds to the options available to meet
customers’ needs. The utilization of these components varies depending on demand and
operating conditions. This chapter discusses the available regional commodity resources
and Avista’s procurement plan strategies, the regional pipeline resource options available
to deliver the commodity to customers, and the storage resource options available to
provide additional supply diversity, enhanced reliability, favorable price opportunities, and
flexibility to meet a varied demand profile. Non-traditional resources are also considered.

Commodity Resources

Supply Basins
The Northwest continues to enjoy a low cost commodity environment with abundant
supply availability, especially when compared across the globe. This is primarily due to
increasing production in areas of the Northeast and Southern United States. New large-
capacity pipelines, like the Rover pipeline located in Ohio and Michigan, are entering
Chapter
Highlights
•Actively optimize
resources to drive down
customer costs
•An increased drilling
efficiency in production
per rig, year over year
•The Pacific Northwest is
geographically located in
some of the lowest prices
for natural gas in the
world
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 92 of 190
service and increasing the take away capacity from these prolific production areas. This
supply is serving an increasing amount of demand in the population heavy areas in the
middle and eastern portions of Canada and the U.S displacing supplies that had
historically been delivered from the Western Canadian Sedimentary Basis (WCSB).
Current forecasts show a long-term regional price advantage for Western Canada and
Rockies gas basins as the need for this gas diminishes. To put this into perspective, 2005
Canadian imports accounted for nearly 20% of the U.S. demand. Fast forward to 2017
and this number is less than 10%, showing the sheer growth in U.S. supply. This glut of
Canadian gas paired with limited options for flowing gas into demand areas has created
a deeply discounted commodity in the Northwest when compared to the Henry Hub.
Adding to these fundamentals is the recent increase in the price of West Texas
Intermediate (WTI) oil to levels not seen since 2014 (figure 4.3). This is leading to an
increased level of drilling for oil throughout North America and with it a large amount of
associated gas.
Figure 4.3: WTI Spot Price FOB

Access to these abundant supplies of natural gas and to major markets across the
continent has also led to the construction of multiple LNG plants. Sabine Pass and Cove
Point are both operational and will be supplying the world with a total of over 3 Bcf of
$-
$20
$40
$60
$80
$100
$120
$per Barrel
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 93 of 190
natural gas daily. There are currently eighteen export terminals1 proposed in North
America, awaiting FERC review and approval which have a liquefaction capacity of over
23 Bcf per day. A listing of facilities awaiting approval for import or export in North
America is showing a large number of projects with pending applications. In the western
U.S. there is one proposed project the Jordan Cove export facility in Oregon. After initially
being rejected for approval to export, Jordan Cove has refiled their application and is
expecting a FERC decision by the second half of 2019. A Canadian project – LNG
Canada located in Kitimat B.C., has received National Energy Board (NEB) approval and
is awaiting a final investment decision expected Q3 or Q4 2018. Its initial capacity, like
Jordan Cove, is roughly 1 Bcf per day, but contains an option for up to 3.5 Bcf per day in
total. The large increase of natural gas demand by either of these facilities moving
forward could cause pressure on commodity prices with the limited infrastructure in the
Pacific Northwest.
Another relatively new demand area is Mexico. In 2013, Mexico reformed its energy
sector allowing new market participants, innovative technologies and foreign investment.
This market reformation opened up new opportunities for natural gas export to Mexico..
Since these market changes, Mexican imports which were historically less than 2 Bcf per
day have more than doubled and are expected to rise to more than triple by just 2021.
Recent estimates from both the EIA and Natural Resources Canada reflect a large
potential supply of natural gas in North America of over 4,000 trillion cubic feet (Tcf) or
enough supply to last 100’s of years at current demand levels. This estimate, is based
on known geological areas combined with the ability to economically recover natural gas
as infrastructure expands and technology improves.
Regional Market Hubs
There are numerous regional market hubs in the Pacific Northwest where natural gas is
traded extending from the two primary basins. These regional hubs are typically located
at pipeline interconnects. Avista is located near, and transacts at, most of the Pacific
Northwest regional market hubs, enabling flexible access to geographically diverse
supply points. These supply points include:
• AECO – The AECO-C/Nova Inventory Transfer market center located in Alberta is
a major connection region to long-distance transportation systems which take
natural gas to points throughout Canada and the United States. Alberta is the
major Canadian exporter of natural gas to the U.S. and historically produces 90
percent of Canada's natural gas.
1 https://www.ferc.gov/industries/gas/indus-act/lng.asp
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 94 of 190
• Rockies – This pricing point represents several locations on the southern end of
the NWP system in the Rocky Mountain region. The system draws on Rocky
Mountain natural gas-producing areas clustered in areas of Colorado, Utah, New
Mexico and Wyoming.
• Sumas/Huntingdon – The Sumas, Washington pricing point is on the
U.S./Canadian border where the northern end of the NWP system connects with
Enbridge’s Westcoast Pipeline and predominantly markets Canadian natural gas
from Northern British Columbia.
• Malin – This pricing point is at Malin, Oregon, on the California/Oregon border
where TransCanada’s Gas Transmission Northwest (GTN) and Pacific Gas &
Electric Company connect.
• Station 2 – Located at the center of the Enbridge’s Westcoast Pipeline system
connecting to northern British Columbia natural gas production.
• Stanfield – Located near the Washington/Oregon border at the intersection of the
NWP and GTN pipelines.
• Kingsgate – Located at the U.S./Canadian (Idaho) border where the GTN pipeline
connects with the TransCanada Foothills pipeline.

Given the ability to transport natural gas across North America, natural gas pricing is often
compared to the Henry Hub price. Henry Hub, located in Louisiana, is the primary natural
gas pricing point in the U.S. and is the trading point used in NYMEX futures contracts.
Figure 4.1 shows historic natural gas prices for first-of-month index physical purchases
at AECO, Station 2, Rockies and Henry Hub. The figure has changed in recent years due
to a change in flows of natural gas specifically coming from Western Canada. In 2017
the United States flipped from being a net importer to a net exporter.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 95 of 190
Figure 4.1: Monthly Index Prices

Northwest regional natural gas prices typically move together; however, the basis
differential can change depending on market or operational factors. This includes
differences in weather patterns, pipeline constraints, and the ability to shift supplies to
higher-priced delivery points in the U.S. or Canada. By monitoring these price shifts,
Avista can often purchase at the lowest-priced trading hubs on a given day, subject to
operational and contractual constraints.
Liquidity is generally sufficient in the day-markets at most Northwest supply points. AECO
continues to be the most liquid supply point, especially for longer-term transactions.
Sumas has historically been the least liquid of the four major regional supply points
(AECO, Rockies, Sumas and Malin). This illiquidity contributes to generally higher relative
prices in the high demand winter months.
Avista procures natural gas via contracts. Contract specifics vary from transaction-to-
transaction, and many of those terms or conditions affect commodity pricing. Some of the
terms and conditions include:
• Firm vs. Non-Firm: Most term contracts specify that supplies are firm except for
force majeure conditions. In the case of non-firm supplies, the standard provision
is that they may be cut for reasons other than force majeure conditions.
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Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 96 of 190
• Fixed vs. Floating Pricing: The agreed-upon price for the delivered gas may be
fixed or based on a daily or monthly index.
• Physical vs. Financial: Certain counterparties, such as banking institutions, may
not trade physical natural gas, but are still active in the natural gas markets. Rather
than managing physical supplies, those counterparties choose to transact
financially rather than physically. Financial transactions provide another way for
Avista to financially hedge price.
• Load Factor/Variable Take: Some contracts have fixed reservation charges
assessed during each of the winter months, while others have minimum daily or
monthly take requirements. Depending on the specific provisions, the resulting
commodity price will contain a discount or premium compared to standard terms.
• Liquidated Damages: Most contracts contain provisions for symmetrical penalties
for failure to take or supply natural gas.

For this IRP, the SENDOUT® model assumes natural gas purchases under a firm,
physical, fixed-price contract, regardless of contract execution date and type of contract.
Avista pursues a variety of contractual terms and conditions to capture the most value for
customers. Avista‘s natural gas buyers actively assess the most cost-effective way to
meet customer demand and optimize unutilized resources.

Transportation Resources
Although proximity to liquid market hubs is important from a cost perspective, supplies
are only as reliable as the pipeline transportation from the hubs to Avista’s service
territories. Capturing favorable price differentials and mitigating price and operational risk
can also be realized by holding multiple pipeline transportation options. Avista contracts
for a sufficient amount of diversified firm pipeline capacity from various receipt and
delivery points (including storage facilities), so that firm deliveries will meet peak day
demand. This combination of firm transportation rights to Avista’s service territory, storage
facilities and access to liquid supply basins ensure peak supplies are available to serve
core customers.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 97 of 190

*NWGA 2017 outlook
The major pipelines servicing the region include:

• Williams - Northwest Pipeline (NWP):
A natural gas transmission pipeline serving the Pacific Northwest moving natural
gas from the U.S./Canadian border in Washington and from the Rocky Mountain
region of the U.S.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 98 of 190
• TransCanada Gas Transmission Northwest (GTN): A natural gas transmission
pipeline originating at Kingsgate, Idaho, (Canadian/U.S. border) and terminating
at the California/Oregon border close to Malin, Oregon.
• TransCanada Alberta System (NGTL): This natural gas gathering and
transmission pipeline in Alberta, Canada, delivers natural gas into the
TransCanada Foothills pipeline at the Alberta/British Columbia border.
• TransCanada Foothills System: This natural gas transmission pipeline delivers
natural gas between the Alberta - British Columbia border and the Canadian/U.S.
border at Kingsgate, Idaho.
• TransCanada Tuscarora Gas Transmission: This natural gas transmission
pipeline originates at Malin, Oregon, and terminates at Wadsworth, Nevada.
• Enbridge - Westcoast Pipeline: This natural gas transmission pipeline originates
at Fort Nelson, British Columbia, and terminates at the Canadian/U.S. border at
Huntington, British Columbia/Sumas, Washington.
• El Paso Natural Gas - Ruby pipeline: This natural gas transmission pipeline
brings supplies from the Rocky Mountain region of the U.S. to interconnections
near Malin, Oregon.

Avista has contracts with all of the above pipelines (with the exception of Ruby Pipeline)
for firm transportation to serve core customers. Table 4.1 details the firm
transportation/resource services contracted by Avista. These contracts are of different
vintages with different expiration dates; however, all have the right to be renewed by
Avista. This gives Avista and its customer’s available capacity to meet existing core
demand now and in the future.
Table 4.1: Firm Transportation Resources Contracted (Dth/Day)

Firm Transportation Winter Summer Winter Summer
NWP TF-1 157,869 157,869 42,699 42,699
GTN T-1 100,605 75,782 42,260 20,640
NWP TF-2 91,200
Total 349,674 233,651 87,582 63,339
Firm Storage Resources - Max Deliverability
Total 346,667 54,623
* Represents original contract amounts after releases expire.
Avista Avista
North South

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 99 of 190
Avista defines two categories of interstate pipeline capacity. Direct-connect pipelines
deliver supplies directly to Avista’s local distribution system from production areas,
storage facilities or interconnections with other pipelines. Upstream pipelines deliver
natural gas to the direct-connect pipelines from remote production areas, market centers
and out-of-area storage facilities. Firm Storage Resources - Max Deliverability is
specifically tied to Avista’s withdrawal rights at the Jackson Prairie storage facility and is
based on our one third ownership rights. This number only indicates how much we can
withdraw from the facility as transport on NWP is needed to move it from the facility itself.
Figure 4.2 illustrates the direct-connect pipeline network relative to Avista’s supply
sources and service territories.2

Figure 4.2: Direct-Connect Pipelines

Supply-side resource decisions focus on where to purchase natural gas and how to
deliver it to customers. Each LDC has distinct service territories and geography relative
2 Avista has a small amount of pipeline capacity with TransCanada Tuscarora Gas Transmission, a
natural gas transmission pipeline originating at Malin, Oregon, to service a small number of Oregon customers near the southern border of the state.
Roseburg
Medford
Stanfield
Washington / Idaho
SUMAS AECO
ROCKS
La Grande
MALIN
Klamath Falls Roseburg & Medford
Stanfield
NWP GTN
Washington & Idaho
LaGrande
JP Storage
Malin
Klamath Falls
AECO Kingsgate Station 2
Sumas
Rockies
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 100 of 190
to supply sources and pipeline infrastructure. Solutions that deliver supply to service
territories among regional LDCs are similar but are rarely generic.
The NWP system is effectively a fully-contracted. With the exception of La Grande, OR,
Avista’s service territories lie at the end of NWP pipeline laterals. The Spokane, Coeur
d’Alene and Lewiston laterals serve Washington and Idaho load, and the Grants Pass
lateral serves Roseburg and Medford. Capacity expansions of these laterals would be
lengthy and costly endeavors which Avista would likely bear most of the incremental
costs.
The GTN system runs from the Kingsgate trading point on the Idaho-Canadian border
down to Malin on the Oregon-California border. This pipeline runs directly through or near
most of Avista’s service territories. Mileage based rates provide an attractive option for
securing incremental resource needs. Until recently, GTN had a large amount of
unsubscribed capacity. However as prices continue their downward fall, producers are
increasingly contracting for this excess capacity in order to move gas down to more
favorable markets themselves rather than relying on current market dynamics. This may
have some future pricing implications on the commodity side.
Peak day planning aside, both pipelines provide an array of options to flexibly manage
daily operations. The NWP and GTN pipelines directly serve Avista’s two largest service
territories, providing diversification and risk mitigation with respect to supply source, price
and reliability. Northwest Pipeline (NWP) provides direct access to Rockies and British
Columbia supply and facilitates optionality for storage facility management. The Stanfield
interconnect of the two lines is also geographically well situated to Avista’s service
territories.
The rates used in the planning model start with filed rates currently in effect (See
Appendix 4.1 – Current Transportation/Storage Rates and Assumptions). Forecasting
future pipeline rates is challenging. Assumptions for future rate changes are the result of
market information on comparable pipeline projects, prior rate case experience, and
informal discussions with regional pipeline owners. Pipelines will file to recover costs at
rates equal to their cost of service.
NWP and GTN also offer interruptible transportation services. Interruptible transportation
is subject to curtailment when pipeline capacity constraints limit the amount of natural gas
that may be moved. Although the commodity cost per dekatherm transported is generally
the same as firm transportation, there are no demand or reservation charges in these
transportation contracts.. Avista does not rely on interruptible capacity to meet peak day
core demand requirements.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 101 of 190
Avista's transportation acquisition strategy is to contract for firm transportation to serve
core customers on a peak day in the planning horizon. Since contracts for pipeline
capacity are often lengthy and core customer demand needs can vary over time,
determining the appropriate level of firm transportation is a complex analysis. The
analysis includes the projected number of firm customers and their expected annual and
peak day demand, opportunities for future pipeline or storage expansions, and relative
costs between pipelines and upstream supplies. This analysis is done on semi-annual
basis and through the IRP. Active management of underutilized transportation capacity
either through the capacity release market or engaging in optimization transactions to
recover some transportation costs. Timely analysis is also important to maintain an
appropriate time cushion to allow for required lead times should the need for securing
new capacity arise (See Chapter 6 – Integrated Resource Portfolio for a description of the
management of underutilized pipeline resources).
Avista manages existing resources through optimization to mitigate the costs incurred by
customers until the resource is required to meet demand. The recovery of transportation
costs is often market based with rules governed by the FERC. The management of long-
and short-term resources ensures the goal to meet firm customer demand in a reliable
and cost-effective manner. Unutilized resources like supply, transportation, storage and
capacity can be combined to create products that capture more value than the individual
pieces. Avista has structured long-term arrangements with other utilities that allow
available resources utilization and provide products that no individual component can
satisfy. These products provide more cost recovery of the fixed charges incurred for the
resources. Another strategy to mitigate transportation costs is to participate in the daily
market to assess if unutilized capacity has value. Avista seeks daily opportunities to
purchase natural gas, transport it on existing unutilized capacity, and sell it into a higher
priced market to capture the cost of the natural gas purchased and recover some pipeline
charges. The recovery is market dependent and may or may not recover all pipeline costs,
but mitigates pipeline costs to customers.

Storage Resources
Storage is a valuable strategic resource that enables improved management of a highly
seasonal and varied demand profile. Storage benefits include:

• Flexibility to serve peak period needs;
• Access to typically lower cost off-peak supplies;
• Reduced need for higher cost annual firm transportation;
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 102 of 190
• Improved utilization of existing firm transportation via off-season storage injections;
and
• Additional supply point diversity.

While there are several storage facilities available in the region, Avista’s existing storage
resources consist solely of ownership and leasehold rights at the Jackson Prairie Storage
facility.
Avista optimizes storage as part of its asset management program. This helps to ensure
a controlled cost mechanism is in place to manage the large supply found within the
storage facility. An example of this storage optimization is selling today at a cash price
and buying a forward month contract. Since forward months have risks or premiums built
into the price the result is Avista locking in a given spread. All optimization of assets go
directly to the customer to reduce their monthly billing.
Jackson Prairie Storage
Avista is one-third owner, with NWP and Puget Sound Energy (PSE), of the Jackson
Prairie Storage Project for the benefit of its core customers in all three states. Jackson
Prairie Storage is an underground reservoir facility located near Chehalis, Washington
approximately 30 miles south of Olympia, Washington. The total working natural gas
capacity of the facility is approximately 25 Bcf. Avista’s current share of this capacity for
core customers is approximately 8.5 Bcf and includes 398,667 Dth of daily deliverability
rights. Besides ownership rights, Avista leased an additional 95,565 Dth of Jackson
Prairie capacity with 2,623 Dth of deliverability from NWP to serve Oregon customers.

Incremental Supply-Side Resource Options
Avista’s existing portfolio of supply-side resources provides a mix of assets to manage
demand requirements for average and peak day events. Avista monitors the following
potential resource options to meet future requirements in anticipation of changing demand
requirements. When considering or selecting a transportation resource, the appropriate
natural gas supply pairs with the transportation resource and the SENDOUT® model
prices the resources accordingly.

Capacity Release Recall
Pipeline capacity not utilized to serve core customer demand is available to sell to other
parties or optimized through daily or term transactions. Released capacity is generally
marketed through a competitive bidding process and can be on a short-term (month-to-
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 103 of 190
month) or long-term basis. Avista actively participates in the capacity release market with
short-term and long-term capacity releases. Avista assesses the need to recall capacity
or extend a release of capacity on an on-going basis. The IRP process evaluates if or
when to recall some or all long-term releases.

Existing Available Capacity
In some instances, there is available capacity on existing pipelines. NWP’s mainline is
fully subscribed and while GTN has recently seen a significant increase in contracting
activity, they currently maintain the ability to flow additional supply from Kingsgate to
Spokane as noted in Chapter 7. Avista has modeled access to the GTN capacity as an
option to meet future demand needs in addition to some capacity in the La Grande area
where some quantities are available on NWP.

GTN Backhauls
The GTN interconnection with the Ruby Pipeline has enabled GTN the physical capability
to provide a limited amount of firm back-haul service from Malin with minor modifications
to their system. Fees for utilizing this service are under the existing Firm Rate Schedule
(FTS-1) and currently include no fuel charges. Additional requests for back-haul service
may require additional facilities and compression (i.e., fuel).
This service can provide an interesting solution for Oregon customers. For example,
Avista can purchase supplies at Malin, Oregon and transport those supplies to Klamath
Falls or Medford. Malin-based natural gas supplies typically include a higher basis
differential to AECO supplies, but are generally less expensive than the cost of forward-
haul transporting traditional supplies south and paying the associated demand charges.
The GTN system is a mileage-based system, so Avista pays only a fraction of the rate if
it is transporting supplies from Malin to Medford and Klamath Falls. The GTN system is
approximately 612 miles long and the distance from Malin to the Medford lateral is only
about 12 miles.

New Pipeline Transportation Additional firm pipeline transportation resources are viable and attractive resource
options. However, determining the appropriate level, supply source and associated
pipeline path, costs and timing, and if existing resources will be available at the
appropriate time, make this resource difficult to analyze. Firm pipeline transportation
provides several advantages; it provides the ability to receive firm supplies at the
production basin, it provides for base-load demand, and it can be a low-cost option given
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 104 of 190
optimization and capacity release opportunities. Pipeline transportation has several
drawbacks, including typically long-dated contract requirements, limited need in the
summer months (many pipelines require annual contracts), and limited availability and/or
inconvenient sizing/timing relative to resource need.
Pipeline expansions are typically more expensive than existing pipeline capacity and
often require long-term contracts. Even though expansions may be more expensive than
existing capacity, this approach may still provide the best option given that some of the
other options require matching pipeline transportation. Matching pipeline transportation is
creating equivalent volumes on different pipelines from the basin to the delivery point in
order to fully utilize subscribed capacity. Expansions may also provide increased reliability
or access to supply that cannot be obtained through existing pipelines. This is the case
with the Pacific Connector pipeline being proposed as the connecting feedstock for the
Jordan Cove LNG facility in Oregon. The pipeline’s current path connects into Northwest
Pipelines Grants Pass Lateral where capacity is limited. The Pacific Connector pipeline
would add an additional 50,000 Dth/day of capacity along that lateral flowing south from
the Roseburg interconnect.
Several specific projects have been proposed for the region. The following summaries
describe these projects while Figure 4.3 illustrates their location.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 105 of 190
Figure 4.3: Proposed Pipeline Locations

• FortisBC Southern Crossing Expansion:
The Southern Crossing pipeline system is a bidirectional pipeline connecting
Westcoast T South system at Kingsvale, BC and TransCanada’s BC. This
expansion would include over 90 miles of pipeline looping allowing access to an
additional 300-400 MMcf/d of bi-directional capacity, tying together station 2 and
AECO markets.
Source: Northwest Gas Association

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 106 of 190
• TransCanada GTN Trail West/N-MAX
The pipeline taking natural gas off of GTN and onto NWP hub near Molalla is
referred to as Trail West/N-MAX. TransCanada GTN, Northwest Natural and
Northwest Pipeline are the project sponsors of this 106-mile, 30-inch diameter
pipeline. The initial design capacity of this pipeline is 500 MMcf/d and expandable
up to 1,000 MMcf/d. This could be an important project if built as it would bring
more gas into the I-5 corridor where unused pipeline capacity is quickly
disappearing based on the demand for natural gas and population increase.

• Sumas Express
NWP continues to explore options to expand service from Sumas, Wash., to
markets along the Interstate-5 corridor. This project could help relieve the
congestion along this highly populated geographical region in both Washington
and Oregon. Various methods could be used to add this additional capacity
including looping, additional compression and increasing the pipe size and can be
scaled based off of demand.

• Enbridge/FortisBC T-South System Looping
FortisBC and Enbridge are system enhancement on the T-South pipeline.
Removing constraints will allow expansion of Endbridge’s T-South enhanced
service offering, which provides shippers the options of delivering to Sumas or the
Kingsgate market. Expanding the bi-directional Southern Crossing system would
increase capacity at Sumas during peak demand periods. Initial capacity from the
Enbridge system to Kingsgate would increase capacity by 190MMcf/d. This would
add incremental gas into the Huntington/Sumas market through looping and
compressor station upgrades along the system.

• Pacific Connector
Pembina is currently attempting to acquire approval for a 232-mile, 36-inch
diameter pipeline designed to transport up to 1.2 billion cubic feet of natural gas
per day from interconnects near Malin, Oregon, to the Jordan Cove LNG terminal
in Coos Bay, Oregon. The pipeline would deliver the feedstock to the LNG terminal
providing natural gas to international markets, but also to the Pacific Northwest.
The pipeline will connect with Williams’ Northwest Pipeline on the Grants Pass
lateral. This ties in directly within Avista’s service territory and will bring in an
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 107 of 190
additional 50,000 Dth/day of capacity into that area. This new option could provide
Avista’s customers in the area new capacity for growth and supply diversity.

• NGTL – West Path expansion
In order to meet existing aggregate demand in southern AB and incremental long-
term delivery commitments at the A/BC border, NGTL is proposing this project
underpinned by long-term contracts to increase the delivery point capacity at the
A/BC border by 288,000 GJ/day. This project would operationally true-up capacity
differences between NGTL and Foothills and provide additional export capacity
into the US.

Avista supports proposals that bring supply diversity and reliability to the region. Supply
diversity provides a varied supply base in the procurement of natural gas. Since there are
few options in the Northwest, supply diversity provides options and security when
constraints or high demand are present. Avista engages in discussions and analysis of
the potential impact of each regional proposal from a demand serving and
reliability/supply diversity perspective. In most cases, for Avista to consider them a viable
incremental resource to meet demand needs would require combining them with
additional capacity on existing pipeline resources. However, the IRP considers a generic
expansion that represents a new pipeline build to Avista’s service territories.

In-Ground Storage In-ground storage provides advantages when natural gas from storage can be delivered
to Avista’s city-gates. It enables deliveries of natural gas to customers during peak cold
weather events. It also facilitates potentially lower-cost supply for customers by capturing
peak/non-peak pricing differentials and potential arbitrage opportunities within individual
months. Although additional storage can be a valuable resource, without deliverability to
Avista’s service territory, this storage cannot be an incremental firm peak serving
resource.
Jackson Prairie
Jackson Prairie is a potential resource for expansion opportunities. Any future storage
expansion capacity does not include transportation and therefore cannot be considered
an incremental peak day resource. However, Avista will continue to look for exchange
and transportation release opportunities that could fully utilize these additional resource
options. When an opportunity presents itself, Avista assesses the financial and reliability
impact to customers. Due to the fast paced growth in the region, and the need for new
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 108 of 190
resources, a future expansion is possible, though a robust analysis would be required to
determine feasibility. Currently, there are no plans for immediate expansion of Jackson
Prairie.

Other In-Ground Storage
Other regional storage facilities exist and may be cost effective. Additional capacity at
Northwest Natural’s Mist facility, capacity at one of the Alberta area storage facilities,
Questar’s Clay Basin facility in northeast Utah, Ryckman Creek in Uinta County, Wyo.,
and northern California storage are all possibilities. Transportation to and from these
facilities to Avista’s service territories continues to be the largest impediment to these
options. Avista will continue to look for exchange and transportation release opportunities
while monitoring daily metrics of load, transport and market environment.

LNG and CNG
LNG is another resource option in Avista’s service territories and is suited for meeting
peak day or cold weather events. Satellite LNG uses natural gas that is trucked to the
facilities in liquid form from an offsite liquefaction facility. Alternatively, small-scale
liquefaction and storage may also be an effective resource option if natural gas supply
during non-peak times is sufficient to build adequate inventory for peak events. Permitting
issues notwithstanding, facilities could be located in optimal locations within the
distribution system.
CNG is another resource option for meeting demand peaks and is operationally similar to
LNG. Natural gas could be compressed offsite and delivered to a distribution supply point
or compressed locally at the distribution supply point if sufficient natural gas supply and
power for compression is available during non-peak times.
LNG and CNG supply resource options for LDCs are becoming more attractive as the
market for LNG and CNG as alternative transportation fuels develops. The combined
demand for peaking and transportation fuels can increase the volume and utilization of
these resource assets thus lowering unit costs for the benefit of both market segments.
Estimates for LNG and CNG resources vary because of sizing and location issues. This
IRP uses estimates from other facilities constructed in the area and from conversations
with experts in the industry. Avista will monitor and refine the costs of developing LNG
and CNG resources while considering lead time requirements and environmental issues.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 109 of 190
Plymouth LNG NWP owns and operates an LNG storage facility at Plymouth, Wash., which provides
natural gas liquefaction, storage and vaporization service under its LS-1, LS-2F and LS-
3F tariffs. An example ratio of injection and withdrawal rates show that it can take more
than 200 days to fill to capacity, but only three to five days to empty. As such, the resource
is best suited for needle-peak demands. Incremental transportation capacity to Avista’s
service territories would have to be obtained in order for it to be an effective peaking
resource. With available capacity, Plymouth LNG was considered in our supply side
resource modeling but was not selected.

Avista-Owned Liquefaction LNG
Avista could construct a liquefaction LNG facility in the service area. Doing so could use
excess transportation during off-peak periods to fill the facility, avoid tying up
transportation during peak weather events, and it may avoid additional annual pipeline
charges.
Construction would depend on regulatory and environmental approval as well as cost-
effectiveness requirements. Preliminary estimates of the construction, environmental,
right-of-way, legal, operating and maintenance, required lead times, and inventory costs
indicate company-owned LNG facilities have significant development risks. Avista
modeling included LNG, but it was not selected as a resource when compared to existing
resources.
Renewable Natural Gas (RNG)
Renewable Natural Gas, or biogas, typically refers to a mixture of gases produced by the
biological breakdown of organic matter in the absence of oxygen. RNG can be produced
by anaerobic digestion or fermentation of biodegradable materials such as woody
biomass, manure or sewage, municipal waste, green waste and energy crops. Depending
on the type of RNG there are different factors for the amount of methane saved by its
capture as methane has been found to have a multiplier effect on global warming of, at a
minimum, 253 times that of carbon dioxide. Each type of RNG has a different carbon
intensity as compared to natural gas as shown in table 4.2.

3 https://www.epa.gov/ghgemissions/understanding-global-warming-potentials
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 110 of 190
Table 4.2 Carbon intensity4:

RNG is a renewable fuel, so it may qualify for renewable energy subsidies. Once
contained, RNG can be used by boilers for heat, as power generation, compressed
natural gas vehicles for transportation or directly injected into the natural gas grid. The
further down this line greater the need for pipeline quality gas.
Biogas projects are unique, so reliable cost estimates are difficult to obtain. Project
sponsorship has many complex issues, and the more likely participation in such a project
is as a long-term contracted purchaser. Avista considered biogas as a resource in this
planning cycle, as depending on the location of the facility it may be cost effective. This
is especially the case when found within Avista’s internal distribution system where
transportation and fuel costs can be avoided.
Avista’s Natural Gas Procurement Plan
No company can accurately predict future natural gas prices, but market conditions and
experience help shape the overall approach to procurement. Avista’s natural gas
procurement plan process seeks to acquire natural gas supplies while reducing exposure
to short-term price volatility. The procurement strategy includes hedging, storage
utilization and index purchases. Although the specific provisions of the procurement plan
will change based on ongoing analysis and experience, the following principles guide
Avista’s procurement plan.
Avista employs a time, location and counterparty diversified hedging strategy. It is
appropriate to hedge over a period of time and establish hedge phases when portions of
future demand are physically and/or financially hedged. Avista views hedging as a type
4 California Air Resources Board
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 111 of 190
of risk insurance and an appropriate part of a diversified procurement plan with a mission
to provide a diversified portfolio of reliable supply and a level of price certainty in
volatile markets. Hedges may not be at the lowest possible price, but they still protect
customers from price volatility. With access to multiple supply basins, Avista transacts
with the lowest priced basin at the time of the hedge. Furthermore, Avista transacts with
a range of counterparties to spread supply among a wider range of market participants.
In utilizing
Avista uses a disciplined, but flexible hedging approach. Avista’s hedging strategy
begins with the prompt month and extends for up to thirty six months out based on market
availability of winter and summer pricing strips. This program is run through a mechanism
utilizing an upper and lower control limit or bands to help control market cost and risk.
These control limits measure the volatility in the market place, by basin, and will adjust
inward toward the price, when rising, or allow the lower control limit to fall with volatility
when prices go down. Also, in response to the Washington Utilities and Transportation
Commission (WUTC) hedging policy UG-132019, Avista is also developing an additional
methodology to measure the total value at risk (VaR) of its entire portfolio of hedges. This
methodology is based off of market volatility and statistical measurements of the
marketplace and may allow Avista to hedge less based on current market fundamentals,
while also controlling the financial risk of a rising market.
Avista regularly reviews its procurement plan in light of changing market
conditions and opportunities. Avista’s plan is open to change in response to ongoing
review of the procurement plan assumptions. Even though the initial plan establishes
various targets, policies provide flexibility to exercise judgment to revise targets in
response to changing conditions.
Avista utilizes a number of tools to help mitigate financial risks. Avista purchases gas in
the spot market and forward markets. Spot purchases are for the next day or weekend.
Forward purchases are for future delivery. Many of these tools are financial instruments
or derivatives that can provide fixed prices or dampen price volatility. Avista continues to
evaluate how to manage daily demand volatility, whether through option tools from
counterparties or through access to additional storage capacity and/or transportation.

Market-Related Risks and Risk Management
There are several types of risk and approaches to risk management. The 2018 IRP
focuses on two areas of risk: the financial risk of the cost of natural gas to supply
customers will be unreasonably high or volatile, and the physical risk that there may not
be enough natural gas resources (either transportation capacity or the commodity) to
serve core customers.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Avista’s Risk Management Policy describes the policies and procedures associated with
financial and physical risk management. The Risk Management Policy addresses issues
related to management oversight and responsibilities, internal reporting requirements,
documentation and transaction tracking, and credit risk.
Two internal organizations assist in the establishment, reporting and review of Avista’s
business activities as they relate to management of natural gas business risks:
• The Risk Management Committee includes corporate officers and senior-level
management. The committee establishes the Risk Management Policy and
monitors compliance. They receive regular reports on natural gas activity and meet
regularly to discuss market conditions, hedging activity and other natural gas-
related matters.
• The Strategic Oversight Group coordinates natural gas matters among internal
natural gas-related stakeholders and serves as a reference/sounding board for
strategic decisions, including hedges, made by the Natural Gas Supply
department. Members include representatives from the Gas Supply, Accounting,
Regulatory, Credit, Power Resources, and Risk Management departments. While
the Natural Gas Supply department is responsible for implementing hedge
transactions, the Strategic Oversight Group provides input and advice.

Supply Scenarios
The 2018 IRP includes two supply scenarios. Additional details about the results of the
supply scenarios are in Chapters 6 and 7.
• Existing Resources: This scenario represents all resources currently owned or
contracted by Avista.
• Existing + Expected Available: In this scenario, existing resources plus supply
resource options expected to be available when resource needs are identified. This
includes currently available south and north bound GTN, NWP, capacity release
recalls, RNG, Hydrogen and LNG.
Supply Issues
The abundance and accessibility of shale gas has fundamentally altered North American
natural gas supply and the outlook for future natural gas prices. Even though the supply
is available and the technology exists to access it, there are issues that can affect the
cost and availability of natural gas.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Hydraulic Fracturing Hydraulic fracturing (commonly referred to as fracking) was invented by Hubbert and
Willis of Standard Oil and Gas Corporation back in the late 1940’s. The process involves
a technique to fracture shale rock with a pressurized liquid. In the past 15 years, the
techniques and materials used have become increasingly perfected opening up large
deposits of shale gas formations at a low prices. The Energy Information Administration
(EIA) tracks production per well in the seven key oil and natural gas production formations
in the United States as shown in Figure 4.4. Figure 4.5 shows the continued increase in
efficiency of production compared to just a year ago as shown by the EIA’s Drilling
Productivity Report 4.55.

Figure 4.4 – seven major drilling regions in the United States

5 Drilling Productivity Report, https://www.eia.gov/petroleum/drilling/pdf/summary.pdf
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Figure 4.5 – June 2018 Drilling Productivity Report, EIA

With the increasingly prevalent use of hydraulic fracturing came concerns of chemicals
used in the process. The publicity caused by movies, documentaries and articles in
national newspapers about “fracking” has plagued the natural gas and oil industry. There
is concern that hydraulic fracturing is contaminating aquifers, increasing air pollution and
causing earthquakes. One common misconception with the process is that hydraulic
fracturing causes earthquakes. The actual cause of earthquakes is wastewater injection
used in operations at the well site. Based on research at the U.S. Geological Survey,
only a small number of these earthquakes are from fracking itself.6 Additionally,
wastewater injections are used for all wells, not just those where fracking is involved.
The wide-spread publicity generated interest in the production process and caused some
states to issue bans or moratoriums on drilling until further research was conducted. To
help combat these fears, Frac Focus7 was created and is a chemical disclosure registry
allowing users to view chemicals used by over 125,000 wells throughout North America.
This information, voluntarily submitted by Exploration and production companies,
provides a detailed list of materials used to frack each individual well.
6 https://profile.usgs.gov/myscience/upload_folder/ci2015Jun1012005755600Induced_EQs_Review.pdf
7 https://fracfocus.org/
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Pipeline Availability The Pacific Northwest has efficiently utilized its relatively sparse network of pipeline
infrastructure to meet the region’s needs. As the amount of renewable energy increases,
future demand for natural gas-fired generation will increase. Pipeline capacity is the link
between natural gas and power.
There are currently a few industrial plants being considered in the Pacific Northwest. The
project with the highest likelihood is the project located in Washington’s Port of Kalama.
This process uses large amounts of natural gas as a feedstock for creating methanol,
which is used to make other chemicals and as a fuel. At over 300,000 Dth per day this
plant would consume large amounts of natural gas.

Ongoing Activity
Without resource deficiencies or a need to acquire incremental supply-side resources to
meet peak day demands over the next 20 years, Avista will focus on normal activities in
the near term, including:
• Continue to monitor supply resource trends including the availability and price of
natural gas to the region, LNG exports, supply dynamics and marketplace, and
pipeline and storage infrastructure availability.
• Monitor availability of resource options and assess new resource lead-time
requirements relative to resource need to preserve flexibility.
• Appropriate management of existing resources including optimizing underutilized
resources to help reduce costs to customers.

Conclusion
Abundant supply availability around the Northwest may lead to an increased demand in
this planning horizon by large industrials. While keeping a watchful eye on the market,
Avista has continued to make adjustments to its procurement plan to help reduce short
term volatility and is actively engaged in new strategies and mechanisms to help manage
overall financial risk related to hedging. Our supply mix is diversified between multiple
basins with firm take away rights thus helping to reduce the risk of not meeting demand
on a cold day. This in combination with the optimization of our storage, transportation and
basin resources have helped Avista to provide natural gas reliably to our customers at a
fair and reasonable price.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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5: Policy Considerations

Regulatory environments regarding energy topics
such as renewable energy and greenhouse gas
regulation continue to evolve since publication of the last IRP. Current and proposed regulations by
federal and state agencies, coupled with political
and legal efforts, have implications for the
development and continued use of coal and natural
gas-fired generation. This chapter discusses pertinent public policy issues relevant to the IRP.
Environmental Issues
The evolving and sometimes contradictory nature
of environmental regulation from state and federal
perspectives creates challenges for resource
planning. The IRP cannot add renewables or
reduce emissions in isolation from topics such as system reliability, least cost requirements, price
mitigation, financial risk management, and meeting
changing environmental requirements. Each generating resource has distinctive
operating characteristics, cost structures, and environmental regulatory challenges that
can change significantly based on timing and location. All resource choices have costs and benefits requiring careful consideration of the utility and customer needs being
fulfilled, their location, and the regulatory and policy environment at the time of
procurement.

Renewable energy technologies such as renewable natural gas (RNG) have different benefits and challenges. Renewable resources have low or no fuel costs and few, if any,
direct emissions. Renewable resources are often located to maximize capability rather
than proximity to load centers. The need to site renewable resources in remote locations
often requires significant investments in distribution and capacity expansion, as well as
mitigating possible wildlife and aesthetic issues. Transportation costs and logistics also complicate the location of RNG plants.

The long-term economics of renewable resources also faces some uncertainties. Federal
investment and production tax credits are set to expire. The extension credits and grants may not be sustainable given their impact on government finances and the maturity of wind and solar technologies. Many relatively unpredictable factors affect renewables,
such as renewable portfolio standards (RPS), construction and component prices,
international trade issues and currency exchange rates. Decreasing capital costs for wind
and solar may slow or stop. The design and scope of greenhouse gas regulation is in a state of flux due to legal
challenges and evolving political realities. As a result, greenhouse gas policy-making is
shifting from the federal to the state and local level. Since the 2016 IRP publication,
•Electrification has become
an increasingly recurrent topic in the Northwest
•Avista’s Climate Policy Council monitors
greenhouse gas legislation and environmental regulation
issues
•Both Washington and Oregon are actively creating bills to tax, trade,
or charge a fee for releasing carbon dioxide into the atmosphere

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 118 of 190
changes in the approach to greenhouse gas emissions regulation and supporting programs, include:

• The EPA proposed actions to regulate greenhouse gas emissions under the Clean
Air Act (CAA) through the proposed Clean Power Plan (CPP) were stayed by the U.S. Supreme Court on February 9, 2016;
• On August 20, 2018 the EPA proposed a CPP replacement rule, referred to as the
“Affordable Clean Energy Rule”, establishing individual plant greenhouse gas emissions in contrast to the CPP which targeted emission’s across each states
energy sector;
• The President signaled a shift in federal priorities through Executive Orders as well
as proposed budgets.
• The State of Washington invalidated the Clean Air Rule
• Regulations or laws placing a monetary value on the cost of carbon through a tax,
fee or cap-and-trade program are becoming increasingly recurrent in the states of
Oregon and Washington.

Natural Gas System Emissions
The physical makeup of the natural gas system includes extraction rigs, pipelines and
storage; each of these facilities have fugitive emissions. Fugitive emissions are the unintended or irregular releases of natural gas as part of the production cycle. The EPA
introduced the Natural Gas STAR Program in 1993 in response to these emissions
concerns. This Natural Gas STAR Program is a voluntary program allowing the self-
reporting of emission reduction technologies and practices and includes all of the major
industry sectors. In May 2016, the EPA finalized rules to reduce methane emissions from wells under the CAA. The program requires natural gas well owners to find and repair
leaks at the well site no less than twice per year and four times per year at compressor
stations. The EPA placed a 90-day delay on portions of the rule to allow additional
comments.
Natural gas wells utilizing shale deposits have a high production curve at the beginning
of the extraction process and then dramatically levels off. If not constructed properly, there
is a risk of leakage that may lower the return on investment. In addition, risk of increased
regulation incentivizes producers to manage emissions as effectively as possible as more
regulations generally increase costs and reduce return on investments. Over time a smaller return on investment could mean the difference in survival outcomes for each
producer. Natural gas emissions in 1990, as shown in table 7.1, were higher than in 2016
even though the production was just slightly over 50 Bcf/day compared to roughly 78
Bcf/day in 2016. This is nearly equivalent to reducing emissions by half when accounting
for the additional production.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 119 of 190
Table 5.1: Non-combustion CO2 Emissions from Natural Gas Systems (kt)1
Avista’s Climate Change Policy Efforts
Avista’s Climate Policy Council is an interdisciplinary team of management and other
employees that:
• Facilitates internal and external communications regarding climate change issues;
• Analyzes policy impacts, anticipates opportunities, and evaluates strategies for
Avista Corporation; and
• Develops recommendations on climate related policy positions and action plans.

The core team of the Climate Policy Council includes members from Environmental
Affairs, Government Relations, External Communications, Engineering, Energy Solutions, and Resource Planning groups. Other areas participate for topics as needed.
The meetings for this group include work for both immediate and long-term concerns.
Immediate concerns include reviewing and analyzing proposed or pending state and
federal legislation and regulation, reviewing corporate climate change policy, and
responding to internal and external requests about climate change issues. Longer-term issues involve emissions measurement and reporting, different greenhouse gas policies,
actively participating in legislation, and benchmarking climate change policies and
activities against other organizations.
EPA Regulations EPA regulations, or the States’ authorized versions, directly, or indirectly, affecting
electricity generation include the CAA, along with its various components, including the
Acid Rain Program, the National Ambient Air Quality Standard, the Hazardous Air
Pollutant rules, and Regional Haze Programs. The U.S. Supreme Court ruled the EPA
has authority under the CAA to regulate greenhouse gas emissions from new motor vehicles and the EPA has issued such regulations. When these regulations became
effective, carbon dioxide and other greenhouse gases became regulated pollutants under
the Prevention of Significant Deterioration (PSD) preconstruction permit program and the
Title V operating permit program. Both of these programs apply to power plants and other
commercial and industrial facilities. In 2010, the EPA issued a final rule, known as the Tailoring Rule, governing the application of these programs to stationary sources, such
as power plants. EPA proposed a rule in early 2012, and modified in 2013, setting
1 Source is from “3-80 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2016” Pg. 80 https://www.epa.gov/sites/production/files/2018-01/documents/2018_chapter_3_energy.pdf

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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standards of performance for greenhouse gas emissions from new and modified fossil fuel-fired electric generating units and for existing sources through the draft CPP in June
2014. The EPA released the final CPP rules and the Carbon Pollution Standards (CPS)
as published in the Federal Register on October 23, 2015, when they were both
challenged thorough a series of lawsuits. Standards under Section 111(d) of the CAA are currently stayed by the Supreme Court. The EPA also finalized new source performance standards (NSPS) for new, modified and reconstructed fossil fuel-fired generation under
CAA section 111(b).

EPA Mandatory Reporting Rule Any facility emitting over 25,000 metric tons of greenhouse gases per year must report
its emissions to EPA. The Mandatory Reporting Rule requires greenhouse gas reporting
for natural gas distribution system throughput, fugitive emissions from electric power
transmission and distribution systems, fugitive emissions from natural gas distribution systems, and from natural gas storage facilities. Washington requires mandatory greenhouse gas emissions reporting similar to the EPA requirements and Oregon has
similar reporting requirements.

State and Regional Level Policy Considerations The lack of a comprehensive federal greenhouse gas policy encouraged states, such as California, to develop their own climate change laws and regulations. Climate change
legislation takes many forms, including economy-wide regulation under a cap and trade
system, a carbon tax, and emissions performance standards for power plants.
Comprehensive climate change policy can include multiple components, such as renewable portfolio standards, DSM standards, and emission performance standards. Washington enacted all of these components, but other Avista jurisdictions have not.
Individual state actions produce a patchwork of competing rules and regulations for
utilities to follow and may be particularly problematic for multi-jurisdictional utilities such
as Avista. Idaho Policy Considerations
Idaho does not regulate greenhouse gases. There is no indication Idaho is moving toward
regulation of greenhouse gas emissions beyond federal regulations.
Oregon Policy Considerations
The State of Oregon has a history of greenhouse gas emissions and renewable portfolio
standards legislation. The Legislature enacted House Bill 3543 in 2007, calling for, but
not requiring, reductions of greenhouse gas emissions to 10 percent below 1990 levels by 2020 and 75 percent below 1990 levels by 2050. Compliance is expected through a combination of the RPS and other complementary policies, like low carbon fuel standards
and DSM measures. The state has been working towards the adaptation of
comprehensive requirements to meet these goals. HB 2135, or the cap and trade bill, is
under consideration at the time this chapter is being written. This bill would repeal the greenhouse gas emissions goals stated above and would require the Environmental Quality Commission to adopt greenhouse gas emissions goals for 2025, and set limits for
years 2035 and 2050.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 121 of 190
These reduction goals are in addition to a 1997 regulation requiring fossil-fueled
generation developers to offset carbon dioxide (CO2) emissions exceeding 83 percent of
the emissions of a state-of-the-art gas-fired combined cycle combustion turbine by
funding offsets through the Climate Trust of Oregon. Oregon’s Cap-and-Trade
A set of cap-and-trade bills were included in the Oregon Legislature, but did not make it
out due to the short session. In spite of this, a joint legislative committee announced
plans to create a “cap-and-invest” program in time for the 2019 session. This committee
will be funded by $1.4 million to help fund a Carbon Policy Office and to determine how these programs would impact Oregon’s economy, jobs and emissions. These two bills, HB 4001 and SB 1507 would both create a cap and trade system for entities emitting over
25,000 metric tons of carbon annually. In 2021, the Oregon Environmental Quality
Commission would set a statewide emissions on about 100 companies who would need
to reduce emissions or buy allowances. The revenue from these programs would be invested in clean energy or emissions mitigation programs leading to the final goal of 80% emissions reduction by 2050.
Oregon RNG
In Oregon, Senate Bill 3342 was passed to help develop, update, and maintain the biogas
inventory available. This includes the sites and potential production quantities available
in addition to the quantity of renewable natural gas available for use to reduce greenhouse
gas emissions. This bill will also help promote RNG and identify the barriers and removal
of barriers to develop and utilize RNG. A report is due by September 2018.

Washington State Policy Considerations
Former Governor Christine Gregoire signed Executive Order 07-02 in February 2007
establishing the following GHG emissions goals:
• 1990 levels by 2020;
• 25 percent below 1990 levels by 2035;
• 50 percent below 1990 levels by 2050 or 70 percent below Washington’s expected
emissions in 2050;
• Increase clean energy jobs to 25,000 by 2020; and
• Reduce statewide fuel imports by 20 percent. The Washington Department of Ecology adopted regulations to ensure that its State
Implementation Plan comports with the requirements of the EPA's regulation of
greenhouse gas emissions. We will continue to monitor actions by the Department as it
may proceed to adopt additional regulations under its CAA authorities.
2 https://olis.leg.state.or.us/liz/2017R1/Downloads/MeasureDocument/SB334
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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April 29, 2014, Washington Governor Jay Inslee issued Executive Order 14-04, “Washington Carbon Pollution Reduction and Clean Energy Action.” The order created a
“Climate Emissions Reduction Task Force” tasked with providing recommendations to the
Governor on designing and implementing a market-based carbon pollution program to
inform possible legislative proposals in 2015. The order also called on the program to “establish a cap on carbon pollution emissions, with binding requirements to meet our statutory emission limits.” The order also states that the Governor’s Legislative Affairs
and Policy Office “will seek negotiated agreements with key utilities and others to reduce
and eliminate over time the use of electrical power produced from coal.” The Task Force
issued a report summarizing its efforts, which included a range of potential carbon-reducing proposals. Subsequently, in January 2015, at Governor Inslee’s request, the Carbon Pollution Accountability Act was introduced as a bill in the Washington legislature.
The bill includes a proposed cap and trade system for carbon emissions from a wide
range of sources, including fossil-fired electrical generation, “imported” power generated
by fossil fuels, natural gas sales and use, and certain uses of biomass for electrical generation. The bill was not enacted during the 2015 legislative session. After the conclusion of the 2015 legislative sessions, Governor Inslee directed the Department of
Ecology to commence a rulemaking process to impose a greenhouse gas emission
limitation and reduction mechanism under the agency’s CAA authority to meet the future
emissions limits established by the Legislature in 2008. This resulted in Washington’s Clean Air Rule (CAR).
The CAR intended to impose new compliance obligations on sources identified by
Ecology. The rule imposes caps and requirements to reduce or offset emissions on large
emitting facilities, fuel providers and natural gas distribution companies. It initially applies to 29 entities. Compliance obligations for energy-intensive trade-exposed industries, including pulp and paper manufacturers, steel and aluminum manufacturers and food
processors, are deferred for three years. When fully implemented, the CAR could cover
as many as 70 emitters who account for about two-thirds of Washington’s emissions. The
CAR caps emissions for facilities emitting more than 100,000 metric tons per year, and reduces the emissions threshold by 5,000 metric tons per year, until covering all entities emitting over 70,000 metric tons by 2035. The Washington Commission may implement
rules regarding RCW 70.235, from the Executive Order 07-02. The CAR became effective
January 1, 2017, but was ruled invalid on December 15, 2017 in Thurston County
Superior Court. This ruling found that local distribution companies are not emitters, and have no choice under the law to meet the supply demands of its customers. On May 14, 2018 the Department of Ecology appealed this ruling with the Washington State Supreme
Court. If a policy comes into law comparable to the CAR, the number of ERU’s required
for Avista’s natural gas customers would create a demand for renewable energy. This
would likely lead to the procurement of RNG, but due to the large amount of needed MTCO2e offsets would also drive the need for wind and solar. Figure 5.1 shows a potential outcome of a program like the CAR and its impacts on Avista’s Washington
customers.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Figure 5.1: Avista – Washington only CO2e emissions reduction estimate from CAR

Deep Decarbonization
In December of 2016 Governor Inslee’s office commissioned a deep decarbonization pathway study on reducing emissions required to curb a global temperature increase to below
two degrees Celsius. This study lists three possible scenarios seen as a pathway for
Washington State to reduce 1990 emission to below 80% 2050. These methods are
electrification, renewable pipeline and innovation. Electrification involves electrifying end-uses to the greatest extent possible while reducing natural gas use. The second involves creating a renewable pipeline where all gas comes from decarbonized biogas, synthetic
natural gas and hydrogen. Finally innovation is seen as both electrifying end-uses coupled
with innovation in the areas of electric and autonomous vehicles, fuel cells, and offshore wind.
In order to show demand impacts of this type of scenario within Avista’s natural gas operations, we modeled this scenario as “80% below 1990 emissions”. This scenario does
not assume the technology, costs involved, or methods used to reduce emissions. Rather,
the intent is to show the overall loss of demand if the resource mix is solely natural gas with
no renewable supply resources. Please refer to Chapter 7 – Alternate Scenarios, Portfolios and Stochastic Analysis for results.

-
200,000
400,000
600,000
800,000
1,000,000
1,200,000
1,400,000
MT
C
O
2
e
# of Needed ERUs Avista WA CO2e…CAR Goal
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Washington RNG Washington State House Bill 25803 was signed by Governor Jay Inslee on March 22,
2018 and will become effective on July 1, 2018 bringing into law a bill to help encourage
production of renewable natural gas (RNG). This bill requires the Washington State
University Extension Energy Program and the Department of Commerce (DOC) along
with the consulting of the Washington State Utilities and Transportation Commission, to
submit recommendations on promoting the sustainable development of RNG. The DOC
will consult with natural gas utilities and other state agencies to explore developing
voluntary gas quality standards for the injection of RNG into natural gas pipeline systems
in the state. The tax incentive is equal to the value of the product multiplied by the rate
of the specific commodity or product as detailed in the bill.

3 http://apps2.leg.wa.gov/billsummary?Year=2017&BillNumber=2580&Year=2017&BillNumber=2580
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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6: Integrated Resource
Portfolio

Overview
This chapter combines the previously discussed
IRP components and the model used to determine
resource deficiencies during the 20-year planning
horizon. This chapter provides an analysis of
potential resource options to meet resource
deficiencies as exhibited in the High Growth, Low
Prices scenario.
The foundation for integrated resource planning is
the criteria used for developing demand forecasts.
Avista uses the coldest day on record as its
weather-planning standard for determining peak-day demand. This is consistent with past
IRPs as described in Chapter 2 − Demand Forecasts. This IRP utilizes coldest day on
record and average weather data for each demand region. Avista plans to serve expected
peak day in each demand region with firm resources. Firm resources include natural gas
supplies, firm pipeline transportation and storage resources. In addition to peak
requirements, Avista also plans for non-peak periods such as winter, shoulder and
summer demand. The modeling process includes a daily optimization for every day of the
20-year planning period.
It is assumed that on a peak day all interruptible customers have left the system to provide
service to firm customers. Avista does not make firm commitments to serve interruptible
customers, so IRP analysis of demand-serving capabilities only includes the firm
residential, commercial and industrial classes. Using coldest day on record weather
criteria, a blended price curve developed by industry experts, and an academically
backed customer forecast all work together to develop stringent planning criteria.
Forecasted demand represents the amount of natural gas supply needed. In order to
deliver the forecasted demand, the supply forecast needs to increase between 1.0
percent and 3.0 percent on both an annual and peak-day basis to account for additional
supplies purchased primarily for pipeline compressor station fuel. The range of 1.0
percent to 3.0 percent, known as fuel, varies depending on the pipeline. The FERC and
National Energy Board approved tariffs govern the percentage of required additional fuel
supply.

•No resource shortage in
the expected case
•An increase in DSM
potential in Washington
and Oregon
•Idaho is now broken out
into its own demand area
•Higher Carbon Costs vs.
2016 IRP
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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SENDOUT® Planning Model
The SENDOUT® Gas Planning System from Ventyx performs integrated resource
optimization modeling. Avista purchased the SENDOUT® model in April 1992 and has
used it to prepare all IRPs since then. Avista has a maintenance agreement with Ventyx
for software updates and enhancements. Enhancements include software corrections
and improvements driven by industry needs.
SENDOUT® is a linear programming model widely used to solve natural gas supply and
transportation optimization questions. Linear programming is a proven technique to solve
minimization/maximization problems. SENDOUT® analyzes the complete problem at one
time within the study horizon, while accounting for physical limitations and contractual
constraints.
The software analyzes thousands of variables and evaluates possible solutions to
generate a least cost solution given a set of constraints. The model considers the
following variables:

• Demand data, such as customer count forecasts and demand
coefficients by customer type (e.g., residential, commercial and
industrial).
• Weather data, including minimum, maximum and average
temperatures.
• Existing and potential transportation data which describes the network
for physical movement of natural gas and associated pipeline costs.
• Existing and potential supply options including supply basins, revenue
requirements as the key cost metric for all asset additions and prices.
• Natural gas storage options with injection/withdrawal rates, capacities
and costs.
• Conservation potential.

Figure 6.1 is a SENDOUT® network diagram of Avista’s demand centers and resources.
This diagram illustrates current transportation and storage assets, flow paths and
constraint points.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Figure 6.1 SENDOUT® Model Diagram

The SENDOUT® model provides a flexible tool to analyze scenarios such as:

• Pipeline capacity needs and capacity releases;
• Effects of different weather patterns upon demand;
• Effects of natural gas price increases upon total natural gas costs;
• Storage optimization studies;
• Resource mix analysis for conservation;
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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• Weather pattern testing and analysis;
• Transportation cost analysis;
• Avoided cost calculations; and
• Short-term planning comparisons.

SENDOUT® also includes Monte Carlo capabilities, which facilitates price and demand
uncertainty modeling and detailed portfolio optimization techniques to produce probability
distributions. More information and analytical results are located in Chapter 7 – Alternate
Scenarios, Portfolios and Stochastic Analysis. The SENDOUT® model is used by many
LDC’s across the U.S., however it is becoming increasingly outdated for the current
regulatory environment. Because of this, Avista will be looking into additional software
products or alternatives to help increase the necessary flexibility when modeling the future
IRPs.
Resource Integration
The following sections summarize the comprehensive analysis bringing demand
forecasting and existing and potential supply and demand-side resources together to form
the 20-year, least-cost plan.

Demand Forecasting
Chapter 2 - Demand Forecasts describes Avista’s demand forecasting approach.
Avista forecasts demand in the SENDOUT® model in eleven service areas given the
existence of distinct weather and demand patterns for each area and pipeline
infrastructure dynamics. The SENDOUT® areas are Washington and Idaho (each state
is disaggregated into three sub-areas because of pipeline flow limitations); Medford
(disaggregated into two sub-areas because of pipeline flow limitations); and Roseburg,
Klamath Falls and La Grande. In addition to area distinction, Avista also models demand
by customer class within each area. The relevant customer classes are residential,
commercial and firm industrial customers.
Customer demand is highly weather-sensitive. Avista’s customer demand is not only
highly seasonable, but also highly variable. Figure 6.2 captures this variability showing
monthly system-wide average demand, minimum demand day observed by month,
maximum demand day observed in each month, and winter projected peak day demand
for the first year of the Expected Case forecast as determined in SENDOUT®.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Figure 6.2: Total System Average Daily Load (Average, Minimum and Maximum)

Natural Gas Price Forecasts
Natural gas prices play a central part of the IRP and has the largest impact on the costs
used for determining the cost-effectiveness of DSM measures as well as new potential
resources. The price of natural gas also influences consumption, so price elasticity is part
of the demand evaluation shown in Chapter 2 – Demand Forecasts.
The natural gas price outlook has changed dramatically in recent years in response to
several influential events and trends affecting the industry including drilling methods and
technology used in oil and natural gas production, export demand from Mexico and LNG.
These factors combined with the renewable energy standards and the increased need to
back these resources up with natural gas-fired generation are creating. The rapidly
changing environment and uncertainty in predicting future events and trends, requires
modeling a range of forecasts.
The two consultants end up in the same expected price by around 2027 timeframe,
though differ in the timing of LNG export facilities and industrial demand, causing a split
in pricing around the 2021 timeframe. Both consultants expect similar power burn
reaching levels of around 50 Bcf per day by 2035. The Nymex forward curve expects
sufficient supply to provide additional demand throughout its time horizon causing a flat
price curve.
-
50,000
100,000
150,000
200,000
250,000
300,000
350,000
400,000
Dt
h
/
D
a
y
Total System Average Daily Load
(Average, Min, Max)
Max Load Min Load Average Load Peak Day
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Many additional factors influence natural gas pricing and volatility, such as regional
supply/demand issues, weather conditions, storage levels, natural gas-fired generation,
infrastructure disruptions, and infrastructure additions (e.g. new pipelines and LNG
terminals).
Even though Avista continually monitors these factors, we cannot accurately predict
future prices for the 20-year horizon of this IRP. This IRP reviewed several price forecasts
from credible industry experts. Figure 6.3 depicts the price forecasts considered in the
IRP analyses.

Figure 6.3: Henry Hub Forecasted Price (Nominal $/Dth)

The expected curve was a blended price derived from two consulting services
subscriptions along with the New York Mercantile Exchange (NYMEX) forward strip on
February 9, 2018. The expected price curve was weighted heavily toward the NYMEX
prices in the first few years

In the outer years the fundamental curves from the two consultants were more heavily
weighted. This is based on the premise that the market knows more than any single entity
$-
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Nymex (2/9/2018)Consultant 2 Consultant 1
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 131 of 190
or model in the near term. Below is the specific methodology used to develop the
expected price curve:
• Two fundamental forecasts (Consultant #1 & Consultant #2)
• Forward prices
1. Year 1 - forward price only
2. Year 2 - 75% forward price / 25% average consultant forecasts
3. Year 3 - 50% forward price / 50% average consultant forecasts
4. Year 4 – 6 25% forward price / 75% average consultant forecasts
5. Year 7 - 50% average consultant without CO2 / 50% average consultant with CO2

The high and low price curves were derived by varying the price from the expected price
to create a reasonably higher and lower curve while maintaining symmetry. These high
and low prices provide a way to measure pricing risk all while maintaining the balance to
the expected price. The curves are in nominal dollars in Figure 6.4. Additionally,
stochastic modeling of natural gas prices is also completed. The results from that analysis
are in Chapter 7 – Alternate Scenarios, Portfolios and Stochastic Analysis. With the
assistance of the TAC, Avista selected high, expected and low price curves to consider
possible outcomes and their impact on resource planning.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 132 of 190
Figure 6.4 Henry Hub Forecasts for IRP Low/ Expected/ High Forecasted Price – Nominal
$/Dth

Each of the price forecasts above are for Henry Hub, which is located in Louisiana just
onshore from the Gulf of Mexico. Henry Hub is recognized as the most important pricing
point in the U.S. because of its proximity to a large portion of U.S. natural gas production
and the sheer volume traded in the daily or spot market, as well as the forward markets
via the NYMEX futures contracts. Consequently, all other trading points tend to be priced
off of the Henry Hub with a positive or negative basis differential and is based off of a
consultant forecast. Of the two consultants Avista uses, only one has basis pricing going
throughout the twenty year timeframe and at the points modeled. Two of the market points
modeled by Avista, Kingsgate and Stanfield, do not have a futures market making it
difficult to derive a price expectation without a global model of the North America gas
supply landscape.
The primary physical supply points at Sumas, AECO and the Rockies (and other
secondary regional market hubs) determine Avista’s costs. Prices at these points typically
trade at a discount, or negative basis differential, to Henry Hub because of their proximity
to the two largest natural gas basins in North America (Western Canada and the Rockies).
$- $1.00 $2.00 $3.00 $4.00 $5.00 $6.00 $7.00 $8.00 $9.00 $10.00 $11.00 $12.00
$
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High Price Low Price Expected Price
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 133 of 190
Table 6.1 shows the Pacific Northwest regional prices from the consultants, historic
averages and the prior IRP as a percent of Henry Hub price, along with three-year
historical comparisons.

Table 6.1: Regional Price as a Percent of Henry Hub Price
Forecast Average
Consultant2 Forecast Average
Historic Cash Three Year
67.3% 88.2% 90.5% 94.4% 90.7%
88.5% 95.5% 96.8% 98.9% 97.5%

This IRP used monthly prices for modeling purposes because of Avista’s winter-weighted
demand profile. Table 6.2 depicts the monthly price shape used in this IRP. A slight
change to the shape of the pricing curve occurred since the 2016 IRP. Supply availability
drove this change because the forecasted differential between winter and summer pricing
has decreased to some extent compared to historic data.

Table 6.2: Monthly Price as a Percent of Average Price
104.2% 103.8% 100.5% 95.0% 95.6% 96.7%
100.4% 100.3% 98.8% 97.9% 98.4% 99.8%
107.0% 107.2% 97.5% 95.2% 95.6% 96.2%

100.3% 101.9% 100.4% 100.7% 98.3% 102.5%
100.9% 101.6% 101.2% 100.7% 100.1% 100.1%
97.6% 98.4% 98.3% 98.6% 101.8% 106.7%

Avista selected a blend of Consultant 1 and Consultant 2’s forecast of regional prices and
monthly shapes. Appendix 6.1 – Monthly Price Data by Basin contains detailed monthly
price data behind the summary table information discussed above.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 134 of 190
Carbon Policy Avista models carbon as an incremental price adder to address any potential policy.
Carbon adders increase the price of a dekatherm of natural gas and can impact resource
selections and demand through expected elasticity (Chapter 2 – Demand Forecasts,
Price Elasticity). The price of carbon in Oregon was based on the 2018 California annual
auction reserve price of $14.53 per greenhouse gas emissions allowance while growing
by the 5% plus the rate of inflation as indicated by the program structure section 95911
of the California Cap-and-Trade Regulation.1 The starting price for Oregon was assumed
to be similar to California’s cap and trade system where the initial floor was set at $17.86
per metric tons of carbon dioxide equivalent (MTCO2e) and begins in January 20212 rising
to $51.58 by 2037. Washington State was modeled at $10 per MTCO2e starting in 2019
and rising to $30 per MTCO2e by 2030. These carbon tax figures were based on the
initial proposed carbon legislation from Governor Inslee known as Senate Bill 6203.3 The
State of Idaho does not have a carbon adder as there is no current or proposed state or
federal legislation associated with carbon in that jurisdiction. Avista also completed
sensitivities with both a lower and higher than expected price of carbon. These derived
values were taken from the EPA calculations of the social cost of carbon as updated on
January 19, 2017.4 The low carbon price is based on 5 percent average (discount rate
and statistic) and begins at $11.60 per MTCO2e in 2018 and increases to $21.20 by 2037.
The high carbon price is the EPA’s high impact scenario of the average of 95 percent of
results at a 3 percent discount rate. This rate produces much higher cost of carbon
beginning in 2018 at $115.80 and increasing to $174 per MTCO2e by 2037. The effect of
these modeled carbon prices, combined with our expected elasticity as described in
Chapter 2 Demand Forecasts, change demand as shown in Figure 6.5.

1 Article 5 California Cap on Greenhouse gas emissions and market-based compliance mechanisms. https://www.arb.ca.gov/cc/capandtrade/capandtrade/unofficial_ct_100217.pdf

2 Senate Bill 1070 https://olis.leg.state.or.us/liz/2017R1/Downloads/MeasureDocument/SB1070
3 Senate Bill 6203 http://lawfilesext.leg.wa.gov/biennium/2017-18/Pdf/Bills/Senate%20Bills/6203-S.pdf
4Social cost of carbon EPA https://19january2017snapshot.epa.gov/climatechange/social-cost-carbon_.html
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 135 of 190

Figure 6.5: Carbon Legislation sensitivities

Transportation and Storage
Valuing natural gas supplies is a critical first step in resource integration. Equally
important is capturing all costs to deliver the natural gas to customers. Daily capacity of
existing transportation resources (described in Chapter 4 – Supply-Side Resources) is
represented by the firm resource duration curves depicted in Figures 6.6 and 6.7.

30,000
32,000
34,000
36,000
38,000
40,000
42,000
44,000
MD
t
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2018 Demand Sensitivities -Carbon Legislation
Annual Demand -Total System
Carbon Legislation-Low Carbon Legislation-Expected Carbon Legislation-High
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 136 of 190
Figure 6.6: Existing Firm Transportation Resources – Washington & Idaho

Figure 6.7: Existing Firm Transportation Resources – Oregon

0
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1 31 61 91 121 151 181 211 241 271 301 331 361
MDth
Day of Year
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1 31 61 91 121 151 181 211 241 271 301 331 361
MDth
Day of Year
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 137 of 190
Current rates for capacity are in Appendix 6.1 – Monthly Price Data by Basin. Forecasting
future pipeline rates can be challenging because of the need to estimate the amount and
timing of rate changes. Avista’s estimates and timing of future pipeline rate increases are
based on knowledge obtained from industry discussions and participation in pipeline rate
cases. This IRP assumes pipelines will file to recover costs at rates equal to increases in
GDP (see Appendix 6.2 – Weighted Average Cost of Capital).
Demand-Side Management
Chapter 3 – Demand-Side Resources describes the methodology used to identify
conservation potential and the interactive process that utilizes avoided cost thresholds for
determining the cost effectiveness of conservation measures on an equivalent basis with
supply-side resources.

Preliminary Results
After incorporating the above data into the SENDOUT® model, Avista generated an
assessment of demand compared to existing resources for several scenarios. Chapter 2
– Demand Forecasts discusses the demand results from these cases, with additional
details in Appendices 2.1 through 2.9.
Figures 6.8 through 6.11 provide graphic summaries of Average Case demand as
compared to existing resources on a peak day. This demand is net of conservation
savings and shows the adequacy of Avista’s resources under normal weather conditions.
For this case, current resources meet demand needs over the planning horizon.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 138 of 190
Figure 6.8: Average Case – Washington/Idaho Existing Resources vs. Peak Day Demand – February 15th

Figure 6.9: Average Case – Medford / Roseburg Existing Resources vs. Peak Day Demand – December 20th

0
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Spokane Supply Average Day Demand
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Existing GTN Existing NWP JP TF-2 Average Day Demand
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 139 of 190
Figure 6.10: Average Case – Klamath Falls Existing Resources vs. Peak Day Demand – December 20th

Figure 6.11: Average Case – La Grande Existing Resources vs. Peak Day Demand –
February 15th

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Existing NWP JP TF-2 Average Day Demand
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 140 of 190
Figures 6.12 through 6.15 summarize Expected Case peak day demand compared to
existing resources, as well as demand comparisons to the 2016 IRP. This demand is net
of conservation savings. Based on this information, and more specifically where a
resource deficiency is nearly present as shown in Figure 6.9, Avista has time to carefully
monitor, plan and take action on potential resource additions as described in the Ongoing
Activities section of Chapter 9 – Action Plan. Any underutilized resources will be optimized
to mitigate the costs incurred by customers until the resource is required to meet demand.
This management, of both long- and short-term resources, ensures the goal to meet firm
customer demand in a reliable and cost-effective manner as described in Supply Side
Resources – Chapter 4.

Figure 6.12: Expected Case – Washington & Idaho Existing Resources vs. Peak Day
Demand – February 15th

0
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100,000
150,000
200,000
250,000
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350,000
400,000
Dth
Existing GTN Existing NWP JP TF-2
Spokane Supply Peak Day Demand Prior IRP Peak Day Demand
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 141 of 190
Figure 6.13: Expected Case – Medford / Roseburg Existing Resources vs. Peak Day Demand – December 20th

Figure 6.14: Expected Case – Klamath Falls Existing Resources vs. Peak Day Demand –
December 20th

0
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Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 142 of 190
Figure 6.15: Expected Case – La Grande Existing Resources vs. Peak Day Demand – February 15th

If demand grows faster than expected, the need for new resources will be earlier. Flat
demand risk requires close monitoring for signs of increasing demand and reevaluation
of lead times to acquire preferred incremental resources. Monitoring of flat demand risk
includes a reconciliation of forecasted demand to actual demand on a monthly basis. This
reconciliation helps identify customer growth trends and use-per-customer trends. If they
meaningfully differ compared to forecasted trends, Avista will assess the impacts on
planning from procurement and resource sufficiency standing.
Table 6.3 quantifies the forecasted total demand net of conservation savings and
unserved demand from the above charts.

0
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Existing NWP JP TF-2 Peak Day Demand Prior IRP Peak Day Demand
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 143 of 190
Table 6.3: Peak Day Demand – Served and Unserved (MDth/day)

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 144 of 190
New Resource Options
When existing resources are not sufficient to meet expected demand, there are many
important considerations in determining the appropriateness of potential resources.
Interruptible customers’ transportation may be cut, as needed, when existing resources
are not sufficient to meet firm customer demand.

Resource Cost
Resource cost is the primary consideration when evaluating resource options, although
other factors mentioned below also influence resource decisions. Newly constructed
resources are typically more expensive than existing resources, but existing resources
are in shorter supply. Newly constructed resources provided by a third party, such as a
pipeline, may require a significant contractual commitment. However, newly constructed
resources are often less expensive per unit, if a larger facility is constructed, because of
economies of scale.

Lead Time Requirements
New resource options can take one to five or more years to put in service. Open season
processes to determine interest in proposed pipelines, planning and permitting,
environmental review, design, construction, and testing contribute to lead time
requirements for new facilities. Recalls of released pipeline capacity typically require
advance notice of up to one year. Even DSM programs can require significant time from
program development and rollout to the realization of natural gas savings.

Peak versus Base Load
Avista’s planning efforts include the ability to serve firm natural gas loads on a peak day,
as well as all other demand periods. Avista’s core loads are considerably higher in the
winter than the summer. Due to the winter-peaking nature of Avista’s demand, resources
that cost-effectively serve the winter without an associated summer commitment may be
preferable. Alternatively, it is possible that the costs of a winter-only resource may exceed
the cost of annual resources after capacity release or optimization opportunities are
considered.

Resource Usefulness
Available resources must effectively deliver natural gas to the intended region. Given
Avista’s unique service territories, it is often impossible to deliver resources from a
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 145 of 190
resource option, such as storage, without acquiring additional pipeline transportation.
Pairing resources with transportation increases cost. Other key factors that can contribute
to the usefulness of a resource are viability and reliability. If the potential resource is either
not available currently (e.g., new technology) or not reliable on a peak day (e.g., firm),
they may not be considered as an option for meeting unserved demand.

“Lumpiness” of Resource Options
Newly constructed resource options are often “lumpy.” This means that new resources
may only be available in larger-than-needed quantities and only available every few
years. This lumpiness of resources is driven by the cost dynamics of new construction,
where lower unit costs are available with larger expansions and the economics of
expansion of existing pipelines or the construction of new resources dictate additions
infrequently. The lumpiness of new resources provides a cushion for future growth.
Economies of scale for pipeline construction provide the opportunity to secure resources
to serve future demand increases.

Competition LDCs, end-users and marketers compete for regional resources. The Northwest has
efficiently utilized existing resources and has an appropriately sized system. Currently,
the region can accommodate the regional demand needs. However, future needs vary,
and regional LDCs may find they are competing with each other and other parties to
secure firm resources for customers.

Risks and Uncertainties Investigation, identification, and assessment of risks and uncertainties are critical
considerations when evaluating supply resource options. For example, resource costs
are subject to degrees of estimation, partly influenced by the expected timeframe of the
resource need and rigor determining estimates, or estimation difficulties because of the
uniqueness of a resource. Lead times can have varying degrees of certainty ranging from
securing currently available transport (high certainty) to building underground storage
(low certainty).

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 146 of 190
Resource Selection After identifying supply-side resource options and evaluating them based on the above
considerations, Avista entered the supply-side scenarios (see Table 6.2) and
conservation measures (see Chapter 3 – Demand-Side Resources) into the SENDOUT®
model for it to select the least cost approach to meeting resource deficiencies, if they
exist. SENDOUT® compares demand-side and supply-side resources (see Appendix 6.3
– Supply Side Resource Options for a list of available options) using PVRR analysis to
determine which resource is a least cost/least risk resource.

Demand-Side Resources

Integration by Price
As described in Chapter 3 – Demand-Side Resources, the model runs without future DSM
programs. This preliminary model run provides an avoided cost curve for Applied Energy
Group (AEG) to evaluate the cost effectiveness of DSM programs against the initial
avoided cost curve using the Utility Cost Test, Program Administrator Costs Test, Total
Resource Cost Test, and Participant Cost Test. The therm savings and associated
program costs are incorporated into the SENDOUT® model. After incorporation, the
avoided costs are re-evaluated. This process continues until the change in avoided cost
curve is immaterial.
Avoided Cost
The SENDOUT® model determined avoided-cost figures represent the unit cost to serve
the next unit of demand with a supply-side resource option during a given period. If a
conservation measure’s total resource cost (for Idaho and Oregon), or utility cost (for
Washington), is less than this avoided cost, it will be cost effective to reduce customer
demand and Avista can avoid commodity, storage, transportation and other supply
resource costs.
SENDOUT® calculates marginal cost data by day, month and year for each demand area.
A summary graphical depiction of avoided annual and winter costs for the
Washington/Idaho and Oregon areas is in Figure 6.16. The detailed data is in Appendix
6.4 – Avoided Cost Details. Other than the carbon tax adder embedded in the expected
price curve, avoided costs do not include additional environmental externality adders for
adverse environmental impacts. Appendix 3.2 – Environmental Externalities discusses
this concept more fully and includes specific requirements required in modeling for the
Oregon service territory.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 147 of 190
Figure 6.16: Avoided Cost (Includes Commodity & Transport Cost – 2016 vs. 2018 $/Dth)

Conservation Potential Using the avoided cost thresholds, AEG selected all potential cost effective DSM
programs. Table 6.4 shows potential DSM savings in each region from the selected
conservation potential for the Expected Case. The conservation potential includes
anticipated annual acquisition and is cumulative.

$0.00
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$/Dth Avoided Cost Comparison2016 IRP vs. 2018 IRP
WA/ID Annual - 2018 OR Annual - 2018
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 148 of 190
Table 6.4: Annual and Average Daily Demand Served by Conservation

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 149 of 190
Conservation Acquisition Goals
The avoided cost established in SENDOUT®, the conservation potential selected, and
the amount of therm savings is the basis for determining conservation acquisition goals
and subsequent DSM program implementation planning. Chapter 3 – Demand-Side
Resources has additional details on this process.

Supply-Side Resources
SENDOUT® considers all options entered into the model, determines when and what
resources are needed, and which options are cost effective. Selected resources represent
the best cost/risk solution, within given constraints, to serve anticipated customer
requirements. Since the Expected Case has no resource additions in the planning
horizon, Avista will continue to review and refine knowledge of resource options and will
act to secure best cost/risk options when necessary or advantageous.

Resource Utilization
Avista plans to meet firm customer demand requirements in a cost-effective manner. This
goal encompasses a range of activities from meeting peak day requirements in the winter
to acting as a responsible steward of resources during periods of lower resource
utilization. As the analysis presented in this IRP indicates, Avista has ample resources to
meet highly variable demand under multiple scenarios, including peak weather events.
Avista acquired the majority of its upstream pipeline capacity during the deregulation or
unbundling of the natural gas industry. Pipelines were required to allocate capacity and
costs to their existing customers as they transitioned to transportation only service
providers. The FERC allowed a rate structure for pipelines to recover costs through a
Straight Fixed Variable rate design. This structure is based on a higher reservation charge
to cover pipeline costs whether natural gas is transported or not, and a much smaller
variable charge which is incurred only when natural gas is transported. An additional fuel
charge is assessed to account for the compressors required to move the natural gas to
customers. Avista maintains enough firm capacity to meet peak day requirements under
the Expected Case in this IRP. This requires pipeline capacity contracts at levels in
excess of the average and above minimum load requirements. Given this load profile and
the Straight Fixed Variable rate design, Avista incurs ongoing pipeline costs during non-
peak periods.
Avista chooses to have an active, hands-on management of resources to mitigate
upstream pipeline and commodity costs for customers when the capacity is not utilized
for system load requirements. This management simultaneously deploys multiple long-
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 150 of 190
and short-term strategies to meet firm demand requirements in a cost effective manner.
The resource strategies addressed are:
• Pipeline contract terms;
• Pipeline capacity;
• Storage;
• Commodity and transport optimization; and
• Combination of available resources.

Pipeline Contract Terms
Some pipeline costs are incurred whether the capacity is utilized or not. Winter demand
must be satisfied and peak days must be met. Ideally, capacity could be contracted from
pipelines only for the time and days it is required. Unfortunately, this is not how pipelines
are contracted or built. Long-term agreements at fixed volumes are usually required for
building or acquiring firm transport. This assures the pipeline of long-term, reasonable
cost recovery.
Avista has negotiated and contracted for several seasonal transportation agreements.
These agreements allow volumes to increase during the demand intensive winter months
and decrease over the lower demand summer period. This is a preferred contracting
strategy because it eliminates costs when demand is low. Avista refers to this as a front
line strategy because it attempts to mitigate costs prior to contracting the resource. Not
all pipelines offer this option. Avista seeks this type of arrangement where available.
Avista currently has some seasonal transportation contracts on TransCanada GTN,
TransCanada BC and TransCanada Alberta. These pipelines match up transport capacity
to move natural gas from Alberta (AECO) to Avista’s service territories. Avista also
contracted for TF2 on NWP. This is a storage specific contract and matches up the
withdrawal capacity at Jackson Prairie with pipeline transport to Avista’s service
territories. TF2 is a firm service and allows for contracting a daily amount of transportation
for a specified number of days rather than a daily amount on an annual basis as is usually
required. For example, one of the TF2 agreements allows Avista to transport 91,200
Dth/day for 31 days. This is a more cost effective strategy for storage transport than
contracting for an annual amount. Through NWP’s tariff, Avista maintains an option to
increase and decrease the number of days this transportation option is available. More
days correspond to increased costs, so balancing storage, transport and demand is
important to ensure an optimal blend of cost and reliability.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 151 of 190
Pipeline Capacity
After contracting for pipeline capacity, its management and utilization determine the
actual costs. The worst-case economic scenario is to do nothing and simply incur the
costs associated with this transport contract over the long-term to meet current and future
peak demand requirements. Avista develops strategies to ensure this does not happen
on a regular basis if at all possible.

Capacity Release
Through the pipeline unbundling of transportation, the FERC establishes rules and
procedures to ensure a fair market developed to manage pipeline capacity as a
commodity. This evolved into the capacity release market and is governed by FERC
regulations through individual pipelines. The pipelines implement the FERC’s posting
requirements to ensure a transparent and fair market is maintained for the capacity. All
capacity releases are posted on the pipelines Bulletin Boards and, depending on the
terms, may be subject to bidding in an open market. This provides the transparency
sought by the FERC in establishing the release requirements. Avista utilizes the capacity
release market to manage both long-term and short-term transportation capacity.
For capacity under contract that may exceed current demand, Avista seeks other parties
that may need it and arranges for capacity releases to transfer rights, obligations and
costs. This shifts all or a portion of the costs away from Avista’s customers to a third party
until it is needed to meet customer demand.
Many variables determine the value of natural gas transportation. Certain pipeline paths
are more valuable and this can vary by year, season, month and day. The term, volume
and conditions present also contribute to the value recoverable through a capacity
release. For example, a release of winter capacity to a third party may allow for full cost
recovery; while a release for the same period that allows Avista to recall the capacity for
up to 10 days during the winter may not be as valuable to the third party, but of high value
to us. Avista may be willing to offer a discount to retain the recall rights during high
demand periods. This turns a seasonal-for-annual cost into a peaking-only cost. Market
terms and conditions are negotiated to determine the value or discount required by both
parties.
Avista has several long-term releases, some extending through 2025 providing full
recovery of all the pipeline costs. These releases maintain Avista’s long-term rights to the
transportation capacity without incurring the costs of waiting until demand increases. As
the end of these release terms near, Avista surveys the market against the IRP to
determine if these contracts should be reclaimed or released, and for what duration.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 152 of 190
Through this process, Avista retains the rights to vintage capacity without incurring the
costs or having to participate in future pipeline expansions that will cost more than current
capacity.
On a shorter term, excess capacity not fully utilized on a seasonal, monthly or daily basis
can also be released. Market conditions often dictate less than full cost recovery for
shorter-term requirements. Mitigating some costs for an unutilized, but required resource
reduces costs to our customers.

Segmentation Through a process called segmentation, Avista creates new firm pipeline capacity for the
service territory. This doubles some of the capacity volumes at no additional cost to
customers. With increased firm capacity, Avista can continue some long-term releases,
or even reduce some contract levels, if the release market does not provide adequate
recovery. An example of segmentation is if the original receipt and delivery points are
from Sumas to Spokane. Avista can alter this path from Sumas to Sipi, Sipi to Jackson
Prairie, Jackson Prairie to Spokane. This segmentation allows Avista to flow three times
the amount of natural gas on most days or non-peak weather events. In the event of a
peak day, and the transport needs to be firm, the transportation can be rolled back up to
ensure the natural gas will be delivered into the original firm path.
Storage
As a one-third owner of the Jackson Prairie Storage facility, Avista holds an equal share
of capacity (space available to store natural gas) and delivery (the amount of natural gas
that can be withdrawn on a daily basis).
Storage allows lower summer-priced natural gas to be stored and used in the winter
during high demand or peak day events. Similar to transportation, unneeded capacity and
delivery can be optimized by selling into a future higher priced market. This allows Avista
to manage storage capacity and delivery to meet growing peak day requirements when
needed.
The injection of natural gas into storage during the summer utilizes existing pipeline
transport and helps increase the utilization factor of pipeline agreements. Avista employs
several storage optimization strategies to mitigate costs. Revenue from this activity flows
through the annual PGA/Deferral process.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 153 of 190
Commodity and Transportation Optimization
Another strategy to mitigate transportation costs is to participate in the daily market to
assess if unutilized capacity has value. Avista seeks daily opportunities to purchase
natural gas, transport it on existing unutilized capacity, and sell it into a higher priced
market to capture the cost of the natural gas purchased and recover some pipeline
charges. The amount of recovery is market dependent and may or may not recover all
pipeline costs, but does mitigate pipeline costs to customers.

Combination of Resources Unutilized resources like supply, transportation, storage and capacity can combine to
create products that capture more value than the individual pieces. Avista has structured
long-term arrangements with other utilities that allow available resource utilization and
provide products that no individual component can satisfy. These products provide more
cost recovery of the fixed charges incurred for the resources while maintaining the rights
to utilize the resource for future customer needs.

Resource Utilization Summary
As determined through the IRP modeling of demand and existing resources, new
resources under the Expected Case are not required over the next 20 years. Avista
manages the existing resources to mitigate the costs incurred by customers until the
resource is required to meet demand. The recovery of costs is often market based with
rules governed by the FERC. Avista is recovering full costs on some resources and partial
costs on others. The management of long- and short-term resources meets firm customer
demand in a reliable and cost-effective manner.

Conclusion
Choosing reliable information and methods to utilize in these analyses help Avista
determine an expected criteria. To do this, Avista utilizes industry experts to help
determine an expected price and market environment, decades of historic weather by
major service area, daily weather adjusted usage metrics combined with a statistical
based customer forecast all help to provide a reasonable range of expectations for this
planning period. There are no expected resource deficiencies during this 20-year forecast
in either the Average Case or Expected Case in this IRP. Avista will rely on its Expected
Case for peak operational planning activities and in its optimization programs to
sufficiently plan for cold day events.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 154 of 190
Avista recognizes that there are other potential outcomes. The process described in this
chapter applies to the alternate demand and supply resource scenarios covered in
Chapter 7 – Alternate Scenarios, Portfolios and Stochastic Analysis.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 155 of 190
7: Alternate Scenarios,
Portfolios and Stochastic
Analysis

Overview
Avista applied the IRP analysis in Chapter 6 –
Integrated Resource Portfolio to alternate demand
and supply resource scenarios to develop a range
of alternate portfolios. This deterministic modeling
approach considered different underlying
assumptions vetted with the TAC members to
develop a consensus about the number of cases to
model.
Avista also performed stochastic modeling for
estimating probability distributions of potential
outcomes by allowing for random variation in
natural gas prices and weather based on
fluctuations in historical data. This statistical analysis, in conjunction with the deterministic
analysis, enabled statistical quantification of risk from reliability and cost perspectives
related to resource portfolios under varying price and weather conditions.

Alternate Demand Scenarios
As discussed in the Demand Forecasting section, Avista identified alternate scenarios for
detailed analysis to capture a range of possible outcomes over the planning horizon.
Table 7.1 summarizes these scenarios and Chapter 2 – Demand Forecasts and
Appendices 2.6 and 2.7 describes them in detail. The scenarios consider different
demand influencing factors and price elasticity effects for various price influencing factors.

Chapter
Highlights
•High Growth and Low
Price case results in
unserved demand
•Multiple portfolios
considered to help
measure range of
possible outcomes
•RNG and Hydrogen are
considered in the
available resource stack
for the first time
•Landfill RNG is selected
as a resource in the High
Growth and Low Price
case
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 156 of 190
Table 7.1: 2018 IRP Scenarios

Demand profiles over the planning horizon for each of the scenarios shown in Figures 7.1
and 7.2 reflect the two winter peaks modeled for the different service territories (Dec. 20
and Feb. 15).

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 157 of 190
Figure 7.1 Peak Day (Feb 15) – 2018 IRP Demand Scenarios

Figure 7.2 Peak Day (Dec 20) – 2018 IRP Demand Scenarios

100
150
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250
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450
MD
t
h
High and Low Expected Case
80 % Below 1990 Emissions Cold Day 20yr Weather Std
Average Case
100
150
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450
MD
t
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High and Low Expected Case
80 % Below 1990 Emissions Cold Day 20yr Weather Std
Average Case
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 158 of 190
As in the Expected Case, Avista used SENDOUT® to model the same resource
integration and optimization process described in this section for each of the six demand
scenarios (see Appendix 2.7 for a complete listing of portfolios considered). This
deterministic analysis identified the first year unserved dates for each scenario by service
territory shown in Figure 7.3.

Figure 7.3: First Year Peak Demand Not Met with Existing Resources

Steeper demand highlights the flat demand risk discussed earlier. The likelihood of this
scenario occurring is remote due to a yearly recurrence of coldest day on record weather
paired with a much steeper growth of customer population; however, any potential for
accelerated unserved dates warrants close monitoring of demand trends and resource
lead times as described in the Ongoing Activities section of Chapter 9 – Action Plan. The
remaining scenarios do not identify resource deficiencies in the planning horizon.
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
WA/ID Medford/Roseburg Klamath La Grande
Fi
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Expected Case 80 % Below 1990 EmissionsHigh Growth & Low Prices Low Growth & High PricesCold Day 20yr Weather Std Average Case
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 159 of 190
Alternate Supply Resources
Avista identified supply-side resources that could meet resource deficiencies or provide
a least cost solution. There are other options Avista considered in its modeling approach
to solve for High Growth & Low Price unserved conditions and to determine whether the
Expected Case with existing resources is least cost/least risk. A list of the modeled
available supply resources are included in Table 7.2 and potential future resources are
included in Table 7.3.
Table 7.2: Available Supply Resources

Table 7.3: Future Supply Resources

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 160 of 190
For example, contracted city gate deliveries in the form of a structured purchase
transaction could meet peak conditions. However, the market-based price and other
terms are difficult to reliably determine until a formal agreement is negotiated. Exchange
agreements also have market-based terms and are hard to reliably model when the
resource need is later in the planning horizon. Current tariff prices were used to model
additional GTN capacity and Plymouth LNG, while an estimate was provided from GTN
for the upsized Medford lateral compressor combined with tariff rates in order to flow the
gas. For those costs specifically related to all four RNG projects and hydrogen Avista
contracted with a consultant to provide cost estimates for these types of facilities. Some
of the major costs include: Capital, O&M, Avista’s revenue requirement, federal income
tax, and depreciation. Avista also included any subsidies known at the time of modeling.
These projects include a cost of carbon adder for any amount of carbon intensity still
associated with each project type. Specifically, dairy and solid waste have a negative
carbon intensity as compared to natural gas as a fuel source (Table 4.2). The net effect
of using this is the removal of carbon from the atmosphere. Finally, Renewable
Identification Number (RIN)1 values were not included in the valuation of RNG as it is
assumed that these RIN’s would be needed to provide proof of Avista’s utilization of RNG
or in complying with new environmental legislation.
Many of the potential resources are not yet commercially available or well tested,
technically making them speculative. Resources such as coal-bed methane, LNG imports
and natural gas hydrates would fall into this category. Avista will continue to monitor all
resources and assess their appropriateness for inclusion in future IRPs as described in
Chapter 9 – Action Plan.
One resource which will be closely observed is exported LNG. While Avista considered
LNG exports, it was primarily as a price-influencing factor. However, if the proposed
export LNG terminal in Oregon is approved and a pipeline built to supply that facility, it
potentially could bring new supply through Avista’s service territory. Avista will monitor
(Chapter 9 – Action Plan) this situation through industry publications and daily operations
to consider inclusion of this supply scenario for future IRPs.
Deterministic – Portfolio Evaluation
There is no resource deficiency identified in the planning period and the existing resource
portfolio is adequate to meet forecasted demand. The alternate demand scenarios and
supply scenarios are placed in the model as predicted future conditions that the supply
portfolio will have to satisfy via least cost and least risk strategies. This creates bounds
for analyzing the Expected Case by creating high and low boundaries for customer count,
weather and pricing. Each portfolio runs through SENDOUT® where the supply resources
1 https://www.epa.gov/renewable-fuel-standard-program/renewable-identification-numbers-rins-under-
renewable-fuel-standard
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 161 of 190
(Chapter 4 – Supply Side Resources) and conservation resources (Chapter 3 – Demand
Side Management – see tables 3.2, 3.3 and 3.4) are compared and selected on a least
cost basis. Once new resources are determined, a net present value of the revenue
requirement (PVRR) is calculated.

Table 7.4: PVRR by Portfolio
Expected Case $ (5,035,892)
High Growth & Low Prices $ (3,093,097)
80% Below 1990 Levels $ (2,990,501)
Average Case $ (4,900,092)
Cold Day 20yr Weather Std $ (5,018,719)
Low Growth & High Prices $ (6,087,380)

Stochastic Analysis2
The scenario (deterministic) analysis described earlier in this chapter represents specific
what if situations based on predetermined assumptions, including price and weather.
These factors are an integral part of scenario analysis. To understand a particular
portfolio’s response to cost and risk, through price and weather, Avista applied stochastic
analysis to generate a variety of price and weather events.
Deterministic analysis is a valuable tool for selecting an optimal portfolio. The model
selects resources to meet peak weather conditions in each of the 20 years. However, due
to the recurrence of design conditions in each of the 20 years, total system costs over the
planning horizon can be overstated because of annual recurrence of design conditions
and the recurrence of price increases in the forward price curve. As a result, deterministic
analysis does not provide a comprehensive look at future events. Utilizing Monte Carlo
simulation in conjunction with deterministic analysis provides a more complete picture of
portfolio performance under multiple weather and price profiles.
This IRP employs stochastic analysis in two ways. The first tested the weather-planning
standard and the second assessed risk related to costs of our Expected Case (existing
portfolio) under varying price environments. The Monte Carlo simulation in SENDOUT®
can vary index price and weather simultaneously. This simulates the effects each have
on the other.
2 SENDOUT® uses Monte Carlo simulation to support stochastic analysis, which is a mathematical
technique for evaluating risk and uncertainty. Monte Carlo simulation is a statistical modeling method used to imitate future possibilities that exist with a real-life system.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 162 of 190
Weather In order to evaluate weather and its effect on the portfolio, Avista developed 200
simulations (draws) through SENDOUT®’s stochastic capabilities. Unlike deterministic
scenarios or sensitivities, the draws have more variability from month-to-month and year-
to-year. In the model, random monthly total HDD draw values (subject to Monte Carlo
parameters – see Table 7.5) are distributed on a daily basis for a month in history with
similar HDD totals. The resulting draws provide a weather pattern with variability in the
total HDD values, as well as variability in the shape of the weather pattern. This provides
a more robust basis for stress testing the deterministic analysis.

Table 7.5: Example of Monte Carlo Weather Inputs – Spokane

Avista models five weather areas: Spokane, Medford, Roseburg, Klamath Falls and La
Grande. Avista assessed the frequency that the peak day occurs in each area from the
simulation data. The stochastic analysis shows that in over 200, 20-year simulations,
peak day (or more) occurs with enough frequency to maintain the current planning
standard for this IRP. This topic remains a subject of continued analysis. For example,
the Medford weather pattern over the 200 20-year draws (i.e, 4,000 years). HDDs at or
above peak weather (61 HDDs) occur 128 times. This equates to a peak day occurrence
once every 31 years (4,000 simulation years divided by 128 occurrences). The Spokane
area has the least occurrences of peak day (or more) occurrences and La Grande has
the most occurrences. This is primarily due to the frequency in which each region’s peak
day HDD occurs within the historical data, as well as near peak day HDDs. See Figures
7.4 through 7.8 for the number of peak day occurrences by weather area.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 163 of 190
Figure 7.4: Frequency of Peak Day Occurrences – Spokane

Figure 7.5: Frequency of Peak Day Occurrences – Medford

0
0.5
1
1.5
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1 8 15 22 29 36 43 50 57 64 71 78 85 92 99
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82HDD
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61HDD
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 164 of 190
Figure 7.6: Frequency of Peak Day Occurrences – Roseburg

Figure 7.7: Frequency of Peak Day Occurrences – Klamath Falls

0
1
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1 8 15 22 29 36 43 50 57 64 71 78 85 92 99
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55HDD
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72HDD
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 165 of 190
Figure 7.8: Frequency of Peak Day Occurrences – La Grande

Price
While weather is an important driver for the IRP, price is also important. As seen in recent
years, significant price volatility can affect the portfolio. In deterministic modeling, a single
price curve for each scenario is used for analysis. There is risk that the price curve in the
scenario will not reflect actual results.
Avista used Monte Carlo simulation to test the portfolio and quantify the risk to customers
when prices do not materialize as forecast. Avista performed a simulation of 200 draws,
varying prices, to investigate whether the Expected Case total portfolio costs from the
deterministic analysis is within the range of occurrences in the stochastic analysis. Figure
6.9 shows a histogram of the total portfolio cost of all 200 draws, plus the Expected Case
results. This histogram depicts the frequency and the total cost of the portfolio among all
the draws, the mean of the draws, the standard deviation of the total costs, and the total
costs from the Expected Case. The figure confirms that Expected Case total portfolio cost
is within an acceptable range of total portfolio costs based on 200 unique pricing
scenarios.

0
1
2
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1 8 15 22 29 36 43 50 57 64 71 78 85 92 99
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74HDD
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 166 of 190
Figure 7.9: 2018 IRP Total 20-Year Cost

Performing stochastic analysis on weather and price in the demand analysis provided a
statistical approach to evaluate and confirm the findings in the scenario analysis with
respect to adequacy and reasonableness of the weather-planning standard and the
natural gas price forecast. This analytical perspective provides confidence in the
conclusions and stress tests the robustness of the selected portfolio of resources, thereby
mitigating analytical risks.

Solving Unserved Demand
The components, methods and topics covered in this and previous chapters will now help
to solve unserved demand in The High Growth & Low Price scenario. This scenario
includes customer growth rates higher than the Expected Case, incremental demand
driven by emerging markets and no adjustment for price elasticity. Even with aggressive
assumptions, deterministic analysis shows resource shortages do not occur until late in
the planning horizon.
• 2032 in Washington/Idaho
• 2031 in Medford/Roseburg
• 2032 in La Grande
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 167 of 190
We begin to solve for unserved demand by adding additional resources as supply side
options. The resources Avista modeled for the current IRP include 5 types of renewable
natural gas, hydrogen, and an upsized compressor on the Medford lateral, additional GTN
capacity and Plymouth LNG as seen in Table 7.2. All costs are entered by location with
the associated daily, pipeline quality, volume available to inform the model. A
deterministic resource mix is performed allowing the model to solve the demand based
on the optimal least cost solution for the system as a whole. Avista performed this
selection process both deterministically and stochastically. In Figure 7.10, the
deterministic resource add by supply type is shown by cost and risk.

Figure 7.10: Deterministic analysis by resource

Table 7.6 demonstrates, by new supply resource or type from the deterministic runs:
1. the twenty year system cost of only the specific resource
2. the average monthly risk or standard deviation of the system cost and
3. if resource would solve system unserved demand.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 168 of 190
Table 7.6 – System cost, standard deviation and outcome of adding resource to system:
Once an optimal resource is found deterministically a stochastic analysis takes place to
measure risk. Figure 7.11 depicts a stochastic simulation with all options available in order
to solve the unserved system demand in a least cost solution.

The optimal solution Figure 7.11: High Growth and Low Price Cost vs. Risk (200 Draws)

$0
$1,000
$2,000
$3,000
$4,000
$5,000
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$2,600,000 $2,700,000 $2,800,000 $2,900,000 $3,000,000 $3,100,000
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(Deterministic)
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 169 of 190
Stochastically, the model solved the unserved demand by selecting the following supply
sources, below, and can be seen in Figure 7.12:
1. Additional capacity from Kingsgate to Spokane in 2026
2. Centralized landfill gas in Idaho (LFC_ID35) in 2035
3. Upsized compressor on Medford lateral in 2026

Figure 7.12: High Growth and Low Price - Average Supply by Source and Area on
February 15th (200 Draws)

AECO
LFC_ID35 KingsgateMalinRMP
Spokane
Stanfield
STN2
Sumas
JP
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AECO LFC_ID35 Kingsgate Malin RMP Spokane Stanfield STN2 Sumas JP
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 170 of 190
The stochastic analysis shows a supply resource need in the 2026 timeframe. In a
stochastic analysis, variability and randomness based on historical information is utilized
to measure risk and unknown elements (price and weather). An example of this lies within
our expected coldest on record weather assumption. Within the deterministic model this
value is equal to exactly 82 HDD in Avista’s Washington and Idaho service territories, but
in a single random draw, this value is slightly higher at 82.18 HDD affecting the overall
demand. A slight increase in weather expectations can alter the unserved timeframe,
especially in areas with higher populations or those nearing their current resource limits.
Of the 200 – 20 year futures, less than 10 observe an unserved demand earlier than those
in the deterministic analysis. Randomly simulated future prices provide the model with the
ability to select from a variety of potential supply side resources over a range of 200 – 20
year future draws. When looking for the lowest cost and least risk portfolio, the model will
look to solve unserved demand in each 20 year scenario with the lowest cost resources
based on the values simulated (weather and price) and provided costs(transportation
costs, storage costs, etc.) Additional detailed information on this and other scenarios is
included in the following appendices:
1. Demand and Existing Resources graph by service territory (High Growth Case
only) – Appendix 7.1
2. Peak Day Demand, Served and Unserved table (all cases) – Appendix 7.2
Regulatory Requirements
IRP regulatory requirements in Idaho, Oregon and Washington call for several key
components. The completed plan must demonstrate that the IRP:
• Examines a range of demand forecasts.
• Examines feasible means of meeting demand with both supply-side and demand-
side resources.
• Treats supply-side and demand-side resources equally.
• Describes the long-term plan for meeting expected demand growth.
• Describes the plan for resource acquisitions between planning cycles.
• Takes planning uncertainties into consideration.
• Involves the public in the planning process.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 171 of 190
Avista addressed the applicable requirements throughout this document. Appendix 1.2 –
IRP Guideline Compliance Summaries lists the specific requirements and guidelines of
each jurisdiction and describes Avista’s compliance.
The IRP is also required to consider risks and uncertainties throughout the planning and
analytical processes. Avista’s approach in addressing this requirement was to identify
factors that could cause significant deviation from the Expected Case planning
conclusions. This included dynamic demand analytical methods and sensitivity analysis
on demand drivers that impacted demand forecast assumptions. From this, Avista
created 15 demand sensitivities and modeled five demand scenario alternatives, which
incorporated different customer growth, use-per-customer, weather, and price elasticity
assumptions.
Avista analyzed peak day weather planning standard, performing sensitivity on HDDs and
modeling an alternate weather-planning standard using the coldest day in 20 years.
Stochastic analysis using Monte Carlo simulations in SENDOUT® supplemented this
analysis. Avista also used simulations from SENDOUT® to analyze price uncertainty and
the effect on total portfolio cost.
Avista examined risk factors and uncertainties that could affect expectations and
assumptions with respect to DSM programs and supply-side scenarios. From this, Avista
assessed the expected available supply-side resources and potential conservation
savings for evaluation.
The investigation, identification, and assessment of risks and uncertainties in our IRP
process should reasonably mitigate surprise outcomes.
Conclusion
In planning, a reasonable set of criteria is necessary to help measure the inherent risk of
the unknown in future events. In prior years the “Low Growth and High Prices” scenario
was considered our lower band of risk. In the 2018 IRP, Avista has added a new risk in
the scenario referred to as “80% below 1990 emissions” due to a continued policy shift
toward a reduced role of natural gas as a fuel choice. In all but one scenario, High Growth
and Low Prices, the firm customer demand is served with existing resources. Simulating
random future events by case with unserved demand provides a better idea of the risk
and costs involved in each resource. This will allow Avista to monitor customer growth
and demand while maintaining a watchful eye on policy and new resources.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 172 of 190

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 173 of 190
8: Distribution Planning

Overview
Avista’s IRP evaluates the safe, economical and
reliable full-path delivery of natural gas from basin
to the customer meter. Securing adequate natural
gas supply and ensuring sufficient pipeline
transportation capacity to Avista’s city gates
become secondary issues if distribution system
growth behind the city gates increases faster than
expected and the system becomes severely
constrained. Important parts of the distribution
planning process include forecasting local demand
growth, determining potential distribution system
constraints, analyzing possible solutions and
estimating costs for eliminating constraints.
Analyzing resource needs to this point has focused
on ensuring adequate capacity to the city gates, especially during a peak event.
Distribution planning focuses on determining if there will be adequate pressure during a
peak hour. Despite this altered perspective, distribution planning shares many of the
same goals, objectives, risks and solutions as integrated resource planning.
Avista’s natural gas distribution system consists of approximately 3,300 miles of
distribution main and services pipelines in Idaho, 3,700 miles in Oregon and 5,800 miles
in Washington; as well as numerous regulator stations, service distribution lines,
monitoring and metering devices, and other equipment. Currently, there are no storage
facilities or compression systems within Avista’s distribution system. Distribution network
pipelines and regulating stations operate and maintain system pressure solely from the
pressure provided by the interstate transportation pipelines.

Distribution System Planning
Avista conducts two primary types of evaluations in its distribution system planning
efforts: capacity requirements and integrity assessments.
Capacity requirements include distribution system reinforcements and expansions.
Reinforcements are upgrades to existing infrastructure, or new system additions, which
increase system capacity, reliability and safety. Expansions are new system additions to
accommodate new demand. Collectively, these reinforcements and expansions are
distribution enhancements.
Highlights
•Avista maintains its
distribution system based
on economics, safety and
reliability
•Avista maintains a total of
12,800 miles of
distribution in three
jurisdictions
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 174 of 190
Ongoing evaluations of each distribution network in the four primary service territories
identify strategies for addressing local distribution requirements resulting from customer
growth. Customer growth assessments are made based on factors including IRP demand
forecasts, monitoring gate station flows and other system metering, new service requests,
field personnel discussion, and inquiries from major developers.
Avista regularly conducts integrity assessments of its distribution systems. Ongoing
system evaluation can indicate distribution-upgrading requirements for system
maintenance needs rather than customer and load growth. In some cases, the timing for
system integrity upgrades coincides with growth-related expansion requirements. These
planning efforts provide a long-term planning and strategy outlook and integrate into the
capital planning and budgeting process, which incorporates planning for other types of
distribution capital expenditures and infrastructure upgrades.
Gas Engineering planning models are also compared with capacity limitations at each
city gate station. Referred to as city gate analysis, the design day hourly demand
generated from planning analyses must not exceed the actual physical limitation of the
city gate station. A capacity deficiency found at a city gate station establishes a potential
need to rebuild or add a new city gate station.

Network Design Fundamentals
Natural gas distribution networks rely on pressure differentials to flow natural gas from
one place to another. When pressures are the same on both ends of a pipe, the natural
gas does not move. As natural gas exits the pipeline network, it causes a pressure drop
due to its movement and friction. As customer demand increases, pressure losses
increase, reducing the pressure differential across the pipeline network. If the pressure
differential is too small, flow stalls and the network could run out of pressure.
It is important to design a distribution network such that intake pressure from gate stations
and/or regulator stations within the network is high enough to maintain an adequate
pressure differential when natural gas leaves the network.
Not all natural gas flows equally throughout a network. Certain points within the network
constrain flow and restrict overall network capacity. Network constraints can occur as
demand requirements evolve. Anticipating these demand requirements, identifying
potential constraints and forming cost-effective solutions with sufficient lead times without
overbuilding infrastructure are the key challenges in network design.

Computer Modeling
Developing and maintaining effective network design is aided by computer modeling for
network demand studies. Demand studies have evolved with technology to become a
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 175 of 190
highly technical and powerful means of analyzing distribution system performance. Using
a pipeline fluid flow formula, a specified parameter for each pipe element can be
simultaneously solved. Many pipeline equations exist, each tailored to a specific flow
behavior. These equations have been refined through years of research to the point
where modeling solutions closely resemble actual system behavior.
Avista conducts network load studies using GL Noble Denton’s Synergi software. This
modeling tool allows users to analyze and interpret solutions graphically.

Determining Peak Demand
Avista’s distribution network is comprised of high pressure (90-500 psig) and intermediate
pressure (5-60 psig) mains. Avista operates its intermediate networks at a relatively low
maximum pressure of 60 psig or less for ease of maintenance and operation, public
safety, reliable service, and cost considerations. Since most distribution systems operate
through relatively small diameter pipes, there is essentially no line-pack capability for
managing hourly demand fluctuations. Line pack is the difference between the natural
gas contents of the pipeline under packed (fully pressurized) and unpacked
(depressurized) conditions. Line pack is negligible in Avista’s distribution system due to
the smaller diameter pipes and lower pressures. In transmission and inter-state pipelines,
line-pack contributes to the overall capacity due to the larger diameter pipes and higher
operating pressures.
Core demand typically has a morning peaking period between 6 a.m. and 10 a.m. and
the peak hour demand for these customers can be as much as 50 percent above the
hourly average of daily demand. Because of the importance of responding to hourly
peaking in the distribution system, planning capacity requirements for distribution systems
uses peak hour demand.1

Distribution System Enhancements
Demand studies facilitate modeling multiple demand forecasting scenarios, constraint
identification and corresponding optimum combinations of pipe modification, and
pressure modification solutions to maintain adequate pressures throughout the network.
Distribution system enhancements do not reduce demand nor do they create additional
supply. Enhancements can increase the overall capacity of a distribution pipeline system
while utilizing existing gate station supply points. The two broad categories of distribution
enhancement solutions are pipelines and regulators.
1 This method differs from the approach that Avista uses for IRP peak demand planning, which focuses on peak day requirements to the city gate.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 176 of 190
Pipelines Pipeline solutions consist of looping, upsizing and uprating. Pipeline looping is the most
common method of increasing capacity in an existing distribution system. Looping
involves constructing new pipe parallel to an existing pipeline that has, or may become,
a constraint point. Constraint points inhibit flow capacities downstream of the constraint
creating inadequate pressures during periods of high demand. When the parallel line
connects to the system, this alternative path allows natural gas flow to bypass the original
constraint and bolsters downstream pressures. Looping can also involve connecting
previously unconnected mains. The feasibility of looping a pipeline depends upon the
location where the pipeline will be constructed. Installing natural gas pipelines through
private easements, residential areas, existing paved surfaces, and steep or rocky terrain
can increase the cost to a point where alternative solutions are more cost effective.
Pipeline upsizing involves replacing existing pipe with a larger size pipe. The increased
pipe capacity relative to surface area results in less friction, and therefore a lower
pressure drop. This option is usually pursued when there is damaged pipe or where pipe
integrity issues exist. If the existing pipe is otherwise in satisfactory condition, looping
augments existing pipe, which remains in use.
Pipeline uprating increases the maximum allowable operating pressure of an existing
pipeline. This enhancement can be a quick and relatively inexpensive method of
increasing capacity in the existing distribution system before constructing more costly
additional facilities. However, safety considerations and pipe regulations may prohibit the
feasibility or lengthen the time before completion of this option. Also, increasing line
pressure may produce leaks and other pipeline damage creating costly repairs. A
thorough review is conducted to ensure pipeline integrity before pressure is increased.

Regulators
Regulators, or regulator stations, reduce pipeline pressure at various stages in the
distribution system. Regulation provides a specified and constant outlet pressure before
natural gas continues its downstream travel to a city’s distribution system, customer’s
property or natural gas appliance. Regulators also ensure that flow requirements are met
at a desired pressure regardless of pressure fluctuations upstream of the regulator.
Regulators are at city gate stations, district regulator stations, farm taps and customer
services.

Compression
Compressor stations present a capacity enhancing option for pipelines with significant
natural gas flow and the ability to operate at higher pressures. For pipelines experiencing
a relatively high and constant flow of natural gas, a large volume compressor installation
along the pipeline boosts downstream pressure.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 177 of 190
A second option is the installation of smaller compressors located close together or
strategically placed along a pipeline. Multiple compressors accommodate a large flow
range and use smaller and very reliable compressors. These smaller compressor stations
are well suited for areas where natural gas demand is growing at a relatively slow and
steady pace, so that purchasing and installing these less expensive compressors over
time allows a pipeline to serve growing customer demand into the future.
Compressors can be a cost effective option to resolving system constraints; however,
regulatory and environmental approvals to install a compressor station, along with
engineering and construction time can be a significant deterrent. Adding compressor
stations typically involves considerable capital expenditure. Based on Avista’s detailed
knowledge of the distribution system, there are no foreseeable plans to add compressors
to the distribution network.

Conservation Resources
The evaluation of distribution system constraints includes consideration of targeted
conservation resources to reduce or delay distribution system enhancements. The
consumer is still the ultimate decision-maker regarding the purchase of a conservation
measure. Because of this, Avista attempts to influence conservation through the DSM
measures discussed in Chapter 3 – Demand-Side Resources, but does not depend on
estimates of peak day demand reductions from conservation to eliminate near-term
distribution system constraints. Over the longer-term, targeted conservation programs
may provide a cumulative benefit that could offset potential constraint areas and may be
an effective strategy.

Distribution Scenario Decision-Making Process
After achieving a working load study, analyses are performed on every system at design
day conditions to identify areas where potential outages may occur.

Avista’s design HDD for distribution system modeling is determined using the coldest day on record for each given service area. This practice is consistent with the peak day
demand forecast utilized in other sections of Avista’s natural gas IRP.

Utilizing a peak planning standard of the coldest temperature on record may seem
aggressive given a temperature experienced rarely, or only once. Given the potential impacts of an extreme weather event on customers’ personal safety and property damage to customer appliances and Avista’s infrastructure, it is a prudent regionally accepted
planning standard.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 178 of 190
These areas of concern are then risk ranked against each other to ensure the highest risk areas are corrected first. Within a given area, projects/reinforcements are selected using
the following criteria:

• The shortest segment(s) of pipe that improves the deficient part of the distribution system.
• The segment of pipe with the most favorable construction conditions, such as
ease of access or rights or traffic issues.
• Minimal to no water, railroad, major highway crossings, etc.
• The segment of pipe that minimizes environmental concerns including minimal to
no wetland involvement, and the minimization of impacts to local communities
and neighborhoods.
• The segment of pipe that provides opportunity to add additional customers.
• Total construction costs including restoration.
Once a project/reinforcement is identified, the design engineer or construction project
coordinator begins a more thorough investigation by surveying the route and filing for
permits. This process may uncover additional impacts such as moratoriums on road excavation, underground hazards, discontent among landowners, etc., resulting in another iteration of the above project/reinforcement selection criteria. Figure 7.1 provides
a schematic representation of the distribution scenario process.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 179 of 190
Figure 8.1: Distribution Scenario Process

An example of the distribution scenario decision making process is from the Medford high pressure loop reinforcement where the analysis resulted in multiple paths or pipeline
routes. The initial path was based on quantitative factors, specifically the shortest length
and least cost route. However, as field investigations and coordination with local city and
county governments began, alternative routes had to be determined to minimize future conflicts, environmental considerations, and field and community disruptions. The final path was based on several qualitative factors that including:

• Available right-of-way along city streets;
• Availability of private easements from property owners;
• Restrictions due to City of Medford future planned growth with limited planning
information; and
• Potential to avoid conflict with other utilities including a large electric substation
along the initial route.

Planning Results
Table 8.1 summarizes the cost and timing, as of the publication date of this IRP, of major
distribution system enhancements addressing growth-related system constraints, system
integrity issues and the timing of expenditures.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 180 of 190
The Distribution Planning Capital Projects criteria includes:
• Prioritized need for system reliability (necessary to maintain reliable service);
• Scale of project (large in magnitude and will require significant engineering
and design support); and
• Budget approval (will require approval for capital funding).
These projects are preliminary estimates of timing and costs of major reinforcement
solutions. The scope and needs of distribution system enhancement projects generally
evolve with new information requiring ongoing reassessment. Actual solutions may differ
due to differences in actual growth patterns and/or construction conditions that differ from
the initial assessment and timing of planned completion may change based on the
aforementioned ongoing reassessment of information.
The following discussion provides information about key near-term projects.

Coeur d’Alene High Pressure Reinforcement – Post Falls Phase: The last phase of
this project will reinforce the Post Falls distribution system, where the current distribution
pipe has not been able to meet growing customer demand. Additionally, during cold
weather conditions, supply resources have been constrained. Approximately 14,600 feet
of high pressure steel gas main was designed in 2017 and construction began in 2018.

Cheney High Pressure Reinforcement: This project will reinforce the Cheney
distribution system, whose customer demands have exceeded the capacity of the high
pressure feeder constructed in 1957. During cold weather conditions, Avista periodically
asks some large customers to reduce their nature gas usage in order to serve core
customer demand. Approximately 27,700 feet of high pressure steel gas main will be
designed in 2018 and construction is expected to begin in 2019.

Schweitzer Mountain Road and Warden High Pressure Reinforcements: The
Schweitzer Mountain Road and Warden high pressure reinforcements are necessary to
serve either new or increased industrial customer demand. At this time, both industrial
customers, whose projected demands necessitated reinforcements, have either
cancelled expansion plans or are considering alternative locations. In anticipation of
similar industrial loads in the future, Avista will continue to list each project, but defer
construction until distribution constraints materialize.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 181 of 190
Table 8.1 Distribution Planning Capital Projects
Coeur d’Alene High
Pressure
Reinforcement; Post $4,000,000
Pressure $4,900,000 $4,100,000
Mountain Rd High Pressure $1,500,000
Pressure $6,000,000

Table 8.2 shows city gate stations identified as over utilized or under capacity. Estimated
cost, year and the plan to remediate the capacity concern are shown.
These projects are preliminary estimates of timing and costs of city gate station upgrades.
The scope and needs of each project generally evolve with new information requiring
ongoing reassessment. Actual solutions may differ due to differences in actual growth patterns and/or construction conditions that differ from the initial assessment.

The Post Falls City Gate Station will be reconfigured to accommodate a new high
pressure feeder. The supplying pipeline has not been able to meet the increase in
customer growth and demand in this area. An increase in flow and capacity will be achieved by the new high pressure feeder directing gas from Rathdrum to Post Falls, the
third phase of the Coeur d’Alene High Pressure Reinforcement.

The remaining city gate station projects in Table 8.2 have relatively small capacity
constraints, and thus will be periodically reevaluated to determine if upgrades need to be accelerated or deferred. Under current planning considerations, these projects will be
tentatively scheduled for 2020 or later.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 182 of 190
Table 8.2 City Gate Station Upgrades
Post Falls, ID Post Falls #215 Reconfigure in Table 2018
CDA East #221 TBD - 2020+
Bonners Bonners Ferry #208 TBD - 2020+
Klamath Klamath Falls #2703 TBD - 2022+

CONCLUSION
Avista’s goal is to maintain its natural gas distribution systems reliably and cost effectively
to deliver natural gas to every customer. This goal relies on modeling to increase the
capacity and reliability of the distribution system by identifying specific areas that may
require changes. The ability to meet the goal of reliable and cost effective natural gas
delivery is enhanced through localized distribution planning, which enables coordinated
targeting of distribution projects responsive to customer growth patterns.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 183 of 190
9: Action Plan

The purpose of an action plan is to position Avista to provide the best cost/risk resource
portfolio and to support and improve IRP planning. The Action Plan identifies needed
supply and demand side resources and highlights key analytical needs in the near term.
It also highlights essential ongoing planning initiatives and natural gas industry trends
Avista will monitor as a part of its planning processes.

2017-2018 Action Plan Review

o The price of natural gas has dropped significantly since the 2014 IRP. This is primarily
due to the amount of economically extractable natural gas in shale formations, more
efficient drilling techniques, and warmer than normal weather. Wells have been drilled,
but left uncompleted due to the poor market economics. This is depressing natural
gas prices and forcing many oil and natural gas companies into bankruptcy. Due to
historically low prices Avista will research market opportunities including procuring a
derivative based contract, 10-year forward strip, and natural gas reserves.
o Result: After exploring the opportunity of some type of reserves ownership, it
was determined the price as compared to risk of ownership was inappropriate
to go forward with at this time. As an ongoing aspect of managing the business,
Avista will continue to look for opportunities to help stabilize rates and/or reduce
risk to our customers.
o Avista’s 2018 IRP will contain a dynamic DSM program structure in its analytics. In
prior IRP’s, it was a deterministic method based on Expected Case assumptions. In
the 2018 IRP, each portfolio will have the ability to select conservation to meet
unserved customer demand. Avista will explore methods to enable a dynamic
analytical process for the evaluation of conservation potential within individual
portfolios.
o Result: After attempting to get dynamic dsm into the Sendout model we
determined an alternate method will be necessary. Some reasons for this are:
 1 – The total dsm measures has a maximum of 999 measures. If we
were to model our areas as is combined with 400 measures by area we
would come up with a total need of 4400 measures.
 2 – If we were able to group them by dollars or efficiency levels it takes
away the desired approach of measure by measure.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 184 of 190
 3 – We have every bit of data both ETO and AEG can provide and the
model is not acting appropriately and cannot determine a stopping point
for taking a single measure. This means it would take the maximum, if
cheaper than gas, to fill the entire demand.
 4 – The output data from ETO and AEG is very different and we need to
understand it better before modeling.

o Monitor actual demand for accelerated growth to address resource deficiencies arising
from exposure to “flat demand” risk. This will include providing Commission Staff with
IRP demand forecast-to-actual variance analysis on customer growth and use-per-
customer at least bi-annually.
o Result: actual demand was closely tracked and shared with Commissions in
semi-annual or quarterly meetings and trended closely to the IRP forecast per
customer. No new resources were necessary during this timeframe.
o In the 2018 IRP, include a section in the IRP that discusses the specific impacts of the
new Clean Air Rule in Washington (WAC 173-441 and 173-442).
o Result: Carbon Policy including the Clean Power Plan and Clean Air Rule
were both reviewed and included in TAC 2 Meeting materials on 2/22/2018. An
indicator of where Avista’s carbon reduction requirements under the CAR was
also included. Since the CAR was invalidated on 12/15/2017 in Thurston
County Superior Court this analysis is intended to meet the action item in
addition to showing the potential impacts of similar policies.
o In the 2018 IRP, provide more detail on Avista’s natural gas hedging strategy,
including information on upper and lower pricing points, transactions with
counterparties, and how diversification of the portfolio is achieved.
o Result: Avista’s natural gas hedging strategy was discussed during the TAC
2 Meeting on 2/22/2018. The upper and lower pricing points in Avista’s
programmatic hedges is controlled by taking into consideration the volatility
over the past year for the specific hedging period. This volatility is weighted
toward the more recent volatility. The window length and quantity of windows
is also a part of the equation. Avista transacts on ICE with counterparties
meeting our credit rating criteria. The diversification of the portfolio is achieved
through the following methods:
 Components: The plan utilizes a mix of index, fixed price, and storage
transactions.
 Transaction Dates: Hedge windows are developed to distribute the
transactions throughout the plan.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 185 of 190
 Supply Basins: Plan to primarily utilize AECO, execute at lowest price
basis at the time.
 Delivery Periods: Hedges are completed in annual and/or seasonal
timeframes. Long-term hedges may be executed.
o
o Carbon Policy including federal and state regulations specifically those surrounding
the clean air rule and clean power plan.
o Result: Carbon Policy including the Clean Power Plan and Clean Air Rule
were both reviewed and included in TAC 2 Meeting materials on 2/22/2018. An
indicator of where Avista’s carbon reduction requirements under the CAR was
also included. Since the CAR was invalidated on 12/15/2017 in Thurston
County Superior Court this analysis is intended to meet the action item in
addition to showing the potential impacts of similar policies.
o Weather analysis specific to Avista’s service territories.
o Result: A weather analysis was included and reviewed in TAC 2 meeting
materials on 2/22/2018 and can be found in Chapter 2 Demand Forecasts.
o Stochastic Modeling and supply resources.
o Result: This was shown in detail and with risk and cost in TAC 4 on 5/10/2018.
Regional pipelines were discussed in TAC 2 meeting on 2/22/2018. Potential
resources were 4 types of RNG, Plymouth LNG, additional Kingsgate to
Spokane and an upsized compressor on GTN’s Medford lateral. A list of these
resources modeled can be found in Chapter 7 Alternate Scenarios Portfolios
Stochastic Analysis along with the results.
o Updated DSM methodology including the integration of ETO.
o Result: See chapter 3 Demand Side Resources and action item
o In the 2018 IRP, ensure that the entity performing the Conservation Potential
Assessment (CPA) evaluates and includes the following information:
o All conservation measures excluded from the CPA, including those excluded
prior to technical potential determination;
 Result: Very few measures were excluded from the current CPA prior
to estimation of technical potential. Those explicitly excluded were highly
custom commercial and industrial controls/process measures that were
instead captured under a retrocommissioning or strategic energy
management program.
o Rationale for excluding any measure;
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 186 of 190
 Result: Measures that did not pass the economic screen were still
counted within achievable technical potential, allowing Avista to review
for inclusion in programs if portfolio-level cost-effectiveness allows.
o Description of Unit Energy Savings (UES) for each measure included in the
CPA; specify how it was derived and the source of the data; and
 Result: The measure list developed during the CPA includes
descriptions of each measure included. AEG will provide this as an
appendix to the final report. Source documentation for assumptions,
including UES, lifetime, and costs (including NEIs) may be found in the
“Measure Summary” spreadsheet delivered as an appendix to the final
report. This will include the name of the source and version (if
applicable)
o Explain the efforts to create a fully-balanced TRC cost effectiveness metric
within the planning horizon. Additionally, while evaluating the effort to
eventually revert back to the TRC, Avista should consult the DSM Advisory
Group and discuss appropriate non-energy benefits to include in the CPA.
 Result: TRC potential was estimated alongside UCT for each measure
analyzed. In this study, we expanded the scope of non-energy/non-gas
impacts to include the following:
• 10% Conservation Credit in Washington
• Quantified and monetized non-energy impacts (e.g. water,
detergent, wood)
• Projected cost of carbon in Washington
• Heating calibration credit for secondary fuels (12% for space
heating, 6% for secondary heating)
• Electric benefits for applicable measures (e.g. cooling savings for
smart thermostats, lighting and refrigeration savings for retro-
commissioning)
o Staff believes public participation could be further enhanced through “bill stuffers,
public flyers, local media, individual invitations, and other methods.”
o Result: Avista utilized it’s Regional Business Managers in addition to digital
communications and newsletters in all states in order to try and gain more
public participation in addition to an eCommunity newsletter was distributed
January 15, 2018.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 187 of 190
o Avista forecast its number of customers using at least two different methods and to
compare the accuracy of the different methods using actual data as a future task in its
next IRP.
o Result: Avista analyzed the data, but there was nothing material discovered
the come up with a meaningful forecast alternative.
2019-2020 Action Plan
Avista’s 2019-2020 Action Plan outlines activities for study, development and preparation
for the 2020 IRP.

New Activities for the 2020 IRP
1. Avista’s 2020 IRP will contain an individual measure level for dynamic DSM
program structure in its analytics. In prior IRP’s, it was a deterministic method
based on based on Expected Case assumptions. In the 2020 IRP, each portfolio
will have the ability to select conservation to meet unserved customer demand.
Avista will explore methods to enable a dynamic analytical process for the
evaluation of conservation potential within individual portfolios.
2. Work with Staff to get clarification on types of natural gas distribution system
analyses for possible inclusion in the 2020 IRP.
3. Work with Staff to clarify types of distribution system costs for possible inclusion in
our avoided cost calculation.
4. Revisit coldest on record planning standard and discuss with TAC for prudency.
5. Provide additional information on resource optimization benefits and analyze risk
exposure.
6. DSM—Integration of ETO and AEG/CPA data. Discuss the integration of ETO and
AEG/CPA data as well as past program(s) experience, knowledge of current and
developing markets, and future codes and standards.
7. Carbon Costs – consult Washington State Commission’s Acknowledgement Letter
Attachment in its 2017 Electric IRP (Docket UE-161036), where emissions price
modeling is discussed, including the cost of risk of future greenhouse gas
regulation, in addition to known regulations.
8. Avista will ensure Energy Trust (ETO) has sufficient funding to acquire therm
savings of the amount identified and approved by the Energy Trust Board.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 188 of 190
9. Regarding high pressure distribution or city gate station capital work, Avista does
not expect any supply side or distribution resource additions to be needed in our
Oregon territory for the next four years, based on current projections. However,
should conditions warrant that capital work is needed on a high pressure
distribution line or city gate station in order to deliver safe and reliable services to
our customers, the Company is not precluded from doing such work. Examples of
these necessary capital investments include the following:
• Natural gas infrastructure investment not included as discrete projects in IRP
– Consistent with the preceding update, these could include system
investment to respond to mandates, safety needs, and/or maintenance
of system associated with reliability
• Including, but not limited to Aldyl A replacement, capacity
reinforcements, cathodic protection, isolated steel replacement,
etc.
– Anticipated PHMSA guidance or rules related to 49 CFR Part §192
that will likely requires additional capital to comply
• Officials from both PHMSA and the AGA have indicated it is not
prudent for operators to wait for the federal rules to become final
before improving their systems to address these expected rules.
– Construction of gas infrastructure associated with growth
– Other special contract projects not known at the time the IRP was
published
• Other non-IRP investments common to all jurisdictions that are ongoing, for
example:
– Enterprise technology projects & programs
– Corporate facilities capital maintenance and improvements

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 189 of 190
Ongoing Activities

• Continue to monitor supply resource trends including the availability and price of
natural gas to the region, LNG exports, methanol plants, supply and market
dynamics and pipeline and storage infrastructure availability.
• Monitor availability of resource options and assess new resource lead-time
requirements relative to resource need to preserve flexibility.
• Meet regularly with Commission Staff to provide information on market activities
and significant changes in assumptions and/or status of Avista activities related to
the IRP or natural gas procurement practices.
• Appropriate management of existing resources including optimizing underutilized
resources to help reduce costs to customers.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1, Page 190 of 190
2018
Natural Gas
Integrated Resource Plan
August 31, 2018
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 1 of 829
Safe Harbor Statement

This document contains forward-looking statements. Such statements are subject to a
variety of risks, uncertainties and other factors, most of which are beyond the Company’s
control, and many of which could have a significant impact on the Company’s operations,
results of operations and financial condition, and could cause actual results to differ
materially from those anticipated.
For a further discussion of these factors and other important factors, please refer to the
Company’s reports filed with the Securities and Exchange Commission. The forward-
looking statements contained in this document speak only as of the date hereof. The
Company undertakes no obligation to update any forward-looking statement or statements to reflect events or circumstances that occur after the date on which such statement is made or to reflect the occurrence of unanticipated events. New risks,
uncertainties and other factors emerge from time to time, and it is not possible for
management to predict all of such factors, nor can it assess the impact of each such factor
on the Company’s business or the extent to which any such factor, or combination of factors, may cause actual results to differ materially from those contained in any forward-looking statement.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 2 of 829
TABLE OF CONTENTS: APPENDICES
Appendix 0.1 TAC Member List ........................................................................ Page 1
0.2 Comments and Responses to the 2014 IRP ........................................ 2
Appendix 1.1 Avista Corporation 2014 Natural Gas IRP Work Plan ........................... 6
1.2 IRP Guideline Compliance Summaries .............................................. 12
Appendix 2.1 Economic Outlook and Customer Count Forecast .............................. 24
2.2 Customer Forecasts by Region .......................................................... 41
2.3 Demand Coefficient Calculations ....................................................... 77
2.4 Heating Degree Day Data .................................................................. 84
2.5 Demand Sensitivities and Demand Scenarios .................................... 90
2.6 Demand Forecast Sensitivities and Scenarios Descriptions ............... 92
2.7 Annual Demand, Avg Day & Peak Day Demand (Net of DSM) .......... 96
2.8 Demand Before and After DSM ........................................................ 101
2.9 Detailed Demand Data ..................................................................... 106
Appendix 3.1 Avista Gas CPA Report Final 4/23/2014 .......................................... 118
3.2 Environmental Externalities .............................................................. 212
Appendix 4.1 Current Transportation/Storage Rates and Assumptions ................. 215
Appendix 6.1 Monthly Price Data by Basin ............................................................ 216
6.2 Weighted Average Cost of Capital ................................................... 222
6.3 Supply Side Resource Options ........................................................ 223
6.4 Avoided Costs Detail ........................................................................ 224
Appendix 7.1 High Case Demand and Resources Selected Graphs ...................... 239
7.2 Other Scenario Peak Day Demand Table ........................................ 241
Appendix 8.1 Distribution System Modeling .......................................................... 247
8.2 Oregon Capital … ............................................................................. 251
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 3 of 829
Appendix A TAC Meeting #1 .......................................................................... 253
B TAC Meeting #2 .......................................................................... 354
C TAC Meeting #3 .......................................................................... 465
D TAC Meeting #4 .......................................................................... 680

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 4 of 829
APPENDIX 0.1: TAC MEMBER LIST
Organization Representatives
Applied Energy Group Kurtis Kolnowski
Avista
Terrence Browne Jody Morehouse
Mike Dillon Tom Pardee
Ryan Finesilver Kaylene Schultz
Grant Forsyth Eric Scott
James Gall Kerry Shroy
Justin Dorr Debbie Simock
John Lyons Shawn Bonfield
Annette Brandon Jeff Webb
Cascade Natural Gas Company Ashton Davis Brian Robertson
Energy Trust of Oregon Jack Cullen Spencer
Moersfelder
Fortis Robert Schuster Ken Ross
Idaho Public Utility Commission Brad Iverson-Long Kevin Keyt Stacey Donohue
Northwest Gas Association Dan Kirschner
Northwest Natural Gas Tammy Linver Steve Storm
Oregon Public Utility Commission Lisa Gorsuch Seth Wiggins
TransCanada Jay Story
Washington Utilities and
Transportation Commission Kathi Scanlan Dave Nightingale
Andrew Rector
Williams Northwest Pipeline Mike Rasmuson Jon Rowley
Rob Harmen
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 5 of 829
APPENDIX 0.2: COMMENTS AND RESPONSES TO 2018 DRAFT INTEGRATED
RESOURCE PLAN
The following table summarizes the significant comments on our DRAFT as submitted by TAC members and
Avista’s responses. This IRP produced reduced forecasted demand scenarios and no near term resource needs
even in our most robust demand scenario. We appreciate the time and effort invested by all our TAC members
throughout the IRP process. Many good suggestions have been made and we have incorporated those that
enhance the document.

Document Reference[1] Comment/Question Avista Response
6 - Integrated
Resource
Portfolio
Low/Medium/High natural gas price forecasts.
Reasonable price forecasts are important in developing a utility’s avoided cost threshold and determining cost-effectiveness of conservation measures. For Avista’s
expected case, the company projects its nominal gas price in
the 4 dollar per dekatherm ($/Dth) range for 2026-2027,
which amounts to a 30 percent increase over a ten-year span. Beyond 2027, Avista projects an increase to $7/Dth and a 75 percent increase in natural gas prices in the outer-years.
Over the entire IRP planning horizon, Avista projects 133
percent change in natural gas prices. Staff is concerned
Avista may perpetuate a high-side bias of natural gas prices. Further, staff recognizes no company can accurately predict future natural gas prices; however, the company must ensure
its natural gas price forecasts represent the most reasonable
expectation of the future.
Added
supplemental
language to
Chapter 6
beginning with
page 125
In July, staff requested the company provide additional
information regarding its consultants’ gas price forecasts. On
July 13, 2018, the company filed confidential electronic
workpapers of its gas price forecast data in Docket UG-
170940. Staff appreciates Avista prompt response to the data request. Staff also requests a more detailed description of the
company’s gas price (and expected price strip) forecast at
the Henry Hub, including how Avista derived its regional
gas price variation from the company’s two fundamental
price forecasts from credible industry sources. Further, staff asks Avista to explain its blending methodology of its forwards and outer-year price forecasts, and also discuss the
qualitative and quantitative factors that correlate with the
projected rise in prices, especially in the outer-years of its
natural gas price forecast.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 6 of 829
2 - Demand
Forecasts
Fuel conversion program impact-emerging natural gas demand. Compared to previous IRPs, Avista's new 20-year
outlook for customer growth has increased by nearly 12,000
customers. Avista indicates that much of its new, emerging demand is directly related to a conversion program offered in Washington (and Idaho), where customers are offered
assistance in converting to natural gas and fuel switching. Additional
clarification
added to page 29
- Chapter 2
1111Staff requests additional information on whether Avista is referring to 1) Washington's line extension allowance pilot
(LEAP), 2) the company's existing fuel conversion program
funded through the electric conservation rider, Electric
Schedule 91, or 3) the cumulative impact of LEAP and the
fuel conversion program. Staff recommends the company provide additional data, narrative and specificity with regard
to projections of emerging natural gas demand related to
consumer-funded programs or incentives.
6 - Integrated
Resource
Portfolio
1111Resource cost test. Avista evaluates the cost
effectiveness of demand-side management (DSM) programs against the initial avoided cost curve using appropriate
resource cost tests. Staff asks Avista to clarify the resource
cost test(s) used.
Added to Chapter
6 page 142
9 - Action Plan
DSM—Integration of ETO and AEG/CPA data. Effective
January 1, 2017, Avista transitioned its Oregon gas DSM regular income, commercial, and industrial customer
programs to the Energy Trust of Oregon (ETO), with the
ETO being the sole administrator. Staff requests additional
information about the difference between DSM output data
from ETO’s RA model and Applied Energy Group (AEG) Conservation Potential Assessment (CPA) tool, which
identify the total 20-year cost-effective modeled savings
potential to estimate Avista’s final savings forecast. For the
next IRP, staff recommends the Advisory Group discuss the
integration of ETO and AEG/CPA data as well as past program(s) experience, knowledge of current and developing
markets, and future codes and standards.
Added to Action
Plan section

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 7 of 829
5 - Policy
Considerations
Dynamic-DSM. Avista’s current analytical process for the
Conservation Potential Assessment (CPA) is based on a
deterministic model, as compared to the assumptions within
the expected case. For the 2018 IRP, Avista attempted to apply a dynamic-DSM using the Sendout model, but the company determined an alternate method would be
necessary due to current model constraints. As outlined in
Avista’s 2019-2020 action plan, the next IRP will contain a
dynamic DSM program structure utilizing new analytics. Avista intends to recreate its Sendout model and inputs and transform it into a new Excel-based tool. This new tool and
methodology will allow flexibility to model DSM and other
potential supply side resources on a case by case basis.
Added specific
language to
action item.
Avista will model
on an individual
level of DSM
measure
Staff suggests Avista discuss whether the company will use
individual or bundling of DSM measures, including
grouping by dollars or efficiency levels. Avista’s departure
from its current modeling also will allow for a unique
opportunity for comparison of methodologies. Staff also requests the company evaluate its deterministic and dynamic
DSM tools, including the results and benefits of each
methodology.
9 - Action Plan
Carbon costs. Based on the initial proposed carbon
legislation in Senate Bill 6203, Avista modelled Washington carbon costs at $10 per MTCO2e starting in 2019 and rising
to $30 per MTCO2e by 2030. Further, the company
analyzed three carbon sensitivities and associated impacts on
demand forecasts to address the uncertainty about carbon
legislation. Staff is pleased Avista introduced a new risk scenario in its 2018 IRP: 80% below 1990 emissions. Added to 2020
Avista Natural
Gas IRP Action
Item

Staff notes that the low-priced natural gas, in addition to
carbon taxes or other programs, has led to a higher potential for DSM measures as compared to the previous three IRP’s.
Further, Staff recognizes the uncertainties in carbon policy.
For the next IRP, Staff suggests the company consult the
Commission’s Acknowledgement Letter Attachment in its
2017 Electric IRP (Docket UE-161036), where emissions price modelling is discussed, including the cost of risk of future greenhouse gas regulation, in addition to known
regulations.
7 - Alternate
Scenarios,
Portfolios,
Stochastic
Analysis
Supply resource comparison. For this IRP, the only case
that identifies a resource deficiency is the High Growth/Low Price scenario. At Staff’s request, Avista added Tables 7.2 and 7.3 to this IRP, which includes costs/rates as well as
availability. Staff appreciates Avista’s response to this
request.
Added detail and
explanation
within the
chapter
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 8 of 829
7 - Alternate
Scenarios,
Portfolios,
Stochastic
Analysis
Renewable natural gas (RNG). Effective July 1, 2018,
House Bill 2580 became law and promotes the sustainable
development of RNG supply. For the first time in its natural
gas IRP, the company identified RNG as a “solve” where landfill RNG is selected as a resource in Idaho. In addition to Tables 7.2 and 7.3, staff requests additional narrative
regarding subsidies that may make RNG-qualified
renewable fuel a least-cost optimization solution, which may
further contribute to the decarbonization of Avista’s natural gas system. Additional data and discussion regarding the company’s RNG resource cost assumptions, including
subsidies, rates, plant efficiency and size would be helpful.
Added detail and
explanation
within the
chapter
9 - Action Plan
Reconcile peak planning standard and natural gas optimization. Avista’s planning standard is determined using the coldest day on record for each service area, which is an aggressive planning standard given a temperature
“experienced rarely, or only once.” Further, there is a high
correlation between usage and temperature, as depicted in
the company’s use-per-customer forecast in Figure 2.2. In this IRP, slightly higher customer growth continues to be offset by lower use-per-customer and an increased amount
of DSM, which has eliminated the need for Avista to acquire
additional supply-side resources. Added to 2020
Avista Natural
Gas IRP Action
Item

Yet the company continues to realize unutilized resources
like supply, transportation, storage and capacity—when
combined, create valuable Avista products. With its ongoing
surplus and well-positioned resources exceeding system
demand, Staff suggests providing additional information on optimization benefits, and also analyzing potential risk
exposure in its next IRP. Further, Staff recommends
discussing with its Advisory Group whether its current
coldest day on record planning standard continues to be a
prudent long-term planning approach. The company could look at peer utilities in with similar climate and compare
Avista’s planning approach.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 9 of 829
APPENDIX 1.1: AVISTA CORPORATION 2020 NATURAL GAS INTEGRATED
RESOURCE PLAN WORK PLAN
IRP WORK PLAN REQUIREMENTS
Section 480-90-238 (4), of the natural gas Integrated Resource Plan (“IRP”) rules, specify requirements for
the IRP Work Plan:
Not later than twelve months prior to the due date of a plan, the utility must provide a work
plan for informal commission review. The work plan must outline the content of the
integrated resource plan to be developed by the utility and the method for assessing
potential resources.
Additionally, Section 480-90-238 (5) of the WAC states:
The work plan must outline the timing and extent of public participation.
OVERVIEW
This Work Plan outlines the process Avista will follow to complete its 2020 Natural Gas IRP by August
31, 2020. Avista uses a public process to obtain technical expertise and guidance throughout the planning
period via Technical Advisory Committee (TAC) meetings. The TAC will be providing input into
assumptions, scenarios, and modeling techniques.
PROCESS
The 2020 IRP process will be similar to that used to produce the previously published plan. Avista will use
SENDOUT® (a PC based linear programming model widely used to solve natural gas supply and
transportation optimization questions) to develop the risk adjusted least-cost resource mix for the 20 year
planning period.
This plan will continue to include demand analysis, demand side management and avoided cost
determination, existing and potential supply-side resource analysis, resource integration and alternative
sensitivities and scenario analysis.
Additionally, Avista intends to incorporate action plan items identified in the 2018 Natural Gas IRP
including more detailed demand analysis regarding use per customer, demand side management results and
possible price elastic responses to evolving economic conditions, an updated assessment of conservation
potential in our service territories, consideration of alternate forecasting methodologies, and the changing
landscape of natural gas supply (i.e. shale gas, Canadian exports, and US LNG exports) and its implications
to the planning process. Further details about Avista’s process for determining the risk adjusted least-cost
resource mix is shown in Exhibit 1.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 10 of 829
TIMELINE
The following is Avista’s TENTATIVE 2020 Natural Gas IRP timeline:
subject to change

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 11 of 829
EXHIBIT 1: AVISTA’S 2020 NATURAL GAS IRP MODELING PROCESS

Demand Forecast by Area and Class
Customer counts
Use per customer
Elasticity
Gas Prices
Basis differential
Volatility
Seasonal Spreads
Existing Supply-Side Resources
Costs
Operational Characteristics

Weather
20-year NOAA average by area plus
SENDOUT®
Optimization
Run

Identify when and where
deficiencies occur in the 20-
SENDOUT®
Optimization
Run

Solve for deficiencies and
incorporate those into the
least costs resource mix
for the 20-year period. Determine Base
Case Scenario
Avoided Cost
Determination Compile Data and Write
the IRP Document.
Key Considerations
Resource Cost
Peak vs. Base Load
Lead Time Requirements
Resource Usefulness
“Lumpiness” of Resource Options
Sensitivity/Scenario
Analysis
Customer
Counts
Use per
customer
DSM
Monte Carlo
Etc.
Gate Station
Analysis
Price Curve
Analysis
Planning
Standard Review
What's Best
Solver
Solve scenarios
based on demand-
side management
measures
Enter all Future Resource Options:
Supply-Side Demand-
Side
Demand-Side Resources
Assess DSM resource options
Integrate DSM in resource
portfolio through Dynamic DSM
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 12 of 829
APPENDIX 1.2: WASHINGTON PUBLIC UTILITY COMMISSION IRP POLICIES AND
GUIDELINES – WAC 480-90-238
Rule Requirement Plan
Citation
WAC 480-90-238(4) Work plan filed no later than 12 months before next IRP due date. Work plan submitted to the WUTC on August 31, 2017, See
attachment to this Appendix 1.1.
WAC 480-90-238(4) Work plan outlines content of IRP. See work plan attached to this Appendix 0.1.
WAC 480-90-238(4) Work plan outlines method for
assessing potential resources. (See LRC analysis below)
See Appendix 1.1.
WAC 480-90-238(5) Work plan outlines timing and extent of
public participation.
See Appendix 1.1.
WAC 480-90-238(4) Integrated resource plan submitted within two years of previous plan. Last Integrated Resource Plan was submitted on August 31, 2016
WAC 480-90-238(5) Commission issues notice of public hearing after company files plan for
review.
TBD
WAC 480-90-238(5) Commission holds public hearing. TBD
WAC 480-90-238(2)(a) Plan describes mix of natural gas
supply resources.
See Chapter 4 on Supply Side
Resources
WAC 480-90-238(2)(a) Plan describes conservation supply. See Chapter 3 on Demand Side Resources
WAC 480-90-238(2)(a) Plan addresses supply in terms of
current and future needs of utility and ratepayers.
See Chapter 4 on Supply Side
Resources and Chapter 6 Integrated Resource Portfolio
WAC 480-90-
238(2)(a)&(b)
Plan uses lowest reasonable cost
(LRC) analysis to select mix of resources.
See Chapters 3 and 4 for Demand
and Supply Side Resources. Chapters 6 and 7 details how
Demand and Supply come together to select the least
cost/best risk portfolio for ratepayers.
WAC 480-90-238(2)(b) LRC analysis considers resource
costs.
See Chapters 3 and 4 for Demand
and Supply Side Resources. Chapters 6 and 7 details how
Demand and Supply come together to select the least
cost/best risk portfolio for ratepayers.
WAC 480-90-238(2)(b) LRC analysis considers market-
volatility risks.
See Chapter 4 on Supply Side
Resources
WAC 480-90-238(2)(b) LRC analysis considers demand side uncertainties. See Chapter 2 Demand Forecasting
WAC 480-90-238(2)(b) LRC analysis considers resource
effect on system operation.
See Chapter 4 and Chapter 6
WAC 480-90-238(2)(b) LRC analysis considers risks
imposed on ratepayers.
See Chapter 4 procurement plan
section. We seek to minimize but cannot eliminate price risk for our
customers.
WAC 480-90-238(2)(b) LRC analysis considers public policies regarding resource preference See Chapter 2 demand scenarios
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 13 of 829
adopted by Washington state or federal government.
WAC 480-90-238(2)(b) LRC analysis considers cost of risks associated with environmental effects
including emissions of carbon dioxide.
See Chapters 2 and 6 on demand scenarios and Integrated Resource
Portfolio
WAC 480-90-238(2)(b) LRC analysis considers need for security of supply. See Chapter 4 on Supply Side Resources
Rule Requirement Plan Citation
WAC 480-90-238(2)(c) Plan defines conservation as any reduction in natural gas consumption
that results from increases in the efficiency of energy use or distribution.
See Chapter 3 on Demand Side Resources
WAC 480-90-238(3)(a) Plan includes a range of forecasts of
future demand.
See Chapter 2 on Demand
Forecast
WAC 480-90-238(3)(a) Plan develops forecasts using methods that examine the effect of
economic forces on the consumption of natural gas.
See Chapter 2 on Demand Forecast
WAC 480-90-238(3)(a) Plan develops forecasts using
methods that address changes in the number, type and efficiency of natural
gas end-uses.
See Chapter 2 on Demand
Forecast
WAC 480-90-238(3)(b) Plan includes an assessment of commercially available conservation,
including load management.
See Chapter 3 on Demand Side Management including demand
response section.
WAC 480-90-238(3)(b) Plan includes an assessment of currently employed and new policies
and programs needed to obtain the conservation improvements.
See Chapter 3 and Appendix 3.1.
WAC 480-90-238(3)(c) Plan includes an assessment of
conventional and commercially available nonconventional gas
supplies.
See Chapter 4 on Supply Side
Resources
WAC 480-90-238(3)(d) Plan includes an assessment of opportunities for using company-
owned or contracted storage.
See Chapter 4 on Supply Side Resources
WAC 480-90-238(3)(e) Plan includes an assessment of pipeline transmission capability and
reliability and opportunities for additional pipeline transmission
resources.
See Chapter 4 on Supply Side Resources
WAC 480-90-238(3)(f) Plan includes a comparative evaluation of the cost of natural gas purchasing
strategies, storage options, delivery resources, and improvements in
conservation using a consistent method to calculate cost-effectiveness.
See Chapter 3 on Demand Side Resources and Chapter 4 on
Supply Side Resources
WAC 480-90-238(3)(g) Plan includes at least a 10 year long-
range planning horizon.
Our plan is a comprehensive 20
year plan.
WAC 480-90-238(3)(g) Demand forecasts and resource
evaluations are integrated into the long range plan for resource acquisition.
Chapter 6 Integrated Resource
Portfolio details how demand and supply come together to form the
least cost/best risk portfolio.
WAC 480-90-238(3)(h) Plan includes a two-year action plan that implements the long range plan. See Section 9 Action Plan
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 14 of 829
WAC 480-90-238(3)(i) Plan includes a progress report on the implementation of the previously filed
plan.
See Section 9 Action Plan
WAC 480-90-238(5) Plan includes description of consultation with commission staff.
(Description not required)
See Section 1 Introduction
WAC 480-90-238(5) Plan includes description of completion of work plan. (Description not required) See Appendix 1.1.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 15 of 829
APPENDIX 1.2: IDAHO PUBLIC UTILITY COMMISSION IRP POLICIES AND
GUIDELINES – ORDER NO. 2534
DESCRIPTION OF REQUIREMENT FULLFILLMENT OF REQUIREMENT
1 Purpose and Process. Each gas utility regulated by
the Idaho Public Utilities Commission with retail sales of more than 10,000,000,000 cubic feet in a
calendar year (except gas utilities doing business in Idaho that are regulated by contract with a
regulatory commission of another State) has the responsibility to meet system demand at least cost
to the utility and its ratepayers. Therefore, an ‘‘integrated resource plan’’ shall be developed by
each gas utility subject to this rule.
Avista prepares a comprehensive 20 year
Integrated Resource Plan every two years. Avista will be filing its 2018 IRP on or before
August 31, 2018.
2 Definition. Integrated resource planning. ‘‘Integrated resource planning’’ means planning by
the use of any standard, regulation, practice, or policy to undertake a systematic comparison
between demand-side management measures and the supply of gas by a gas utility to minimize life-
cycle costs of adequate and reliable utility services to gas customers. Integrated resource planning
shall take into account necessary features for system operation such as diversity, reliability,
dispatchability, and other factors of risk and shall treat demand and supply to gas consumers on a
consistent and integrated basis.
Avista's IRP brings together dynamic demand forecasts and matches them against
demand-side and supply-side resources in order to evaluate the least cost/best risk
portfolio for its core customers. While the primary focus has been to ensure customer's
needs are met under peak or design weather conditions, this process also evaluates the
resource portfolio under normal/average operating conditions. The IRP provides the
framework and methodology for evaluating Avista's natural gas demand and resources.
3 Elements of Plan. Each gas utility shall submit to
the Commission on a biennial basis an integrated resource plan that shall include:
2018 IRP to be filed on or before August 31,
2018. The last IRP was filed on August 31, 2016.
A range of forecasts of future gas demand in firm
and interruptible markets for each customer class for one, five, and twenty years using methods that
examine the effect of economic forces on the consumption of gas and that address changes in
the number, type and efficiency of gas end-uses.
See Chapter 2 - Demand Forecasts and
Appendix 2 et.al. for a detailed discussion of how demand was forecasted for this IRP.
An assessment for each customer class of the
technically feasible improvements in the efficient use of gas, including load management, as well as
the policies and programs needed to obtain the efficiency improvements.
See Chapter 3 - Demand Side Management and DSM Appendices 3 et.al. for detailed information on the DSM potential
evaluated and selected for this IRP and the operational implementation process.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 16 of 829
An analysis for each customer class of gas supply
options, including: (1) a projection of spot market versus long-term purchases for both firm and
interruptible markets; (2) an evaluation of the opportunities for using company-owned or
contracted storage or production; (3) an analysis of prospects for company participation in a gas futures
market; and (4) an assessment of opportunities for access to multiple pipeline suppliers or direct
purchases from producers.
See Chapter 4 - Supply-Side Resources for
details about the market, storage, and pipeline transportation as well as other
resource options considered in this IRP. See also the procurement plan section in this
same chapter for supply procurement strategies.
A comparative evaluation of gas purchasing options and improvements in the efficient use of
gas based on a consistent method for calculating cost-effectiveness.
See Methodology section of Chapter 3 - Demand-Side Resources where we
describe our process on how demand-side and supply-side resources are compared on par with each other in the SENDOUT® model. Chapter 3 also includes how results
from the IRP are then utilized to create operational business plans. Operational
implementation may differ from IRP results due to modeling assumptions.
The integration of the demand forecast and
resource evaluations into a long-range (e.g., twenty-year) integrated resource plan describing
the strategies designed to meet current and future needs at the lowest cost to the utility and its
ratepayers.
See Chapter 6 - Integrated Resource Portfolio for details on how we model demand and supply coming together to
provide the least cost/best risk portfolio of resources.
A short-term (e.g., two-year) plan outlining the specific actions to be taken by the utility in
implementing the integrated resource plan.
See Chapter 9 - Action Plan for actions to be taken in implementing the IRP.
4 Relationship Between Plans. All plans following the
initial integrated resource plan shall include a progress report that relates the new plan to the
previously filed plan.
Avista strives to meet at least bi-annually with
Staff and/or Commissioners to discuss the state of the market, procurement planning
practices, and any other issues that may impact resource needs or other analysis
within the IRP. 5 Plans to Be Considered in Rate Cases. The integrated resource plan will be considered with
other available information to evaluate the performance of the utility in rate proceedings before
the Commission.
We prepare and file our plan in part to establish a public record of our plan.
6 Public Participation. In formulating its plan, the gas
utility must provide an opportunity for public participation and comment and must provide
methods that will be available to the public of validating predicted performance.
Avista held four Technical Advisory
Committee meetings beginning in January and ending in April. See Chapter 1 - Introduction for more detail about public participation in the IRP process.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 17 of 829
7 Legal Effect of Plan. The plan constitutes the base
line against which the utility's performance will ordinarily be measured. The requirement for
implementation of a plan does not mean that the plan must be followed without deviation. The
requirement of implementation of a plan means that a gas utility, having made an integrated resource
plan to provide adequate and reliable service to its gas customers at the lowest system cost, may and
should deviate from that plan when presented with responsible, reliable opportunities to further lower
its planned system cost not anticipated or identified in existing or earlier plans and not undermining the
utility's reliability.
See section titled "Avista's Procurement
Plan" in Chapter 4 - Supply-Side Resources. Among other details we discuss
plan revisions in response to changing market conditions.
8 In order to encourage prudent planning and prudent deviation from past planning when presented with
opportunities for improving upon a plan, a gas utility's plan must be on file with the Commission
and available for public inspection. But the filing of a plan does not constitute approval or disapproval
of the plan having the force and effect of law, and deviation from the plan would not constitute
violation of the Commission's Orders or rules. The prudence of a utility's plan and the utility's prudence
in following or not following a plan are matters that may be considered in a general rate proceeding or
other proceedings in which those issues have been noticed.
See also section titled "Alternate Supply-Side Scenarios" in Chapter 6 - Integrated
Resource Portfolio where we discuss different supply portfolios that are responsive
to changing assumptions about resource alternatives.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 18 of 829
APPENDIX 1.2: OREGON PUBLIC UTILITY COMMISSION IRP STANDARD AND
GUIDELINES – ORDER 07- 002
Guideline 1: Substantive Requirements
1.a.1 All resources must be evaluated on
a consistent and comparable basis.
All resource options considered, including demand-
side and supply-side are modeled in SENDOUT®
utilizing the same common general assumptions,
approach and methodology.
1.a.2 All known resources for meeting the
utility’s load should be considered,
including supply-side options which
focus on the generation, purchase
and transmission of power – or gas
purchases, transportation, and
storage – and demand-side options
which focus on conservation and
demand response.
Avista considered a range of resources including
demand-side management, distribution system
enhancements, capacity release recalls, interstate
pipeline transportation, interruptible customer supply,
and storage options including liquefied natural gas.
Chapter 3 and Appendix 3.1 documents Avista’s
demand-side management resources considered.
Chapter 4 and Appendix 6.3 documents supply-side
resources. Chapter 6 and 7 documents how Avista
developed and assessed each of these resources.

1.a.3 Utilities should compare different
resource fuel types, technologies,
lead times, in-service dates,
durations and locations in portfolio
risk modeling.
Avista considered various combinations of
technologies, lead times, in-service dates, durations,
and locations. Chapter 6 provides details about the
modeling methodology and results. Chapter 4
describes resource attributes and Appendix 6.3
summarizes the resources’ lead times, in-service
dates and locations.
1.a.4 Consistent assumptions and
methods should be used for
evaluation of all resources.
Appendix 6.2 documents general assumptions used in
Avista’s SENDOUT® modeling software. All portfolio
resources both demand and supply-side were
evaluated within SENDOUT® using the same sets of
inputs.
1.a.5 The after-tax marginal weighted-
average cost of capital (WACC)
should be used to discount all future
resource costs.
Avista applied its after-tax WACC of 4.36% to discount
all future resource costs. (See general assumptions at
Appendix 6.2)
1.b.1 Risk and uncertainty must be
considered. Electric utilities only
Not Applicable
1.b.2 Risk and uncertainty must be
considered. Natural gas utilities
should consider demand (peak,
swing and base-load), commodity
supply and price, transportation
availability and price, and costs to
comply with any regulation of
greenhouse gas (GHG) emissions.
Risk and uncertainty are key considerations in long
term planning. In order to address risk and
uncertainties a wide range of sensitivity, scenario and
portfolio analysis is completed. A description of risk
associated with each scenario is included in Appendix
2.6.

One of the key risks is the “flat demand” risk as
described in Chapter 1. Avista performed 15
sensitivities on demand. From there five demand
scenarios were developed (Table 1.1) for SENDOUT®
modeling purposes. Monthly demand coefficients were
developed for base, heating demand while peak
demand was contemplated through modeling a
weather planning standard of the coldest day on
record (see heating degree day data in Appendix 2.4).
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 19 of 829
Avista evaluated several price forecasts and selected
high, medium and low price scenarios for modeling
purposes. The annual average prices are then
weighted by month using fundamental forecast data.
Additionally, the Henry Hub price forecasts are basis
adjusted using the same fundamental forecast data.

Four supply scenarios were also evaluated, see Table
4.3. These supply scenarios were combined with
demand scenarios in order to establish portfolios for
evaluation. Ultimately 9 portfolios were evaluated
(See Table 6.3 for the PVRR results).

Avista stochastic modeling techniques for price and
weather variables to analyze weather sensitivity and
to quantify the risk to customers under varying price
environments. While there continues to be some
uncertainty around GHG emission, Avista considered
GHG emissions regulatory compliance costs in
Appendix 3.2. As currently modeled, we include a
carbon adder to our price curve to capture the costs of
emission regulation.
Utilities should identify in their plans
any additional sources of risk and
uncertainty.
Avista evaluated additional risks and uncertainties.
Risks associated with the planning environment are
detailed in Chapter 0 Introduction. Avista also
analyzed demand risk which is detailed in Chapter 2.
Chapter 3 discusses the uncertainty around how much
DSM is achievable. Supply-side resource risks are
discussed in Chapter 4. Chapter 6 and 7 discusses
the variables modeled for scenario and stochastic risk
analysis.
1c The primary goal must be the
selection of a portfolio of resources
with the best combination of
expected costs and associated risks
and uncertainties for the utility and
its customers.
Avista evaluated cost/risk tradeoffs for each of the risk
analysis portfolios considered. See Chapter 5 and 6
plus supporting information in Appendix 2.6 for
Avista’s portfolio risk analysis and determination of the
preferred portfolio.
The planning horizon for analyzing
resource choices should be at least
20 years and account for end
effects. Utilities should consider all
costs with a reasonable likelihood of
being included in rates over the long
term, which extends beyond the
planning horizon and the life of the
resource.
Avista used a 20-year study period for portfolio
modeling. Avista contemplated possible costs beyond
the planning period that could affect rates including
end effects such as infrastructure decommission costs
and concluded there were no significant costs
reasonably likely to impact rates under different
resource selection scenarios.
Utilities should use present value of
revenue requirement (PVRR) as the
key cost metric. The plan should
include analysis of current and
estimated future costs of all long-
lived resources such as power
plants, gas storage facilities and
pipelines, as well as all short-lived
Avista’s SENDOUT® modeling software utilizes a
PVRR cost metric methodology applied to both long
and short-lived resources.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 20 of 829
resources such as gas supply and
short-term power purchases.
To address risk, the plan should
include at a minimum: 1) Two
measures of PVRR risk: one that
measures the variability of costs and
one that measures the severity of
bad outcomes. 2) Discussion of the
proposed use and impact on costs
and risks of physical and financial
hedging.
Avista, through its stochastic analysis, modeled 200
scenarios around varying gas price inputs via Monte
Carlo iterations developing a distribution of Total 20
year cost estimates utilizing SENDOUT®’s PVRR
methodology. Chapter 7 further describes this
analysis. The variability of costs is plotted against the
Expected Case while the scenarios beyond the 95th
percentile capture the severity of outcomes. Chapter 4
discusses Avista’s physical and financial hedging
methodology.
The utility should explain in its plan
how its resource choices
appropriately balance cost and risk.
Chapter 4, 5, 6, and 7 describe various specific
resource considerations and related risks, and
describes what criteria we used to determine what
resource combinations provide an appropriate balance
between cost and risk.
1d The plan must be consistent with
the long-run public interest as
expressed in Oregon and federal
energy policies.
Avista considered current and expected state and
federal energy policies in portfolio modeling. Chapter
6 describes the decision process used to derive
portfolios, which includes consideration of state
resource policy directions.
Guideline 2: Procedural Requirements
2a The public, including other utilities,
should be allowed significant
involvement in the preparation of the
IRP. Involvement includes
opportunities to contribute
information and ideas, as well as to
receive information. Parties must
have an opportunity to make
relevant inquiries of the utility
formulating the plan.
Chapter 1 provides an overview of the public process
and documents the details on public meetings held for
the 2018 IRP. Avista encourages participation in the
development of the plan, as each party brings a
unique perspective and the ability to exchange
information and ideas makes for a more robust plan.
While confidential information must
be protected, the utility should make
public, in its plan, any non-
confidential information that is
relevant to its resource evaluation
and action plan.
The entire IRP, as well as the TAC process, includes
all of the non-confidential information the company
used for portfolio evaluation and selection. Avista also
provided stakeholders with non-confidential
information to support public meeting discussions via
email. The document and appendices will be available
on the company website for viewing.
The utility must provide a draft IRP
for public review and comment prior
to filing a final plan with the
Commission.
Avista distributed a draft IRP document for external
review to all TAC members on July 2, 2018 and
requested comments by July 13, 2018.
Guideline 3: Plan Filing, Review and Updates
3a Utility must file an IRP within two
years of its previous IRP
acknowledgement order.
This Plan complies with this requirement as the 2016
Natural Gas IRP was acknowledged on March 21,
2017.
3b Utility must present the results of its
filed plan to the Commission at a
public meeting prior to the deadline
for written public comment.
Avista will work with Staff to fulfill this guideline
following filing of the IRP.
3c Commission staff and parties should
complete their comments and
Pending
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 21 of 829
recommendations within six months
of IRP filing
3d The Commission will consider
comments and recommendations on
a utility’s plan at a public meeting
before issuing an order on
acknowledgment. The Commission
may provide the utility an
opportunity to revise the plan before
issuing an acknowledgment order
Pending
3e The Commission may provide
direction to a utility regarding any
additional analyses or actions that
the utility should undertake in its
next IRP.
Pending
3f Each utility must submit an annual
update on its most recently
acknowledged plan. The update is
due on or before the
acknowledgment order anniversary
date. Once a utility anticipates a
significant deviation from its
acknowledged IRP, it must file an
update with the Commission, unless
the utility is within six months of
filing its next IRP. The utility must
summarize the update at a
Commission public meeting. The
utility may request acknowledgment
of changes in proposed actions
identified in an update
The annual update was submitted on March 1, 2018.
The filing was primarily an informational filing only as
Avista intends to file an updated IRP by August 31,
2018. In addition to the filing, Avista has provided
updates and comparisons to its 2016 IRP during its
2018 IRP TAC meetings held on January 25, 2018,
February 22, 2018, March 29, 2018, and May 10,
2018, in which Commission Staff and other TAC
members were present. In addition the Company
provided an update during its Natural Gas Quarterly
update meeting held on August 15, 2018. No request
for acknowledgement was required as no significant
deviation from the 2016 IRP was anticipated.
3g Unless the utility requests
acknowledgement of changes in
proposed actions, the annual update
is an informational filing that:
 Describes what actions the utility
has taken to implement the plan;
 Provides an assessment of what
has changed since the acknowledgment order that
affects the action plan, including changes in such factors as load,
expiration of resource contracts, supply-side and demand-side
resource acquisitions, resource costs, and transmission
availability; and
 Justifies any deviations from the
acknowledged action plan.
The updates described in 3f above explained changes
since acknowledgment of the 2016 IRP and an update
of emerging planning issues. The updates did not
request acknowledgement of any changes.

Guideline 4: Plan Components
At a minimum, the plan must include the following elements:

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 22 of 829
4a An explanation of how the utility met
each of the substantive and
procedural requirements.
This table summarizes guideline compliance by
providing an overview of how Avista met each of the
substantive and procedural requirements for a natural
gas IRP.
4b Analysis of high and low load growth
scenarios in addition to stochastic
load risk analysis with an
explanation of major assumptions.
Avista developed six demand growth forecasts for
scenario analysis. Stochastic variability of demand
was also captured in the risk analysis. Chapter 2
describes the demand forecast data and Chapter 7
provides the scenario and risk analysis results.
Appendix 5 details major assumptions.
4c For electric utilities only Not Applicable
4d A determination of the peaking,
swing and base-load gas supply and
associated transportation and
storage expected for each year of
the plan, given existing resources;
and identification of gas supplies
(peak, swing and base-load),
transportation and storage needed
to bridge the gap between expected
loads and resources.
Figures 6, 7, and 8 summarize graphically projected
annual peak day demand and the existing and
selected resources by year to meet demand for the
expected case. Appendix 6.1 and 6.2 summarizes the
peak day demand for the other demand scenarios.
4e Identification and estimated costs of
all supply-side and demand-side
resource options, taking into
account anticipated advances in
technology
Chapter 3 and Appendix 3.1 identify the demand-side
potential included in this IRP. Chapter 4 and 6 and
Appendix 6.3 identify the supply-side resources.
4f Analysis of measures the utility
intends to take to provide reliable
service, including cost-risk tradeoffs.
Chapter 6 and 7 discuss the modeling tools, customer
growth forecasting and cost-risk considerations used
to maintain and plan a reliable gas delivery system.
These Chapters also capture a summary of the
reliability analysis process demonstrated at the
second TAC meeting.
Chapter 4 discusses the diversified infrastructure and
multiple supply basin approach that acts to mitigate
certain reliability risks. Appendix 2.6 highlights key
risks associated with each portfolio.
4g Identification of key assumptions
about the future (e.g. fuel prices and
environmental compliance costs)
and alternative scenarios
considered.
Appendix 7 and Chapter 7 describe the key
assumptions and alternative scenarios used in this
IRP.
4h Construction of a representative set
of resource portfolios to test various
operating characteristics, resource
types, fuels and sources,
technologies, lead times, in-service
dates, durations and general
locations - system-wide or delivered
to a specific portion of the system.
This Plan documents the development and results for
portfolios evaluated in this IRP (see Table 4.3 for
supply scenarios considered).
4i Evaluation of the performance of the
candidate portfolios over the range
of identified risks and uncertainties.
We evaluated our candidate portfolio by performing
stochastic analysis using SENDOUT® varying price
under 200 different scenarios. Additionally, we test
the portfolio of options with the use of SENDOUT®
under deterministic scenarios where demand and
price vary. For resources selected, we assess other
risk factors such as varying lead times required and Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 23 of 829
potential for cost overruns outside of the amounts
included in the modeling assumptions.
4j Results of testing and rank ordering
of the portfolios by cost and risk
metric, and interpretation of those
results.
Avista’s four distinct geographic Oregon service
territories limit many resource option synergies which
inherently reduces available portfolio options.
Feasibility uncertainty, lead time variability and
uncertain cost escalation around certain resource
options also reduce reasonably viable options.
Chapter 4 describes resource options reviewed
including discussion on uncertainties in lead times and
costs as well as viability and resource availability (e.g.
LNG). Appendix 6.3 summarizes the potential
resource options identifying investment and variable
costs, asset availability and lead time requirements
while results of resources selected are identified in
Table 6.5 as well as graphically presented in Figure
6.18 and 6.19 for the Expected Case and Appendix
7.1 for the High Growth case.
4k Analysis of the uncertainties
associated with each portfolio
evaluated
See the responses to 1.b above.
4l Selection of a portfolio that
represents the best combination of
cost and risk for the utility and its
customers
Avista evaluated cost/risk tradeoffs for each of the risk
analysis portfolios considered. Chapter 6 and
Appendix 2.6 show the company’s portfolio risk
analysis, as well as the process and determination of
the preferred portfolio.
4m Identification and explanation of any
inconsistencies of the selected
portfolio with any state and federal
energy policies that may affect a
utility's plan and any barriers to
implementation
This IRP is presumed to have no inconsistencies.
4n An action plan with resource
activities the utility intends to
undertake over the next two to four
years to acquire the identified
resources, regardless of whether
the activity was acknowledged in a
previous IRP, with the key attributes
of each resource specified as in
portfolio testing.
Chapter 9 presents the IRP Action Plan with focus on
the following areas:
 Modeling
 Supply/capacity/distribution
 Forecasting
 Regulatory communication
 DSM
Guideline 5: Transmission
5 Portfolio analysis should include
costs to the utility for the fuel
transportation and electric
transmission required for each
resource being considered. In
addition, utilities should consider
fuel transportation and electric
transmission facilities as resource
options, taking into account their
value for making additional
purchases and sales, accessing
less costly resources in remote
Not applicable to Avista’s gas utility operations.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 24 of 829
locations, acquiring alternative fuel
supplies, and improving reliability.
Guideline 6: Conservation
6a Each utility should ensure that a
conservation potential study is
conducted periodically for its entire
service territory.
AEG performed a conservation potential assessment
study for our 2018 IRP. A discussion of the study is
included in Chapter 3. The full study document is in
Appendix 3.1. Avista incorporates a comprehensive
assessment of the potential for utility acquisition of
energy-efficiency resources into the regularly-
scheduled Integrated Resource Planning process.
6b To the extent that a utility controls
the level of funding for conservation
programs in its service territory, the
utility should include in its action
plan all best cost/risk portfolio
conservation resources for meeting
projected resource needs,
specifying annual savings targets.
A discussion on the treatment of conservation
programs is included in Chapter 3 while selection
methodology is documented in Chapter 6. The action
plan details conservation targets, if any, as developed
through the operational business planning process.
These targets are updated annually, with the most
current avoided costs. Given the challenge of the low
cost environment, current operational planning and
program evaluation is still underway and targets for
Oregon have not yet been set.
6c To the extent that an outside party
administers conservation programs
in a utility's service territory at a
level of funding that is beyond the
utility's control, the utility should: 1)
determine the amount of
conservation resources in the best
cost/ risk portfolio without regard to
any limits on funding of conservation
programs; and 2) identify the
preferred portfolio and action plan
consistent with the outside party's
projection of conservation
acquisition.
Not applicable. See the response for 6.b above.
Guideline 7: Demand Response
7 Plans should evaluate demand response resources,
including voluntary rate programs, on par with other
options for meeting energy, capacity, and transmission
needs (for electric utilities) or gas supply and
transportation needs (for natural gas utilities).
Avista has periodically evaluated
conceptual approaches to
meeting capacity constraints
using demand-response and
similar voluntary programs.
Technology, customer
characteristics and cost issues
are hurdles for developing
effective programs. See Chapter
3 Demand Response section for
more discussion.
Guideline 8: Environmental Costs
8 Utilities should include, in their base-case analyses, the
regulatory compliance costs they expect for CO2, NOx,
SO2, and Hg emissions. Utilities should analyze the
range of potential CO2 regulatory costs in Order No. 93-
695, from $0 - $40 (1990$). In addition, utilities should
perform sensitivity analysis on a range of reasonably
possible cost adders for NOx, SO2, and Hg, if applicable.
Avista’s current direct gas
distribution system infrastructure
does not result in any CO2, NOx,
SO2, or Hg emissions. Upstream
gas system infrastructure
(pipelines, storage facilities, and
gathering systems) do produce
CO2 emissions via compressors Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 25 of 829
used to pressurize and move gas
throughout the system. The
Environmental Externalities
discussion in Appendix 3.2
describes our analysis
performed. See also the
guidelines addendum reflecting
revised guidance for
environmental costs per Order
08-339.

Guideline 9: Direct Access Loads
9 An electric utility's load-resource balance should exclude
customer loads that are effectively committed to service
by an alternative electricity supplier.
Not applicable to Avista’s gas
utility operations.
Guideline 10: Multi-state utilities
10 Multi-state utilities should plan their generation and
transmission systems, or gas supply and delivery, on an
integrated-system basis that achieves a best cost/risk
portfolio for all their retail customers.
The 2018 IRP conforms to the
multi-state planning approach.
Guideline 11: Reliability
11 Electric utilities should analyze reliability within the risk
modeling of the actual portfolios being considered. Loss
of load probability, expected planning reserve margin,
and expected and worst-case unserved energy should
be determined by year for top-performing portfolios.
Natural gas utilities should analyze, on an integrated
basis, gas supply, transportation, and storage, along with
demand-side resources, to reliably meet peak, swing,
and base-load system requirements. Electric and natural
gas utility plans should demonstrate that the utility’s
chosen portfolio achieves its stated reliability, cost and
risk objectives.
Avista’s storage and transport
resources while planned around
meeting a peak day planning
standard, also provides
opportunities to capture off
season pricing while providing
system flexibility to meet swing
and base-load requirements.
Diversity in our transport options
enables at least dual fuel source
options in event of a transport
disruption. For areas with only
one fuel source option the cost of
duplicative infrastructure is not
feasible relative to the risk of
generally high reliability
infrastructure.

Guideline 12: Distributed Generation
12 Electric utilities should evaluate distributed
generation technologies on par with other supply-side
resources and should consider, and quantify where
possible, the additional benefits of distributed generation.
Not applicable to Avista’s gas
utility operations.
Guideline 13: Resource Acquisition
13a An electric utility should: identify its proposed acquisition
strategy for each resource in its action plan; Assess the
advantages and disadvantages of owning a resource
instead of purchasing power from another party; identify any Benchmark Resources it plans to consider in competitive bidding.
Not applicable to Avista’s gas
utility operations.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 26 of 829
13b Natural gas utilities should either describe in the IRP
their bidding practices for gas supply and transportation,
or provide a description of those practices following IRP
acknowledgment.
A discussion of Avista’s
procurement practices is detailed
in Chapter 4.
Guideline 8: Environmental Costs
a. BASE CASE AND OTHER COMPLIANCE SCENARIOS:
The utility should construct a base-case scenario to
reflect what it considers to be the most likely regulatory
compliance future for carbon dioxide (CO2), nitrogen
oxides, sulfur oxides, and mercury emissions. The utility
also should develop several compliance scenarios
ranging from the present CO2 regulatory level to the
upper reaches of credible proposals by governing
entities. Each compliance scenario should include a time
profile of CO2 compliance requirements. The utility
should identify whether the basis of those requirements,
or “costs”, would be CO2 taxes, a ban on certain types of
resources, or CO2 caps (with or without flexibility
mechanisms such as allowance or credit trading or a
safety valve). The analysis should recognize significant
and important upstream emissions that would likely have
a significant impact on its resource decisions. Each
compliance scenario should maintain logical consistency,
to the extent practicable, between the CO2 regulatory
requirements and other key inputs.
Avista’s current direct gas
distribution system infrastructure
does not result in any CO2, NOx,
SO2, or Hg emissions. Upstream
gas system infrastructure
(pipelines, storage facilities, and
gathering systems) do produce
CO2 emissions via compressors
used to pressurize and move gas
throughout the system.

The Environmental Externalities
discussion in Appendix 3.2
describes our process for
addressing these costs.

b. TESTING ALTERNATIVE PORTFOLIOS AGAINST THE
COMPLIANCE SCENARIOS: The utility should
estimate, under each of the compliance scenarios, the
present value of revenue requirement (PVRR) costs and
risk measures, over at least 20 years, for a set of
reasonable alternative portfolios from which the preferred
portfolio is selected. The utility should incorporate end-
effect considerations in the analyses to allow for
comparisons of portfolios containing resources with
economic or physical lives that extend beyond the
planning period. The utility should also modify projected
lifetimes as necessary to be consistent with the
compliance scenario under analysis. In addition, the
utility should include, if material, sensitivity analyses on a
range of reasonably possible regulatory futures for
nitrogen oxides, sulfur oxides, and mercury to further
inform the preferred portfolio selection.
The Environmental Externalities
discussion in Appendix 3.2
describes our process for
addressing these costs.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 27 of 829
APPENDIX 2.1: ECONOMIC OUTLOOK AND CUSTOMER COUNT FORECAST
I. Service Area Economic Performance and Outlook

Avista’s core service area for natural gas includes Eastern Washington, Northern Idaho, and Southwest Oregon.
Smaller service islands are also located in rural South-Central Washington and Northeast Oregon. Our service area
is dominated by four metropolitan statistical areas (MSAs): the Spokane-Spokane Valley, WA MSA (Spokane-
Stevens counties); the Coeur d’Alene, ID MSA (Kootenai County); the Lewiston-Clarkson, ID-WA MSA (Nez Perce-
Asotin counties); the Medford, OR MSA (Jackson County); and Grants Pass, OR MSA (Josephine County). These
five MSAs represent the primary demand for Avista’s natural gas and account for 75% of both customers (i.e.,
meters) and load. The remaining 25% of customers and load are spread over low density rural areas in all three
states.

Figure 1: Employment and Population Recovery, December 2007- June 2018

Data source: Employment from the BLS; population from the U.S. Census.

In the wake of the Great Recession, our service area recovered more slowly than the U.S. Although the U.S.
recession officially ended in June 2009 (dated by the National Bureau of Economic Research), our service area did
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Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 28 of 829
not start a significant employment recovery until the second half of 2012 (Figure 1, top and bottom graph).
However, by the end of 2015, year-over-year employment growth exceeded U.S. growth and employment levels
returned to pre-recession levels. Due to strong employment growth in 2016 and 2017, the total percentage gain in
employment was roughly the same as the U.S. by the middle of 2018. As a result, service area population growth,
which is significantly influenced by in-migration through employment opportunities, continued to improve sense
the last IRP (Figure 2).

Figure 2: Avista MSA Annual Population Growth, 2005-2017

In 2011, Avista’s MSA population growth fell to around 0.6%, the lowest since the late 1980s, but has increased to
around 1.7% by 2017. This is important because population growth is a significant contributor to overall customer
growth.

Figure 3 shows that compared to forecasted customer growth in the 2016 IRP, actual average customer growth in
WA-ID over the 2016-2017 period is considerably higher. This reflects (1) stronger than expected population
growth and (2) Avista’s LEAP gas conversion program in WA. The structure of the LEAP program, which expires in
September 2019, was unknown at the time of the 2016 IRP. In contrast, OR’s actual growth rate is slightly lower
than forecasted over the same period. This reflects actual population growth being lower than the forecast
assumption in the 2016 IRP. Given that average annual population forecast over this period was close to actual
growth, reflects a lower than expected level of conversions by existing households. This can be seen in Figure 4
(bottom graph) which shows that since 2015, customer growth in the OR service area is nearly identical to
population growth. The presence of significant conversions would generate customer growth that exceeds
population growth, as can be seen in WA-ID (top graph).

Given the impact of the LEAP program and stronger than expected population growth since 2016 IRP, this IRP
shows an upward revision of approximately 16,750 customers in WA-ID by 2037. That is, because the 2018 IRP
forecast is starting from a higher than expected base, this generates a higher forecast out to 2037. In contrast,
OR’s forecast shows approximately 4,700 few forecasted customers in 2037 compared to 2016 IRP. This change
reflects lower forecasted population growth compared to the 2016 IRP, especially I the Medford and Klamath
service regions. System-wide, this is an upward revision of approximately 13,500 customers. Figure 5 and Table 1
show the change in the customer forecast by for the system and by class between the 2016 and 2018 IRPs.

1.6%
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1.7%1.7%
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2.0%
2.5%
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
An
n
u
a
l

G
r
o
w
t
h
Population Growth in Avista WA-ID-OR MSAs
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 29 of 829

Figure 3: Comparison of 2014-IRP Customer Growth Forecasts to Actuals, 2016-2017

Data source: Company data.

1.25%1.23%1.24%
2.05%
2.49%
2.27%
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
2016 2017 2016-2017 Average
WA-ID Forecasted vs. Actual Customer Growth Rates
WA-ID 2016 IRP Forecast WA-ID Actual
1.43%1.40%1.41%
1.13%
1.29%1.21%
0.0%
0.2%
0.4%
0.6%
0.8%
1.0%
1.2%
1.4%
1.6%
2016 2017 2016-2017 Average
OR Forecasted vs. Actual Customer Growth Rates
OR 2016 IRP Forecast OR Actual
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 30 of 829

Figure 4: Customer and Population Growth, 2005-2017
Data source: Company data.

0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
OR Population Growth vs. Residential Customer Growth
OR Customer Growth OR Population Growth
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
WA-ID Population Growth vs. Residential Customer Growth
WA-ID Customer Growth WA-ID Population Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 31 of 829

Table 1: Change in Forecast between the 2016 IRP and 2018 IRP in 2037
WA-ID +16,174 +608 -32 +16,750
OR -4,755 +103 -2 -4,654
System +11,419 +711 -34 +12,906

Figure 5: Comparison IRP Forecasted Customer Growth in WA-ID and OR, 2017-2037
Data source: Company data.

In past IRPs, the modeling approach for the majority of commercial customers assumed that residential customer
growth is a driver of commercial customer growth. This is still the case for ID and OR. The use of residential
customers as forecast driver for commercial customers reflects the historically high correlation between
residential and commercial customer growth rates. However, because of the LEAP program, residential customers
is no longer the primary driver in the commercial forecast in WA. The LEAP program altered the historical
relationship between residential and commercial customer growth because the program was not offered to
commercial customers. As a result, population has replaced residential customers as the direct driver of
commercial customer forecast.

The forecast for system-wide industrial customers is lower compared to the 2016 IRP. Approximately 90% of
industrial customers are in WA-ID. Figure 6 (top graph) shows total system-wide firm industrial customers since
2004. Following a sharp drop over the 2004-2006 period, firm industrial customers have remained stable at
around 260. Separating out WA-ID and OR (middle graph), the number of firm customers in WA-ID continuously
fell over the 2004-2011 period. In contrast, OR customers increased over the 2004-2011 period (bottom graph).
However, after a period of stability during the 2011-2014 period, customer declined modestly. That is, over the
last five years there has been no appreciable change in firm industrial customers our service area. Therefore, in
contrast to the 2016 IRP which showed a flat industrial base, the current forecast shows a declining base.

300,000
320,000
340,000
360,000
380,000
400,000
420,000
440,000
2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037
WA-ID-OR-Base 2016 IRP WA-ID-OR-Base 2018 IRP
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 32 of 829
Figure 7: Industrial Customer Count, 2004-2017

Data source: Company data.

240
245
250
255
260
265
270
275
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
WA-ID-OR Firm Industrial Customers
200
210
220
230
240
250
260
270
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
WA-ID Firm Industrial Customers
0
5
10
15
20
25
30
35
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
OR Firm Industrial Customers
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 33 of 829
II. IRP Forecast Process and Methodology

The customer forecasts are generated from forecasting models that are either regression models with ARIMA error
corrections or simple smoothing models. The ARIMA error correction models are estimated using SAS/ETS
software. The customer forecasts are used as input into Sendout® to generate the IRP load forecasts.
Population growth is the key driver for the residential and commercial customer forecasts. Other variables include
(1) seasonal dummy variables and (2) outlier dummy variables that control for extreme customer counts
associated with double billing, software conversions, and customer movements from one billing schedule to
another.

Population growth forecast is the key driver behind the customer forecast for residential schedules 101 in WA-ID
and 410 in OR. These two schedules represent the majority of customers and, therefore, drive overall residential
customer growth. Because of their size and growth potential, a multi-step forecasting process has been
developed for the Spokane-Spokane Valley, Coeur d’Alene, and Medford MSAs. The process for forecasting
population growth starts with an intermediate forecast horizon (seven years). This medium-term forecast is
typically used for the annual financial forecast. However, during IRP years, this medium-term forecast horizon is
augmented with third party forecasts that cover the next twenty years. Starting with Figure 8, the six-year
population forecast is a multi-step process that begins with a GDP forecast that drives the regional employment
forecast, which in turn, drives a six year population forecast.

Figure 8: Forecasting Population Growth, 2018-2024

The forecasting models for regional employment growth are:

[1] 𝐺𝐸𝑀𝑃𝑦,𝑆𝑃𝐾= 𝜗0 + 𝜗1𝐺𝐺𝐷𝑃𝑦,𝑈𝑆+ 𝜗2𝐺𝐺𝐷𝑃𝑦−1,𝑈𝑆+ 𝜗3𝐺𝐺𝐷𝑃𝑦−2,𝑈𝑆+ 𝜔𝑆𝐶𝐷𝐾𝐶,1998−2000=1+ 𝜔𝑆𝐶𝐷𝐻𝐵,2005−2007=1 + 𝜖𝑡,𝑦

[2] 𝐺𝐸𝑀𝑃𝑦,𝐾𝑂𝑂𝑇= 𝛿0 + 𝛿1𝐺𝐺𝐷𝑃𝑦,𝑈𝑆+ 𝛿2𝐺𝐺𝐷𝑃𝑦−1,𝑈𝑆+ 𝛿3𝐺𝐺𝐷𝑃𝑦−2,𝑈𝑆+ 𝜔𝑂𝐿𝐷1994=1+ 𝜔𝑂𝐿𝐷2009=1 + 𝜔𝑆𝐶𝐷𝐻𝐵,2005−2007=1 + 𝜖𝑡,𝑦

[3] 𝐺𝐸𝑀𝑃𝑦,𝐽𝐴𝐶𝐾+𝐽𝑂𝑆= 𝜙0 + 𝜙1𝐺𝐺𝐷𝑃𝑦,𝑈𝑆+ 𝜙2𝐺𝐺𝐷𝑃𝑦−1,𝑈𝑆+ 𝜙3𝐺𝐺𝐷𝑃𝑦−2,𝑈𝑆+ 𝜔𝑆𝐶𝐷𝐻𝐵,2004−2005=1 + 𝐴𝑅𝐼𝑀𝐴𝜖𝑡,𝑦 (1,0,0)(0,0,0)12

SPK is Spokane, WA (Spokane MSA), KOOT is Kootenai, ID (Coeur d’Alene MSA), and JACK+JOS is for the
combination of Jackson County, OR (Medford MSA) and Josephine County, OR (Grants Pass MSA). GEMPy is
employment growth in year y, GGDPy,US is U.S. real GDP growth in year y. DKC is a dummy variable for the collapse
of Kaiser Aluminum in Spokane, and DHB, is a dummy for the housing bubble, specific to each region. The average
GDP forecasts are used in the estimated model to generate five-year employment growth forecasts. The
employment forecasts are then averaged with IHS’s forecasts for the same counties so that:

[4] 𝐹𝐴𝑣𝑔(𝐺𝐸𝑀𝑃𝑦,𝑆𝑃𝐾) = 𝐹(𝐺𝐸𝑀𝑃𝑦,𝑆𝑃𝐾)+𝐹(𝐺𝐼𝐻𝑆𝐸𝑀𝑃)𝑦,𝑆𝑃𝐾)
2

Average GDP Growth
Forecasts:
IMF, FOMC,
Bloomberg, etc.
Average forecasts
out 6-yrs.
Growth Model:
Model links year y, y-1,
and y-2 GDP growth to
year y regional
employment growth.
Forecast out 7-yrs.
Averaged with GI

Model links regional, U.S., and CA
year y-1 employment growth to year
y county population growth.
Forecast out 7-yrs for Spokane, WA;
Kootenai, ID; and
Jackson+Josephine, OR.
Averaged with IHS forecasts in ID
and OR and OFM forecasts in WA.
Growth rates used to generate
population forecasts for customer
forecasts for residential schedules 1,
EMP GDP
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 34 of 829
[5] 𝐹𝐴𝑣𝑔(𝐺𝐸𝑀𝑃𝑦,𝐾𝑂𝑂𝑇) = 𝐹(𝐺𝐸𝑀𝑃𝑦,𝐾𝑂𝑂𝑇 )+𝐹(𝐺𝐼𝐻𝑆𝐸𝑀𝑃𝑦,𝐾𝑂𝑂𝑇)
2

[6] 𝐹𝐴𝑣𝑔(𝐺𝐸𝑀𝑃𝑦,𝐽𝐴𝐶𝐾) = 𝐹(𝐺𝐸𝑀𝑃𝑦,𝐽𝐴𝐶𝐾 )+𝐹(𝐺𝐼𝐻𝑆𝐸𝑀𝑃𝑦,𝐽𝐴𝐶𝐾)
2

Averaging reduces the systematic errors of a single-source forecast. The averages [8.4] through [8.6] are used to
generate the population growth forecasts, which are described next.

The forecasting models for regional population growth are:

[7] 𝐺𝑃𝑂𝑃𝑦,𝑆𝑃𝐾= 𝜅0 + 𝜅1𝐺𝐸𝑀𝑃𝑦−1,𝑆𝑃𝐾+ 𝜅2𝐺𝐸𝑀𝑃𝑦−2,𝑈𝑆+ 𝜔𝑂𝐿𝐷2001=1+𝜖𝑡,𝑦

[8] 𝐺𝑃𝑂𝑃𝑦,𝐾𝑂𝑂𝑇= 𝛼0 + 𝛼1𝐺𝐸𝑀𝑃𝑦−1,𝐾𝑂𝑂𝑇+ 𝛼2𝐺𝐸𝑀𝑃𝑦−2,𝑈𝑆+ 𝜔𝑂𝐿𝐷1994=1 + 𝜔𝑂𝐿𝐷2002=1+ 𝜔𝑆𝐶𝐷𝐻𝐵,2007↑=1 + 𝜖𝑡,𝑦

[9] 𝐺𝑃𝑂𝑃𝑦,𝐽𝐴𝐶𝐾+𝐽𝑂𝑆= 𝜓0 + 𝜓1𝐺𝐸𝑀𝑃𝑦−1,𝐽𝐴𝐶𝐾+𝐽𝑜𝑠+ 𝜓2𝐺𝐸𝑀𝑃𝑦−2,𝐶𝐴+ 𝜔𝑂𝐿𝐷1991=1+ 𝜔𝑆𝐶𝐷𝐻𝐵,2004−2006=1 + 𝜖𝑡,𝑦

D2001=1 and D1991=1 are a dummy variables for recession impacts. GEMPy-1,US is U.S. employment growth in year y-1
and GEMPy-2, and CA is California Employment growth in year y-1. Because of its close proximity to CA, CA
employment growth is better predictor of Jackson, OR employment growth than U.S. growth. The averages [8.4]
through [8.6] are used in [7] through [9] to generate population growth forecasts. These forecasts are combined
with IHS’s forecasts for Kootenai, ID; Jackson, OR; Josephine, OR, and the Office for Financial Management (OFM)
for Spokane, WA in the form of a simple average:

[10] 𝐹𝐴𝑣𝑔(𝐺𝑃𝑂𝑃𝑦,𝑆𝑃𝐾) = 𝐹(𝐺𝑃𝑂𝑃𝑦,𝑆𝑃𝐾)+𝐹(𝐺𝑂𝐹𝑀𝑃𝑂𝑃𝑦,𝑆𝑃𝐾)
2

[11] 𝐹𝐴𝑣𝑔(𝐺𝑃𝑂𝑃𝑦,𝐾𝑂𝑂𝑇) = 𝐹(𝐺𝑃𝑂𝑃𝑦,𝐾𝑂𝑂𝑇 )+𝐹(𝐺𝐼𝐻𝑆𝑃𝑂𝑃𝑦,𝐾𝑂𝑂𝑇)
2

[12] 𝐹𝐴𝑣𝑔(𝐺𝑃𝑂𝑃𝑦,𝐽𝐴𝐶𝐾+𝐽𝑂𝑆) = 𝐹(𝐺𝑃𝑂𝑃𝑦,𝐽𝐴𝐶𝐾+𝐽𝑂𝑆 )+𝐹(𝐺𝐼𝐻𝑆𝑃𝑂𝑃𝑦,𝐽𝐴𝐶𝐾+𝐽𝑂𝑆)
2

Here, FAvg(GPOPy) is used to forecast population to forecast residential customers in schedules 101 (WA-ID) and
410 (OR) for the Spokane, Kootenai, and Jackson+Josephine areas. In the case of Spokane, OFM forecasts are used
because the IHS’s forecasts exhibit a level and time-path that is inconsistent with recent population behavior. The
population growth forecasts for the Douglas (Roseburg), Klamath (Klamath Falls); and Union (La Grande) counties
come directly from IHS. Since all forecasted growth rates are annualized, they are converted to monthly rates as
FAvg(GPOPt,y)= [1+ FAvg(GPOPy)]1/12 – 1. By way of example, the following is regression model for residential 101
customers for the Spokane region:

𝐶𝑡,𝑦,𝑊𝐴101.𝑟= 𝛼0 + 𝜏𝑃𝑂𝑃𝑡,𝑦,𝑆𝑃𝐾+𝝎𝑺𝑫𝑫𝒕,𝒚+ 𝜔𝑆𝐶𝐷𝐽𝑎𝑛 2007↑=1 + 𝛾𝑅𝐴𝑀𝑃𝑇𝐽𝑎𝑛 2007 + 𝜔𝑂𝐿𝐷𝑂𝑐𝑡 2005=1+ 𝜔𝑂𝐿𝐷𝐴𝑢𝑔 2010=1 + 𝜔𝑂𝐿𝐷𝑆𝑒𝑝 2012=1 + 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2015=1 + 𝜔𝑂𝐿𝐷𝑂𝑐𝑡 2015=1+ 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2016=1 + 𝜔𝑂𝐿𝐷𝑀𝑎𝑟 2018=1 + 𝐴𝑅𝐼𝑀𝐴𝜖𝑡,𝑦 (11,1,0)(0,0,0)12

Where:

POPt,y,SPK =  is the coefficient to be estimated and POPt,y,SPK is the interpolated population level in month t, in
year y, for Spokane. The monthly interpolation of historical data assumes that between years, population
accumulates following the standard population growth model: POPy,SPK = POPy-1,SPKer.

SDDt,y = SD is a vector of seasonal dummy (SD) coefficients to be estimated and Dt,y is a vector monthly
seasonal dummies to account of customer seasonality. Dt,y = 1 for the relevant month.

SCDJan 2007↑=1 + RampTJan 2007 = structural change (SC) and trend (Ramp) coefficients and variables that control
for the sharp fall in residential customer growth that cannot be fully accounted for by the population
variable. This reflects the impact of the housing bubble collapse and the subsequent Great Recession. DJan
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 35 of 829
2007↑=1 takes a value of 1 over both the estimation and forecast period starting in January 2007, and TJan 2007 is
a linear time-trend that starts in January 2007 and continues over the estimation and forecast period.

OLDOct 2005=1 = OL outlier (OL) coefficient to be estimated and D is a dummy that equals 1 for August 2010.
There are three additional outlier dummies that follow August 2010.

ARIMAt,y(11,1,0)(0,0,0)12 = is the error correction applied to the model’s initial error structure. This term
follows the following from ARIMAt,y (p,d,q)(pk,dk,qk)k. The term p is the autoregressive (AR) order, d is the
differencing order, and q is the moving average (MA) order. The term pk is the order of seasonal AR terms, dk
is the order of seasonal differencing, and qk is the seasonal order of MA terms. The seasonal values are
related to “k,” which is the frequency of the data. With the current data set, k = 12.

The customer forecast is generated by inputting forecasted values of POPt,y,SPK into the model estimated with
historical data. All customer forecast equations are shown in the last section.

The above describes the population forecast for the annual six-year forecast. For IRP years, the customer forecast
needs to be extended out an additional 15 years beyond medium term forecast. This is done using the IHS
population forecast for Kootenai, Jackson+Josephine, Douglas, Klamath, and Union counties. That is, IHS is the sole
source for forecasted population growth beyond the seven-year time horizon generated by [10] through [12]. In
the case of Spokane County, the forecast from Washington’s Office of Financial Management (OFM) is instead of
IHS’s. The choice to use OFM’s forecasts reflects the unusually sharp changes that have occurred in the IHS
forecasts for the Spokane MSA over a short period of time. Figure 9 shows how much these forecasts have
changed in level and shape since June 2012. From the October 2015 to March 2017 forecasts, there was as
significant changes for the 2015-2019 period. There is no clear rational for why IHS’s forecasts changed so
significantly between 2012 and 2017.

Figure 9: Spokane MSA Forecast Comparison

Data source: IHS, Washington State of Office of Financial Management, and U.S. Census.

0.0%
0.2%
0.4%
0.6%
0.8%
1.0%
1.2%
1.4%
1.6%
1.8%
2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035
IHS June 2012 Forecast IHS October 2015 Forecast IHS March 2016 Forecast
Actual OFM 2017 IHS March 2017 Forecast
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 36 of 829
Figure 10: Annual Customer Growth for the Three Rate Classes, 2005-2017

Data source: Company data.

Figure 10 demonstrates that residential and commercial growth rates are highly correlated and maintain similar
levels over the long-run—over the period shown, residential and commercial averaged about 1.6% and 1.1%,
respectively. This growth is slightly higher than population growth because of the housing boom and existing
households converting to natural gas. However, by 2009, with the collapse of the housing bubble and increased
natural gas saturation, customer growth moved closer to population growth.

In contrast, the behavior of Industrial customer growth looks quite different. Customer growth is both lower and
more volatile. The average growth rate since 2005 is -1.0%, reflecting a trend of nearly flat or slowly declining
customers, depending on the jurisdiction. In addition, the standard deviation of year-over-year growth is 1.9%
compared to 0.9% for residential and 0.7% for commercial growth. The current IRP forecast reflects this historical
trend of weak growth. Some energy industry analysts believe the U.S.’s increased supply of natural gas and oil will
attract industrial production back from overseas locations. However, in this IRP, we do not assume plentiful
energy supplies in the U.S. will alter long-run trends in industrial customer growth in our service area.

Establishing High-Low Cases for IRP Customer Forecast

The customer forecasts for this IRP include high and low cases that set the expected bounds around the base-case.
Table 2 shows the base, low, and high customer forecasts along with the underlying population growth
assumption. The underlying population forecast is the primary driver for each of the three cases.

Table 2: Alternative Growth Cases, 2018-2037
WA-ID:
WA-ID Customers 0.9% 1.3% 1.6%
WA Population 0.5% 0.8% 1.1%
ID Population 1.1% 1.6% 2.1%

OR:
OR Customers 0.6% 0.9% 1.3%
OR Population 0.5% 0.8% 1.1%
System:
System Customers 0.8% 1.2% 1.5%
System Population 0.5% 0.9% 1.2%

-5%
-4%
-3%
-2%
-1%
0%
1%
2%
3%
4%
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Residential Commercial Industrial
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 37 of 829
III. IRP Customer Forecast Equations

1. WA residential customer forecast models:

[1] 𝐶𝑡,𝑦,𝑊𝐴101.𝑟= 𝛼0 + 𝜏𝑃𝑂𝑃𝑡,𝑦,𝑆𝑃𝐾+𝝎𝑺𝑫𝑫𝒕,𝒚+ 𝜔𝑆𝐶𝐷𝐽𝑎𝑛 2007↑=1 + 𝛾𝑅𝐴𝑀𝑃𝑇𝐽𝑎𝑛 2007 + 𝜔𝑂𝐿𝐷𝑂𝑐𝑡 2005=1 +
𝜔𝑂𝐿𝐷𝐴𝑢𝑔 2010=1 + 𝜔𝑂𝐿𝐷𝑆𝑒𝑝 2012=1 + 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2015=1 + 𝜔𝑂𝐿𝐷𝑂𝑐𝑡 2015=1 + 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2016=1 +
𝐴𝑅𝐼𝑀𝐴𝜖𝑡,𝑦 (11,1,0)(0,0,0)12

[1] Model notes:
1. SC dummy and ramping time trend control for a change in the time-path of customer growth staring in January 2007.

[2] 𝐶𝑡,𝑦,𝑊𝐴102.𝑟= {
1
12 ∑𝐶𝑡−𝑗12𝑗=1 𝑓𝑜𝑟 𝑟𝑒𝑚𝑖𝑎𝑛𝑖𝑛𝑔 𝑚𝑜𝑛𝑡ℎ𝑠 𝑖𝑛 𝑐𝑢𝑟𝑟𝑒𝑛𝑡 𝑦𝑒𝑎𝑟,𝑦𝑐
𝐶𝐶𝑎𝑝 𝑓𝑜𝑟 𝑦𝑐+𝑗 𝑤ℎ𝑒𝑟𝑒 𝑗 = 1,…,23

[2] Model notes:
1. WA schedule 102 customers are schedule 101 customers that have been moved to a new low-income schedule. The schedule started in
October 2015, so there is insufficient data for a more complicated model. The schedule is currently capped at 300 customers, so the forecast is
set at this value following the current year of the forecast. It is possible this cap will increase in the future. The new cap level will be subject to
negotiation with regulators.

[3] 𝐶𝑡,𝑦,𝑊𝐴111.𝑟= 𝛼0 + 𝜔𝑆𝐶𝐷𝑂𝑐𝑡 2011↑=1 + 𝜔𝑆𝐶𝐷𝑂𝑐𝑡 2013↑=1 + 𝜔𝑂𝐿𝐷𝑀𝑎𝑟 2005=1 + 𝜔𝑂𝐿𝐷𝐷𝑒𝑐 2006=1 + 𝜔𝑂𝐿𝐷𝐽𝑎𝑛 2007=1 +
𝜔𝑂𝐿𝐷𝑆𝑒𝑝 2007=1 + 𝜔𝑂𝐿𝐷𝑁𝑜𝑣 2007=1 + 𝜔𝑂𝐿𝐷𝑂𝑐𝑡 2011=1 + 𝜔𝑂𝐿𝐷𝐽𝑎𝑛 2015=1 + 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2015=1 + 𝜔𝑂𝐿𝐷𝐴𝑝𝑟 2015=1 +
𝜔𝑂𝐿𝐷𝑂𝑐𝑡 2015=1 + 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2016=1 + 𝜔𝑂𝐿𝐷𝑂𝑐𝑡 2016=1 + 𝐴𝑅𝐼𝑀𝐴𝜖𝑡,𝑦 (1,1,0)(0,0,0)12

[3] Model notes:
1. Error structure white noise but not normally distributed.
2. SC dummies control for a step-up in customers starting in October 2011 and October 2013.

2. ID residential customer forecast models:

[4] 𝐶𝑡,𝑦,𝐼𝐷101.𝑟= 𝛽0 + 𝜏𝑃𝑂𝑃𝑡,𝑦,𝐾𝑂𝑂𝑇+𝝎𝑺𝑫𝑫𝒕,𝒚+𝜔𝑆𝐶𝐷𝐽𝑎𝑛 2007↑=1 + 𝛾𝑅𝐴𝑀𝑃𝑇𝐽𝑎𝑛 2007 + 𝜔𝑂𝐿𝐷𝑀𝑎𝑦 2005=1 + 𝜔𝑂𝐿𝐷𝐽𝑢𝑙 2005=1 +
𝜔𝑂𝐿𝐷𝑂𝑐𝑡 2005=1 + 𝜔𝑂𝐿𝐷𝐷𝑒𝑐 2005=1+𝜔𝑂𝐿𝐷𝐽𝑢𝑛 2006=1 + 𝜔𝑂𝐿𝐷𝐽𝑎𝑛 2006=1 + 𝜔𝑂𝐿𝐷𝐽𝑢𝑛 2007=1 + 𝜔𝑂𝐿𝐷𝑁𝑜𝑣 2007=1 +
𝜔𝑂𝐿𝐷𝐴𝑢𝑔 2009=1 + 𝜔𝑂𝐿𝐷𝐴𝑢𝑔 2011=1 + 𝜔𝑂𝐿𝐷𝑆𝑒𝑝𝑡 2011=1 + 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2015=1 + 𝐴𝑅𝐼𝑀𝐴𝜖𝑡,𝑦 (2,1,0)(0,0,0)12

[4] Model notes:
1. SC dummy and ramping time trend control for a change in the time-path of customer growth staring in January 2007.

[5] 𝐶𝑡,𝑦,𝐼𝐷111.𝑟= 𝛽0+𝛾𝑅𝐴𝑀𝑃𝑇𝐷𝑒𝑐 2011 + 𝜔𝑆𝐶𝐷𝐷𝑒𝑐 2008↑=1+𝜔𝑆𝐶𝐷𝐷𝑒𝑐 2011↑=1 + 𝜔𝑂𝐿𝐷𝑁𝑜𝑣 2008=1 + 𝜔𝑂𝐿𝐷𝑀𝑎𝑟 2010=1 +
𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2011=1 + 𝜔𝑂𝐿𝐷𝑁𝑜𝑣 2011=1 + 𝜔𝑂𝐿𝐷𝑀𝑎𝑟 2015=1 + 𝜔𝑂𝐿𝐷𝐷𝑒𝑐 2015=1 + 𝐴𝑅𝐼𝑀𝐴𝜖𝑡,𝑦 (9,1,0)(0,0,0)12

[5] Model notes:
1. SC dummies control for a step-up in customers starting in December 2008 and December 2011.
2. Ramping time trend controls for no customer growth since 2012.

3. WA commercial customer forecast models:

[6] 𝐶𝑡,𝑦,𝑊𝐴101.𝑐= 𝛼0 + 𝛼1𝑃𝑂𝑃𝑡,𝑦,𝑆𝑃𝐾+ 𝝎𝑺𝑫𝑫𝒕,𝒚+ 𝜔𝑂𝐿𝐷𝑁𝑜𝑣 2005=1 + 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2007=1 + 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2015=1 + 𝜔𝑂𝐿𝐷𝑆𝑒𝑝 2013=1 +
+𝜔𝑂𝐿𝐷𝑂𝑐𝑡 2013=1 + 𝜔𝑂𝐿𝐷𝐴𝑝𝑟 2015=1 + 𝜔𝑂𝐿𝐷𝐷𝑒𝑐 2015=1 + 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2016=1 + 𝐴𝑅𝐼𝑀𝐴𝜖𝑡,𝑦 (1,1,0)(0,0,0)12

[6] Model notes:
1. In the June 2017 forecast, Ct,y,WA101.r (residential customers from residential schedule 101) was replaced with POP for Spokane. This was done
to account for a new hookup tariff for residential gas customers in WA’s LEAP program. This tariff is more generous than the previous long-
standing tariff. In addition, any savings in the hookup process could be passed on to the customer for equipment purchases or replacement.
Since this tariff change excluded commercial and industrial customers, this significantly accelerated residential hookups but not commercial
hookups. As a result, this historical relationship between residential and commercial customer growth has been altered.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 38 of 829

[7] 𝐶𝑡,𝑦,𝑊𝐴111.𝑐= 𝛼0 + 𝝎𝑺𝑫𝑫𝒕,𝒚+ 𝜔𝑆𝐶𝐷𝐴𝑝𝑟 2016↑=1 + 𝜔𝑂𝐿𝐷𝐽𝑎𝑛 2007=1 + 𝜔𝑂𝐿𝐷𝑂𝑐𝑡 2013=1 +
𝜔𝑂𝐿𝐷𝑁𝑜𝑣 2013=1 + 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2015=1 + 𝜔𝑂𝐿𝐷𝐴𝑝𝑟 2015=1 + 𝜔𝑂𝐿𝐷𝐷𝑒𝑐 2015=1 + 𝐴𝑅𝐼𝑀𝐴𝜖𝑡,𝑦 (5,1,0)(0,0,0)12

[7] Model notes:
1. SC dummy controls for a step-up in customers starting in April 2016.
2. Distribution of error terms not quite normal; however, they do pass the white-noise test.

4. ID commercial customer forecast models:

[8] 𝐶𝑡,𝑦,𝐼𝐷101.𝑐= 𝛽0 + 𝛽1𝐶𝑡,𝑦,𝐼𝐷101.𝑟+ 𝝎𝑺𝑫𝑫𝒕,𝒚+𝜔𝑆𝐶𝐷𝑁𝑜𝑣 2005↑=1+𝜔𝑆𝐶𝐷𝑆𝑒𝑝 2006↑=1+𝜔𝑆𝐶𝐷𝑁𝑜𝑣 2007↑=1 +
𝜔𝑂𝐿𝐷𝑀𝑎𝑟 2005=1 + 𝜔𝑂𝐿𝐷𝐽𝑢𝑛 2005=1 + 𝜔𝑂𝐿𝐷𝑂𝑐𝑡 2005=1 + 𝜔𝑂𝐿𝐷𝐷𝑒𝑐 2005=1 + 𝜔𝑂𝐿𝐷𝑀𝑎𝑟 2007=1 + 𝜔𝑂𝐿𝐷𝑀𝑎𝑟 2008=1 +
𝜔𝑂𝐿𝐷𝐷𝑒𝑐 2014=1 + 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2015=1 + 𝜔𝑂𝐿𝐷𝐷𝑒𝑐 2015=1 + 𝐴𝑅𝐼𝑀𝐴𝜖𝑡,𝑦 (10,1,0)(0,0,0)12

[8] Model notes:
1. Ct,y,ID101.r are residential customers from residential schedule 101. They are being used as a forecast driver because of the historical positive
correlation between residential and commercial customer growth. See Tables 5.1 and 5.2.
2. SC dummies control for a step-up in customers in November 2005, September 2006, and November 2007.

[9] 𝐶𝑡,𝑦,𝐼𝐷111.𝑐= 𝛽0 +𝛾𝑅𝐴𝑀𝑃𝑇𝐽𝑎𝑛 2012 + 𝜔𝑆𝐶𝐷𝑁𝑜𝑣 2008↑=1+𝜔𝑆𝐶𝐷𝑁𝑜𝑣 2011↑=1+𝜔𝑆𝐶𝐷𝐽𝑎𝑛 2012↑=1 + 𝜔𝑂𝐿𝐷𝐽𝑎𝑛 2005=1 +
𝜔𝑂𝐿𝐷𝑆𝑒𝑝 2009=1 + 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2011=1 + 𝜔𝑂𝐿𝐷𝐷𝑒𝑐 2011=1 + 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2015=1 + 𝜔𝑂𝐿𝐷𝐷𝑒𝑐 2015=1 + 𝐴𝑅𝐼𝑀𝐴𝜖𝑡,𝑦 (6,1,0)(0,0,0)12

[9] Model notes:
1. SC dummies control for a large step-up in customers starting in November 2008 and November 2011.
2. Ramping time trend and SC dummy starting in Jan 2012 control for a slowdown in customer growth.

5. WA industrial customer forecasts models:

[10] 𝐶𝑡,𝑦,𝑊𝐴101.𝑖= 𝛼0 + 𝜔𝑆𝐶𝐷𝐴𝑝𝑟 2008↑=1+ 𝜔𝑆𝐶𝐷𝑂𝑐𝑡 2013↑=1 + 𝜔𝑂𝐿𝐷𝑂𝑐𝑡 2006=1+𝜔𝑂𝐿𝐷𝐽𝑎𝑛 2007=1+ 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2007=1 +
+ 𝜔𝑂𝐿𝐷𝐷𝑒𝑐 2013=1+ 𝜔𝑂𝐿𝐷𝐽𝑎𝑛 2014=1+ 𝜔𝑂𝐿𝐷𝐽𝑎𝑛 2015=1+ 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2015=1+ 𝜔𝑂𝐿𝐷𝐴𝑝𝑟 2016=1+ 𝜔𝑂𝐿𝐷𝑀𝑎𝑟 2017=1 +
𝐴𝑅𝐼𝑀𝐴𝜖𝑡,𝑦 (7,1,0)(0,0,0)12

[10] Model notes:
1. SC dummies control for a step-down in customers starting in April 2008 and October 2013.

[11] 𝐶𝑡,𝑦,𝑊𝐴111.𝑖= 𝛼0 + 𝜔𝑂𝐿𝐷𝑆𝑒𝑝 2005=1+ 𝜔𝑂𝐿𝐷𝑂𝑐𝑡 2006=1+ 𝜔𝑂𝐿𝐷𝐷𝑒𝑐 2006=1+ 𝜔𝑂𝐿𝐷𝐽𝑎𝑛 2007=1+ 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2007=1+ 𝜔𝑂𝐿𝐷𝑀𝑎𝑟 2008=1
+ 𝜔𝑂𝐿𝐷𝐽𝑢𝑛 2014=1+ 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2015=1 + 𝜔𝑂𝐿𝐷𝑂𝑐𝑡 2015=1+ 𝜔𝑂𝐿𝐷𝐴𝑝𝑟 2016=1+𝐴𝑅𝐼𝑀𝐴𝜖𝑡,𝑦 (2,0,0)(0,0,0)12

[11] Model notes:
1. Error structure is white noise, but not normally distributed.

6. ID industrial customer forecast models:

[12] 𝐶𝑡,𝑦,𝐼𝐷101.𝑖= 𝛽0 + 𝜔𝑆𝐶𝐷𝐷𝑒𝑐 2010↑=1+ 𝜔𝑆𝐶𝐷𝑁𝑜𝑣 2011↑=1+ 𝜔𝑆𝐶𝐷𝐷𝑒𝑐 2011↑=1+ 𝜔𝑆𝐶𝐷𝐽𝑢𝑛 2014↑=1 + 𝜔𝑂𝐿𝐷𝑀𝑎𝑟 2005=1 +
𝜔𝑂𝐿𝐷𝐴𝑢𝑔 2005=1+ 𝜔𝑂𝐿𝐷𝑂𝑐𝑡 2005=1 + 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2006=1 + 𝜔𝑂𝐿𝐷𝑀𝑎𝑟 2007=1+ 𝜔𝑂𝐿𝐷𝐷𝑒𝑐 2008=1+ 𝜔𝑂𝐿𝐷𝐽𝑎𝑛 2011=1 +
𝜔𝑂𝐿𝐷𝐴𝑢𝑔 2011=1+ 𝜔𝑂𝐿𝐷𝐽𝑢𝑙 2014=1 + 𝜔𝑂𝐿𝐷𝐽𝑎𝑛 2015=1+ 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2015=1 + 𝜔𝑂𝐿𝐷𝐷𝑒𝑐 2015=1+ 𝜔𝑂𝐿𝐷𝐽𝑎𝑛 2016=1 +
𝐴𝑅𝐼𝑀𝐴𝜖𝑡,𝑦 (4,0,0)(0,0,0)12

[12] Model notes:
1. SC dummies control for step-downs in customers starting in December 2010, November 2011, and December 2011; June 2014 controls for a
step-up in customers.

[13] 𝐶𝑡,𝑦,𝐼𝐷111.𝑖= 1
12 ∑𝐶𝑡−𝑗12𝑗=1

[13] Model notes:
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 39 of 829
1. Period of restriction reflects the restriction on the UPC model for this schedule.
2. Customer count stabilized in 2012; customer count fluctuates between 31 and 34 without any clear trend or seasonality.

[14] 𝐶𝑡,𝑦,𝐼𝐷112.𝑖= 1
12∑𝐶𝑡−𝑗12𝑗=1

[14] Model notes:
1. Customer count tends to increase in steps following prolonged periods of stability. No clear seasonality present.

7. Medford, OR forecasting models:

The forecasting models for the Medford region (Jackson County) are given below for the residential, commercial,
and industrial sectors:

Residential Sector, Customers:
[15] 𝐶𝑡,𝑦,𝑀𝐸𝐷410.𝑟= 𝛼0 + 𝛼1𝑃𝑂𝑃𝑡,𝑦,𝐽𝐴𝐶𝐾+𝐽𝑂𝑆+𝝎𝑺𝑫𝑫𝒕,𝒚+ 𝛾𝑅𝐴𝑀𝑃𝑇𝐽𝑎𝑛 2008 + 𝜔𝑆𝐶𝐷𝐽𝑎𝑛 2008↑ =1 +
𝜔𝑆𝐶𝐷𝑁𝑜𝑣 2004↑ =1 + 𝜔𝑂𝐿𝐷𝐷𝑒𝑐 2004 =1 + 𝜔𝑂𝐿𝐷𝐷𝑒𝑐 2005 =1 + 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2015 =1 + 𝐴𝑅𝐼𝑀𝐴𝜖𝑡,𝑦 (7,1,0)(0,0,0)12

[15] Model notes:
1. SC dummy and ramping time trend control for a change in the time-path of customer growth staring in January 2008.
2. POP is Jackson plus Josephine counties.

Commercial Sector, Customers:
[16] 𝐶𝑡,𝑦,𝑀𝐸𝐷420.𝑐= 𝛼0 +𝛼1𝐶𝑡,𝑦,𝑀𝐸𝐷410.𝑟 + 𝝎𝑺𝑫𝑫𝒕,𝒚+ 𝜔𝑂𝐿𝐷𝐷𝑒𝑐 2004=1 + 𝜔𝑂𝐿𝐷𝑆𝑒𝑝 2005 =1 + 𝜔𝑂𝐿𝐷𝑁𝑜𝑣 2009 =1 +
𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2015 =1 + 𝜔𝑂𝐿𝐷𝐽𝑎𝑛 2016 =1 +𝐴𝑅𝐼𝑀𝐴𝜖𝑡,𝑦 (7,1,0)(1,0,0)12

[16] Model notes:
1. Ct,y,MED410.r are residential customers from residential schedule 410. They are being used as a forecast driver because of the historical positive
correlation between residential and commercial customer growth. However, in the future, POP may become a better driver. Model results
with POP are fairly close to model shown above.

[17] 𝐶𝑦,𝑀𝐸𝐷424.𝑐= 𝐶𝑦−1 + (𝛼0̂ +𝛼1̂∆𝐸𝑀𝑃𝑦−1,4𝐶𝑜𝑢𝑛𝑡𝑦)

[17] Model notes:
1. This model reflects a recommendation by Oregon staff in the 2016 rate case to include employment as an economic driver for schedule 424
commercial customers. The estimated equation in parenthesis reflects the regression estimated of ∆𝐶𝑦,𝑀𝐸𝐷424.𝑐=
𝛼0 +𝛼1∆𝐸𝑀𝑃𝑦−1,4𝐶𝑜𝑢𝑛𝑡𝑦+ 𝜀𝑡 using annual customer data since 2004. Annual data is used to smooth over the sometimes volatile changes
in the monthly customer number. In addition, customer increases and decreases around the long-run trend tend to occur in steps. The
combination of steps and month-to-month volatility creates significant economic problems when trying to model around the monthly data. For
example, even with intervention variables, tests for error normality always indicated non-normal error terms with the use of monthly data.
2. ∆𝐶𝑦,𝑀𝐸𝐷424.𝑐 is the change in customers in year y (customer change between year y and y-1) and ∆𝐸𝑀𝑃𝑦−1,4𝐶𝑜𝑢𝑛𝑡𝑦 is the change in total
non-farm employment in Jackson, Josephine, Klamath, and Douglas counties in year y-1 (employment change between year y-1 and y-2). Staff
originally suggested lagged total employment for Oregon, but the correlation between schedule 424 customers and employment for the three
county area is higher. The forecasted employment values for Jackson+Josephine County are derived from the employment growth forecasts
used in the Jackson+Josephine County population forecast. The forecasts for Douglas and Klamath counties come from IHS. In IRP years, IHS
forecasts for Jackson and Josephine counties will be used for the out years.
3. The annual forecast value for each year, F(∙), is assumed to hold for each month of that year. That is: 𝐹(𝐶𝑦,𝑀𝐸𝐷424.𝑐) = 𝐹(𝐶𝑡,𝑦,𝑀𝐸𝐷424.𝑐).
Given the step-like behavior of the monthly series, this is a reasonable assumption.
4. The forecast and regressions for this schedule can be found in the Excel file folder “OR MED-ROS-KLM Sch 424c Cus” for the June 2017
forecast.

[18] 𝐶𝑡,𝑦,𝑀𝐸𝐷444.𝑐= 1 𝑖𝑓 (𝑇𝐻𝑀/𝐶𝑡,𝑦)𝑀𝐸𝐷,444.𝑐> 0

[18] Model notes:
1. There is typically only one customer served by this schedule. Therefore, the customer forecast is automatically set to one whenever the load
forecast is greater than zero. The June 2017 customer forecast was used and repeated out to monthly until December 2040.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 40 of 829

Industrial Sector, Customers:

[19] 𝐶𝑡,𝑦,𝑀𝐸𝐷420.𝑖= 1
12 ∑𝐶𝑡−𝑗12𝑗=1

[19] Model notes:
1. Data starts November 2006. Excluding outliers in November 2006, November 2009, and February 2011, the customer count fluctuates
between 9 and 16 without any clear trend or seasonality. Changes in the customer count occur in steps between prolonged periods of
stability.

[20] 𝐶𝑡,𝑦,𝑀𝐸𝐷424.𝑖=1
12 ∑𝐶𝑡−𝑗12𝑗=1

[20] Model notes:
1. Data starts January 2009. Excluding a January 2009 outlier, the customer count fluctuates between 1 and 3 without any clear trend or
seasonality. Customer count is most frequently reported as 2; however, starting in March 2018, the customer count fell to one.

8. Roseburg, OR forecasting models:

The forecasting models for the Roseburg region (Douglas County) are given below for the residential, commercial,
and industrial sectors:
Residential Sector, Customers:

[21] 𝐶𝑡,𝑦,𝑅𝑂𝑆410.𝑟= 𝜑0+𝜑1𝑃𝑂𝑃𝑡,𝑦,𝐷𝑂𝑈𝐺𝐿𝐴𝑆+ 𝝎𝑺𝑫𝑫𝒕,𝒚+ 𝜔𝑂𝐿𝐷𝐽𝑢𝑙 2004 =1 + 𝜔𝑂𝐿𝐷𝑁𝑜𝑣 2004 =1 + 𝜔𝑂𝐿𝐷𝐷𝑒𝑐 2004 =1 +
𝜔𝑂𝐿𝐷𝑁𝑜𝑣 2005 =1 + 𝜔𝑂𝐿𝐷𝐷𝑒𝑐 2005 =1 + 𝜔𝑂𝐿𝐷𝑁𝑜𝑣 2006 =1 + 𝜔𝑂𝐿𝐷𝐷𝑒𝑐 2007 =1 + 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2008 =1 + 𝜔𝑂𝐿𝐷𝑁𝑜𝑣 2009 =1 +
𝜔𝑂𝐿𝐷𝑂𝑐𝑡 2012 =1 + 𝜔𝑂𝐿𝐷𝐴𝑝𝑟 2014 =1 + 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2015 =1 + 𝐴𝑅𝐼𝑀𝐴𝜖𝑡,𝑦 (12,1,0)(0,0,0)12

[21] Model notes:
1. POP is population for Douglas County, OR.

Commercial Sector, Customers:

[22] 𝐶𝑡,𝑦,𝑅𝑂𝑆420.𝑐= 𝜑0 + 𝜑1𝑃𝑂𝑃𝑡,𝑦,𝐷𝑂𝑈𝐺𝐿𝐴𝑆+ 𝝎𝑺𝑫𝑫𝒕,𝒚+ 𝜔𝑆𝐶𝐷𝐷𝑒𝑐 2004↑ =1 + 𝜔𝑂𝐿𝐷𝑁𝑜𝑣 2004 =1 + 𝜔𝑂𝐿𝐷𝐽𝑎𝑛 2005 =1 +
𝜔𝑂𝐿𝐷𝐷𝑒𝑐 2005 =1 + 𝜔𝑂𝐿𝐷𝑀𝑎𝑟 2006 =1 + 𝜔𝑂𝐿𝐷𝐽𝑎𝑛 2008 =1 + 𝜔𝑂𝐿𝐷𝑀𝑎𝑟 2008 =1 + 𝜔𝑂𝐿𝐷𝑀𝑎𝑟 2009=1 + 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2015=1 +
𝜔𝑂𝐿𝐷𝑀𝑎𝑦 2016=1 + 𝐴𝑅𝐼𝑀𝐴𝜖𝑡,𝑦 (9,1,0)(1,0,0)12

[22] Model notes:
1. Model does not use schedule 410 customers as driver. This reflects the lack of correlation between residential 410 and commercial 420
customer growth. However, POP was added for the 2018 gas IRP and it is significant at the 10% level
2. The lack of correlation noted in Point 1 could reflect Roseburg’s position between larger cities that offer a range of commercial activities.
Competition from these cities may be inhibiting commercial growth in Roseburg.
3. SC dummy controls for a significant step-up in customers starting in December 2004.

[23] 𝐶𝑡,𝑦,𝑅𝑂𝑆424.𝑐= 𝐶𝑦−1 + (𝜑0̂ +𝜑1̂∆𝐸𝑀𝑃𝑦−1,4𝐶𝑜𝑢𝑛𝑡𝑦)

[23] Model notes:
1. This model reflects a recommendation by Oregon staff in the 2016 rate case to include employment as an economic driver for schedule 424
commercial customers. The estimated equation in parenthesis reflects the regression estimated of ∆𝐶𝑦,𝑅𝑂𝑆424.𝑐= 𝛼0 +
𝛼1∆𝐸𝑀𝑃𝑦−1,4𝐶𝑜𝑢𝑛𝑡𝑦+ 𝜀𝑡 using annual customer data since 2004. Annual data is used to smooth over the sometimes volatile changes in the
monthly customer number. In addition, customer increases and decreases around the long-run trend tend to occur in steps. The combination
of steps and month-to-month volatility creates significant economic problems when trying to model around the monthly data. For example,
even with intervention variables, tests for error normality always indicated non-normal error terms with the use of monthly data.
2. ∆𝐶𝑦,𝑅𝑂𝑆424.𝑐 is the change in customers in year y (customer change between year y and y-1) and ∆𝐸𝑀𝑃𝑦−1,4𝐶𝑜𝑢𝑛𝑡𝑦 is the change in total non-
farm employment in Jackson, Josephine, Klamath, and Douglas counties in year y-1 (employment change between year y-1 and y-2). Staff
originally suggested lagged total employment for Oregon, but the correlation between schedule 424 customers and employment for the three Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 41 of 829
county area is higher. The forecasted employment values for Jackson+Josephine County are derived from the employment growth forecasts
used in the Jackson+Josephine County population forecast. The forecasts for Douglas and Klamath counties come from IHS. In IRP years, IHS
forecasts for Jackson and Josephine counties will be used for the out years.
3. The annual forecast value for each year, F(∙), is assumed to hold for each month of that year. That is: 𝐹(𝐶𝑦,𝑅𝑂𝑆424.𝑐) = 𝐹(𝐶𝑡,𝑦,𝑅𝑂𝑆424.𝑐).
Given the step-like behavior of the monthly series, this is a reasonable assumption.
4. The forecast and regressions for this schedule can be found in the Excel file folder “OR MED-ROS-KLM Sch 424c Cus” for the June 2017
forecast.

Industrial Sector, Customers:

[24] 𝐶𝑡,𝑦,𝑅𝑂𝑆420.𝑖= 1
12 ∑𝐶𝑡−𝑗12𝑗=1

[24] Model notes:
1. Data starts September 2009. Excluding a February 2015 outlier, the customer count fluctuates between 1 and 2 without any clear trend or
seasonality.
2. Due to the Compass software conversion, February 2015 is excluded from the historical data. The conversion resulted in a double counting
of customers in February 2015. Therefore, including this month leads to a significant over-forecast of customers.

[25] 𝐶𝑡,𝑦,𝑅𝑂𝑆424.𝑖= 1
12 ∑𝐶𝑡−𝑗12𝑗=1

[25] Model notes:
1. Schedule appears to have died. No customers are currently being reported.

9. Klamath Falls, OR forecasting models:

The forecasting models for the Klamath Falls region (Klamath County) are given below for the residential,
commercial, and industrial sectors:
Residential Sector, Customers:

[26] 𝐶𝑡,𝑦,𝐾𝐿𝑀410.𝑟= 𝛽0 + 𝛽1𝑃𝑂𝑃𝑡,𝑦,𝐾𝐿𝐴𝑀𝐴𝑇𝐻+ 𝝎𝑺𝑫𝑫𝒕,𝒚 +𝜔𝑂𝐿𝐷𝑁𝑜𝑣 2004=1+ 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2015 =1+ 𝜔𝑂𝐿𝐷𝐴𝑝𝑟 2015 =1 +
𝐴𝑅𝐼𝑀𝐴𝜖𝑡,𝑦 (7,1,0)(0,0,0)12

[26] Model notes:
1. POP is for Klamath County, OR.

Commercial Sector, Customers:

[27] 𝐶𝑡,𝑦,𝐾𝐿𝑀420.𝑐= 𝛽0 + 𝛽1𝐶𝑡,𝑦,𝐾𝐿𝑀410.𝑟+ 𝝎𝑺𝑫𝑫𝒕,𝒚 + 𝜔𝑂𝐿𝐷𝑂𝑐𝑡 2006=1 + 𝐴𝑅𝐼𝑀𝐴𝜖𝑡,𝑦 (11,1,0)(2,0,0)12

[27] Model notes:
1. Ct,y,KLM410.r are residential customers from residential schedule 410. They are being used as a forecast driver because of the historical positive
correlation between residential and commercial customer growth. See Tables 5.1 and 5.2.

[28] 𝐶𝑡,𝑦,𝐾𝐿𝑀424.𝑐= 𝐶𝑦−1 + (𝛽0̂+𝛽1̂∆𝐸𝑀𝑃𝑦−1,4𝐶𝑜𝑢𝑛𝑡𝑦)

[28] Model notes:
1. This model reflects a recommendation by Oregon staff in the 2016 rate case to include employment as an economic driver for schedule 424
commercial customers. The estimated equation in parenthesis reflects the regression estimated of ∆𝐶𝑦,𝐾𝐿𝑀424.𝑐=
𝛼0 +𝛼1∆𝐸𝑀𝑃𝑦−1,4𝐶𝑜𝑢𝑛𝑡𝑦+ 𝜀𝑡 using annual customer data since 2004. Annual data is used to smooth over the sometimes volatile changes
in the monthly customer number. In addition, customer increases and decreases around the long-run trend tend to occur in steps. The
combination of steps and month-to-month volatility creates significant economic problems when trying to model around the monthly data. For
example, even with intervention variables, tests for error normality always indicated non-normal error terms with the use of monthly data.
2. ∆𝐶𝑦,𝐾𝐿𝑀424.𝑐 is the change in customers in year y (customer change between year y and y-1) and ∆𝐸𝑀𝑃𝑦−1,4𝐶𝑜𝑢𝑛𝑡𝑦 is the change in total
non-farm employment in Jackson, Josephine, Klamath, and Douglas counties in year y-1 (employment change between year y-1 and y-2). Staff
originally suggested lagged total employment for Oregon, but the correlation between schedule 424 customers and employment for the three
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 42 of 829
county area is higher. The forecasted employment values for Jackson+Josephine County are derived from the employment growth forecasts
used in the Jackson+Josephine County population forecast. The forecasts for Douglas and Klamath counties come from IHS. In IRP years, IHS
forecasts for Jackson and Josephine counties will be used for the out years.
3. The annual forecast value for each year, F(∙), is assumed to hold for each month of that year. That is: 𝐹(𝐶𝑦,𝐾𝐿𝑀424.𝑐) = 𝐹(𝐶𝑡,𝑦,𝐾𝐿𝑀424.𝑐).
Given the step-like behavior of the monthly series, this is a reasonable assumption.
4. The forecast and regressions for this schedule can be found in the Excel file folder “OR MED-ROS-KLM Sch 424c Cus” for the June 2017
forecast.

Industrial Sector, Customers:

[29] 𝐶𝑡,𝑦,𝐾𝐿𝑀420.𝑖= 1
12 ∑𝐶𝑡−𝑗12𝑗=1

[29] Model notes:
1. Data starts December 2006. The customer count fluctuates between 4 and 9 without any clear trend or seasonality.

[30] 𝐶𝑡,𝑦,𝐾𝐿𝑀424.𝑖= 1
12∑𝐶𝑡−𝑗12𝑗=1

[30] Model notes:
1. Data starts April 2009. The customer count fluctuates between 1 and 4 without any clear trend or seasonality.

10. La Grande, OR forecasting models:

The forecasting models for the La Grande region (Union County) are given below for the residential, commercial,
and industrial sectors:
Residential Sector, Customers:

[31] 𝐶𝑡,𝑦,𝐿𝑎𝐺410.𝑟= 𝜃0 + 𝜃1𝑃𝑂𝑃𝑡,𝑦,𝑈𝑁𝐼𝑂𝑁+ 𝝎𝑺𝑫𝑫𝒕,𝒚+ 𝜔𝑂𝐿𝐷𝑂𝑐𝑡 2004=1 + 𝜔𝑂𝐿𝐷𝐽𝑢𝑙 2006=1 + 𝜔𝑂𝐿𝐷𝐷𝑒𝑐 2009=1+ 𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2015=1 +
𝐴𝑅𝐼𝑀𝐴𝜖𝑡,𝑦 (9,1,0)(1,0,0)12

[31] Model notes:
1. POP is population for Union County, OR.

Commercial Sector, Customers:

[32] 𝐶𝑡,𝑦,𝐿𝑎𝐺420.𝑐= 𝜃0 + 𝝎𝑺𝑫𝑫𝒕,𝒚+ 𝜔𝑂𝐿𝐷𝐽𝑢𝑙 2005 =1 + 𝜔𝑂𝐿𝐷𝐽𝑎𝑛 2007 =1 + 𝜔𝑂𝐿𝐷𝐷𝑒𝑐 2008 =1 + 𝜔𝑂𝐿𝐷𝑀𝑎𝑟 2011 =1 +
𝜔𝑂𝐿𝐷𝑀𝑎𝑦 2011 =1 + 𝜔𝑂𝐿𝐷𝐽𝑎𝑛 2016 =1 + 𝐴𝑅𝐼𝑀𝐴𝜖𝑡,𝑦 (12,1,0)(0,0,0)12

[32] Model notes:
1. Ct,y,LaG410.r, residential customers from residential schedule 410, are no longer used as a forecast driver. The estimated coefficient on Ct,y,LaG410.r
was no longer statistically significant and its sign flips between positive and negative, depending on the form of the model. POP for union
county was also tried as a driver, but had the same issues as Ct,y,LaG410.r.

[33] 𝐶𝑡,𝑦,𝐿𝑎𝐺424.𝑐= 1
12∑𝐶𝑡−𝑗12𝑗=1

[33] Model notes:
1. Data starts January 2007. The customer count fluctuates between 2 and 4 without any clear trend or seasonality. Changes in the customer
count appear as steps after prolonged periods of stability.

[34] 𝐶𝑡,𝑦,𝐿𝑎𝐺444.𝑐= 1
𝑁∑(𝐶𝑡,𝑦−𝑗)𝑁𝑗=1 𝑖𝑓 (𝑇𝐻𝑀/𝐶𝑡,𝑦)𝐿𝑎𝑔,444.𝑐≥ 0

[34] Model notes:
1. Data starts September 2011. The customer forecast is a derivative of the schedule’s load forecast. The June 2017 customer forecast was
used and repeated out to monthly until December 2040.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 43 of 829

Industrial Sector, Customers:

[35] 𝐶𝑡,𝑦,𝐿𝑎𝐺444.𝑖= 𝜃0 + 𝝎𝑺𝑫𝑫𝒕,𝒚+ 𝜔𝑂𝐿𝐷𝐴𝑢𝑔 2007=1 + 𝜔𝑂𝐿𝐷𝑆𝑒𝑝𝑡 2008 =1 + 𝜔𝑂𝐿𝐷𝑁𝑜𝑣 2009 =1 + 𝜔𝑂𝐿𝐷𝐽𝑎𝑛 2010 =1 +
+ 𝜔𝑂𝐿𝐷𝑁𝑜𝑣 2010=1 + 𝜔𝑂𝐿𝐷𝐴𝑢𝑔 2011 =1 + 𝜔𝑂𝐿𝐷𝐴𝑢𝑔 2012 =1 + 𝜔𝑂𝐿𝐷𝑁𝑜𝑣 2012 =1 + 𝜔𝑂𝐿𝐷𝐷𝑒𝑐 2012=1 + 𝜔𝑂𝐿𝐷𝐽𝑎𝑛 2013 =1 +
𝜔𝑂𝐿𝐷𝐹𝑒𝑏 2013 =1 + 𝜔𝑂𝐿𝐷𝐽𝑎𝑛 2014 =1 + 𝜔𝑂𝐿𝐷𝑂𝑐𝑡 2015 =1 + 𝐴𝑅𝐼𝑀𝐴𝜖𝑡,𝑦 (10,0,0)(0,0,0)12

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 44 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
WASHINGTON

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Nov-17 147,093 14,591 130 148,027 14,683 130 146,161 14,498 129
Dec-17 147,522 14,666 130 148,506 14,764 130 146,539 14,568 129
Jan-18 148,039 14,678 130 149,076 14,781 130 147,006 14,576 129
Feb-18 148,149 14,716 130 149,234 14,824 131 147,067 14,609 129
Mar-18 148,048 14,718 130 149,180 14,831 131 146,920 14,606 128
Apr-18 148,092 14,700 130 149,272 14,817 131 146,916 14,583 128
May-18 148,164 14,676 130 149,393 14,798 131 146,940 14,555 128
Jun-18 148,176 14,696 129 149,453 14,823 132 146,905 14,570 128
Jul-18 148,402 14,665 129 149,726 14,796 132 147,085 14,535 127
Aug-18 148,536 14,674 129 149,906 14,809 132 147,174 14,540 127
Sep-18 148,725 14,674 129 150,141 14,814 132 147,317 14,535 127
Oct-18 149,191 14,687 129 150,656 14,831 133 147,734 14,544 127
Nov-18 149,864 14,719 129 151,380 14,868 133 148,356 14,571 126
Dec-18 150,346 14,791 129 151,913 14,945 133 148,789 14,638 126
Jan-19 150,632 14,800 129 152,247 14,959 133 149,028 14,643 126
Feb-19 150,590 14,838 129 152,250 15,002 134 148,942 14,676 126
Mar-19 150,673 14,840 128 152,379 15,008 134 148,980 14,673 125
Apr-19 150,668 14,821 128 152,420 14,993 134 148,930 14,650 125
May-19 150,707 14,797 128 152,505 14,974 134 148,925 14,622 125
Jun-19 150,634 14,816 128 152,476 14,997 135 148,808 14,636 125
Jul-19 150,721 14,785 128 152,609 14,970 135 148,848 14,601 124
Aug-19 150,854 14,794 128 152,790 14,984 135 148,935 14,606 124
Sep-19 151,160 14,795 128 153,146 14,990 135 149,192 14,602 124
Oct-19 151,606 14,808 128 153,645 15,007 136 149,587 14,611 124
Nov-19 152,244 14,840 128 154,338 15,044 136 150,171 14,638 123
Dec-19 152,667 14,912 128 154,814 15,122 136 150,543 14,705 123
Jan-20 152,907 14,922 128 155,104 15,136 136 150,734 14,710 123
Feb-20 152,959 14,960 127 155,203 15,180 137 150,740 14,743 123
Mar-20 153,025 14,962 127 155,316 15,186 137 150,758 14,741 122
Apr-20 153,008 14,943 127 155,346 15,172 137 150,696 14,717 122
May-20 152,996 14,920 127 155,381 15,153 137 150,639 14,690 122
Jun-20 152,850 14,939 127 155,279 15,177 138 150,450 14,705 122
Jul-20 152,982 14,909 127 155,461 15,151 138 150,534 14,671 121
Aug-20 153,137 14,918 127 155,666 15,164 138 150,640 14,675 121
Sep-20 153,446 14,918 127 156,028 15,169 138 150,898 14,670 121
Oct-20 153,862 14,931 127 156,499 15,187 139 151,261 14,679 121
Nov-20 154,464 14,964 127 157,158 15,225 139 151,806 14,707 120
Dec-20 154,895 15,036 127 157,644 15,303 139 152,183 14,773 120
Jan-21 155,161 15,046 126 157,963 15,318 139 152,398 14,778 120
Feb-21 155,220 15,085 126 158,072 15,362 140 152,409 14,812 120
Washington -
Expected Growth
Washington -
High Growth
Washington -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 45 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
WASHINGTON

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Mar-21 155,265 15,087 126 158,166 15,369 140 152,407 14,809 119
Apr-21 155,218 15,068 126 158,166 15,354 140 152,315 14,786 119
May-21 155,185 15,045 126 158,181 15,336 140 152,236 14,759 119
Jun-21 155,063 15,065 126 158,105 15,361 141 152,070 14,774 119
Jul-21 155,199 15,032 126 158,288 15,331 141 152,160 14,738 118
Aug-21 155,339 15,042 126 158,475 15,346 141 152,253 14,743 118
Sep-21 155,623 15,041 126 158,810 15,349 141 152,488 14,738 118
Oct-21 156,011 15,053 126 159,252 15,366 142 152,825 14,746 118
Nov-21 156,614 15,086 126 159,913 15,404 142 153,372 14,774 117
Dec-21 157,048 15,158 126 160,402 15,482 142 153,753 14,840 117
Jan-22 157,308 15,167 125 160,713 15,495 142 153,964 14,845 117
Feb-22 157,346 15,205 125 160,798 15,539 143 153,957 14,878 117
Mar-22 157,363 15,207 125 160,861 15,545 143 153,930 14,875 116
Apr-22 157,307 15,188 125 160,848 15,530 143 153,830 14,853 116
May-22 157,274 15,163 125 160,861 15,509 143 153,754 14,824 116
Jun-22 157,150 15,182 125 160,780 15,533 144 153,590 14,838 116
Jul-22 157,280 15,150 125 160,958 15,504 144 153,673 14,803 115
Aug-22 157,408 15,160 125 161,135 15,519 144 153,754 14,808 115
Sep-22 157,687 15,160 125 161,467 15,523 144 153,983 14,804 115
Oct-22 158,080 15,172 125 161,915 15,540 145 154,323 14,812 115
Nov-22 158,691 15,204 125 162,587 15,577 145 154,876 14,839 114
Dec-22 159,125 15,275 125 163,077 15,655 145 155,254 14,904 114
Jan-23 159,376 15,286 124 163,381 15,670 145 155,455 14,910 114
Feb-23 159,406 15,324 124 163,458 15,714 146 155,440 14,943 114
Mar-23 159,425 15,326 124 163,524 15,720 146 155,414 14,941 113
Apr-23 159,373 15,306 124 163,517 15,704 146 155,320 14,917 113
May-23 159,342 15,282 124 163,532 15,684 146 155,245 14,889 113
Jun-23 159,215 15,300 124 163,448 15,707 147 155,078 14,903 113
Jul-23 159,334 15,269 124 163,615 15,679 147 155,151 14,868 112
Aug-23 159,458 15,277 124 163,788 15,692 147 155,229 14,872 112
Sep-23 159,738 15,278 124 164,120 15,697 147 155,458 14,869 112
Oct-23 160,131 15,289 124 164,569 15,713 148 155,798 14,875 112
Nov-23 160,737 15,322 124 165,237 15,751 148 156,345 14,903 111
Dec-23 161,160 15,393 124 165,717 15,828 148 156,713 14,968 111
Jan-24 161,406 15,403 124 166,016 15,843 148 156,909 14,974 111
Feb-24 161,433 15,441 123 166,089 15,886 149 156,892 15,007 111
Mar-24 161,452 15,442 123 166,154 15,892 149 156,868 15,004 110
Apr-24 161,396 15,422 123 166,142 15,876 149 156,770 14,980 110
May-24 161,360 15,397 123 166,150 15,854 149 156,691 14,952 110
Jun-24 161,226 15,416 123 166,058 15,878 150 156,518 14,966 110
Washington -
Expected Growth
Washington -
High Growth
Washington -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 46 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
WASHINGTON

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Jul-24 161,347 15,385 123 166,228 15,851 150 156,593 14,932 109
Aug-24 161,474 15,393 123 166,405 15,863 150 156,673 14,935 109
Sep-24 161,755 15,393 123 166,740 15,868 150 156,903 14,931 109
Oct-24 162,148 15,405 123 167,191 15,884 151 157,240 14,939 109
Nov-24 162,752 15,438 123 167,861 15,923 151 157,783 14,967 108
Dec-24 163,176 15,509 123 168,344 16,000 151 158,150 15,031 108
Jan-25 163,424 15,519 123 168,645 16,015 151 158,346 15,037 108
Feb-25 163,454 15,556 122 168,723 16,058 152 158,332 15,069 108
Mar-25 163,473 15,559 122 168,789 16,065 152 158,307 15,067 107
Apr-25 163,417 15,539 122 168,778 16,049 152 158,209 15,044 107
May-25 163,380 15,514 122 168,786 16,027 152 158,130 15,016 107
Jun-25 163,247 15,533 122 168,695 16,052 153 157,957 15,030 107
Jul-25 163,365 15,501 122 168,862 16,023 153 158,030 14,995 106
Aug-25 163,488 15,509 122 169,033 16,035 153 158,107 14,999 106
Sep-25 163,764 15,509 122 169,363 16,039 153 158,333 14,995 106
Oct-25 164,152 15,521 122 169,808 16,056 154 158,665 15,002 106
Nov-25 164,752 15,553 122 170,474 16,093 154 159,203 15,029 105
Dec-25 165,172 15,624 122 170,954 16,171 154 159,567 15,094 105
Jan-26 165,416 15,634 122 171,252 16,186 154 159,761 15,100 105
Feb-26 165,441 15,670 122 171,323 16,227 155 159,743 15,130 105
Mar-26 165,455 15,671 122 171,382 16,233 155 159,714 15,127 104
Apr-26 165,395 15,652 121 171,366 16,217 155 159,614 15,105 104
May-26 165,353 15,627 121 171,367 16,195 155 159,532 15,077 104
Jun-26 165,218 15,646 121 171,271 16,219 156 159,358 15,091 104
Jul-26 165,334 15,614 121 171,436 16,190 156 159,429 15,057 103
Aug-26 165,454 15,622 121 171,604 16,203 156 159,504 15,060 103
Sep-26 165,727 15,622 121 171,932 16,207 156 159,726 15,056 103
Oct-26 166,112 15,633 121 172,375 16,223 157 160,056 15,063 103
Nov-26 166,710 15,665 121 173,040 16,260 157 160,591 15,090 102
Dec-26 167,129 15,736 121 173,520 16,338 157 160,954 15,155 102
Jan-27 167,370 15,744 121 173,815 16,350 157 161,145 15,158 102
Feb-27 167,393 15,782 121 173,882 16,394 158 161,124 15,191 102
Mar-27 167,405 15,783 121 173,940 16,399 158 161,095 15,188 101
Apr-27 167,343 15,763 121 173,920 16,383 158 160,994 15,165 101
May-27 167,300 15,738 120 173,920 16,361 158 160,911 15,137 101
Jun-27 167,161 15,756 120 173,820 16,384 159 160,736 15,151 101
Jul-27 167,273 15,724 120 173,980 16,355 159 160,804 15,116 100
Aug-27 167,391 15,732 120 174,146 16,367 159 160,878 15,120 100
Sep-27 167,661 15,732 120 174,470 16,371 159 161,097 15,116 100
Oct-27 168,043 15,743 120 174,911 16,387 160 161,424 15,123 100
Washington -
Expected Growth
Washington -
High Growth
Washington -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 47 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
WASHINGTON

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Nov-27 168,639 15,773 120 175,574 16,422 160 161,955 15,148 99
Dec-27 169,055 15,845 120 176,051 16,501 160 162,315 15,213 99
Jan-28 169,293 15,853 120 176,343 16,513 160 162,503 15,217 99
Feb-28 169,312 15,890 120 176,406 16,556 161 162,481 15,249 99
Mar-28 169,321 15,891 120 176,460 16,561 161 162,449 15,246 98
Apr-28 169,256 15,871 120 176,436 16,544 161 162,347 15,223 98
May-28 169,210 15,846 120 176,432 16,522 161 162,262 15,195 98
Jun-28 169,069 15,864 120 176,329 16,545 162 162,087 15,209 98
Jul-28 169,178 15,832 119 176,484 16,516 162 162,152 15,175 97
Aug-28 169,292 15,839 119 176,645 16,527 162 162,222 15,178 97
Sep-28 169,560 15,838 119 176,967 16,530 162 162,440 15,173 97
Oct-28 169,939 15,848 119 177,405 16,544 163 162,764 15,179 97
Nov-28 170,531 15,880 119 178,066 16,582 163 163,292 15,206 96
Dec-28 170,943 15,951 119 178,539 16,660 163 163,648 15,270 96
Jan-29 171,178 15,959 119 178,827 16,672 163 163,833 15,274 96
Feb-29 171,194 15,996 119 178,887 16,715 164 163,810 15,306 96
Mar-29 171,201 15,996 119 178,936 16,719 164 163,776 15,302 95
Apr-29 171,132 15,976 119 178,907 16,702 164 163,671 15,280 95
May-29 171,083 15,951 119 178,898 16,680 164 163,585 15,252 95
Jun-29 170,938 15,969 119 178,790 16,703 165 163,407 15,266 95
Jul-29 171,044 15,935 119 178,942 16,671 165 163,471 15,230 94
Aug-29 171,156 15,943 118 179,101 16,683 165 163,540 15,234 94
Sep-29 171,420 15,941 118 179,419 16,685 165 163,754 15,228 94
Oct-29 171,797 15,952 118 179,855 16,700 166 164,077 15,235 94
Nov-29 172,386 15,983 118 180,513 16,737 166 164,601 15,261 93
Dec-29 172,796 16,053 118 180,984 16,814 166 164,954 15,325 93
Jan-30 173,028 16,062 118 181,269 16,827 166 165,137 15,330 93
Feb-30 173,042 16,099 118 181,325 16,870 167 165,112 15,361 93
Mar-30 173,044 16,099 118 181,369 16,874 167 165,076 15,358 92
Apr-30 172,973 16,078 118 181,337 16,856 167 164,970 15,334 92
May-30 172,921 16,052 118 181,325 16,832 167 164,882 15,306 92
Jun-30 172,773 16,069 118 181,211 16,854 168 164,703 15,319 92
Jul-30 172,875 16,036 118 181,359 16,823 168 164,764 15,284 91
Aug-30 172,984 16,043 118 181,512 16,834 168 164,830 15,287 91
Sep-30 173,245 16,042 118 181,826 16,837 168 165,043 15,283 91
Oct-30 173,617 16,053 117 182,257 16,852 169 165,361 15,290 91
Nov-30 174,202 16,083 117 182,912 16,887 169 165,881 15,315 90
Dec-30 174,608 16,153 117 183,379 16,965 169 166,231 15,378 90
Jan-31 174,836 16,161 117 183,659 16,977 169 166,411 15,382 90
Feb-31 174,846 16,198 117 183,710 17,019 170 166,384 15,414 90
Washington -
Expected Growth
Washington -
High Growth
Washington -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 48 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
WASHINGTON

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Mar-31 174,845 16,198 117 183,750 17,023 170 166,346 15,411 89
Apr-31 174,770 16,177 117 183,711 17,005 170 166,237 15,387 89
May-31 174,714 16,150 117 183,693 16,980 170 166,147 15,358 89
Jun-31 174,563 16,167 117 183,575 17,002 171 165,967 15,371 89
Jul-31 174,663 16,134 117 183,719 16,971 171 166,026 15,336 88
Aug-31 174,768 16,141 117 183,870 16,982 171 166,090 15,340 88
Sep-31 175,027 16,140 117 184,182 16,984 171 166,301 15,335 88
Oct-31 175,398 16,150 117 184,612 16,999 172 166,617 15,342 88
Nov-31 175,980 16,180 117 185,265 17,034 172 167,134 15,367 87
Dec-31 176,384 16,250 116 185,730 17,111 172 167,482 15,430 87
Jan-32 176,611 16,258 116 186,008 17,123 172 167,661 15,434 87
Feb-32 176,619 16,294 116 186,057 17,165 173 167,632 15,465 87
Mar-32 176,615 16,294 116 186,093 17,169 173 167,592 15,462 86
Apr-32 176,538 16,273 116 186,052 17,150 173 167,483 15,438 86
May-32 176,480 16,246 116 186,031 17,125 173 167,392 15,410 86
Jun-32 176,326 16,263 116 185,909 17,147 174 167,210 15,422 86
Jul-32 176,423 16,230 116 186,049 17,116 174 167,268 15,388 85
Aug-32 176,526 16,236 116 186,197 17,126 174 167,331 15,390 85
Sep-32 176,782 16,235 116 186,504 17,128 174 167,538 15,386 85
Oct-32 177,150 16,244 116 186,931 17,141 175 167,852 15,392 85
Nov-32 177,729 16,275 116 187,581 17,177 175 168,366 15,418 84
Dec-32 178,130 16,344 116 188,044 17,254 175 168,711 15,480 84
Jan-33 178,352 16,352 116 188,317 17,266 175 168,886 15,484 84
Feb-33 178,357 16,387 115 188,361 17,306 176 168,856 15,514 84
Mar-33 178,351 16,388 115 188,394 17,311 176 168,815 15,512 83
Apr-33 178,270 16,365 115 188,348 17,290 176 168,704 15,487 83
May-33 178,210 16,339 115 188,322 17,266 176 168,611 15,459 83
Jun-33 178,053 16,356 115 188,195 17,288 177 168,428 15,472 83
Jul-33 178,148 16,322 115 188,334 17,255 177 168,484 15,437 82
Aug-33 178,247 16,328 115 188,476 17,265 177 168,544 15,439 82
Sep-33 178,500 16,327 115 188,781 17,268 177 168,750 15,435 82
Oct-33 178,865 16,336 115 189,205 17,281 178 169,061 15,441 82
Nov-33 179,442 16,366 115 189,854 17,316 178 169,572 15,466 81
Dec-33 179,839 16,435 115 190,312 17,392 178 169,914 15,528 81
Jan-34 180,059 16,442 115 190,583 17,403 178 170,088 15,532 81
Feb-34 180,062 16,478 115 190,623 17,445 179 170,056 15,562 81
Mar-34 180,053 16,477 115 190,652 17,447 179 170,013 15,558 80
Apr-34 179,970 16,455 114 190,602 17,427 179 169,901 15,534 80
May-34 179,906 16,429 114 190,573 17,403 179 169,807 15,507 80
Jun-34 179,746 16,446 114 190,441 17,425 180 169,622 15,520 80
Jul-34 179,838 16,412 114 190,576 17,392 180 169,676 15,485 79
Washington -
Expected Growth
Washington -
High Growth
Washington -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 49 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
WASHINGTON

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Aug-34 179,936 16,418 114 190,717 17,402 180 169,735 15,487 79
Sep-34 180,186 16,416 114 191,019 17,403 180 169,938 15,482 79
Oct-34 180,549 16,425 114 191,440 17,416 181 170,247 15,488 79
Nov-34 181,124 16,454 114 192,087 17,450 181 170,756 15,512 78
Dec-34 181,519 16,524 114 192,543 17,528 181 171,095 15,575 78
Jan-35 181,737 16,531 114 192,812 17,539 181 171,268 15,579 78
Feb-35 181,737 16,566 114 192,849 17,579 182 171,235 15,609 78
Mar-35 181,725 16,565 114 192,874 17,581 182 171,190 15,605 77
Apr-35 181,640 16,543 114 192,821 17,561 182 171,077 15,581 77
May-35 181,573 16,517 114 192,787 17,537 182 170,981 15,554 77
Jun-35 181,413 16,533 114 192,654 17,558 183 170,796 15,566 77
Jul-35 181,504 16,499 113 192,787 17,525 183 170,849 15,531 76
Aug-35 181,600 16,505 113 192,926 17,535 183 170,907 15,533 76
Sep-35 181,849 16,502 113 193,228 17,535 183 171,109 15,528 76
Oct-35 182,211 16,512 113 193,649 17,549 184 171,417 15,534 76
Nov-35 182,784 16,542 113 194,295 17,584 184 171,924 15,559 75
Dec-35 183,178 16,611 113 194,751 17,661 184 172,261 15,621 75
Jan-36 183,395 16,618 113 195,019 17,671 184 172,433 15,625 75
Feb-36 183,394 16,653 113 195,055 17,712 185 172,399 15,655 75
Mar-36 183,382 16,652 113 195,079 17,714 185 172,354 15,651 74
Apr-36 183,296 16,630 113 195,024 17,694 185 172,241 15,627 74
May-36 183,228 16,604 113 194,989 17,670 185 172,144 15,600 74
Jun-36 183,065 16,620 113 194,853 17,690 186 171,958 15,612 74
Jul-36 183,155 16,585 113 194,985 17,656 186 172,011 15,576 73
Aug-36 183,249 16,591 113 195,122 17,666 186 172,067 15,579 73
Sep-36 183,497 16,588 112 195,422 17,666 186 172,268 15,573 73
Oct-36 183,857 16,598 112 195,842 17,680 187 172,574 15,579 73
Nov-36 184,430 16,627 112 196,488 17,714 187 173,079 15,604 72
Dec-36 184,822 16,697 112 196,942 17,792 187 173,415 15,667 72
Jan-37 185,038 16,703 112 197,209 17,802 187 173,585 15,669 72
Feb-37 185,035 16,739 112 197,243 17,844 188 173,550 15,700 72
Mar-37 185,021 16,737 112 197,265 17,845 188 173,505 15,695 71
Apr-37 184,932 16,715 112 197,206 17,825 188 173,389 15,672 71
May-37 184,863 16,688 112 197,170 17,799 188 173,292 15,644 71
Jun-37 184,699 16,704 112 197,031 17,819 189 173,106 15,656 71
Jul-37 184,790 16,670 112 197,164 17,786 189 173,159 15,621 70
Aug-37 184,883 16,676 112 197,299 17,796 189 173,214 15,624 70
Sep-37 185,129 16,673 112 197,598 17,796 189 173,413 15,618 70
Oct-37 185,487 16,682 112 198,016 17,809 190 173,717 15,624 70
Nov-37 186,058 16,712 111 198,662 17,844 190 174,220 15,649 69
Dec-37 186,449 16,780 111 199,115 17,920 190 174,555 15,710 69
Washington -
Expected Growth
Washington -
High Growth
Washington -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 50 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
IDAHO

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Nov-17 73,590 8,874 94 74,177 8,945 94 73,005 8,803 94
Dec-17 73,890 8,909 94 74,511 8,984 94 73,272 8,834 94
Jan-18 74,021 8,917 94 74,674 8,996 94 73,370 8,839 93
Feb-18 74,021 8,924 95 74,706 9,007 95 73,340 8,842 93
Mar-18 74,022 8,915 95 74,738 9,001 95 73,310 8,829 93
Apr-18 73,986 8,914 95 74,733 9,004 95 73,243 8,824 93
May-18 73,968 8,913 95 74,746 9,007 95 73,194 8,820 93
Jun-18 73,964 8,920 95 74,774 9,018 95 73,160 8,823 93
Jul-18 74,060 8,927 95 74,901 9,028 95 73,223 8,826 92
Aug-18 74,149 8,933 95 75,023 9,038 96 73,280 8,828 92
Sep-18 74,350 8,932 95 75,258 9,041 96 73,448 8,824 92
Oct-18 74,521 8,937 96 75,463 9,050 96 73,586 8,825 92
Nov-18 74,777 8,938 96 75,754 9,055 96 73,808 8,822 92
Dec-18 75,100 8,967 96 76,113 9,088 96 74,096 8,847 92
Jan-19 75,236 8,978 96 76,283 9,103 96 74,199 8,854 91
Feb-19 75,235 8,979 96 76,314 9,108 97 74,167 8,851 91
Mar-19 75,237 8,967 96 76,348 9,099 97 74,138 8,836 91
Apr-19 75,203 8,965 96 76,345 9,101 97 74,073 8,830 91
May-19 75,186 8,968 96 76,360 9,108 97 74,025 8,829 91
Jun-19 75,185 8,971 96 76,390 9,115 97 73,992 8,829 91
Jul-19 75,283 8,985 96 76,522 9,133 97 74,057 8,839 90
Aug-19 75,375 8,992 96 76,648 9,144 98 74,116 8,842 90
Sep-19 75,579 8,992 96 76,889 9,148 98 74,285 8,838 90
Oct-19 75,753 8,993 96 77,098 9,153 98 74,424 8,835 90
Nov-19 76,012 8,995 96 77,395 9,159 98 74,647 8,833 90
Dec-19 76,338 9,023 96 77,760 9,191 98 74,935 8,857 90
Jan-20 76,477 9,033 96 77,935 9,205 98 75,040 8,863 89
Feb-20 76,479 9,035 96 77,970 9,211 99 75,010 8,861 89
Mar-20 76,484 9,025 96 78,008 9,205 99 74,983 8,848 89
Apr-20 76,453 9,022 96 78,010 9,206 99 74,921 8,841 89
May-20 76,439 9,027 96 78,029 9,215 99 74,875 8,842 89
Jun-20 76,442 9,029 96 78,064 9,221 99 74,845 8,840 89
Jul-20 76,545 9,043 96 78,203 9,239 99 74,913 8,850 88
Aug-20 76,642 9,049 96 78,337 9,249 100 74,975 8,852 88
Sep-20 76,852 9,050 96 78,586 9,254 100 75,148 8,849 88
Oct-20 77,030 9,050 96 78,803 9,258 100 75,289 8,845 88
Nov-20 77,295 9,053 96 79,109 9,265 100 75,514 8,844 88
Dec-20 77,627 9,081 96 79,483 9,298 100 75,805 8,868 88
Jan-21 77,771 9,092 96 79,666 9,314 100 75,913 8,875 87
Feb-21 77,778 9,094 96 79,708 9,320 101 75,886 8,873 87
Idaho -
Expected Growth
Idaho -
High Growth
Idaho -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 51 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
IDAHO

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Mar-21 77,789 9,083 96 79,754 9,312 101 75,864 8,858 87
Apr-21 77,763 9,080 96 79,763 9,313 101 75,805 8,851 87
May-21 77,755 9,086 96 79,790 9,324 101 75,764 8,853 87
Jun-21 77,762 9,087 96 79,831 9,329 101 75,736 8,850 87
Jul-21 77,866 9,102 96 79,972 9,348 101 75,805 8,861 86
Aug-21 77,964 9,108 96 80,108 9,358 102 75,867 8,863 86
Sep-21 78,175 9,108 96 80,360 9,363 102 76,039 8,859 86
Oct-21 78,354 9,109 96 80,579 9,368 102 76,180 8,856 86
Nov-21 78,620 9,113 96 80,888 9,376 102 76,405 8,856 86
Dec-21 78,953 9,139 96 81,266 9,407 102 76,696 8,878 86
Jan-22 79,098 9,152 96 81,450 9,424 102 76,803 8,886 85
Feb-22 79,106 9,153 96 81,494 9,429 103 76,777 8,884 85
Mar-22 79,117 9,143 96 81,541 9,423 103 76,755 8,870 85
Apr-22 79,092 9,140 96 81,551 9,424 103 76,697 8,863 85
May-22 79,085 9,146 96 81,579 9,434 103 76,657 8,865 85
Jun-22 79,093 9,146 96 81,622 9,438 103 76,630 8,861 85
Jul-22 79,199 9,162 96 81,766 9,459 103 76,700 8,873 84
Aug-22 79,298 9,167 96 81,904 9,468 104 76,762 8,874 84
Sep-22 79,510 9,168 96 82,159 9,473 104 76,934 8,871 84
Oct-22 79,691 9,169 96 82,381 9,479 104 77,076 8,868 84
Nov-22 79,958 9,171 96 82,693 9,485 104 77,301 8,866 84
Dec-22 80,292 9,199 96 83,075 9,518 104 77,590 8,889 84
Jan-23 80,438 9,211 96 83,262 9,534 104 77,697 8,897 83
Feb-23 80,448 9,212 96 83,308 9,539 105 77,673 8,894 83
Mar-23 80,461 9,202 96 83,358 9,533 105 77,652 8,881 83
Apr-23 80,437 9,200 96 83,369 9,535 105 77,595 8,875 83
May-23 80,432 9,204 96 83,399 9,544 105 77,556 8,875 83
Jun-23 80,441 9,206 96 83,444 9,550 105 77,531 8,873 83
Jul-23 80,538 9,221 96 83,578 9,569 105 77,594 8,884 82
Aug-23 80,629 9,226 96 83,705 9,578 106 77,651 8,885 82
Sep-23 80,832 9,227 96 83,949 9,583 106 77,816 8,883 82
Oct-23 81,005 9,228 96 84,162 9,588 106 77,952 8,880 82
Nov-23 81,263 9,230 96 84,463 9,593 106 78,170 8,879 82
Dec-23 81,589 9,258 96 84,835 9,626 106 78,452 8,902 82
Jan-24 81,727 9,269 96 85,012 9,642 106 78,554 8,909 81
Feb-24 81,728 9,270 96 85,047 9,646 107 78,524 8,907 81
Mar-24 81,731 9,260 96 85,083 9,640 107 78,496 8,893 81
Apr-24 81,699 9,256 96 85,084 9,639 107 78,435 8,886 81
May-24 81,685 9,262 96 85,101 9,649 107 78,389 8,888 81
Jun-24 81,685 9,264 96 85,135 9,655 107 78,359 8,887 81
Idaho -
Expected Growth
Idaho -
High Growth
Idaho -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 52 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
IDAHO

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Jul-24 81,781 9,278 96 85,268 9,674 107 78,421 8,897 80
Aug-24 81,871 9,284 96 85,394 9,684 108 78,477 8,899 80
Sep-24 82,073 9,285 96 85,637 9,688 108 78,641 8,897 80
Oct-24 82,244 9,284 96 85,849 9,691 108 78,774 8,892 80
Nov-24 82,501 9,287 96 86,150 9,698 108 78,990 8,892 80
Dec-24 82,825 9,315 96 86,521 9,731 108 79,270 8,915 80
Jan-25 82,962 9,326 96 86,698 9,746 108 79,371 8,922 79
Feb-25 82,961 9,328 96 86,730 9,752 109 79,340 8,921 79
Mar-25 82,964 9,318 96 86,766 9,745 109 79,313 8,908 79
Apr-25 82,930 9,314 96 86,764 9,744 109 79,250 8,901 79
May-25 82,915 9,319 96 86,780 9,753 109 79,204 8,902 79
Jun-25 82,913 9,320 96 86,811 9,758 109 79,172 8,900 79
Jul-25 83,008 9,335 96 86,943 9,778 109 79,233 8,911 78
Aug-25 83,097 9,341 96 87,069 9,787 110 79,289 8,913 78
Sep-25 83,298 9,341 96 87,312 9,791 110 79,451 8,910 78
Oct-25 83,468 9,341 96 87,522 9,795 110 79,584 8,906 78
Nov-25 83,724 9,344 96 87,824 9,802 110 79,798 8,906 78
Dec-25 84,047 9,371 96 88,195 9,834 110 80,076 8,928 78
Jan-26 84,183 9,383 96 88,371 9,850 110 80,176 8,936 77
Feb-26 84,181 9,385 96 88,402 9,856 111 80,144 8,935 77
Mar-26 84,183 9,374 96 88,437 9,848 111 80,116 8,921 77
Apr-26 84,148 9,371 96 88,433 9,848 111 80,053 8,915 77
May-26 84,132 9,376 96 88,448 9,857 111 80,007 8,916 77
Jun-26 84,129 9,377 96 88,478 9,862 111 79,974 8,914 77
Jul-26 84,223 9,392 96 88,609 9,881 111 80,035 8,925 76
Aug-26 84,311 9,398 96 88,734 9,891 112 80,089 8,927 76
Sep-26 84,511 9,397 96 88,977 9,894 112 80,250 8,923 76
Oct-26 84,680 9,398 96 89,187 9,898 112 80,381 8,921 76
Nov-26 84,936 9,400 96 89,489 9,904 112 80,595 8,920 76
Dec-26 85,258 9,428 96 89,861 9,937 112 80,871 8,943 76
Jan-27 85,392 9,440 96 90,035 9,953 112 80,969 8,951 75
Feb-27 85,390 9,440 96 90,066 9,957 113 80,937 8,948 75
Mar-27 85,391 9,430 96 90,100 9,950 113 80,909 8,935 75
Apr-27 85,356 9,427 96 90,095 9,950 113 80,845 8,929 75
May-27 85,338 9,432 96 90,109 9,959 113 80,799 8,930 75
Jun-27 85,335 9,433 96 90,138 9,964 113 80,767 8,928 75
Jul-27 85,430 9,448 96 90,271 9,983 113 80,828 8,939 74
Aug-27 85,518 9,453 96 90,397 9,992 114 80,882 8,941 74
Sep-27 85,719 9,454 96 90,642 9,997 114 81,042 8,938 74
Oct-27 85,889 9,455 96 90,855 10,002 114 81,174 8,936 74
Idaho -
Expected Growth
Idaho -
High Growth
Idaho -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 53 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
IDAHO

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Nov-27 86,145 9,457 96 91,158 10,007 114 81,386 8,935 74
Dec-27 86,468 9,485 96 91,533 10,041 114 81,662 8,958 74
Jan-28 86,603 9,497 96 91,709 10,057 114 81,760 8,966 73
Feb-28 86,602 9,497 96 91,742 10,061 115 81,729 8,963 73
Mar-28 86,603 9,487 96 91,776 10,054 115 81,701 8,950 73
Apr-28 86,569 9,484 96 91,772 10,054 115 81,638 8,944 73
May-28 86,552 9,489 96 91,787 10,063 115 81,593 8,945 73
Jun-28 86,549 9,490 96 91,817 10,068 115 81,561 8,943 73
Jul-28 86,645 9,504 96 91,952 10,086 115 81,622 8,953 72
Aug-28 86,735 9,510 96 92,081 10,096 116 81,677 8,955 72
Sep-28 86,937 9,511 96 92,328 10,101 116 81,838 8,953 72
Oct-28 87,107 9,511 96 92,542 10,104 116 81,969 8,950 72
Nov-28 87,364 9,514 96 92,849 10,111 116 82,181 8,950 72
Dec-28 87,688 9,542 96 93,226 10,145 116 82,456 8,973 72
Jan-29 87,824 9,553 96 93,405 10,160 116 82,554 8,980 71
Feb-29 87,824 9,554 96 93,438 10,165 117 82,525 8,977 71
Mar-29 87,826 9,544 96 93,474 10,158 117 82,497 8,965 71
Apr-29 87,793 9,540 96 93,471 10,157 117 82,435 8,958 71
May-29 87,777 9,546 96 93,488 10,167 117 82,391 8,960 71
Jun-29 87,775 9,547 96 93,519 10,172 117 82,359 8,958 71
Jul-29 87,871 9,561 96 93,655 10,190 117 82,420 8,968 70
Aug-29 87,960 9,567 96 93,783 10,200 118 82,474 8,970 70
Sep-29 88,162 9,568 96 94,032 10,205 118 82,635 8,968 70
Oct-29 88,333 9,568 96 94,248 10,209 118 82,766 8,965 70
Nov-29 88,590 9,571 96 94,555 10,215 118 82,977 8,965 70
Dec-29 88,914 9,598 96 94,935 10,248 118 83,251 8,987 70
Jan-30 89,050 9,610 96 95,114 10,264 118 83,349 8,995 69
Feb-30 89,049 9,611 96 95,146 10,269 119 83,318 8,992 69
Mar-30 89,051 9,600 96 95,182 10,261 119 83,291 8,979 69
Apr-30 89,019 9,597 96 95,181 10,261 119 83,230 8,973 69
May-30 89,002 9,603 96 95,196 10,271 119 83,185 8,975 69
Jun-30 89,000 9,603 96 95,228 10,275 119 83,154 8,972 69
Jul-30 89,099 9,619 96 95,368 10,296 119 83,216 8,984 68
Aug-30 89,192 9,624 96 95,502 10,305 120 83,273 8,985 68
Sep-30 89,397 9,624 96 95,756 10,309 120 83,435 8,982 68
Oct-30 89,570 9,625 96 95,976 10,313 120 83,566 8,980 68
Nov-30 89,831 9,628 96 96,290 10,320 120 83,779 8,979 68
Dec-30 90,157 9,655 96 96,675 10,353 120 84,053 9,001 68
Jan-31 90,297 9,667 96 96,860 10,370 120 84,153 9,009 67
Feb-31 90,299 9,669 96 96,897 10,375 121 84,125 9,008 67
Idaho -
Low Growth
Idaho -
Expected Growth
Idaho -
High Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 54 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
IDAHO

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Mar-31 90,305 9,658 96 96,937 10,367 121 84,099 8,994 67
Apr-31 90,274 9,655 96 96,938 10,368 121 84,040 8,988 67
May-31 90,261 9,660 96 96,959 10,377 121 83,998 8,990 67
Jun-31 90,262 9,661 96 96,995 10,382 121 83,969 8,987 67
Jul-31 90,364 9,677 96 97,140 10,403 121 84,033 8,999 66
Aug-31 90,458 9,681 96 97,276 10,411 122 84,090 9,000 66
Sep-31 90,665 9,682 96 97,534 10,416 122 84,252 8,997 66
Oct-31 90,841 9,683 96 97,759 10,420 122 84,385 8,995 66
Nov-31 91,104 9,686 96 98,078 10,427 122 84,599 8,994 66
Dec-31 91,432 9,713 96 98,467 10,460 122 84,873 9,016 66
Jan-32 91,574 9,726 96 98,655 10,478 122 84,974 9,025 65
Feb-32 91,579 9,726 96 98,696 10,482 123 84,948 9,022 65
Mar-32 91,587 9,716 96 98,740 10,475 123 84,923 9,009 65
Apr-32 91,558 9,713 96 98,744 10,475 123 84,866 9,003 65
May-32 91,547 9,718 96 98,768 10,485 123 84,825 9,004 65
Jun-32 91,551 9,720 96 98,808 10,491 123 84,798 9,003 65
Jul-32 91,654 9,735 96 98,955 10,511 123 84,862 9,014 64
Aug-32 91,750 9,740 96 99,095 10,520 124 84,920 9,015 64
Sep-32 91,959 9,741 96 99,357 10,525 124 85,083 9,013 64
Oct-32 92,137 9,741 96 99,585 10,528 124 85,217 9,009 64
Nov-32 92,401 9,744 96 99,907 10,536 124 85,430 9,009 64
Dec-32 92,732 9,772 96 100,301 10,570 124 85,705 9,031 64
Jan-33 92,875 9,783 96 100,493 10,585 124 85,806 9,038 63
Feb-33 92,882 9,785 96 100,537 10,591 125 85,781 9,037 63
Mar-33 92,892 9,775 96 100,583 10,584 125 85,758 9,024 63
Apr-33 92,865 9,771 96 100,590 10,584 125 85,702 9,017 63
May-33 92,856 9,777 96 100,617 10,594 125 85,663 9,020 63
Jun-33 92,862 9,779 96 100,660 10,600 125 85,637 9,018 63
Jul-33 92,967 9,793 96 100,811 10,619 125 85,703 9,028 62
Aug-33 93,065 9,799 96 100,954 10,630 126 85,762 9,030 62
Sep-33 93,277 9,800 96 101,221 10,635 126 85,926 9,028 62
Oct-33 93,457 9,800 96 101,453 10,639 126 86,060 9,024 62
Nov-33 93,723 9,804 96 101,779 10,647 126 86,273 9,025 62
Dec-33 94,056 9,831 96 102,178 10,680 126 86,548 9,046 62
Jan-34 94,202 9,843 96 102,374 10,697 126 86,651 9,054 61
Feb-34 94,211 9,844 96 102,422 10,702 127 86,628 9,052 61
Mar-34 94,223 9,834 96 102,471 10,695 127 86,606 9,039 61
Apr-34 94,199 9,831 96 102,482 10,696 127 86,552 9,033 61
May-34 94,192 9,837 96 102,512 10,706 127 86,514 9,035 61
Jun-34 94,199 9,837 96 102,557 10,710 127 86,489 9,032 61
Jul-34 94,306 9,853 96 102,711 10,731 127 86,556 9,043 60
Idaho -
Low Growth
Idaho -
Expected Growth
Idaho -
High Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 55 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
IDAHO

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Aug-34 94,406 9,859 96 102,858 10,742 128 86,616 9,045 60
Sep-34 94,619 9,859 96 103,128 10,746 128 86,780 9,042 60
Oct-34 94,801 9,860 96 103,364 10,751 128 86,915 9,040 60
Nov-34 95,069 9,863 96 103,694 10,758 128 87,129 9,039 60
Dec-34 95,404 9,890 96 104,098 10,791 128 87,404 9,061 60
Jan-35 95,551 9,903 96 104,296 10,809 128 87,506 9,069 59
Feb-35 95,563 9,904 96 104,346 10,814 129 87,484 9,067 59
Mar-35 95,576 9,894 96 104,399 10,807 129 87,464 9,054 59
Apr-35 95,553 9,891 96 104,412 10,808 129 87,411 9,048 59
May-35 95,548 9,897 96 104,445 10,819 129 87,375 9,050 59
Jun-35 95,557 9,897 96 104,493 10,822 129 87,351 9,047 59
Jul-35 95,666 9,913 96 104,650 10,844 129 87,419 9,058 58
Aug-35 95,769 9,918 96 104,802 10,853 130 87,481 9,060 58
Sep-35 95,984 9,919 96 105,076 10,859 130 87,645 9,057 58
Oct-35 96,168 9,920 96 105,316 10,864 130 87,780 9,055 58
Nov-35 96,439 9,923 96 105,651 10,871 130 87,995 9,054 58
Dec-35 96,776 9,951 96 106,060 10,906 130 88,270 9,076 58
Jan-36 96,926 9,963 96 106,263 10,923 130 88,375 9,084 57
Feb-36 96,940 9,964 96 106,317 10,928 131 88,354 9,082 57
Mar-36 96,955 9,954 96 106,372 10,921 131 88,335 9,069 57
Apr-36 96,935 9,951 96 106,389 10,922 131 88,285 9,063 57
May-36 96,932 9,956 96 106,425 10,931 131 88,249 9,064 57
Jun-36 96,944 9,958 96 106,478 10,937 131 88,228 9,063 57
Jul-36 97,055 9,974 96 106,639 10,959 131 88,296 9,074 56
Aug-36 97,159 9,979 96 106,793 10,968 132 88,358 9,075 56
Sep-36 97,377 9,980 96 107,072 10,974 132 88,524 9,073 56
Oct-36 97,563 9,981 96 107,316 10,979 132 88,660 9,070 56
Nov-36 97,835 9,984 96 107,655 10,986 132 88,875 9,070 56
Dec-36 98,174 10,012 96 108,067 11,021 132 89,150 9,092 56
Jan-37 98,326 10,023 96 108,275 11,037 132 89,255 9,098 55
Feb-37 98,341 10,025 96 108,330 11,043 133 89,235 9,097 55
Mar-37 98,359 10,015 96 108,390 11,036 133 89,218 9,084 55
Apr-37 98,340 10,011 96 108,409 11,036 133 89,168 9,077 55
May-37 98,340 10,017 96 108,449 11,047 133 89,135 9,079 55
Jun-37 98,353 10,019 96 108,503 11,053 133 89,114 9,078 55
Jul-37 98,466 10,034 96 108,668 11,074 133 89,184 9,088 54
Aug-37 98,572 10,040 96 108,825 11,084 134 89,247 9,090 54
Sep-37 98,791 10,041 96 109,107 11,089 134 89,412 9,088 54
Oct-37 98,978 10,042 96 109,354 11,095 134 89,548 9,085 54
Nov-37 99,252 10,045 96 109,697 11,102 134 89,763 9,085 54
Dec-37 99,592 10,073 96 110,113 11,137 134 90,038 9,107 54
Idaho -
Low Growth
Idaho -
Expected Growth
Idaho -
High Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 56 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
MEDFORD

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Nov-17 54,604 6,919 15 54,965 6,965 15 54,244 6,873 15
Dec-17 54,921 6,966 15 55,302 7,014 15 54,541 6,918 15
Jan-18 55,150 7,001 15 55,551 7,052 15 54,750 6,951 15
Feb-18 55,132 7,025 15 55,552 7,079 15 54,714 6,972 15
Mar-18 55,110 7,009 15 55,548 7,065 15 54,674 6,954 15
Apr-18 55,081 7,004 15 55,537 7,062 15 54,627 6,947 15
May-18 54,977 6,995 15 55,450 7,056 15 54,506 6,935 15
Jun-18 54,860 6,975 15 55,350 7,038 15 54,372 6,913 15
Jul-18 54,730 6,964 15 55,237 7,029 15 54,226 6,900 15
Aug-18 54,648 6,966 15 55,171 7,033 15 54,128 6,900 15
Sep-18 54,650 6,937 15 55,191 7,006 15 54,112 6,869 15
Oct-18 54,917 6,954 15 55,478 7,025 16 54,360 6,884 15
Nov-18 55,303 7,003 15 55,885 7,077 16 54,725 6,930 14
Dec-18 55,650 7,047 15 56,254 7,124 16 55,050 6,971 14
Jan-19 55,862 7,076 15 56,486 7,155 16 55,243 6,998 14
Feb-19 55,858 7,095 15 56,499 7,177 16 55,221 7,014 14
Mar-19 55,847 7,095 15 56,506 7,179 16 55,193 7,012 14
Apr-19 55,810 7,075 15 56,486 7,161 16 55,139 6,990 14
May-19 55,722 7,068 15 56,415 7,156 16 55,035 6,981 14
Jun-19 55,598 7,058 15 56,307 7,148 16 54,895 6,969 14
Jul-19 55,454 7,033 15 56,178 7,125 16 54,736 6,942 14
Aug-19 55,371 7,022 15 56,111 7,116 16 54,638 6,929 14
Sep-19 55,364 7,018 15 56,121 7,114 16 54,614 6,923 14
Oct-19 55,624 7,030 15 56,402 7,128 16 54,854 6,933 14
Nov-19 56,009 7,074 15 56,809 7,175 16 55,217 6,974 14
Dec-19 56,352 7,120 15 57,174 7,224 16 55,538 7,017 14
Jan-20 56,565 7,152 15 57,408 7,258 16 55,731 7,046 14
Feb-20 56,563 7,173 15 57,423 7,282 16 55,712 7,065 14
Mar-20 56,551 7,167 15 57,428 7,278 16 55,684 7,057 14
Apr-20 56,514 7,152 15 57,408 7,265 16 55,630 7,040 14
May-20 56,424 7,145 15 57,334 7,260 16 55,525 7,031 14
Jun-20 56,297 7,131 15 57,222 7,248 16 55,383 7,015 14
Jul-20 56,154 7,111 15 57,094 7,230 16 55,226 6,993 14
Aug-20 56,071 7,105 15 57,027 7,226 16 55,127 6,985 14
Sep-20 56,064 7,091 15 57,037 7,214 16 55,104 6,969 14
Oct-20 56,325 7,104 15 57,320 7,229 17 55,343 6,980 14
Nov-20 56,712 7,151 15 57,732 7,279 17 55,706 7,024 13
Dec-20 57,056 7,196 15 58,100 7,327 17 56,027 7,066 13
Jan-21 57,272 7,227 15 58,337 7,361 17 56,222 7,094 13
Feb-21 57,271 7,247 15 58,354 7,384 17 56,204 7,112 13
Medford -
Expected Growth
Medford -
High Growth
Medford -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 57 of 829

APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
MEDFORD

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Mar-21 57,261 7,244 15 58,362 7,383 17 56,177 7,106 13
Apr-21 57,226 7,227 15 58,344 7,368 17 56,126 7,088 13
May-21 57,138 7,220 15 58,272 7,363 17 56,022 7,079 13
Jun-21 57,011 7,207 15 58,160 7,352 17 55,881 7,064 13
Jul-21 56,867 7,186 15 58,030 7,332 17 55,723 7,041 13
Aug-21 56,783 7,178 15 57,962 7,327 17 55,624 7,031 13
Sep-21 56,776 7,168 15 57,972 7,318 17 55,600 7,019 13
Oct-21 57,036 7,180 15 58,255 7,333 17 55,838 7,029 13
Nov-21 57,422 7,226 15 58,666 7,382 17 56,199 7,072 13
Dec-21 57,766 7,271 15 59,036 7,430 17 56,519 7,114 13
Jan-22 57,981 7,301 15 59,273 7,464 17 56,713 7,141 13
Feb-22 57,980 7,322 15 59,290 7,487 17 56,695 7,160 13
Mar-22 57,969 7,318 15 59,296 7,485 17 56,667 7,154 13
Apr-22 57,933 7,302 15 59,277 7,471 17 56,615 7,136 13
May-22 57,844 7,295 15 59,203 7,466 17 56,511 7,127 13
Jun-22 57,717 7,281 15 59,091 7,454 17 56,370 7,111 13
Jul-22 57,573 7,260 15 58,961 7,435 17 56,213 7,088 13
Aug-22 57,489 7,253 15 58,892 7,430 17 56,114 7,079 13
Sep-22 57,482 7,242 15 58,902 7,421 17 56,091 7,067 13
Oct-22 57,742 7,254 15 59,186 7,435 18 56,328 7,076 13
Nov-22 58,128 7,300 15 59,600 7,485 18 56,688 7,119 12
Dec-22 58,472 7,346 15 59,970 7,534 18 57,006 7,162 12
Jan-23 58,687 7,376 15 60,208 7,568 18 57,199 7,189 12
Feb-23 58,687 7,396 15 60,226 7,590 18 57,182 7,207 12
Mar-23 58,676 7,392 15 60,233 7,588 18 57,154 7,201 12
Apr-23 58,640 7,376 15 60,213 7,574 18 57,102 7,183 12
May-23 58,551 7,369 15 60,140 7,569 18 56,999 7,174 12
Jun-23 58,424 7,356 15 60,027 7,558 18 56,858 7,159 12
Jul-23 58,271 7,334 15 59,885 7,538 18 56,695 7,136 12
Aug-23 58,178 7,326 15 59,805 7,531 18 56,590 7,126 12
Sep-23 58,161 7,315 15 59,802 7,522 18 56,559 7,114 12
Oct-23 58,411 7,327 15 60,075 7,536 18 56,787 7,124 12
Nov-23 58,788 7,372 15 60,478 7,584 18 57,139 7,166 12
Dec-23 59,122 7,417 15 60,837 7,633 18 57,449 7,208 12
Jan-24 59,328 7,447 15 61,065 7,665 18 57,635 7,234 12
Feb-24 59,317 7,467 15 61,069 7,688 18 57,609 7,252 12
Mar-24 59,298 7,463 15 61,065 7,685 18 57,576 7,246 12
Apr-24 59,252 7,446 15 61,033 7,670 18 57,517 7,228 12
May-24 59,153 7,438 15 60,947 7,664 18 57,406 7,218 12
Jun-24 59,016 7,425 15 60,821 7,652 18 57,258 7,204 12
Medford -
Expected Growth
Medford -
High Growth
Medford -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 58 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
MEDFORD

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Jul-24 58,864 7,403 15 60,680 7,631 18 57,096 7,181 12
Aug-24 58,771 7,395 15 60,600 7,625 18 56,991 7,171 12
Sep-24 58,755 7,384 15 60,599 7,616 18 56,961 7,159 12
Oct-24 59,006 7,396 15 60,873 7,630 19 57,190 7,168 12
Nov-24 59,383 7,441 15 61,278 7,678 19 57,541 7,210 11
Dec-24 59,718 7,486 15 61,639 7,727 19 57,850 7,252 11
Jan-25 59,924 7,516 15 61,867 7,759 19 58,035 7,279 11
Feb-25 59,915 7,536 15 61,874 7,782 19 58,012 7,296 11
Mar-25 59,895 7,532 15 61,869 7,780 19 57,977 7,290 11
Apr-25 59,850 7,515 15 61,838 7,764 19 57,919 7,272 11
May-25 59,752 7,508 15 61,753 7,759 19 57,809 7,263 11
Jun-25 59,616 7,494 15 61,628 7,746 19 57,663 7,248 11
Jul-25 59,463 7,472 15 61,485 7,726 19 57,501 7,225 11
Aug-25 59,370 7,464 15 61,405 7,719 19 57,396 7,215 11
Sep-25 59,353 7,453 15 61,402 7,710 19 57,365 7,203 11
Oct-25 59,604 7,465 15 61,678 7,724 19 57,593 7,213 11
Nov-25 59,981 7,510 15 62,083 7,773 19 57,943 7,254 11
Dec-25 60,316 7,555 15 62,446 7,821 19 58,252 7,296 11
Jan-26 60,521 7,585 15 62,674 7,855 19 58,435 7,324 11
Feb-26 60,511 7,604 15 62,679 7,876 19 58,411 7,340 11
Mar-26 60,492 7,600 15 62,675 7,874 19 58,378 7,334 11
Apr-26 60,446 7,583 15 62,643 7,859 19 58,319 7,316 11
May-26 60,348 7,576 15 62,557 7,853 19 58,210 7,307 11
Jun-26 60,211 7,562 15 62,431 7,841 19 58,063 7,292 11
Jul-26 60,057 7,540 15 62,287 7,820 19 57,900 7,269 11
Aug-26 59,964 7,532 15 62,206 7,813 19 57,796 7,260 11
Sep-26 59,946 7,521 15 62,202 7,804 19 57,764 7,247 11
Oct-26 60,197 7,533 15 62,478 7,818 20 57,992 7,257 11
Nov-26 60,573 7,578 15 62,884 7,867 20 58,340 7,299 10
Dec-26 60,907 7,623 15 63,246 7,916 20 58,647 7,340 10
Jan-27 61,112 7,652 15 63,475 7,948 20 58,830 7,366 10
Feb-27 61,102 7,672 15 63,480 7,971 20 58,806 7,384 10
Mar-27 61,081 7,668 15 63,474 7,969 20 58,771 7,378 10
Apr-27 61,035 7,651 15 63,442 7,953 20 58,712 7,360 10
May-27 60,936 7,643 15 63,354 7,946 20 58,602 7,350 10
Jun-27 60,799 7,630 15 63,227 7,935 20 58,456 7,336 10
Jul-27 60,644 7,608 15 63,081 7,914 20 58,293 7,313 10
Aug-27 60,549 7,599 15 62,998 7,906 20 58,188 7,303 10
Sep-27 60,531 7,588 15 62,994 7,897 20 58,157 7,291 10
Oct-27 60,780 7,600 15 63,268 7,911 20 58,382 7,300 10
Medford -
Expected Growth
Medford -
High Growth
Medford -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 59 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
MEDFORD

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Nov-27 61,155 7,645 15 63,674 7,960 20 58,728 7,342 10
Dec-27 61,488 7,690 15 64,036 8,009 20 59,033 7,383 10
Jan-28 61,692 7,720 15 64,264 8,042 20 59,215 7,411 10
Feb-28 61,680 7,739 15 64,267 8,064 20 59,189 7,427 10
Mar-28 61,659 7,735 15 64,260 8,062 20 59,155 7,421 10
Apr-28 61,611 7,718 15 64,226 8,046 20 59,095 7,403 10
May-28 61,511 7,710 15 64,137 8,040 20 58,985 7,394 10
Jun-28 61,373 7,696 15 64,008 8,027 20 58,838 7,379 10
Jul-28 61,216 7,674 15 63,859 8,006 20 58,674 7,356 10
Aug-28 61,120 7,666 15 63,774 7,999 20 58,568 7,346 10
Sep-28 61,099 7,655 15 63,767 7,990 20 58,535 7,334 10
Oct-28 61,347 7,667 15 64,040 8,004 21 58,759 7,344 10
Nov-28 61,720 7,712 15 64,445 8,053 21 59,102 7,385 9
Dec-28 62,052 7,756 15 64,806 8,101 21 59,406 7,426 9
Jan-29 62,254 7,787 15 65,032 8,134 21 59,586 7,453 9
Feb-29 62,240 7,806 15 65,033 8,156 21 59,559 7,470 9
Mar-29 62,217 7,802 15 65,024 8,154 21 59,523 7,464 9
Apr-29 62,168 7,785 15 64,988 8,138 21 59,462 7,446 9
May-29 62,066 7,777 15 64,896 8,131 21 59,351 7,437 9
Jun-29 61,926 7,763 15 64,764 8,119 21 59,203 7,422 9
Jul-29 61,768 7,741 15 64,614 8,097 21 59,039 7,399 9
Aug-29 61,670 7,733 15 64,526 8,091 21 58,932 7,390 9
Sep-29 61,649 7,721 15 64,518 8,080 21 58,899 7,376 9
Oct-29 61,895 7,733 15 64,790 8,095 21 59,120 7,386 9
Nov-29 62,267 7,778 15 65,194 8,144 21 59,462 7,428 9
Dec-29 62,597 7,822 15 65,555 8,191 21 59,764 7,468 9
Jan-30 62,798 7,852 15 65,780 8,225 21 59,942 7,495 9
Feb-30 62,783 7,871 15 65,779 8,247 21 59,915 7,512 9
Mar-30 62,759 7,867 15 65,769 8,244 21 59,878 7,506 9
Apr-30 62,708 7,850 15 65,730 8,229 21 59,816 7,488 9
May-30 62,605 7,842 15 65,637 8,222 21 59,704 7,479 9
Jun-30 62,464 7,828 15 65,504 8,209 21 59,556 7,464 9
Jul-30 62,304 7,806 15 65,350 8,188 21 59,391 7,441 9
Aug-30 62,204 7,797 15 65,259 8,180 21 59,283 7,431 9
Sep-30 62,181 7,786 15 65,249 8,170 21 59,248 7,419 9
Oct-30 62,425 7,797 15 65,519 8,184 22 59,468 7,428 9
Nov-30 62,795 7,842 15 65,922 8,233 22 59,807 7,469 8
Dec-30 63,123 7,887 15 66,280 8,282 22 60,107 7,510 8
Jan-31 63,322 7,917 15 66,504 8,314 22 60,283 7,537 8
Feb-31 63,305 7,936 15 66,500 8,336 22 60,254 7,553 8
Medford -
Expected Growth
Medford -
High Growth
Medford -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 60 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
MEDFORD

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Mar-31 63,278 7,931 15 66,486 8,333 22 60,215 7,547 8
Apr-31 63,226 7,915 15 66,446 8,318 22 60,153 7,530 8
May-31 63,121 7,906 15 66,350 8,310 22 60,040 7,520 8
Jun-31 62,978 7,892 15 66,214 8,297 22 59,891 7,505 8
Jul-31 62,816 7,870 15 66,057 8,276 22 59,725 7,482 8
Aug-31 62,714 7,861 15 65,963 8,268 22 59,615 7,472 8
Sep-31 62,689 7,850 15 65,951 8,258 22 59,579 7,460 8
Oct-31 62,931 7,861 15 66,219 8,271 22 59,797 7,469 8
Nov-31 63,300 7,906 15 66,621 8,320 22 60,135 7,510 8
Dec-31 63,626 7,950 15 66,978 8,369 22 60,432 7,551 8
Jan-32 63,823 7,980 15 67,200 8,402 22 60,606 7,578 8
Feb-32 63,804 7,999 15 67,193 8,424 22 60,576 7,594 8
Mar-32 63,776 7,994 15 67,178 8,421 22 60,536 7,588 8
Apr-32 63,722 7,977 15 67,135 8,404 22 60,473 7,570 8
May-32 63,615 7,969 15 67,036 8,398 22 60,359 7,561 8
Jun-32 63,470 7,955 15 66,897 8,385 22 60,208 7,546 8
Jul-32 63,306 7,932 15 66,738 8,362 22 60,041 7,523 8
Aug-32 63,203 7,923 15 66,643 8,354 22 59,931 7,513 8
Sep-32 63,177 7,912 15 66,628 8,344 22 59,894 7,501 8
Oct-32 63,418 7,923 15 66,896 8,358 23 60,111 7,510 8
Nov-32 63,784 7,968 15 67,296 8,407 23 60,446 7,551 7
Dec-32 64,109 8,012 15 67,652 8,455 23 60,741 7,591 7
Jan-33 64,305 8,042 15 67,873 8,488 23 60,915 7,618 7
Feb-33 64,285 8,062 15 67,865 8,511 23 60,884 7,635 7
Mar-33 64,255 8,056 15 67,847 8,506 23 60,843 7,628 7
Apr-33 64,199 8,039 15 67,801 8,490 23 60,778 7,610 7
May-33 64,091 8,031 15 67,701 8,483 23 60,663 7,601 7
Jun-33 63,944 8,017 15 67,559 8,470 23 60,512 7,586 7
Jul-33 63,780 7,994 15 67,399 8,447 23 60,345 7,563 7
Aug-33 63,675 7,985 15 67,301 8,439 23 60,234 7,553 7
Sep-33 63,647 7,974 15 67,285 8,429 23 60,196 7,541 7
Oct-33 63,887 7,985 15 67,552 8,443 23 60,411 7,550 7
Nov-33 64,252 8,030 15 67,951 8,492 23 60,744 7,591 7
Dec-33 64,576 8,074 15 68,307 8,540 23 61,039 7,631 7
Jan-34 64,770 8,103 15 68,525 8,573 23 61,210 7,658 7
Feb-34 64,748 8,122 15 68,515 8,594 23 61,177 7,674 7
Mar-34 64,717 8,117 15 68,496 8,591 23 61,136 7,668 7
Apr-34 64,660 8,100 15 68,449 8,575 23 61,070 7,650 7
May-34 64,551 8,091 15 68,347 8,567 23 60,956 7,640 7
Jun-34 64,403 8,077 15 68,203 8,554 23 60,804 7,626 7
Jul-34 64,237 8,054 15 68,040 8,531 23 60,636 7,602 7
Medford -
Expected Growth
Medford -
High Growth
Medford -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 61 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
MEDFORD

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Aug-34 64,131 8,046 15 67,941 8,524 23 60,524 7,593 7
Sep-34 64,102 8,034 15 67,923 8,513 23 60,485 7,581 7
Oct-34 64,340 8,045 15 68,188 8,526 24 60,699 7,590 7
Nov-34 64,704 8,090 15 68,587 8,575 24 61,030 7,631 6
Dec-34 65,026 8,134 15 68,941 8,624 24 61,323 7,671 6
Jan-35 65,219 8,163 15 69,158 8,656 24 61,493 7,697 6
Feb-35 65,196 8,182 15 69,147 8,678 24 61,460 7,713 6
Mar-35 65,164 8,177 15 69,126 8,675 24 61,418 7,707 6
Apr-35 65,106 8,159 15 69,078 8,657 24 61,352 7,689 6
May-35 64,995 8,151 15 68,973 8,650 24 61,236 7,680 6
Jun-35 64,845 8,136 15 68,827 8,636 24 61,083 7,664 6
Jul-35 64,679 8,114 15 68,663 8,614 24 60,915 7,642 6
Aug-35 64,573 8,105 15 68,564 8,606 24 60,804 7,632 6
Sep-35 64,543 8,093 15 68,544 8,595 24 60,764 7,620 6
Oct-35 64,781 8,104 15 68,810 8,608 24 60,977 7,628 6
Nov-35 65,145 8,149 15 69,209 8,658 24 61,308 7,669 6
Dec-35 65,467 8,193 15 69,564 8,706 24 61,600 7,709 6
Jan-36 65,660 8,223 15 69,783 8,739 24 61,770 7,736 6
Feb-36 65,637 8,242 15 69,771 8,761 24 61,737 7,752 6
Mar-36 65,604 8,237 15 69,749 8,757 24 61,694 7,746 6
Apr-36 65,545 8,219 15 69,699 8,740 24 61,627 7,728 6
May-36 65,434 8,211 15 69,594 8,733 24 61,511 7,719 6
Jun-36 65,284 8,197 15 69,448 8,720 24 61,359 7,704 6
Jul-36 65,118 8,174 15 69,284 8,697 24 61,192 7,681 6
Aug-36 65,011 8,165 15 69,182 8,689 24 61,080 7,671 6
Sep-36 64,981 8,153 15 69,163 8,678 24 61,040 7,659 6
Oct-36 65,219 8,164 15 69,429 8,691 25 61,253 7,667 6
Nov-36 65,582 8,209 15 69,829 8,740 25 61,582 7,708 5
Dec-36 65,904 8,253 15 70,184 8,789 25 61,873 7,748 5
Jan-37 66,096 8,283 15 70,402 8,822 25 62,042 7,775 5
Feb-37 66,073 8,302 15 70,390 8,844 25 62,009 7,791 5
Mar-37 66,040 8,297 15 70,368 8,840 25 61,967 7,785 5
Apr-37 65,980 8,279 15 70,317 8,823 25 61,899 7,767 5
May-37 65,869 8,271 15 70,211 8,816 25 61,784 7,758 5
Jun-37 65,719 8,257 15 70,064 8,802 25 61,632 7,743 5
Jul-37 65,553 8,234 15 69,900 8,780 25 61,465 7,720 5
Aug-37 65,445 8,225 15 69,797 8,772 25 61,352 7,710 5
Sep-37 65,415 8,213 15 69,778 8,760 25 61,313 7,698 5
Oct-37 65,651 8,224 15 70,042 8,774 25 61,523 7,707 5
Nov-37 66,014 8,269 15 70,442 8,823 25 61,852 7,747 5
Dec-37 66,334 8,313 15 70,796 8,872 25 62,141 7,787 5
Medford -
Expected Growth
Medford -
High Growth
Medford -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 62 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
ROSEBURG

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Nov-17 13,522 2,157 2 13,606 2,171 2 13,438 2,144 2
Dec-17 13,665 2,172 2 13,755 2,186 2 13,575 2,158 2
Jan-18 13,677 2,169 2 13,772 2,184 2 13,583 2,154 2
Feb-18 13,679 2,176 2 13,778 2,192 2 13,580 2,160 2
Mar-18 13,681 2,184 2 13,785 2,201 2 13,577 2,168 2
Apr-18 13,660 2,178 2 13,768 2,195 2 13,552 2,161 2
May-18 13,641 2,174 2 13,754 2,192 2 13,528 2,156 2
Jun-18 13,562 2,171 2 13,679 2,190 2 13,446 2,152 2
Jul-18 13,533 2,163 2 13,654 2,182 2 13,413 2,144 2
Aug-18 13,468 2,153 2 13,592 2,173 2 13,344 2,133 2
Sep-18 13,486 2,157 2 13,615 2,178 2 13,358 2,137 2
Oct-18 13,571 2,155 2 13,705 2,176 3 13,438 2,134 2
Nov-18 13,686 2,165 2 13,825 2,187 3 13,548 2,143 1
Dec-18 13,812 2,182 2 13,957 2,205 3 13,668 2,159 1
Jan-19 13,854 2,184 2 14,003 2,207 3 13,706 2,160 1
Feb-19 13,854 2,190 2 14,008 2,214 3 13,702 2,166 1
Mar-19 13,856 2,192 2 14,014 2,217 3 13,699 2,167 1
Apr-19 13,837 2,185 2 13,999 2,210 3 13,676 2,159 1
May-19 13,798 2,183 2 13,964 2,209 3 13,634 2,157 1
Jun-19 13,732 2,178 2 13,901 2,204 3 13,564 2,151 1
Jul-19 13,688 2,171 2 13,861 2,198 3 13,517 2,144 1
Aug-19 13,628 2,162 2 13,804 2,190 3 13,454 2,134 1
Sep-19 13,637 2,162 2 13,817 2,190 3 13,459 2,133 1
Oct-19 13,721 2,163 2 13,906 2,192 3 13,537 2,134 1
Nov-19 13,840 2,174 2 14,031 2,204 3 13,651 2,144 1
Dec-19 13,969 2,191 2 14,166 2,222 3 13,774 2,160 1
Jan-20 14,018 2,191 2 14,220 2,223 3 13,818 2,160 1
Feb-20 14,012 2,196 2 14,218 2,229 3 13,808 2,164 1
Mar-20 14,022 2,200 2 14,232 2,233 3 13,814 2,168 1
Apr-20 13,996 2,192 2 14,210 2,226 3 13,784 2,159 1
May-20 13,961 2,191 2 14,179 2,225 3 13,746 2,157 1
Jun-20 13,892 2,186 2 14,113 2,221 3 13,674 2,152 1
Jul-20 13,844 2,179 2 14,068 2,215 3 13,622 2,144 1
Aug-20 13,785 2,170 2 14,013 2,206 3 13,560 2,135 1
Sep-20 13,790 2,171 2 14,022 2,208 3 13,561 2,135 1
Oct-20 13,879 2,171 2 14,117 2,208 3 13,644 2,134 0
Nov-20 13,996 2,182 2 14,241 2,220 4 13,755 2,145 0
Dec-20 14,130 2,199 2 14,381 2,238 4 13,882 2,161 0
Jan-21 14,179 2,201 2 14,436 2,241 4 13,926 2,161 0
Feb-21 14,176 2,205 2 14,437 2,245 4 13,919 2,165 0
Roseburg -
Expected Growth
Roseburg -
High Growth
Roseburg -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 63 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
ROSEBURG

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Mar-21 14,187 2,209 2 14,453 2,250 4 13,925 2,168 0
Apr-21 14,162 2,202 2 14,432 2,244 4 13,896 2,160 0
May-21 14,128 2,200 2 14,402 2,242 4 13,859 2,158 0
Jun-21 14,056 2,195 2 14,333 2,238 4 13,784 2,152 0
Jul-21 14,010 2,188 2 14,290 2,232 4 13,734 2,145 0
Aug-21 13,948 2,179 2 14,232 2,223 4 13,669 2,135 0
Sep-21 13,954 2,180 2 14,242 2,225 4 13,671 2,135 0
Oct-21 14,043 2,180 2 14,338 2,225 4 13,753 2,135 -
Nov-21 14,161 2,191 2 14,463 2,237 4 13,865 2,145 -
Dec-21 14,296 2,208 2 14,605 2,255 4 13,992 2,161 -
Jan-22 14,345 2,209 2 14,660 2,258 4 14,036 2,162 -
Feb-22 14,344 2,213 2 14,663 2,262 4 14,030 2,165 -
Mar-22 14,355 2,217 2 14,679 2,267 4 14,037 2,168 -
Apr-22 14,331 2,210 2 14,659 2,261 4 14,009 2,161 -
May-22 14,297 2,208 2 14,629 2,260 4 13,971 2,158 -
Jun-22 14,224 2,203 2 14,559 2,255 4 13,895 2,152 -
Jul-22 14,178 2,196 2 14,517 2,249 4 13,846 2,145 -
Aug-22 14,115 2,188 2 14,457 2,241 4 13,780 2,136 -
Sep-22 14,122 2,188 2 14,469 2,242 4 13,782 2,136 -
Oct-22 14,211 2,188 2 14,565 2,243 5 13,865 2,135 -
Nov-22 14,330 2,200 2 14,691 2,256 5 13,976 2,146 -
Dec-22 14,465 2,217 2 14,835 2,274 5 14,103 2,162 -
Jan-23 14,516 2,218 2 14,892 2,275 5 14,148 2,161 -
Feb-23 14,515 2,223 2 14,896 2,281 5 14,143 2,166 -
Mar-23 14,527 2,226 2 14,913 2,285 5 14,150 2,168 -
Apr-23 14,503 2,219 2 14,893 2,278 5 14,122 2,160 -
May-23 14,469 2,217 2 14,863 2,277 5 14,084 2,158 -
Jun-23 14,397 2,213 2 14,794 2,274 5 14,010 2,153 -
Jul-23 14,350 2,206 2 14,750 2,267 5 13,959 2,146 -
Aug-23 14,288 2,197 2 14,691 2,259 5 13,894 2,136 -
Sep-23 14,294 2,198 2 14,702 2,260 5 13,896 2,136 -
Oct-23 14,383 2,198 2 14,799 2,261 5 13,978 2,136 -
Nov-23 14,502 2,209 2 14,926 2,273 5 14,089 2,146 -
Dec-23 14,637 2,226 2 15,070 2,291 5 14,215 2,162 -
Jan-24 14,688 2,227 2 15,127 2,294 5 14,260 2,162 -
Feb-24 14,688 2,231 2 15,132 2,299 5 14,256 2,165 -
Mar-24 14,700 2,235 2 15,149 2,303 5 14,263 2,169 -
Apr-24 14,676 2,228 2 15,129 2,297 5 14,235 2,161 -
May-24 14,642 2,226 2 15,099 2,296 5 14,197 2,159 -
Jun-24 14,570 2,222 2 15,030 2,292 5 14,123 2,154 -
Roseburg -
Expected Growth
Roseburg -
High Growth
Roseburg -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 64 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
ROSEBURG

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Jul-24 14,523 2,214 2 14,986 2,285 5 14,072 2,145 -
Aug-24 14,461 2,206 2 14,927 2,277 5 14,008 2,137 -
Sep-24 14,467 2,206 2 14,938 2,278 5 14,009 2,136 -
Oct-24 14,556 2,207 2 15,035 2,280 6 14,091 2,137 -
Nov-24 14,675 2,218 2 15,163 2,292 6 14,201 2,147 -
Dec-24 14,810 2,235 2 15,307 2,310 6 14,327 2,162 -
Jan-25 14,861 2,236 2 15,365 2,311 6 14,372 2,162 -
Feb-25 14,861 2,241 2 15,370 2,317 6 14,367 2,166 -
Mar-25 14,873 2,244 2 15,387 2,321 6 14,374 2,168 -
Apr-25 14,850 2,237 2 15,368 2,315 6 14,347 2,161 -
May-25 14,816 2,236 2 15,338 2,314 6 14,310 2,159 -
Jun-25 14,743 2,231 2 15,267 2,310 6 14,235 2,154 -
Jul-25 14,696 2,224 2 15,223 2,303 6 14,185 2,146 -
Aug-25 14,633 2,215 2 15,163 2,295 6 14,120 2,137 -
Sep-25 14,639 2,216 2 15,174 2,297 6 14,121 2,137 -
Oct-25 14,728 2,216 2 15,271 2,297 6 14,203 2,137 -
Nov-25 14,847 2,227 2 15,399 2,309 6 14,313 2,147 -
Dec-25 14,982 2,244 2 15,544 2,328 6 14,438 2,162 -
Jan-26 15,032 2,245 2 15,601 2,330 6 14,482 2,163 -
Feb-26 15,032 2,249 2 15,606 2,335 6 14,478 2,166 -
Mar-26 15,044 2,253 2 15,623 2,340 6 14,485 2,169 -
Apr-26 15,020 2,246 2 15,603 2,333 6 14,457 2,162 -
May-26 14,986 2,244 2 15,572 2,332 6 14,420 2,159 -
Jun-26 14,913 2,239 2 15,501 2,327 6 14,345 2,154 -
Jul-26 14,866 2,232 2 15,458 2,321 6 14,295 2,146 -
Aug-26 14,804 2,224 2 15,398 2,313 6 14,231 2,138 -
Sep-26 14,811 2,224 2 15,410 2,314 6 14,233 2,137 -
Oct-26 14,900 2,225 2 15,508 2,316 7 14,314 2,138 -
Nov-26 15,019 2,236 2 15,637 2,328 7 14,423 2,147 -
Dec-26 15,155 2,253 2 15,784 2,347 7 14,549 2,163 -
Jan-27 15,206 2,253 2 15,842 2,348 7 14,593 2,163 -
Feb-27 15,206 2,258 2 15,847 2,354 7 14,589 2,167 -
Mar-27 15,218 2,261 2 15,865 2,358 7 14,595 2,169 -
Apr-27 15,195 2,255 2 15,846 2,352 7 14,569 2,162 -
May-27 15,161 2,253 2 15,816 2,351 7 14,531 2,160 -
Jun-27 15,089 2,248 2 15,746 2,346 7 14,457 2,154 -
Jul-27 15,042 2,241 2 15,702 2,340 7 14,408 2,147 -
Aug-27 14,980 2,232 2 15,642 2,331 7 14,344 2,138 -
Sep-27 14,986 2,233 2 15,653 2,333 7 14,345 2,138 -
Oct-27 15,075 2,233 2 15,751 2,334 7 14,426 2,137 -
Roseburg -
Expected Growth
Roseburg -
High Growth
Roseburg -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 65 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
ROSEBURG

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Nov-27 15,194 2,245 2 15,881 2,347 7 14,535 2,148 -
Dec-27 15,330 2,262 2 16,028 2,365 7 14,660 2,164 -
Jan-28 15,381 2,263 2 16,086 2,367 7 14,704 2,163 -
Feb-28 15,381 2,268 2 16,091 2,373 7 14,700 2,167 -
Mar-28 15,393 2,271 2 16,109 2,377 7 14,706 2,170 -
Apr-28 15,370 2,264 2 16,090 2,370 7 14,680 2,162 -
May-28 15,335 2,262 2 16,059 2,369 7 14,641 2,160 -
Jun-28 15,264 2,258 2 15,989 2,365 7 14,569 2,155 -
Jul-28 15,216 2,251 2 15,944 2,359 7 14,519 2,148 -
Aug-28 15,153 2,242 2 15,883 2,350 7 14,454 2,138 -
Sep-28 15,159 2,242 2 15,894 2,351 7 14,456 2,138 -
Oct-28 15,248 2,243 2 15,992 2,352 8 14,536 2,138 -
Nov-28 15,366 2,254 2 16,121 2,365 8 14,644 2,148 -
Dec-28 15,501 2,271 2 16,268 2,383 8 14,768 2,163 -
Jan-29 15,552 2,271 2 16,326 2,384 8 14,812 2,163 -
Feb-29 15,552 2,276 2 16,331 2,390 8 14,808 2,167 -
Mar-29 15,563 2,280 2 16,348 2,395 8 14,813 2,170 -
Apr-29 15,540 2,273 2 16,328 2,389 8 14,787 2,163 -
May-29 15,505 2,271 2 16,297 2,387 8 14,749 2,161 -
Jun-29 15,433 2,266 2 16,226 2,383 8 14,676 2,155 -
Jul-29 15,385 2,259 2 16,180 2,376 8 14,626 2,148 -
Aug-29 15,321 2,250 2 16,117 2,367 8 14,561 2,139 -
Sep-29 15,327 2,251 2 16,128 2,369 8 14,563 2,139 -
Oct-29 15,415 2,251 2 16,226 2,370 8 14,642 2,138 -
Nov-29 15,533 2,262 2 16,355 2,382 8 14,750 2,148 -
Dec-29 15,668 2,279 2 16,502 2,401 8 14,874 2,164 -
Jan-30 15,718 2,281 2 16,559 2,403 8 14,917 2,164 -
Feb-30 15,717 2,285 2 16,563 2,408 8 14,912 2,168 -
Mar-30 15,728 2,289 2 16,579 2,413 8 14,918 2,171 -
Apr-30 15,704 2,282 2 16,559 2,406 8 14,890 2,164 -
May-30 15,669 2,280 2 16,527 2,405 8 14,853 2,161 -
Jun-30 15,596 2,275 2 16,455 2,400 8 14,779 2,156 -
Jul-30 15,547 2,268 2 16,407 2,393 8 14,729 2,148 -
Aug-30 15,482 2,259 2 16,342 2,384 8 14,664 2,139 -
Sep-30 15,486 2,260 2 16,350 2,386 8 14,664 2,140 -
Oct-30 15,572 2,260 2 16,445 2,386 9 14,742 2,139 -
Nov-30 15,689 2,271 2 16,573 2,399 9 14,849 2,149 -
Dec-30 15,822 2,288 2 16,718 2,417 9 14,972 2,165 -
Jan-31 15,870 2,288 2 16,772 2,418 9 15,013 2,165 -
Feb-31 15,868 2,293 2 16,774 2,424 9 15,008 2,169 -
Roseburg -
Expected Growth
Roseburg -
High Growth
Roseburg -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 66 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
ROSEBURG

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Mar-31 15,877 2,296 2 16,788 2,428 9 15,013 2,171 -
Apr-31 15,852 2,289 2 16,766 2,421 9 14,985 2,164 -
May-31 15,815 2,287 2 16,731 2,420 9 14,947 2,162 -
Jun-31 15,741 2,282 2 16,656 2,415 9 14,873 2,156 -
Jul-31 15,691 2,275 2 16,607 2,408 9 14,822 2,149 -
Aug-31 15,625 2,266 2 16,541 2,399 9 14,757 2,140 -
Sep-31 15,629 2,266 2 16,549 2,400 9 14,757 2,140 -
Oct-31 15,714 2,267 2 16,643 2,401 9 14,834 2,140 -
Nov-31 15,831 2,278 2 16,771 2,413 9 14,941 2,150 -
Dec-31 15,963 2,295 2 16,915 2,432 9 15,062 2,166 -
Jan-32 16,011 2,296 2 16,970 2,433 9 15,104 2,166 -
Feb-32 16,009 2,300 2 16,971 2,438 9 15,098 2,169 -
Mar-32 16,018 2,304 2 16,985 2,443 9 15,103 2,172 -
Apr-32 15,991 2,297 2 16,960 2,436 9 15,074 2,165 -
May-32 15,954 2,295 2 16,925 2,434 9 15,036 2,163 -
Jun-32 15,879 2,290 2 16,849 2,430 9 14,962 2,157 -
Jul-32 15,829 2,283 2 16,800 2,423 9 14,911 2,150 -
Aug-32 15,763 2,274 2 16,734 2,414 9 14,846 2,141 -
Sep-32 15,767 2,274 2 16,742 2,414 9 14,846 2,141 -
Oct-32 15,852 2,274 2 16,836 2,415 10 14,923 2,140 -
Nov-32 15,968 2,286 2 16,963 2,428 10 15,029 2,151 -
Dec-32 16,100 2,302 2 17,107 2,446 10 15,150 2,166 -
Jan-33 16,148 2,303 2 17,161 2,448 10 15,191 2,167 -
Feb-33 16,145 2,307 2 17,162 2,452 10 15,185 2,170 -
Mar-33 16,154 2,310 2 17,175 2,456 10 15,190 2,172 -
Apr-33 16,128 2,303 2 17,152 2,449 10 15,162 2,165 -
May-33 16,090 2,301 2 17,115 2,448 10 15,123 2,163 -
Jun-33 16,015 2,297 2 17,039 2,444 10 15,049 2,159 -
Jul-33 15,965 2,289 2 16,990 2,436 10 14,999 2,151 -
Aug-33 15,899 2,280 2 16,923 2,427 10 14,934 2,142 -
Sep-33 15,902 2,281 2 16,930 2,429 10 14,933 2,142 -
Oct-33 15,987 2,281 2 17,024 2,429 10 15,010 2,142 -
Nov-33 16,103 2,292 2 17,151 2,441 10 15,116 2,152 -
Dec-33 16,235 2,309 2 17,296 2,460 10 15,236 2,167 -
Jan-34 16,282 2,309 2 17,349 2,461 10 15,277 2,167 -
Feb-34 16,279 2,313 2 17,350 2,466 10 15,271 2,170 -
Mar-34 16,288 2,317 2 17,363 2,470 10 15,276 2,174 -
Apr-34 16,261 2,310 2 17,338 2,464 10 15,247 2,166 -
May-34 16,223 2,308 2 17,301 2,462 10 15,208 2,164 -
Jun-34 16,148 2,303 2 17,225 2,457 10 15,135 2,159 -
Jul-34 16,097 2,296 2 17,174 2,450 10 15,084 2,152 -
Roseburg -
Expected Growth
Roseburg -
High Growth
Roseburg -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 67 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
ROSEBURG

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Aug-34 16,031 2,287 2 17,108 2,441 10 15,019 2,143 -
Sep-34 16,034 2,287 2 17,114 2,442 10 15,018 2,143 -
Oct-34 16,119 2,287 2 17,209 2,442 11 15,095 2,142 -
Nov-34 16,235 2,299 2 17,336 2,455 11 15,200 2,153 -
Dec-34 16,367 2,315 2 17,481 2,473 11 15,321 2,167 -
Jan-35 16,414 2,317 2 17,535 2,475 11 15,361 2,168 -
Feb-35 16,411 2,321 2 17,535 2,480 11 15,355 2,172 -
Mar-35 16,419 2,324 2 17,548 2,484 11 15,360 2,174 -
Apr-35 16,392 2,317 2 17,522 2,477 11 15,331 2,167 -
May-35 16,355 2,315 2 17,487 2,475 11 15,293 2,165 -
Jun-35 16,279 2,310 2 17,409 2,470 11 15,219 2,160 -
Jul-35 16,229 2,303 2 17,359 2,463 11 15,169 2,153 -
Aug-35 16,162 2,294 2 17,291 2,454 11 15,103 2,144 -
Sep-35 16,165 2,295 2 17,298 2,456 11 15,103 2,144 -
Oct-35 16,251 2,295 2 17,394 2,456 11 15,180 2,144 -
Nov-35 16,366 2,306 2 17,521 2,469 11 15,284 2,153 -
Dec-35 16,498 2,323 2 17,666 2,487 11 15,404 2,169 -
Jan-36 16,546 2,323 2 17,721 2,488 11 15,446 2,169 -
Feb-36 16,543 2,327 2 17,721 2,493 11 15,439 2,172 -
Mar-36 16,551 2,331 2 17,734 2,498 11 15,444 2,175 -
Apr-36 16,524 2,324 2 17,709 2,491 11 15,415 2,168 -
May-36 16,487 2,322 2 17,673 2,489 11 15,377 2,166 -
Jun-36 16,411 2,317 2 17,595 2,485 11 15,303 2,161 -
Jul-36 16,361 2,309 2 17,545 2,477 11 15,253 2,153 -
Aug-36 16,294 2,301 2 17,477 2,469 11 15,188 2,145 -
Sep-36 16,297 2,301 2 17,484 2,469 11 15,187 2,145 -
Oct-36 16,382 2,301 2 17,579 2,470 12 15,263 2,144 -
Nov-36 16,498 2,312 2 17,707 2,482 12 15,368 2,154 -
Dec-36 16,630 2,329 2 17,852 2,501 12 15,488 2,169 -
Jan-37 16,677 2,330 2 17,906 2,502 12 15,528 2,170 -
Feb-37 16,674 2,335 2 17,907 2,508 12 15,522 2,174 -
Mar-37 16,682 2,338 2 17,919 2,511 12 15,527 2,176 -
Apr-37 16,655 2,331 2 17,894 2,504 12 15,498 2,169 -
May-37 16,618 2,329 2 17,858 2,503 12 15,461 2,167 -
Jun-37 16,542 2,324 2 17,780 2,498 12 15,387 2,162 -
Jul-37 16,492 2,317 2 17,730 2,491 12 15,337 2,155 -
Aug-37 16,425 2,308 2 17,662 2,482 12 15,271 2,146 -
Sep-37 16,428 2,308 2 17,668 2,482 12 15,271 2,145 -
Oct-37 16,513 2,308 2 17,764 2,483 12 15,347 2,145 -
Nov-37 16,629 2,320 2 17,892 2,496 12 15,451 2,156 -
Dec-37 16,761 2,336 2 18,038 2,514 12 15,571 2,170 -
Roseburg -
Expected Growth
Roseburg -
High Growth
Roseburg -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 68 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
KLAMATH FALLS

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Nov-17 14,651 1,776 7 14,754 1,788 7 14,549 1,763 7
Dec-17 14,751 1,777 7 14,860 1,790 7 14,643 1,764 7
Jan-18 14,834 1,784 7 14,949 1,798 7 14,719 1,770 7
Feb-18 14,857 1,787 7 14,978 1,801 7 14,737 1,772 7
Mar-18 14,854 1,783 7 14,980 1,798 7 14,728 1,768 7
Apr-18 14,825 1,778 7 14,957 1,794 7 14,694 1,762 7
May-18 14,786 1,774 7 14,923 1,790 7 14,650 1,758 7
Jun-18 14,705 1,768 7 14,847 1,785 7 14,564 1,751 7
Jul-18 14,617 1,759 7 14,763 1,776 7 14,472 1,742 7
Aug-18 14,544 1,748 7 14,694 1,766 7 14,395 1,730 7
Sep-18 14,548 1,752 7 14,702 1,771 7 14,395 1,733 6
Oct-18 14,695 1,762 7 14,856 1,781 7 14,535 1,743 6
Nov-18 14,841 1,780 7 15,008 1,800 7 14,675 1,760 6
Dec-18 14,961 1,782 7 15,134 1,803 8 14,789 1,761 6
Jan-19 15,031 1,793 7 15,210 1,814 8 14,853 1,772 6
Feb-19 15,045 1,802 7 15,229 1,824 8 14,862 1,780 6
Mar-19 15,038 1,796 7 15,227 1,818 8 14,851 1,773 6
Apr-19 15,011 1,789 7 15,204 1,812 8 14,819 1,766 6
May-19 14,968 1,783 7 15,166 1,806 8 14,772 1,759 6
Jun-19 14,881 1,776 7 15,082 1,800 8 14,682 1,752 6
Jul-19 14,795 1,771 7 15,000 1,795 8 14,592 1,746 6
Aug-19 14,726 1,762 7 14,934 1,787 8 14,520 1,737 6
Sep-19 14,730 1,763 7 14,943 1,788 8 14,519 1,738 6
Oct-19 14,877 1,773 7 15,097 1,799 8 14,660 1,747 6
Nov-19 15,024 1,789 7 15,250 1,816 8 14,800 1,762 6
Dec-19 15,144 1,795 7 15,377 1,822 8 14,914 1,767 6
Jan-20 15,213 1,809 7 15,452 1,837 8 14,977 1,780 6
Feb-20 15,225 1,814 7 15,468 1,843 8 14,984 1,785 6
Mar-20 15,217 1,810 7 15,465 1,839 8 14,972 1,780 6
Apr-20 15,189 1,803 7 15,441 1,832 8 14,940 1,773 6
May-20 15,145 1,800 7 15,401 1,830 8 14,892 1,769 6
Jun-20 15,057 1,793 7 15,316 1,823 8 14,801 1,762 6
Jul-20 14,973 1,787 7 15,236 1,818 8 14,714 1,756 6
Aug-20 14,905 1,782 7 15,171 1,813 8 14,642 1,750 5
Sep-20 14,910 1,778 7 15,181 1,810 8 14,642 1,746 5
Oct-20 15,057 1,785 7 15,336 1,818 8 14,782 1,752 5
Nov-20 15,205 1,805 7 15,492 1,839 8 14,923 1,771 5
Dec-20 15,325 1,809 7 15,619 1,843 9 15,035 1,774 5
Jan-21 15,394 1,820 7 15,694 1,856 9 15,098 1,785 5
Feb-21 15,406 1,824 7 15,712 1,860 9 15,105 1,789 5
Klamath Falls -
Low Growth
Klamath Falls -
Expected Growth
Klamath Falls -
High Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 69 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
KLAMATH FALLS

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Mar-21 15,399 1,820 7 15,709 1,857 9 15,093 1,784 5
Apr-21 15,371 1,814 7 15,686 1,851 9 15,061 1,778 5
May-21 15,328 1,810 7 15,647 1,848 9 15,014 1,773 5
Jun-21 15,241 1,804 7 15,563 1,842 9 14,924 1,767 5
Jul-21 15,157 1,797 7 15,482 1,836 9 14,837 1,759 5
Aug-21 15,089 1,790 7 15,418 1,829 9 14,766 1,752 5
Sep-21 15,094 1,789 7 15,428 1,829 9 14,766 1,750 5
Oct-21 15,241 1,797 7 15,583 1,838 9 14,905 1,758 5
Nov-21 15,390 1,816 7 15,741 1,858 9 15,046 1,776 5
Dec-21 15,510 1,819 7 15,869 1,861 9 15,158 1,778 5
Jan-22 15,578 1,831 7 15,944 1,874 9 15,219 1,789 5
Feb-22 15,591 1,837 7 15,962 1,881 9 15,227 1,794 5
Mar-22 15,583 1,832 7 15,959 1,876 9 15,214 1,789 5
Apr-22 15,556 1,825 7 15,936 1,870 9 15,183 1,781 5
May-22 15,513 1,821 7 15,898 1,866 9 15,136 1,777 5
Jun-22 15,426 1,815 7 15,814 1,860 9 15,046 1,770 5
Jul-22 15,342 1,808 7 15,733 1,854 9 14,960 1,763 5
Aug-22 15,275 1,801 7 15,669 1,847 9 14,889 1,755 4
Sep-22 15,280 1,800 7 15,679 1,847 9 14,889 1,754 4
Oct-22 15,427 1,809 7 15,836 1,857 9 15,027 1,762 4
Nov-22 15,576 1,827 7 15,994 1,876 9 15,168 1,779 4
Dec-22 15,696 1,831 7 16,122 1,881 9 15,279 1,782 4
Jan-23 15,765 1,844 7 16,199 1,894 10 15,341 1,794 4
Feb-23 15,777 1,849 7 16,216 1,900 10 15,348 1,798 4
Mar-23 15,771 1,844 7 16,216 1,896 10 15,337 1,793 4
Apr-23 15,744 1,838 7 16,193 1,890 10 15,306 1,786 4
May-23 15,701 1,834 7 16,154 1,886 10 15,259 1,782 4
Jun-23 15,614 1,827 7 16,070 1,880 10 15,169 1,775 4
Jul-23 15,530 1,821 7 15,989 1,874 10 15,083 1,768 4
Aug-23 15,463 1,814 7 15,925 1,868 10 15,013 1,761 4
Sep-23 15,468 1,813 7 15,935 1,867 10 15,013 1,759 4
Oct-23 15,615 1,821 7 16,092 1,876 10 15,150 1,766 4
Nov-23 15,764 1,840 7 16,251 1,896 10 15,290 1,784 4
Dec-23 15,884 1,843 7 16,380 1,900 10 15,401 1,787 4
Jan-24 15,953 1,855 7 16,457 1,914 10 15,463 1,798 4
Feb-24 15,965 1,860 7 16,474 1,920 10 15,469 1,803 4
Mar-24 15,958 1,855 7 16,473 1,915 10 15,458 1,797 4
Apr-24 15,931 1,849 7 16,450 1,910 10 15,426 1,791 4
May-24 15,888 1,845 7 16,411 1,906 10 15,380 1,786 4
Jun-24 15,801 1,839 7 16,327 1,900 10 15,290 1,780 4
Klamath Falls -
Low Growth
Klamath Falls -
Expected Growth
Klamath Falls -
High Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 70 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
KLAMATH FALLS

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Jul-24 15,717 1,832 7 16,245 1,894 10 15,204 1,772 4
Aug-24 15,650 1,826 7 16,181 1,888 10 15,134 1,766 3
Sep-24 15,654 1,824 7 16,190 1,887 10 15,133 1,764 3
Oct-24 15,802 1,832 7 16,349 1,896 10 15,272 1,771 3
Nov-24 15,950 1,851 7 16,507 1,916 10 15,410 1,789 3
Dec-24 16,070 1,855 7 16,637 1,921 11 15,521 1,792 3
Jan-25 16,139 1,867 7 16,713 1,933 11 15,582 1,803 3
Feb-25 16,151 1,872 7 16,731 1,939 11 15,589 1,807 3
Mar-25 16,144 1,868 7 16,729 1,936 11 15,577 1,802 3
Apr-25 16,117 1,861 7 16,707 1,929 11 15,546 1,795 3
May-25 16,074 1,857 7 16,667 1,926 11 15,500 1,791 3
Jun-25 15,987 1,850 7 16,583 1,919 11 15,411 1,783 3
Jul-25 15,903 1,844 7 16,501 1,913 11 15,325 1,777 3
Aug-25 15,835 1,837 7 16,435 1,907 11 15,255 1,770 3
Sep-25 15,840 1,836 7 16,446 1,906 11 15,255 1,768 3
Oct-25 15,987 1,844 7 16,603 1,915 11 15,391 1,775 3
Nov-25 16,135 1,863 7 16,762 1,935 11 15,529 1,793 3
Dec-25 16,255 1,867 7 16,892 1,940 11 15,640 1,796 3
Jan-26 16,323 1,879 7 16,968 1,953 11 15,700 1,807 3
Feb-26 16,335 1,884 7 16,986 1,959 11 15,707 1,811 3
Mar-26 16,328 1,880 7 16,984 1,955 11 15,695 1,807 3
Apr-26 16,301 1,873 7 16,961 1,948 11 15,664 1,799 3
May-26 16,258 1,869 7 16,922 1,945 11 15,618 1,795 3
Jun-26 16,170 1,863 7 16,835 1,939 11 15,529 1,789 3
Jul-26 16,086 1,856 7 16,753 1,933 11 15,443 1,781 3
Aug-26 16,018 1,849 7 16,687 1,926 11 15,373 1,774 2
Sep-26 16,022 1,848 7 16,696 1,925 11 15,373 1,773 2
Oct-26 16,169 1,856 7 16,854 1,934 11 15,509 1,780 2
Nov-26 16,317 1,875 7 17,014 1,955 11 15,646 1,798 2
Dec-26 16,436 1,879 7 17,143 1,959 12 15,756 1,801 2
Jan-27 16,504 1,890 7 17,219 1,972 12 15,816 1,811 2
Feb-27 16,516 1,895 7 17,237 1,978 12 15,823 1,816 2
Mar-27 16,508 1,891 7 17,233 1,974 12 15,811 1,811 2
Apr-27 16,481 1,884 7 17,210 1,967 12 15,780 1,804 2
May-27 16,437 1,880 7 17,169 1,964 12 15,733 1,800 2
Jun-27 16,349 1,874 7 17,083 1,958 12 15,644 1,793 2
Jul-27 16,265 1,867 7 17,000 1,951 12 15,560 1,786 2
Aug-27 16,196 1,861 7 16,932 1,946 12 15,489 1,780 2
Sep-27 16,200 1,859 7 16,941 1,944 12 15,489 1,777 2
Oct-27 16,347 1,867 7 17,100 1,953 12 15,625 1,785 2
Klamath Falls -
Low Growth
Klamath Falls -
Expected Growth
Klamath Falls -
High Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 71 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
KLAMATH FALLS

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Nov-27 16,494 1,886 7 17,259 1,974 12 15,761 1,802 2
Dec-27 16,613 1,890 7 17,388 1,978 12 15,870 1,806 2
Jan-28 16,681 1,902 7 17,464 1,991 12 15,930 1,816 2
Feb-28 16,692 1,907 7 17,481 1,997 12 15,936 1,820 2
Mar-28 16,684 1,903 7 17,477 1,993 12 15,924 1,816 2
Apr-28 16,656 1,896 7 17,453 1,986 12 15,893 1,809 2
May-28 16,613 1,893 7 17,413 1,984 12 15,847 1,805 2
Jun-28 16,524 1,886 7 17,324 1,977 12 15,758 1,798 2
Jul-28 16,439 1,879 7 17,239 1,970 12 15,673 1,791 2
Aug-28 16,370 1,873 7 17,171 1,964 12 15,603 1,785 1
Sep-28 16,373 1,871 7 17,179 1,963 12 15,602 1,783 1
Oct-28 16,519 1,880 7 17,336 1,973 12 15,737 1,791 1
Nov-28 16,665 1,898 7 17,494 1,992 12 15,872 1,807 1
Dec-28 16,784 1,902 7 17,623 1,997 12 15,982 1,811 1
Jan-29 16,851 1,913 7 17,698 2,010 13 16,041 1,821 1
Feb-29 16,861 1,919 7 17,713 2,016 13 16,047 1,827 1
Mar-29 16,852 1,914 7 17,708 2,012 13 16,034 1,821 1
Apr-29 16,824 1,908 7 17,683 2,006 13 16,004 1,815 1
May-29 16,779 1,904 7 17,640 2,002 13 15,957 1,811 1
Jun-29 16,690 1,897 7 17,551 1,995 13 15,868 1,804 1
Jul-29 16,604 1,890 7 17,465 1,988 13 15,783 1,797 1
Aug-29 16,534 1,884 7 17,395 1,982 13 15,713 1,791 1
Sep-29 16,536 1,882 7 17,401 1,981 13 15,711 1,788 1
Oct-29 16,681 1,891 7 17,557 1,991 13 15,845 1,797 1
Nov-29 16,827 1,909 7 17,715 2,010 13 15,981 1,813 1
Dec-29 16,945 1,913 7 17,843 2,015 13 16,089 1,817 1
Jan-30 17,011 1,925 7 17,917 2,027 13 16,148 1,827 1
Feb-30 17,021 1,931 7 17,931 2,034 13 16,154 1,833 1
Mar-30 17,012 1,926 7 17,926 2,029 13 16,142 1,827 1
Apr-30 16,982 1,920 7 17,898 2,023 13 16,110 1,821 1
May-30 16,937 1,916 7 17,855 2,020 13 16,063 1,817 1
Jun-30 16,847 1,909 7 17,764 2,013 13 15,975 1,810 1
Jul-30 16,761 1,903 7 17,677 2,007 13 15,890 1,804 1
Aug-30 16,691 1,896 7 17,607 2,000 13 15,820 1,797 0
Sep-30 16,693 1,895 7 17,613 1,999 13 15,818 1,796 0
Oct-30 16,838 1,903 7 17,770 2,008 13 15,952 1,803 0
Nov-30 16,983 1,922 7 17,926 2,029 13 16,086 1,820 0
Dec-30 17,101 1,925 7 18,055 2,032 13 16,194 1,823 0
Jan-31 17,167 1,938 7 18,129 2,046 14 16,253 1,834 0
Feb-31 17,177 1,943 7 18,143 2,052 14 16,259 1,839 0
Klamath Falls -
Low Growth
Klamath Falls -
Expected Growth
Klamath Falls -
High Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 72 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
KLAMATH FALLS

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Mar-31 17,167 1,938 7 18,136 2,047 14 16,246 1,834 0
Apr-31 17,137 1,932 7 18,109 2,041 14 16,214 1,828 0
May-31 17,092 1,928 7 18,065 2,037 14 16,168 1,823 0
Jun-31 17,002 1,921 7 17,974 2,030 14 16,080 1,816 0
Jul-31 16,916 1,915 7 17,887 2,024 14 15,995 1,810 0
Aug-31 16,846 1,908 7 17,817 2,018 14 15,925 1,803 -
Sep-31 16,849 1,907 7 17,824 2,017 14 15,924 1,802 -
Oct-31 16,994 1,915 7 17,981 2,026 14 16,058 1,809 -
Nov-31 17,140 1,934 7 18,140 2,046 14 16,192 1,827 -
Dec-31 17,258 1,937 7 18,269 2,050 14 16,300 1,829 -
Jan-32 17,324 1,949 7 18,343 2,064 14 16,358 1,841 -
Feb-32 17,334 1,954 7 18,358 2,070 14 16,364 1,845 -
Mar-32 17,325 1,949 7 18,352 2,065 14 16,352 1,840 -
Apr-32 17,295 1,943 7 18,325 2,059 14 16,320 1,834 -
May-32 17,250 1,939 7 18,281 2,055 14 16,274 1,829 -
Jun-32 17,160 1,932 7 18,190 2,048 14 16,185 1,822 -
Jul-32 17,075 1,926 7 18,104 2,042 14 16,101 1,816 -
Aug-32 17,005 1,919 7 18,034 2,035 14 16,032 1,809 -
Sep-32 17,007 1,918 7 18,040 2,035 14 16,030 1,808 -
Oct-32 17,153 1,926 7 18,199 2,044 14 16,164 1,815 -
Nov-32 17,299 1,945 7 18,358 2,064 14 16,297 1,833 -
Dec-32 17,417 1,949 7 18,488 2,069 14 16,405 1,836 -
Jan-33 17,483 1,961 7 18,562 2,082 15 16,463 1,846 -
Feb-33 17,493 1,966 7 18,577 2,088 15 16,469 1,851 -
Mar-33 17,484 1,962 7 18,572 2,084 15 16,457 1,847 -
Apr-33 17,455 1,955 7 18,545 2,077 15 16,426 1,840 -
May-33 17,409 1,951 7 18,500 2,073 15 16,379 1,835 -
Jun-33 17,320 1,945 7 18,410 2,067 15 16,291 1,829 -
Jul-33 17,234 1,938 7 18,323 2,060 15 16,206 1,822 -
Aug-33 17,165 1,931 7 18,254 2,053 15 16,138 1,815 -
Sep-33 17,167 1,930 7 18,260 2,053 15 16,136 1,814 -
Oct-33 17,312 1,938 7 18,419 2,062 15 16,269 1,821 -
Nov-33 17,459 1,957 7 18,579 2,082 15 16,403 1,838 -
Dec-33 17,576 1,961 7 18,708 2,087 15 16,509 1,842 -
Jan-34 17,643 1,972 7 18,784 2,100 15 16,568 1,852 -
Feb-34 17,653 1,977 7 18,799 2,106 15 16,574 1,857 -
Mar-34 17,644 1,973 7 18,793 2,102 15 16,561 1,852 -
Apr-34 17,615 1,966 7 18,767 2,095 15 16,530 1,845 -
May-34 17,570 1,962 7 18,723 2,091 15 16,484 1,841 -
Jun-34 17,480 1,956 7 18,632 2,085 15 16,396 1,835 -
Jul-34 17,395 1,949 7 18,545 2,078 15 16,313 1,828 -
Klamath Falls -
Low Growth
Klamath Falls -
Expected Growth
Klamath Falls -
High Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 73 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
KLAMATH FALLS

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Aug-34 17,325 1,943 7 18,475 2,072 15 16,243 1,822 -
Sep-34 17,327 1,941 7 18,481 2,071 15 16,242 1,820 -
Oct-34 17,472 1,949 7 18,640 2,080 15 16,374 1,827 -
Nov-34 17,618 1,968 7 18,800 2,101 15 16,507 1,844 -
Dec-34 17,736 1,972 7 18,930 2,105 15 16,614 1,848 -
Jan-35 17,802 1,984 7 19,005 2,118 16 16,672 1,858 -
Feb-35 17,812 1,989 7 19,020 2,124 16 16,677 1,862 -
Mar-35 17,803 1,985 7 19,014 2,120 16 16,665 1,858 -
Apr-35 17,774 1,978 7 18,988 2,113 16 16,634 1,851 -
May-35 17,728 1,974 7 18,943 2,109 16 16,588 1,847 -
Jun-35 17,639 1,968 7 18,852 2,103 16 16,501 1,841 -
Jul-35 17,553 1,961 7 18,764 2,096 16 16,416 1,834 -
Aug-35 17,484 1,955 7 18,695 2,091 16 16,348 1,828 -
Sep-35 17,486 1,953 7 18,701 2,089 16 16,346 1,826 -
Oct-35 17,632 1,961 7 18,862 2,098 16 16,479 1,833 -
Nov-35 17,778 1,980 7 19,022 2,119 16 16,611 1,850 -
Dec-35 17,896 1,984 7 19,153 2,123 16 16,718 1,853 -
Jan-36 17,962 1,996 7 19,228 2,136 16 16,775 1,864 -
Feb-36 17,973 2,001 7 19,244 2,142 16 16,782 1,868 -
Mar-36 17,963 1,997 7 19,238 2,139 16 16,769 1,864 -
Apr-36 17,934 1,990 7 19,212 2,132 16 16,738 1,857 -
May-36 17,889 1,987 7 19,168 2,129 16 16,692 1,854 -
Jun-36 17,800 1,980 7 19,077 2,122 16 16,605 1,847 -
Jul-36 17,714 1,973 7 18,989 2,115 16 16,521 1,840 -
Aug-36 17,645 1,967 7 18,919 2,109 16 16,453 1,834 -
Sep-36 17,647 1,965 7 18,926 2,107 16 16,451 1,832 -
Oct-36 17,792 1,974 7 19,086 2,117 16 16,582 1,840 -
Nov-36 17,939 1,992 7 19,248 2,137 16 16,715 1,856 -
Dec-36 18,056 1,996 7 19,378 2,142 16 16,821 1,859 -
Jan-37 18,123 2,008 7 19,454 2,155 17 16,879 1,870 -
Feb-37 18,133 2,014 7 19,469 2,162 17 16,885 1,875 -
Mar-37 18,124 2,009 7 19,464 2,157 17 16,872 1,870 -
Apr-37 18,095 2,003 7 19,437 2,151 17 16,842 1,864 -
May-37 18,049 1,999 7 19,392 2,147 17 16,795 1,860 -
Jun-37 17,960 1,992 7 19,301 2,140 17 16,708 1,853 -
Jul-37 17,874 1,985 7 19,213 2,133 17 16,625 1,846 -
Aug-37 17,805 1,979 7 19,143 2,127 17 16,557 1,840 -
Sep-37 17,807 1,977 7 19,149 2,126 17 16,555 1,838 -
Oct-37 17,952 1,986 7 19,310 2,136 17 16,686 1,845 -
Nov-37 18,099 2,004 7 19,472 2,156 17 16,819 1,862 -
Dec-37 18,216 2,008 7 19,603 2,160 17 16,923 1,865 -
Klamath Falls -
Low Growth
Klamath Falls -
Expected Growth
Klamath Falls -
High Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 74 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
LA GRANDE

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Nov-17 6,649 920 2 6,698 926 2 6,600 913 2
Dec-17 6,692 927 1 6,744 934 1 6,640 919 1
Jan-18 6,726 929 1 6,781 937 1 6,671 922 1
Feb-18 6,727 933 2 6,784 941 2 6,670 925 2
Mar-18 6,718 933 1 6,778 942 1 6,658 925 1
Apr-18 6,703 932 1 6,765 941 1 6,641 924 1
May-18 6,695 932 1 6,760 941 1 6,630 923 1
Jun-18 6,656 927 1 6,723 936 1 6,589 918 1
Jul-18 6,617 925 2 6,686 934 2 6,548 915 2
Aug-18 6,586 926 3 6,657 936 3 6,516 916 3
Sep-18 6,580 923 6 6,653 933 6 6,507 912 6
Oct-18 6,620 924 6 6,696 934 6 6,545 913 6
Nov-18 6,693 925 3 6,772 936 3 6,615 914 3
Dec-18 6,738 932 2 6,819 943 2 6,657 921 2
Jan-19 6,769 936 1 6,853 947 2 6,686 924 1
Feb-19 6,769 937 2 6,855 949 2 6,683 925 1
Mar-19 6,760 936 1 6,848 948 1 6,672 924 0
Apr-19 6,742 936 1 6,832 949 2 6,652 924 1
May-19 6,732 935 1 6,825 948 2 6,640 922 1
Jun-19 6,695 932 1 6,789 945 2 6,602 919 1
Jul-19 6,648 927 2 6,744 940 2 6,553 914 1
Aug-19 6,620 928 3 6,717 942 3 6,524 915 2
Sep-19 6,613 927 7 6,712 940 7 6,515 913 6
Oct-19 6,660 929 6 6,762 943 6 6,559 915 5
Nov-19 6,733 929 3 6,838 944 4 6,629 915 3
Dec-19 6,780 936 2 6,888 951 2 6,673 921 1
Jan-20 6,811 940 1 6,921 955 2 6,702 925 0
Feb-20 6,810 943 2 6,922 958 3 6,699 927 1
Mar-20 6,799 941 1 6,913 957 2 6,686 926 -
Apr-20 6,782 941 1 6,898 957 2 6,667 925 0
May-20 6,768 940 1 6,886 956 2 6,652 923 0
Jun-20 6,731 937 1 6,850 953 2 6,613 920 0
Jul-20 6,682 933 2 6,802 950 3 6,563 916 1
Aug-20 6,656 933 3 6,778 950 4 6,536 916 2
Sep-20 6,648 931 7 6,772 948 7 6,526 914 5
Oct-20 6,698 933 6 6,825 951 7 6,573 916 5
Nov-20 6,772 934 4 6,902 952 4 6,644 917 2
Dec-20 6,820 941 2 6,953 959 3 6,689 923 1
Jan-21 6,850 944 1 6,986 963 3 6,716 926 -
Feb-21 6,850 947 2 6,988 966 3 6,714 928 -
La Grande -
Expected Growth
La Grande -
High Growth
La Grande -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 75 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
LA GRANDE

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Mar-21 6,838 946 1 6,978 965 2 6,701 927 -
Apr-21 6,820 946 1 6,961 966 3 6,681 927 -
May-21 6,806 944 1 6,949 964 3 6,665 925 -
Jun-21 6,768 941 1 6,912 961 3 6,626 921 -
Jul-21 6,718 937 2 6,863 957 3 6,575 917 0
Aug-21 6,693 938 3 6,840 959 4 6,549 918 1
Sep-21 6,685 936 7 6,834 957 8 6,539 915 5
Oct-21 6,736 938 6 6,888 959 7 6,587 917 4
Nov-21 6,810 939 4 6,965 960 5 6,658 918 2
Dec-21 6,859 946 2 7,017 967 3 6,704 924 0
Jan-22 6,889 949 1 7,050 971 3 6,731 927 -
Feb-22 6,889 952 2 7,052 974 4 6,729 929 -
Mar-22 6,877 950 1 7,042 973 3 6,715 928 -
Apr-22 6,858 950 1 7,024 974 3 6,695 928 -
May-22 6,843 949 1 7,011 972 3 6,678 926 -
Jun-22 6,805 946 1 6,974 970 3 6,639 923 -
Jul-22 6,755 942 2 6,925 965 4 6,589 919 -
Aug-22 6,730 943 3 6,901 967 5 6,562 919 1
Sep-22 6,722 940 7 6,895 965 8 6,553 917 4
Oct-22 6,773 943 6 6,949 967 8 6,601 919 4
Nov-22 6,848 943 4 7,028 968 5 6,672 919 1
Dec-22 6,897 950 2 7,080 975 4 6,718 926 -
Jan-23 6,927 954 1 7,113 979 4 6,745 929 -
Feb-23 6,927 956 2 7,115 982 4 6,743 931 -
Mar-23 6,914 955 1 7,104 981 3 6,729 929 -
Apr-23 6,896 955 1 7,087 982 4 6,709 929 -
May-23 6,880 954 1 7,073 980 4 6,692 927 -
Jun-23 6,842 951 1 7,036 978 4 6,653 924 -
Jul-23 6,792 946 2 6,986 973 4 6,603 920 -
Aug-23 6,767 947 3 6,962 975 5 6,577 921 0
Sep-23 6,759 945 7 6,956 972 9 6,567 918 4
Oct-23 6,811 947 6 7,011 975 8 6,616 920 3
Nov-23 6,885 948 4 7,089 976 6 6,686 921 1
Dec-23 6,934 955 2 7,141 983 4 6,732 927 -
Jan-24 6,964 958 1 7,174 987 4 6,759 930 -
Feb-24 6,964 961 2 7,176 990 5 6,758 932 -
Mar-24 6,952 960 1 7,165 989 4 6,744 931 -
Apr-24 6,932 960 1 7,147 990 4 6,723 931 -
May-24 6,917 958 1 7,133 988 4 6,707 929 -
Jun-24 6,878 955 1 7,095 985 4 6,667 926 -
La Grande -
Expected Growth
La Grande -
High Growth
La Grande -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 76 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
LA GRANDE

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Jul-24 6,828 951 2 7,045 981 5 6,617 922 -
Aug-24 6,803 952 3 7,021 982 6 6,591 922 -
Sep-24 6,795 950 7 7,014 980 9 6,582 920 3
Oct-24 6,847 952 6 7,070 983 9 6,631 922 3
Nov-24 6,922 953 4 7,149 984 6 6,702 922 0
Dec-24 6,970 960 2 7,200 991 5 6,747 929 -
Jan-25 7,001 963 1 7,234 995 5 6,775 932 -
Feb-25 7,000 965 2 7,234 998 5 6,772 934 -
Mar-25 6,988 964 1 7,224 997 4 6,759 933 -
Apr-25 6,969 964 1 7,206 997 5 6,739 933 -
May-25 6,953 963 1 7,191 996 5 6,722 931 -
Jun-25 6,914 960 1 7,152 993 5 6,683 928 -
Jul-25 6,864 956 2 7,102 989 5 6,633 924 -
Aug-25 6,839 957 3 7,078 990 6 6,607 924 -
Sep-25 6,831 954 7 7,071 988 10 6,598 922 3
Oct-25 6,882 957 6 7,125 990 9 6,646 924 2
Nov-25 6,957 957 4 7,204 991 7 6,717 924 -
Dec-25 7,006 964 2 7,257 999 5 6,763 931 -
Jan-26 7,036 968 1 7,289 1,003 5 6,791 934 -
Feb-26 7,035 970 2 7,290 1,005 6 6,788 936 -
Mar-26 7,023 969 1 7,279 1,004 5 6,775 935 -
Apr-26 7,003 969 1 7,260 1,005 5 6,755 935 -
May-26 6,987 967 1 7,244 1,003 5 6,738 933 -
Jun-26 6,949 965 1 7,207 1,000 5 6,700 930 -
Jul-26 6,899 960 2 7,157 996 6 6,650 926 -
Aug-26 6,874 961 3 7,133 997 7 6,624 926 -
Sep-26 6,866 959 7 7,126 995 10 6,614 924 2
Oct-26 6,918 961 6 7,182 998 10 6,663 926 2
Nov-26 6,993 962 4 7,262 999 7 6,733 926 -
Dec-26 7,042 969 2 7,315 1,006 6 6,779 933 -
Jan-27 7,072 972 1 7,348 1,010 6 6,806 936 -
Feb-27 7,071 975 2 7,349 1,013 6 6,803 938 -
Mar-27 7,059 974 1 7,338 1,012 5 6,789 936 -
Apr-27 7,040 974 1 7,320 1,013 6 6,769 936 -
May-27 7,024 972 1 7,306 1,011 6 6,752 935 -
Jun-27 6,986 969 1 7,268 1,008 6 6,714 931 -
Jul-27 6,936 965 2 7,219 1,004 6 6,663 927 -
Aug-27 6,911 966 3 7,195 1,006 7 6,637 928 -
Sep-27 6,904 964 7 7,190 1,004 11 6,628 925 2
Oct-27 6,956 966 6 7,247 1,006 10 6,676 927 1
La Grande -
Expected Growth
La Grande -
High Growth
La Grande -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 77 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
LA GRANDE

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Nov-27 7,031 967 4 7,328 1,007 8 6,745 927 -
Dec-27 7,080 973 2 7,381 1,015 6 6,790 934 -
Jan-28 7,111 977 1 7,416 1,019 6 6,817 937 -
Feb-28 7,111 979 2 7,419 1,022 7 6,815 939 -
Mar-28 7,099 978 1 7,409 1,021 6 6,801 937 -
Apr-28 7,080 978 1 7,391 1,021 6 6,781 937 -
May-28 7,064 977 1 7,377 1,020 6 6,763 935 -
Jun-28 7,026 974 1 7,340 1,017 6 6,724 932 -
Jul-28 6,977 970 2 7,292 1,013 7 6,675 928 -
Aug-28 6,952 971 3 7,268 1,015 8 6,648 928 -
Sep-28 6,945 968 7 7,264 1,013 11 6,639 926 1
Oct-28 6,997 971 6 7,321 1,016 11 6,686 928 1
Nov-28 7,072 971 4 7,402 1,017 8 6,755 928 -
Dec-28 7,122 978 2 7,457 1,024 7 6,801 934 -
Jan-29 7,153 982 1 7,493 1,028 7 6,828 937 -
Feb-29 7,152 984 2 7,494 1,031 7 6,824 939 -
Mar-29 7,141 983 1 7,486 1,030 6 6,811 937 -
Apr-29 7,122 983 1 7,469 1,031 7 6,790 937 -
May-29 7,106 981 1 7,455 1,030 7 6,772 935 -
Jun-29 7,068 979 1 7,418 1,027 7 6,734 932 -
Jul-29 7,019 974 2 7,369 1,023 7 6,685 928 -
Aug-29 6,994 975 3 7,345 1,024 8 6,658 928 -
Sep-29 6,987 973 7 7,340 1,022 12 6,649 926 1
Oct-29 7,039 975 6 7,398 1,025 11 6,697 928 0
Nov-29 7,114 976 4 7,479 1,026 9 6,766 928 -
Dec-29 7,163 983 2 7,533 1,034 7 6,810 934 -
Jan-30 7,194 986 1 7,568 1,038 7 6,837 937 -
Feb-30 7,194 989 2 7,571 1,041 8 6,835 939 -
Mar-30 7,182 988 1 7,561 1,040 7 6,821 938 -
Apr-30 7,163 988 1 7,544 1,040 7 6,800 938 -
May-30 7,147 986 1 7,529 1,039 7 6,783 936 -
Jun-30 7,109 983 1 7,492 1,036 7 6,744 933 -
Jul-30 7,059 979 2 7,442 1,032 8 6,695 928 -
Aug-30 7,034 980 3 7,417 1,033 9 6,669 929 -
Sep-30 7,027 978 7 7,412 1,031 12 6,660 927 0
Oct-30 7,079 980 6 7,469 1,034 12 6,708 928 -
Nov-30 7,154 981 4 7,551 1,035 9 6,777 929 -
Dec-30 7,203 987 2 7,605 1,043 8 6,821 935 -
Jan-31 7,234 991 1 7,640 1,047 8 6,848 938 -
Feb-31 7,233 993 2 7,641 1,049 8 6,845 940 -
La Grande -
Expected Growth
La Grande -
High Growth
La Grande -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 78 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
LA GRANDE

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Mar-31 7,221 992 1 7,631 1,048 7 6,832 939 -
Apr-31 7,202 992 1 7,613 1,049 8 6,812 939 -
May-31 7,186 991 1 7,598 1,048 8 6,795 937 -
Jun-31 7,148 988 1 7,561 1,045 8 6,757 934 -
Jul-31 7,098 984 2 7,510 1,041 8 6,707 929 -
Aug-31 7,073 984 3 7,485 1,042 9 6,682 930 -
Sep-31 7,066 982 7 7,480 1,040 13 6,673 928 -
Oct-31 7,118 985 6 7,537 1,043 12 6,721 930 -
Nov-31 7,193 985 4 7,619 1,044 10 6,790 930 -
Dec-31 7,242 992 2 7,673 1,051 8 6,834 936 -
Jan-32 7,272 996 1 7,707 1,055 8 6,860 939 -
Feb-32 7,272 998 2 7,709 1,058 9 6,859 941 -
Mar-32 7,259 997 1 7,697 1,057 8 6,844 940 -
Apr-32 7,240 997 1 7,679 1,057 8 6,825 940 -
May-32 7,224 995 1 7,664 1,056 8 6,808 938 -
Jun-32 7,186 992 1 7,626 1,053 8 6,770 935 -
Jul-32 7,136 988 2 7,575 1,049 9 6,721 931 -
Aug-32 7,111 989 3 7,550 1,050 10 6,696 931 -
Sep-32 7,103 987 7 7,544 1,048 13 6,687 929 -
Oct-32 7,155 989 6 7,601 1,051 13 6,734 931 -
Nov-32 7,230 990 4 7,682 1,052 10 6,803 931 -
Dec-32 7,279 997 2 7,736 1,059 9 6,847 938 -
Jan-33 7,309 1,000 1 7,770 1,063 9 6,874 941 -
Feb-33 7,309 1,003 2 7,772 1,066 9 6,872 943 -
Mar-33 7,296 1,001 1 7,760 1,065 8 6,858 941 -
Apr-33 7,277 1,002 1 7,742 1,066 9 6,838 941 -
May-33 7,261 1,000 1 7,727 1,064 9 6,822 940 -
Jun-33 7,223 997 1 7,688 1,061 9 6,784 937 -
Jul-33 7,173 993 2 7,637 1,057 9 6,736 932 -
Aug-33 7,147 994 3 7,611 1,058 10 6,710 933 -
Sep-33 7,140 991 7 7,605 1,056 14 6,702 931 -
Oct-33 7,191 994 6 7,661 1,059 13 6,749 933 -
Nov-33 7,266 995 4 7,742 1,060 11 6,818 933 -
Dec-33 7,315 1,001 2 7,796 1,067 9 6,862 939 -
Jan-34 7,345 1,005 1 7,829 1,071 9 6,889 943 -
Feb-34 7,344 1,007 2 7,830 1,074 10 6,887 944 -
Mar-34 7,332 1,006 1 7,819 1,073 9 6,874 943 -
Apr-34 7,312 1,006 1 7,799 1,073 9 6,854 943 -
May-34 7,296 1,005 1 7,784 1,072 9 6,837 942 -
Jun-34 7,258 1,002 1 7,745 1,069 9 6,800 939 -
Jul-34 7,208 998 2 7,693 1,065 10 6,752 934 -
La Grande -
Expected Growth
La Grande -
High Growth
La Grande -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 79 of 829
APPENDIX 2.2: CUSTOMER FORECASTS BY REGION
LA GRANDE

Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Residential
Customers
Commercial
Customers
Industrial
Customers
Aug-34 7,182 998 3 7,667 1,066 11 6,726 935 -
Sep-34 7,175 996 7 7,661 1,064 14 6,719 933 -
Oct-34 7,226 998 6 7,717 1,066 14 6,765 935 -
Nov-34 7,301 999 4 7,798 1,067 11 6,834 935 -
Dec-34 7,349 1,006 2 7,851 1,075 10 6,877 941 -
Jan-35 7,380 1,010 1 7,886 1,079 10 6,905 945 -
Feb-35 7,379 1,012 2 7,886 1,082 10 6,903 947 -
Mar-35 7,366 1,011 1 7,874 1,081 9 6,889 946 -
Apr-35 7,347 1,011 1 7,855 1,081 10 6,870 945 -
May-35 7,331 1,009 1 7,840 1,079 10 6,854 943 -
Jun-35 7,292 1,006 1 7,800 1,076 10 6,816 940 -
Jul-35 7,242 1,002 2 7,747 1,072 10 6,768 936 -
Aug-35 7,216 1,003 3 7,721 1,073 11 6,743 937 -
Sep-35 7,209 1,001 7 7,715 1,071 15 6,735 935 -
Oct-35 7,260 1,003 6 7,771 1,074 14 6,781 937 -
Nov-35 7,335 1,004 4 7,852 1,075 12 6,850 938 -
Dec-35 7,383 1,011 2 7,905 1,082 10 6,894 944 -
Jan-36 7,414 1,014 1 7,939 1,086 10 6,922 947 -
Feb-36 7,412 1,017 2 7,938 1,089 11 6,919 949 -
Mar-36 7,400 1,015 1 7,927 1,087 10 6,907 947 -
Apr-36 7,380 1,016 1 7,907 1,089 10 6,887 948 -
May-36 7,364 1,014 1 7,891 1,087 10 6,871 946 -
Jun-36 7,325 1,011 1 7,850 1,084 10 6,833 943 -
Jul-36 7,275 1,007 2 7,798 1,079 11 6,785 939 -
Aug-36 7,250 1,008 3 7,773 1,081 12 6,761 940 -
Sep-36 7,242 1,005 7 7,765 1,078 15 6,752 937 -
Oct-36 7,293 1,008 6 7,821 1,081 15 6,799 940 -
Nov-36 7,368 1,008 4 7,903 1,081 12 6,868 940 -
Dec-36 7,416 1,015 2 7,956 1,089 11 6,911 946 -
Jan-37 7,447 1,019 1 7,990 1,093 11 6,939 950 -
Feb-37 7,445 1,021 2 7,989 1,096 11 6,936 951 -
Mar-37 7,433 1,020 1 7,978 1,095 10 6,924 950 -
Apr-37 7,413 1,020 1 7,958 1,095 11 6,904 950 -
May-37 7,397 1,019 1 7,942 1,094 11 6,888 949 -
Jun-37 7,358 1,016 1 7,901 1,091 11 6,851 946 -
Jul-37 7,308 1,011 2 7,849 1,086 11 6,803 941 -
Aug-37 7,282 1,012 3 7,822 1,087 12 6,778 942 -
Sep-37 7,275 1,010 7 7,816 1,085 16 6,770 940 -
Oct-37 7,326 1,012 6 7,872 1,087 15 6,816 942 -
Nov-37 7,401 1,013 4 7,954 1,089 13 6,885 942 -
Dec-37 7,449 1,020 2 8,006 1,096 11 6,929 949 -
La Grande -
Expected Growth
La Grande -
High Growth
La Grande -
Low Growth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 80 of 829
APPENDIX 2.3: DEMAND COEFFICIENTS

January February March April May June July August September October November December
HEAT COEFFICIENTS
WA | Residential 0.009971 0.009053 0.008839 0.006973 0.004386 0.002250 0.001231 0.002220 0.003217 0.006604 0.008988 0.009706
WA | Commercial 0.053158 0.052741 0.046207 0.034483 0.023712 0.013662 0.005341 0.021608 0.021270 0.034440 0.044822 0.052386 WA | Ind FirmSale 0.152593 0.162081 0.145640 0.175492 0.171513 0.220240 0.016786 0.182679 0.220748 0.111663 0.105711 0.119724
ID | Residential 0.009833 0.008896 0.009330 0.007446 0.005389 0.002417 0.001652 0.000535 0.003860 0.006948 0.009374 0.009923 ID | Commercial 0.039718 0.036697 0.032312 0.023848 0.015239 0.013154 0.003409 0.029932 0.011062 0.020519 0.031871 0.038011
ID | Ind FirmSale 0.170817 0.201851 0.100163 0.100872 0.138682 0.075238 0.197426 0.112444 0.110702 0.088493 0.119407 0.123984
Roseburg | Residential 0.011630 0.009587 0.009809 0.007535 0.005220 0.003216 0.001616 - 0.004154 0.007913 0.010520 0.012343 Roseburg | Commercial 0.050141 0.041226 0.041740 0.032942 0.025395 0.019063 0.009553 - 0.024100 0.034450 0.038878 0.048356
Roseburg | Ind FirmSale 0.033368 0.190335 0.054369 0.108225 0.074334 0.152983 0.099573 - 0.107618 0.161549 0.113511 0.063067
Medford | Residential 0.011013 0.010491 0.009985 0.008122 0.006630 0.004540 0.000188 - 0.003389 0.007070 0.009485 0.010848 Medford | Commercial 0.041792 0.039392 0.036600 0.029937 0.023166 0.021386 - - 0.022369 0.034150 0.037135 0.040772
Medford | Ind FirmSale 0.016071 0.037925 0.031213 0.068237 0.049327 0.091332 - - 0.191349 0.235975 0.122903 0.050094
La Grande | Residential 0.009009 0.008055 0.007211 0.005277 0.004571 0.002192 0.000389 0.012638 0.000063 0.003748 0.008159 0.008895
La Grande | Commercial 0.040793 0.035518 0.029200 0.018954 0.004460 0.002962 0.001004 0.075772 0.000797 0.012805 0.029008 0.037965 La Grande | Ind FirmSale - - - - - - 11.262884 5.257084 1.806537 1.106136 0.024894 -
Klam Falls | Residential 0.008258 0.007906 0.007254 0.005830 0.004592 0.002998 0.001448 0.000377 0.002152 0.004994 0.007559 0.008012
Klam Falls | Commercial 0.030364 0.029036 0.025170 0.019900 0.013838 0.009614 0.005768 0.006738 0.015708 0.020117 0.027158 0.029743 Klam Falls | Ind FirmSale 0.073756 0.094094 0.071758 0.084971 0.048154 0.063523 0.084896 0.252837 0.214762 0.143145 0.184839 0.098340
BASE COEFFICIENTS
WA | Residential 0.047723 0.047723 0.047723 0.047723 0.047723 0.047723 0.047723 0.047723 0.047723 0.047723 0.047723 0.047723
WA | Commercial 0.382871 0.382871 0.382871 0.382871 0.382871 0.382871 0.382871 0.382871 0.382871 0.382871 0.382871 0.382871
WA | Ind FirmSale 3.103665 3.103665 3.103665 3.103665 3.103665 3.103665 3.103665 3.103665 3.103665 3.103665 3.103665 3.103665
ID | Residential 0.044470 0.044470 0.044470 0.044470 0.044470 0.044470 0.044470 0.044470 0.044470 0.044470 0.044470 0.044470 ID | Commercial 0.392338 0.392338 0.392338 0.392338 0.392338 0.392338 0.392338 0.392338 0.392338 0.392338 0.392338 0.392338
ID | Ind FirmSale 4.975098 4.975098 4.975098 4.975098 4.975098 4.975098 4.975098 4.975098 4.975098 4.975098 4.975098 4.975098
Roseburg | Residential 0.034716 0.034716 0.034716 0.034716 0.034716 0.034716 0.034716 0.034716 0.034716 0.034716 0.034716 0.034716 Roseburg | Commercial 0.271081 0.271081 0.271081 0.271081 0.271081 0.271081 0.271081 0.271081 0.271081 0.271081 0.271081 0.271081
Roseburg | Ind FirmSale 2.233618 2.233618 2.233618 2.233618 2.233618 2.233618 2.233618 2.233618 2.233618 2.233618 2.233618 2.233618
Medford | Residential 0.046948 0.046948 0.046948 0.046948 0.046948 0.046948 0.046948 0.046948 0.046948 0.046948 0.046948 0.046948
Medford | Commercial 0.359543 0.359543 0.359543 0.359543 0.359543 0.359543 0.359543 0.359543 0.359543 0.359543 0.359543 0.359543 Medford | Ind FirmSale 4.180638 4.180638 4.180638 4.180638 4.180638 4.180638 4.180638 4.180638 4.180638 4.180638 4.180638 4.180638
La Grande | Residential 0.075894 0.075894 0.075894 0.075894 0.075894 0.075894 0.075894 0.075894 0.075894 0.075894 0.075894 0.075894
La Grande | Commercial 0.423491 0.423491 0.423491 0.423491 0.423491 0.423491 0.423491 0.423491 0.423491 0.423491 0.423491 0.423491 La Grande | Ind FirmSale 57.409752 57.409752 57.409752 57.409752 57.409752 57.409752 57.409752 57.409752 57.409752 57.409752 57.409752 57.409752
Klam Falls | Residential 0.032439 0.032439 0.032439 0.032439 0.032439 0.032439 0.032439 0.032439 0.032439 0.032439 0.032439 0.032439
Klam Falls | Commercial 0.223901 0.223901 0.223901 0.223901 0.223901 0.223901 0.223901 0.223901 0.223901 0.223901 0.223901 0.223901
Klam Falls | Ind FirmSale 3.595971 3.595971 3.595971 3.595971 3.595971 3.595971 3.595971 3.595971 3.595971 3.595971 3.595971 3.595971
SUPER PEAK*
WA | Residential 0.009577 0.009577 0.009577 WA | Commercial 0.052761 0.052761 0.052761
WA | Ind FirmSale 0.144799 0.144799 0.144799
ID | Residential 0.009551 0.009551 0.009551 ID | Commercial 0.038142 0.038142 0.038142
ID | Ind FirmSale 0.165551 0.165551 0.165551
Roseburg | Residential 0.011186 0.011186 0.011186
Roseburg | Commercial 0.046574 0.046574 0.046574 Roseburg | Ind FirmSale 0.095590 0.095590 0.095590
Medford NWP | Residential 0.010784 0.010784 0.010784
Medford NWP | Commercial 0.040652 0.040652 0.040652 Medford NWP | Ind FirmSale 0.034696 0.034696 0.034696
La Grande | Residential 0.008653 0.008653 0.008653
La Grande | Commercial 0.038092 0.038092 0.038092
La Grande | Ind FirmSale - - -
Klam Falls | Residential 0.008059 0.008059 0.008059 Klam Falls | Commercial 0.029714 0.029714 0.029714
Klam Falls | Ind FirmSale 0.088730 0.088730 0.088730
* Average of DEC JAN FEB heat coefficients
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 81 of 829
APPENDIX 2.3: WA BASE COEFFICIENT CALCULATION

Month
7 & 8
Year
2013
Average of Res Demand 6,501
Average of Com Demand 4,988
Average of Ind Demand 336
2014
Average of Res Demand 6,347
Average of Com Demand 5,526
Average of Ind Demand 355
2015
Average of Res Demand 6,625
Average of Com Demand 5,244
Average of Ind Demand 394
2016
Average of Res Demand 7,149
Average of Com Demand 5,908
Average of Ind Demand 410
2017
Average of Res Demand 6,574
Average of Com Demand 5,380
Average of Ind Demand 427
Total Average of Res Demand 6,639
Total Average of Com Demand 5,409
Total Average of Ind Demand 384
Month
7 & 8
Year
2013
Average of Res Cust 135,755
Average of Com Cust 14,185
Average of Ind Cust 134
2014
Average of Res Cust 137,356
Average of Com Cust 14,144
Average of Ind Cust 138
2015
Average of Res Cust 139,093
Average of Com Cust 14,173
Average of Ind Cust 135
2016
Average of Res Cust 141,755
Average of Com Cust 14,456
Average of Ind Cust 130
2017
Average of Res Cust 145,535
Average of Com Cust 14,551 Base Coefficients
Average of Ind Cust 133 (Actual Average Demand/Customer Count)
Total Average of Res Cust 139,898 0.047458 Res Base Usage
Total Average of Com Cust 14,302 0.378215 Com Base Usage
Total Average of Ind Cust 134 2.874961 Ind Base Usage
WA
Average Actual Demand by Class
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 82 of 829
APPENDIX 2.3: ID BASE COEFFICIENT CALCULATION

Month
7 & 8
Year
2013
Average of Res Demand 3,092
Average of Com Demand 2,886
Average of Ind Demand 457
2014
Average of Res Demand 3,276
Average of Com Demand 2,868
Average of Ind Demand 643
2015
Average of Res Demand 2,979
Average of Com Demand 3,511
Average of Ind Demand 436
2016
Average of Res Demand 3,361
Average of Com Demand 3,322
Average of Ind Demand 509
2017
Average of Res Demand 3,140
Average of Com Demand 3,464
Average of Ind Demand 495
Total Average of Res Demand 3,170
Total Average of Com Demand 3,210
Total Average of Ind Demand 508
Month
7 & 8
Year
2013
Average of Res Cust 67,390
Average of Com Cust 8,541
Average of Ind Cust 94
2014
Average of Res Cust 68,329
Average of Com Cust 8,527
Average of Ind Cust 100
2015
Average of Res Cust 69,436
Average of Com Cust 8,613
Average of Ind Cust 100
2016
Average of Res Cust 71,062
Average of Com Cust 8,751
Average of Ind Cust 97
2017
Average of Res Cust 72,686
Average of Com Cust 8,881 Base Coefficients
Average of Ind Cust 93 (Actual Average Demand/Customer Count)
Total Average of Res Cust 69,780 0.045423 Res Base Usage
Total Average of Com Cust 8,663 0.370569 Com Base Usage
Total Average of Ind Cust 97 5.263706 Ind Base Usage
ID
Average Actual Demand by Class
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 83 of 829
APPENDIX 2.3: MEDFORD BASE COEFFICIENT CALCULATION

Month
7 & 8
Year
2013
Average of Res Demand 2,323
Average of Com Demand 2,160
Average of Ind Demand 43
2014
Average of Res Demand 2,290
Average of Com Demand 2,253
Average of Ind Demand 54
2015
Average of Res Demand 2,316
Average of Com Demand 2,303
Average of Ind Demand 60
2016
Average of Res Demand 2,582
Average of Com Demand 2,487
Average of Ind Demand 60
2017
Average of Res Demand 2,596
Average of Com Demand 2,487
Average of Ind Demand 68
Total Average of Res Demand 2,421
Total Average of Com Demand 2,338
Total Average of Ind Demand 57
Month
7 & 8
Year
2013
Average of Res Cust 51,090
Average of Com Cust 6,516
Average of Ind Cust 16
2014
Average of Res Cust 51,662
Average of Com Cust 6,592
Average of Ind Cust 17
2015
Average of Res Cust 52,605
Average of Com Cust 6,596
Average of Ind Cust 15
2016
Average of Res Cust 53,084
Average of Com Cust 6,796
Average of Ind Cust 15
2017
Average of Res Cust 53,920
Average of Com Cust 6,850 Base Coefficients
Average of Ind Cust 15 (Actual Average Demand/Customer Count)
Total Average of Res Cust 52,472 0.046145 Res Base Usage
Total Average of Com Cust 6,670 0.350570 Com Base Usage
Total Average of Ind Cust 16 3.651363 Ind Base Usage
Medford
Average Actual Demand by Class
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 84 of 829
APPENDIX 2.3: ROSEBURG BASE COEFFICIENT CALCULATION

Month
7 & 8
Year
2013
Average of Res Demand 551
Average of Com Demand 665
Average of Ind Demand 39
2014
Average of Res Demand 400
Average of Com Demand 484
Average of Ind Demand 26
2015
Average of Res Demand 430
Average of Com Demand 557
Average of Ind Demand 4
2016
Average of Res Demand 466
Average of Com Demand 557
Average of Ind Demand 4
2017
Average of Res Demand 486
Average of Com Demand 628
Average of Ind Demand 5
Total Average of Res Demand 467
Total Average of Com Demand 578
Total Average of Ind Demand 16
Month
7 & 8
Year
2013
Average of Res Cust 13,020
Average of Com Cust 2,120
Average of Ind Cust 3
2014
Average of Res Cust 13,063
Average of Com Cust 2,127
Average of Ind Cust 3
2015
Average of Res Cust 13,227
Average of Com Cust 2,130
Average of Ind Cust 2
2016
Average of Res Cust 13,242
Average of Com Cust 2,156
Average of Ind Cust 2
2017
Average of Res Cust 13,337
Average of Com Cust 2,141 Base Coefficients
Average of Ind Cust 2 (Actual Average Demand/Customer Count)
Total Average of Res Cust 13,178 0.035406 Res Base Usage
Total Average of Com Cust 2,135 0.270835 Com Base Usage
Total Average of Ind Cust 2 6.521993 Ind Base Usage
Roseburg
Average Actual Demand by Class
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 85 of 829
APPENDIX 2.3: KLAMATH FALLS BASE COEFFICIENT CALCULATION

Month
7 & 8
Year
2013
Average of Res Demand 531
Average of Com Demand 433
Average of Ind Demand 24
2014
Average of Res Demand 515
Average of Com Demand 442
Average of Ind Demand 22
2015
Average of Res Demand 531
Average of Com Demand 484
Average of Ind Demand 30
2016
Average of Res Demand 397
Average of Com Demand 308
Average of Ind Demand 19
2017
Average of Res Demand 458
Average of Com Demand 361
Average of Ind Demand 26
Total Average of Res Demand 486
Total Average of Com Demand 406
Total Average of Ind Demand 24
Month
7 & 8
Year
2013
Average of Res Cust 13,857
Average of Com Cust 1,646
Average of Ind Cust 8
2014
Average of Res Cust 13,872
Average of Com Cust 1,652
Average of Ind Cust 8
2015
Average of Res Cust 14,106
Average of Com Cust 1,667
Average of Ind Cust 7
2016
Average of Res Cust 14,206
Average of Com Cust 1,722
Average of Ind Cust 7
2017
Average of Res Cust 14,397
Average of Com Cust 1,762 Base Coefficients
Average of Ind Cust 7 (Actual Average Demand/Customer Count)
Total Average of Res Cust 14,088 0.034518 Res Base Usage
Total Average of Com Cust 1,689 0.240100 Com Base Usage
Total Average of Ind Cust 7 3.292121 Ind Base Usage
Klamath Falls
Average Actual Demand by Class
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 86 of 829
APPENDIX 2.3: LA GRANDE BASE COEFFICIENT CALCULATION

Month
7 & 8
Year
2013
Average of Res Demand 530
Average of Com Demand 380
Average of Ind Demand 63
2014
Average of Res Demand 541
Average of Com Demand 389
Average of Ind Demand 165
2015
Average of Res Demand 554
Average of Com Demand 441
Average of Ind Demand 122
2016
Average of Res Demand 497
Average of Com Demand 377
Average of Ind Demand 192
2017
Average of Res Demand 439
Average of Com Demand 338
Average of Ind Demand 202
Total Average of Res Demand 512
Total Average of Com Demand 385
Total Average of Ind Demand 149
Month
7 & 8
Year
2013
Average of Res Cust 6,456
Average of Com Cust 894
Average of Ind Cust 4
2014
Average of Res Cust 6,496
Average of Com Cust 892
Average of Ind Cust 3
2015
Average of Res Cust 6,547
Average of Com Cust 897
Average of Ind Cust 4
2016
Average of Res Cust 6,529
Average of Com Cust 919
Average of Ind Cust 3
2017
Average of Res Cust 6,565
Average of Com Cust 914 Base Coefficients
Average of Ind Cust 3 (Actual Average Demand/Customer Count)
Total Average of Res Cust 6,518 0.078587 Res Base Usage
Total Average of Com Cust 903 0.426358 Com Base Usage
Total Average of Ind Cust 3 48.029588 Ind Base Usage
La Grande
Average Actual Demand by Class
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 87 of 829
APPENDIX 2.4: HEATING DEGREE DAY DATA MONTHLY TABLES

Temperature Pattern WA/ID
Gas Year Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct
Annual
Total
2017-2018 868 1,155 1,111 920 772 561 331 139 26 25 165 529 6,601
2018-2019 866 1,149 1,119 914 780 556 328 141 22 21 175 540 6,609
2019-2020 876 1,154 1,119 915 789 561 316 136 20 24 166 539 6,616
2020-2021 868 1,138 1,117 912 785 549 310 138 21 23 171 539 6,571
2021-2022 891 1,155 1,118 920 785 568 312 144 24 24 177 535 6,652
2022-2023 873 1,147 1,116 927 785 557 327 144 24 24 175 539 6,636
2023-2024 862 1,156 1,119 917 772 562 323 135 21 24 168 550 6,610
2024-2025 866 1,153 1,107 931 783 557 319 144 25 23 175 546 6,629
2025-2026 869 1,151 1,103 915 783 554 326 144 22 22 172 552 6,614
2026-2027 872 1,137 1,106 910 777 555 322 137 25 24 167 535 6,568
2027-2028 875 1,150 1,107 911 782 561 319 132 21 24 170 528 6,580
2028-2029 869 1,155 1,117 921 780 555 328 140 24 25 164 528 6,606
2029-2030 862 1,156 1,112 921 789 562 316 140 20 22 170 536 6,606
2030-2031 868 1,156 1,123 902 791 553 322 138 22 23 171 532 6,601
2031-2032 874 1,142 1,121 916 769 558 317 140 23 23 168 539 6,590
2032-2033 863 1,133 1,110 916 769 554 316 136 22 25 169 543 6,556
2033-2034 876 1,161 1,126 920 777 573 318 134 23 23 169 537 6,637
2034-2035 865 1,152 1,112 912 779 561 331 142 23 24 169 541 6,612
2035-2036 877 1,152 1,116 911 788 555 315 142 23 24 170 543 6,616
2036-2037 859 1,154 1,116 922 801 564 318 141 20 23 169 536 6,624
Temperature Pattern Klamath Falls
Gas Year Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct
Annual
Total
2017-2018 866 1,086 1,076 853 805 672 445 221 46 61 230 555 6,916
2018-2019 871 1,096 1,077 865 817 668 447 222 45 62 225 560 6,954
2019-2020 866 1,101 1,075 878 810 674 439 215 45 62 219 558 6,943
2020-2021 861 1,104 1,073 875 807 665 452 223 43 55 224 555 6,938
2021-2022 875 1,102 1,075 855 802 663 433 215 47 64 225 555 6,910
2022-2023 857 1,104 1,059 858 817 672 432 217 44 61 225 548 6,895
2023-2024 872 1,092 1,070 865 817 662 448 216 47 60 224 552 6,927
2024-2025 876 1,099 1,064 858 811 677 442 219 42 61 221 554 6,924
2025-2026 867 1,093 1,082 866 809 656 448 213 43 58 227 561 6,924
2026-2027 869 1,097 1,047 866 817 656 436 230 46 60 218 561 6,902
2027-2028 869 1,098 1,044 862 806 659 449 219 45 65 217 560 6,894
2028-2029 869 1,098 1,071 864 819 668 446 223 46 64 213 557 6,937
2029-2030 860 1,105 1,063 870 797 657 451 223 48 63 219 552 6,908
2030-2031 859 1,105 1,056 873 806 670 460 222 42 62 229 557 6,940
2031-2032 869 1,095 1,074 849 816 665 446 220 47 59 220 548 6,908
2032-2033 863 1,092 1,062 870 817 672 440 219 47 62 226 554 6,923
2033-2034 866 1,095 1,052 853 803 675 451 218 46 64 220 554 6,898
2034-2035 867 1,108 1,068 868 807 666 445 214 45 59 219 557 6,923
2035-2036 860 1,101 1,072 873 808 675 455 216 45 59 217 560 6,941
2036-2037 865 1,091 1,080 861 801 665 450 223 46 60 221 556 6,919
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 88 of 829
APPENDIX 2.4: HEATING DEGREE DAY DATA MONTHLY TABLES

Medford
Gas Year Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct
Annual
Total
2017-2018 599 819 776 586 533 381 203 52 3 4 50 295 4,302
2018-2019 600 821 778 595 531 376 200 53 3 4 49 296 4,304
2019-2020 595 818 779 601 531 379 198 52 3 4 50 286 4,296
2020-2021 589 815 781 589 533 384 198 53 2 4 47 297 4,293
2021-2022 598 812 782 592 530 382 202 56 2 4 47 295 4,302
2022-2023 595 809 790 584 526 378 198 56 3 4 50 299 4,293
2023-2024 606 818 775 589 544 391 189 52 3 4 48 292 4,312
2024-2025 601 813 790 588 529 373 191 56 3 4 46 297 4,291
2025-2026 605 813 784 587 529 379 195 57 3 3 51 295 4,302
2026-2027 603 810 779 595 529 378 205 54 2 4 49 287 4,296
2027-2028 599 825 783 595 524 382 197 52 3 4 53 296 4,313
2028-2029 598 809 776 587 524 378 205 55 2 3 50 293 4,279
2029-2030 605 796 777 587 520 382 198 53 3 3 49 291 4,264
2030-2031 603 809 778 591 518 386 203 58 3 3 49 287 4,287
2031-2032 602 819 773 594 537 386 198 54 3 4 49 297 4,315
2032-2033 595 815 783 587 515 377 194 54 3 4 46 295 4,267
2033-2034 604 815 782 594 537 381 199 55 3 4 51 296 4,320
2034-2035 592 814 782 594 528 385 191 58 3 4 46 297 4,293
2035-2036 601 815 773 591 534 369 197 56 3 3 51 291 4,284
2036-2037 599 811 780 595 530 382 199 55 3 4 47 296 4,300
Roseburg
Gas Year Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct
Annual
Total
2017-2018 531 707 675 544 506 380 223 83 5 5 56 280 3,995
2018-2019 529 710 677 556 506 384 219 81 5 4 56 276 4,003
2019-2020 525 709 686 558 505 384 219 81 5 4 56 278 4,009
2020-2021 523 710 684 546 506 381 225 79 5 5 56 282 4,001
2021-2022 528 707 689 548 502 382 226 83 5 5 56 277 4,006
2022-2023 528 700 698 539 498 379 225 78 5 4 53 275 3,981
2023-2024 535 709 679 545 517 385 216 79 5 5 56 275 4,006
2024-2025 531 700 692 545 497 383 226 85 4 5 55 270 3,993
2025-2026 534 704 691 545 502 388 214 81 5 4 53 277 3,998
2026-2027 535 701 681 551 501 386 224 82 5 4 54 281 4,007
2027-2028 529 715 687 552 499 381 221 77 6 5 56 282 4,010
2028-2029 528 701 674 544 495 395 223 77 5 4 55 280 3,980
2029-2030 534 695 682 543 493 374 217 75 5 4 56 270 3,948
2030-2031 534 703 686 546 490 376 222 78 4 4 56 275 3,974
2031-2032 535 712 674 551 508 370 220 78 5 4 56 275 3,990
2032-2033 524 705 685 543 486 385 213 80 4 4 53 272 3,955
2033-2034 535 708 683 551 506 379 209 81 5 5 55 272 3,990
2034-2035 521 705 685 552 497 382 215 79 5 4 54 282 3,981
2035-2036 529 708 677 547 504 379 216 79 5 5 54 275 3,977
2036-2037 529 702 682 554 503 370 219 75 5 5 55 273 3,972
Temperature Pattern
Temperature Pattern
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 89 of 829
APPENDIX 2.4: HEATING DEGREE DAY DATA MONTHLY TABLES

La Grande
Gas Year Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct
Annual
Total
2017-2018 768 1,051 1,034 810 726 554 357 156 25 34 192 518 6,224
2018-2019 768 1,049 1,022 821 717 556 353 156 21 33 189 510 6,197
2019-2020 783 1,053 1,021 816 717 551 349 157 24 34 186 515 6,205
2020-2021 776 1,054 1,022 817 721 549 361 150 24 33 190 517 6,213
2021-2022 785 1,056 1,026 818 721 556 348 150 29 34 187 513 6,224
2022-2023 778 1,053 1,032 818 723 558 356 152 28 33 192 504 6,227
2023-2024 771 1,065 1,019 808 726 564 352 148 25 36 194 514 6,222
2024-2025 785 1,056 1,030 813 713 552 352 144 24 35 189 508 6,199
2025-2026 763 1,062 1,033 818 727 554 351 152 29 34 189 517 6,231
2026-2027 768 1,058 1,028 820 720 553 357 155 26 33 188 513 6,219
2027-2028 776 1,052 1,025 808 724 556 362 156 26 35 191 519 6,229
2028-2029 784 1,056 1,032 814 722 560 358 153 24 35 192 517 6,249
2029-2030 770 1,057 1,019 809 727 553 351 155 23 33 187 512 6,197
2030-2031 763 1,054 1,017 811 718 558 350 149 26 34 187 517 6,183
2031-2032 779 1,045 1,025 810 711 553 353 150 24 35 194 504 6,185
2032-2033 770 1,054 1,016 812 718 552 353 152 24 34 189 504 6,179
2033-2034 766 1,050 1,030 819 719 559 350 150 26 34 193 508 6,203
2034-2035 772 1,050 1,035 810 720 559 353 151 24 31 189 518 6,211
2035-2036 787 1,050 1,025 812 715 555 353 148 26 35 192 514 6,213
2036-2037 762 1,045 1,018 815 709 562 352 150 27 32 192 510 6,174
Temperature Pattern
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 90 of 829
APPENDIX 2.4: HEATING DEGREE DAILY MONTH BY AREA

WA/ID
Day Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1 38 35 30 22 14 3 0 0 0 9 25 34
2 38 34 29 23 13 6 0 0 0 12 25 34
3 39 34 29 23 13 5 0 0 1 13 26 35
4 36 32 28 22 13 4 0 0 0 13 26 36
5 37 32 27 22 14 5 0 0 2 14 27 36
6 36 32 27 20 15 5 0 0 3 12 26 37
7 35 33 27 19 13 4 0 0 2 12 25 38
8 35 33 28 19 12 6 0 0 2 14 25 38
9 35 33 27 20 13 6 0 0 3 15 26 38
10 36 33 26 19 12 7 0 0 3 17 27 36
11 38 33 25 19 10 7 0 0 2 17 28 36
12 38 31 24 18 10 4 0 0 1 18 26 35
13 36 62 23 19 12 4 0 0 1 15 26 35
14 35 72 23 21 9 5 0 0 1 15 28 35
15 38 82 23 22 9 5 0 0 1 17 27 36
16 38 67 24 19 8 4 0 0 3 17 27 37
17 36 57 25 19 8 4 0 0 5 15 28 37
18 34 31 25 18 8 4 0 0 5 17 29 51
19 35 31 25 17 8 4 0 0 6 16 29 56
20 35 31 24 15 10 3 0 0 8 17 29 61
21 35 30 24 14 9 1 0 0 9 18 31 58
22 35 30 24 15 9 0 0 0 7 17 32 53
23 34 32 24 16 8 1 0 0 7 19 32 38
24 35 34 23 17 7 1 0 0 6 20 33 37
25 33 34 23 16 8 1 0 0 5 21 31 37
26 34 34 24 16 8 0 0 0 7 22 31 38
27 35 32 23 14 7 0 0 0 7 22 33 36
28 35 31 24 15 7 0 0 0 6 22 35 36
29 33 28 22 16 7 0 0 0 6 24 35 37
30 33 65 21 14 5 0 0 0 8 24 34 39
31 33 65 22 65 4 65 0 0 65 24 65 40
Total 1103 1243 773 614 303 164 0 0 182 528 927 1230
Medford
Day Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1 26 24 19 15 8 0 0 0 0 3 15 25
2 26 22 19 15 7 0 0 0 0 6 17 24
3 28 21 21 15 7 0 0 0 0 6 16 25
4 27 21 19 15 8 0 0 0 0 6 17 26
5 26 22 20 15 9 0 0 0 0 6 17 26
6 26 21 20 13 8 0 0 0 0 5 16 25
7 23 20 20 14 7 0 0 0 0 5 16 27
8 24 23 19 14 7 1 0 0 0 6 18 26
9 25 21 18 14 8 1 0 0 0 7 20 24
10 25 22 18 13 8 2 0 0 0 9 18 26
11 24 21 16 13 7 2 0 0 0 10 18 27
12 24 20 16 13 6 0 0 0 0 10 18 25
13 26 32 15 14 5 0 0 0 0 7 18 24
14 26 36 16 16 4 0 0 0 0 7 18 25
15 26 38 16 16 4 0 0 0 0 9 19 27
16 26 32 16 13 4 0 0 0 0 7 20 27
17 26 28 18 12 4 0 0 0 0 8 21 27
18 24 20 16 12 4 0 0 0 0 9 22 50
19 24 21 15 12 5 0 0 0 0 8 20 59
20 26 20 15 10 5 0 0 0 0 10 21 61
21 25 20 14 11 5 0 0 0 0 11 22 56
22 24 21 15 10 4 0 0 0 0 10 22 55
23 24 22 16 11 3 0 0 0 0 11 23 26
24 23 20 15 11 3 0 0 0 0 12 23 27
25 22 21 17 10 3 0 0 0 0 13 21 27
26 23 22 17 10 1 0 0 0 0 13 23 27
27 25 20 17 10 3 0 0 0 0 14 24 26
28 24 20 16 10 3 0 0 0 0 13 23 25
29 23 21 15 9 2 0 0 0 0 14 24 26
30 24 65 15 8 0 0 0 0 1 13 25 27
31 25 65 15 65 0 65 0 0 65 14 65 27
Total 770 802 524 439 152 71 0 0 66 282 660 955
Temperature Pattern
Temperature Pattern
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 91 of 829
APPENDIX 2.4: HEATING DEGREE DAILY MONTH BY AREA

LaGrande
Day Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1 37 32 27 22 14 5 0 0 2 10 24 29
2 35 31 25 22 14 6 0 0 3 12 22 31
3 36 31 27 22 14 6 0 0 2 13 23 32
4 35 28 26 21 14 4 0 0 2 14 22 32
5 35 28 24 21 14 6 0 0 2 15 23 34
6 34 28 26 19 14 6 0 0 3 13 21 33
7 31 28 25 19 13 5 0 0 4 12 22 35
8 30 29 26 19 14 7 0 0 4 13 22 34
9 30 30 24 20 15 7 0 0 5 14 23 34
10 32 30 23 18 14 9 0 0 4 16 23 31
11 33 29 23 19 11 7 0 0 4 17 25 33
12 34 28 21 17 11 6 0 0 3 17 23 32
13 32 51 21 19 12 5 0 0 3 14 24 30
14 32 69 21 21 10 6 0 0 3 14 25 32
15 36 75 21 22 10 4 0 0 3 16 25 32
16 35 74 22 19 10 5 0 0 4 15 25 34
17 34 71 24 17 9 4 0 0 5 14 26 35
18 31 28 23 18 8 5 0 0 6 16 27 51
19 30 28 23 18 9 5 0 0 6 14 25 56
20 31 27 21 16 10 3 0 0 8 16 26 60
21 32 27 22 16 11 2 0 0 9 18 27 57
22 33 27 22 15 10 2 0 0 9 17 28 49
23 32 28 23 16 9 2 0 0 8 17 29 35
24 32 29 21 18 8 2 0 0 7 19 29 35
25 31 29 21 17 9 2 0 0 8 19 29 35
26 32 29 24 16 9 1 0 0 8 21 28 34
27 34 28 23 15 8 0 0 0 8 21 30 34
28 33 27 22 16 9 0 0 0 8 19 31 32
29 32 26 20 17 7 0 0 0 7 21 30 33
30 30 65 21 15 7 0 0 1 7 21 30 37
31 31 65 21 65 6 65 0 1 65 22 65 37
Total 1015 1155 713 615 333 187 0 2 220 500 832 1138
Klamath
Day Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1 36 33 29 25 17 8 0 0 4 13 25 32
2 36 32 29 25 16 9 0 0 3 15 26 32
3 36 30 30 25 16 9 0 0 4 16 26 34
4 37 30 29 25 17 8 0 0 4 16 26 35
5 37 31 28 25 17 9 0 0 6 15 25 35
6 35 29 28 23 17 9 0 0 6 14 24 34
7 32 29 28 23 16 9 0 0 4 14 25 36
8 32 31 28 24 17 10 0 0 4 15 27 35
9 34 31 27 24 18 10 0 0 6 16 29 34
10 33 31 27 23 18 11 0 0 5 17 28 35
11 34 30 25 22 16 11 0 0 3 19 28 36
12 34 29 25 22 16 9 0 0 2 18 26 34
13 34 45 24 23 14 8 0 0 3 15 27 33
14 36 55 25 26 13 7 0 0 5 15 26 36
15 35 57 23 25 13 6 0 0 7 16 26 37
16 34 42 25 23 14 7 0 0 9 16 27 36
17 34 35 26 22 13 7 0 0 9 17 29 37
18 33 30 25 22 14 7 0 0 9 17 29 46.5
19 33 32 24 21 14 7 0 0 9 17 27 62.5
20 33 31 23 20 14 5 0 0 9 19 27 72
21 34 29 24 20 13 4 0 0 9 19 29 66.5
22 34 30 24 19 13 4 0 1 10 18 30 57.5
23 33 32 26 20 12 4 0 2 10 19 31 35
24 33 29 24 20 11 4 0 1 9 19 33 36
25 32 31 26 20 12 4 0 1 10 21 31 35
26 32 31 26 20 11 3 0 1 10 21 33 36
27 34 30 26 18 12 0 0 1 8 22 33 35
28 34 30 25 20 12 0 0 0 8 21 34 34
29 32 33 24 19 11 0 0 0 9 22 34 35
30 32 65 24 18 9 0 0 3 11 22 33 37
31 34 65 25 65 7 65 0 3 65 24 65 38
Total 1052 1098 802 727 433 254 0 13 270 548 919 1217
Temperature Pattern
Temperature Pattern
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 92 of 829
APPENDIX 2.4: HEATING DEGREE DAILY MONTH BY AREA

Roseburg
Day Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1 24 21 18 16 8 2 0 0 0 4 14 21
2 24 20 18 15 7 2 0 0 0 6 14 21
3 24 20 19 15 8 2 0 0 0 6 15 21
4 23 19 18 14 8 1 0 0 0 6 15 21
5 23 19 18 15 9 2 0 0 0 5 15 21
6 22 19 18 13 9 1 0 0 0 4 13 22
7 20 20 18 13 8 2 0 0 0 4 16 24
8 20 20 17 14 8 2 0 0 0 5 16 23
9 22 20 16 14 10 3 0 0 0 6 16 21
10 22 20 16 13 9 5 0 0 0 9 17 23
11 22 19 15 12 8 3 0 0 0 9 16 22
12 21 18 15 13 7 1 0 0 0 9 14 21
13 22 32 15 13 6 1 0 0 0 7 15 22
14 23 37 15 16 5 2 0 0 0 7 15 23
15 23 42 15 15 6 1 0 0 0 8 15 24
16 22 34 16 13 5 1 0 0 0 8 17 23
17 22 28 17 12 5 0 0 0 1 8 17 23
18 21 19 15 12 5 2 0 0 0 8 19 40
19 21 20 15 12 6 1 0 0 0 8 16 53
20 22 20 15 11 6 0 0 0 0 10 19 55
21 21 19 16 11 6 0 0 0 2 10 20 46
22 21 19 16 10 5 1 0 0 1 9 20 48
23 21 20 15 11 4 0 0 0 1 11 21 21
24 21 19 14 11 4 0 0 0 0 12 19 23
25 21 20 16 11 4 0 0 0 2 13 20 23
26 22 20 17 10 3 0 0 0 1 12 20 24
27 22 19 16 10 4 0 0 0 0 14 22 22
28 20 19 15 10 6 0 0 0 0 12 21 22
29 20 20 14 10 4 0 0 0 2 12 21 23
30 20 65 15 9 2 0 0 0 3 13 22 24
31 21 65 15 65 1 65 0 0 65 13 65 24
Total 673 772 498 439 186 100 0 0 78 268 585 824
Temperature Pattern
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 93 of 829
APPENDIX 2.5: DEMAND SENSITIVITIES
SUMMARY OF ASSUMPTIONS – DEMAND SCENARIOS

Re
f
e
r
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n
c
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Re
f
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e
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c
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Pl
u
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P
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k
Lo
w

C
u
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t
Hi
g
h

C
u
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t
Alt
e
r
n
a
t
e

DS
M
Pe
a
k

p
l
u
s

DS
M
80
%

b
e
l
o
w

1
9
9
0

em
i
s
s
i
o
n
s
80
%

b
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w

1
9
9
0

em
i
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s
Al
t
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a
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His
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Alt
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Hi
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Ex
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Lo
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Hi
g
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Ca
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b
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Ca
s
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Ca
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Gr
o
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Gr
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We
a
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r

St
d
Ca
s
e
Ca
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Re
f
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n
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C
a
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e
Re
f
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r
e
n
c
e

P
l
u
s

P
e
a
k
2 Y
e
a
r

U
P
C
5 Y
e
a
r

U
P
C
Ela
s
t
i
c
i
t
y
Pr
i
c
e
s
Pr
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s
Le
g
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a
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Cu
s
t
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m
e
r

G
r
o
w
t
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R
a
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e
Lo
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G
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Hig
h

Gr
o
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Us
e

p
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C
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2
Y
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His
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Y
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His
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We
a
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P
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S
t
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d
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d
De
m
a
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d

S
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M
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m
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t

P
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a
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I
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d
Pr
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P
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c
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P
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c
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a
d
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(
$
/
D
t
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)
Hig
h
/
E
x
p
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c
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/
Lo
w

E
l
a
s
t
i
c
i
t
y
FIR
S
T

Y
E
A
R

U
N
S
E
R
V
E
D
WA
N/A
20
3
4
N/
A
20
2
9
N/
A

N
/
A

N
/
A
N/A
N/A
20
3
0

2
0
3
2
N/
A

N
/
A

N
/
A

N
/
A
ID
N/A

N
/
A

N
/
A

N
/
A

N
/
A

N
/
A

N
/
A
N/A
N/A
N/
A
N/A

N
/
A

N
/
A

N
/
A

N
/
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Me
d
f
o
r
d

N
/
A
20
3
6
N/
A
20
2
9
N/
A

N
/
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N
/
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N/A
N/A
20
3
6
N/A

N
/
A

N
/
A

N
/
A

N
/
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Ro
s
e
b
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g

N
/
A
20
3
5
N/
A
20
3
1
N/
A

N
/
A

N
/
A
N/A
N/A
N/
A
N/A

N
/
A

N
/
A

N
/
A

N
/
A
Kla
m
a
t
h

N
/
A

N
/
A

N
/
A

N
/
A

N
/
A

N
/
A

N
/
A
N/A
N/A
N/
A
N/A

N
/
A

N
/
A

N
/
A

N
/
A
La

G
r
a
n
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e

N
/
A
20
3
4
N/
A
20
2
8
N/
A

N
/
A

N
/
A
N/A
N/A
20
3
0

2
0
3
2
N/
A

N
/
A

N
/
A

N
/
A
DE
M
A
N
D

I
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F
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U
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N
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-

D
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PR
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No
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r

H
i
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i
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3 Y
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d
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d
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t
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c
t
i
o
n
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 94 of 829
APPENDIX 2.5: DEMAND SCENARIOS
PROPOSED SCENARIOS

Proposed Scenarios Expected Cold Day 20yr Average Low Growth 80 % below High Growth
INPUT ASSUMPTIONS Case Weather Std Case & High Prices 1990 emissions & Low Prices
Customer Growth Rate Low Growth
Rate
Reference Case
growth with
emissions 80%
below 1990 target
High Growth
Rate
Demand Side Management
Weather Planning Standard
Historical
Coldest Day
Coldest in 20
years
20 year
average
Prices
Price curve
RESULTS
First Gas Year Unserved
Washington N/A N/A N/A N/A N/A 2032
Idaho N/A N/A N/A N/A N/A 2032
Medford N/A N/A N/A N/A N/A 2031
Roseburg N/A N/A N/A N/A N/A 2031
Klamath N/A N/A N/A N/A N/A N/A
La Grande N/A N/A N/A N/A N/A 2032
Scenario Summary
Most
aggressive
peak planning
case utilizing
Average Case
assumptions as
a starting point
and layering in
coldest weather
on record. The
likelihood of
occurrence is
low.
Evaluates
adopting an
alternate peak
weather
standard. Helps
provide some
bounds around
our sensitivity to
weather.
Case most
representative
of our average
(budget, PGA,
rate case)
planning
criteria.
Stagnant
growth
assumptions in
order to
evaluate if a
shortage does
occur. Not likely
to occur.
Reduction of the
use of natural gas
to 80% below
1990 targets in
OR and WA by
2050. The case
assumes the
overall reduction
is an average
goal before
applying figures
like elasticity and
DSM.
Aggressive
growth
assumptions in
order to
evaluate when
our earliest
resource
shortage could
occur. Not likely
to occur.
Risk Assessment
Use per Customer
Carbon Legislation
($/Metric Ton)
Higher or lower customer growth rates, which are heavily based on economic recovery. Higher or lower growth rates will lead to
accelerated or delayed unserved demand. Looking at various growth assumptions off the Expected Case allows us to capture the
risk in terms of the change in demand linked to customer growth.
Higher or lower use per customer will also lead to accelerated or delayed unserved demand. Use per customer can differ in many
ways. Direct use per customer influencers, such as demand side management, NGV/CNG usage, and derivation of the use per
customer starting point (i.e. one year, three year, etc.). Again, varying these assumptions under our forecasting methodology allows
us to quantify the change each assumption has to our forecast.
Weather volatility and predictability are a key risk. As the most correlated direct demand influencer, varying weather assumptions is
key to understanding the weather related risks.
Indirect influencers including elasticity and price are also important assumptions. The two go hand in hand, as price changes it will
influence how much customers consume. If forecasted prices remain relatively stable over the planning horizon, our current
elasticity assumption will not provide much decreased usage. However, price adders or an overall steepening of the price curve will
trigger a greater decline in usage due to the price elastic response. The magnitude of the elasticity adjustment is also important.
We are using a long run elasticity factor as calculated by the AGA. We continue to evaluate this assumption and are looking to
update the study as part of our Action Plan.
Reference Case Cust Growth Rates
None
$10-$30 WA
$17.86-$51.58 OR
$0 ID
Historical Coldest Day
Expected High
Yes
3 yr Flat + Price
Elasticity3 yr Flat + Price Elasticity
Low
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 95 of 829
APPENDIX 2.6: DEMAND FORECAST SENSITIVITIES AND SCENARIOS
DESCRIPTIONS
DEFINITIONS
DYNAMIC DEMAND METHODOLOGY – Avista’s demand forecasting approach wherein we 1) identify key
demand drivers behind natural gas consumption, 2) perform sensitivity analysis on each demand driver,
and 3) combine demand drivers under various scenarios to develop alternative potential outcomes for
forecasted demand.
DEMAND INFLUENCING FACTORS – Factors that directly influence the volume of natural gas consumed by our
core customers.
PRICE INFLUENCING FACTORS – Factors that, through price elasticity response, indirectly influence the volume
of natural gas consumed by our core customers.
REFERENCE CASE – A baseline point of reference that captures the basic inputs for determining a demand
forecast in SENDOUT® which includes number of customers, use per customer, average daily weather
temperatures and expected natural gas prices.
SENSITIVITIES – Focused analysis of a specific natural gas demand driver and its impact on forecasted
demand relative to the Reference Case when underlying input assumptions are modified.
SCENARIOS – Combination of natural gas demand drivers that make up a demand forecast.
Avista evaluates each sensitivities impact.
SENSITIVITIES
The following Sensitivities were performed on identified demand drivers against the reference case for
consideration in Scenario development. Note that Sensitivity assumptions reflect incremental adjustments
we estimate are not captured in the underlying reference case forecast.
Following are the Demand Influencing (Direct) Sensitivities we evaluated:
REFERENCE CASE PLUS PEAK – Same assumptions as in the Reference Case with an adjustment made to
normal weather to incorporate peak weather conditions. The peak weather data being the coldest day on
record for each weather area.
LOW & HIGH CUSTOMER GROWTH – Discussed in detail in Appendix 2.1: Economic Outlook and Customer
Count Forecast.
ALTERNATE WEATHER STANDARD (COLDEST DAY 20 YRS) – Peak Day weather temperature reduced to coldest
average daily temperature (HDDs) experienced in the most recent 20 years in each region.
DSM – Reference case assumptions including Washington and Idaho DSM potential identified by the
Conservation Potential Assessment provided by Applied Energy Group and Oregon DSM potential
provided by Energy Trust of Oregon. See Appendix 3.1 for full assessment reports.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 96 of 829
PEAK PLUS DSM – Reference plus peak weather assumptions including Washington and Idaho DSM
potential identified by the Conservation Potential Assessment provided by Applied Energy Group and
Oregon DSM potential provided by Energy Trust of Oregon. See Appendix 3.1 for full assessment
reports.
80% BELOW 1990 EMISSIONS REFERENCE CASE – Reference case assumptions including reduction in Oregon
and Washington consumption to 80% below 1990 emission levels by 2050. The case shows the overall
risk of a scenario with the overall goal of reducing natural gas emissions, but does not consider what
methods will be used to get to these levels or their costs.
80% BELOW 1990 EMISSIONS REFERENCE PLUS CASE – Reference plus peak weather assumptions including
reduction in Oregon and Washington consumption to 80% below 1990 emission levels by 2050. The case
shows the overall risk of a scenario with the overall goal of reducing natural gas emissions, but does not
consider what methods will be used to get to these levels or their costs.
ALTERNATE HISTORICAL 2-YEAR USE PER CUSTOMER – Reference case use per customer was based upon three
years of actual use per customer per heating degree day data. This sensitivity used two years of historical
use per customer per heating degree day data.
ALTERNATE HISTORICAL 5-YEAR USE PER CUSTOMER – Reference case use per customer was based upon three
years of actual use per customer per heating degree day data. This sensitivity used five years of historical
use per customer per heating degree day data.
Following are the Price Influencing (Indirect) Sensitivities we evaluated:
EXPECTED ELASTICITY – For our Expected Elasticity Sensitivity, we incorporate reduced consumption in
response to higher natural gas prices utilizing a price elasticity study prepared by the American Gas
Association.
LOW & HIGH PRICES – To capture a wide band of alternative prices forecasts, an adjustment to the expected
price was developed utilizing a higher and lower inflation rate. These rates were then applied to the
expected price helping to maintain the symmetry of the expected price curve while producing a set of
reasonable curves to help measure risk.
CARBON LEGISLATION LOW CASE – Assumes the EPA estimates on the social cost of carbon. Specifically, the
low case has is a 5% discount rate average. These costs begin at $11.40 in 2017 and increase to $21.20
by 2037 for a metric ton of CO2.
CARBON LEGISLATION MEDIUM CASE – The price of carbon in Oregon was based on the 2018 California
annual auction reserve price of $14.53 per greenhouse gas emissions allowance while growing by the 5%
plus the rate of inflation as indicated by the program structure section 95911 of the California Cap-and-
Trade Regulation.1 The starting price for Oregon was assumed to be similar to California’s cap and trade
system where the initial floor was set at $17.86 per metric tons of carbon dioxide equivalent (MTCO2e)
1 Article 5 California Cap on Greenhouse gas emissions and market-based compliance mechanisms.
https://www.arb.ca.gov/cc/capandtrade/capandtrade/unofficial_ct_100217.pdf Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 97 of 829
and begins in January 20212 rising to $51.58 by 2037. Washington State was modeled at $10 per
MTCO2e starting in 2019 and rising to $30 per MTCO2e by 2030.
CARBON LEGISLATION HIGH CASE – Assumes the EPA estimates on the social cost of carbon. Specifically,
the high case includes 95% of results at a 3% discount rate average. These costs begin at $112.20 in 2017
and increase to $174 by 2037 for a metric ton of CO2.
Scenarios
After identifying the above demand drivers and analyzing the various Sensitivities, we have developed
the following demand forecast Scenarios:
AVERAGE CASE – This Scenario we believe represents the most likely average demand forecast modeled.
We assume service territory customer growth rates consistent with the reference case, rolling 20 year
normal weather in each service territory, our expected natural gas price forecast (blend of two consultants,
along with the NYMEX forward strip), expected price elasticity, the CO2 cost adders from our Carbon
Legislation Medium Case Sensitivity, and DSM. The Scenario does not include incremental cost adders
for declining Canadian imports or drilling restrictions beyond what is incorporated in the selected price
forecast.
EXPECTED CASE – This Scenario represents the peak demand forecast. We assume service territory customer
growth rates consistent with the reference case, a weather standard of coldest day on record in each
service territory, our expected natural gas price forecast (blend of two consultants, along with the
NYMEX forward strip), expected price elasticity, DSM, and the CO2 cost adders from our Carbon
Legislation Medium Case Sensitivity.
HIGH GROWTH, LOW PRICE – This Scenario models a rapid return to robust growth in part spurred on by low
energy prices. We assume higher customer growth rates than the reference case, coldest day on record
weather standard, incremental demand from NGV/CNG, our low natural gas price forecast, expected
price elasticity, DSM, and no CO2 adders.
LOW GROWTH, HIGH PRICE – This Scenario models an extended period of slow economic growth in part
resulting from high energy prices. We assume lower customer growth rates than the reference case,
coldest day on record weather standard, our high natural gas price forecast, expected price elasticity,
DSM, and CO2 adders from our Carbon Legislation Medium Case Sensitivity.
ALTERNATE WEATHER STANDARD – This Scenario models all the same assumptions as the Expected Case
Scenario, except for the change in the weather planning standard from coldest day on record to coldest
day in 20 years for each service territory. As noted in the Sensitivity analysis, this change does not affect
the Klamath Falls and La Grande service territories, which have each experienced their coldest day on
record within the last 20 years.
80% BELOW 1990 EMISSIONS – This Scenario models the impact of potential consumption curtailment due
to carbon legislation coupled with low energy prices. We assume a straight line reduction in Washington
and Oregon consumption from reference case growth in order to meet 80% below 1990 emission levels
2 Senate Bill 1070 https://olis.leg.state.or.us/liz/2017R1/Downloads/MeasureDocument/SB1070 Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 98 of 829
by 2050, along with our low natural gas price forecast rather than our expected natural gas price forecast.
All other assumptions remain the same as our Expected Case Scenario.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 99 of 829
APPENDIX 2.7: ANNUAL DEMAND, AVERAGE DAY DEMAND AND PEAK DAY
DEMAND (NET OF DSM) – CASE AVERAGE

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e
r
a
g
e

C
a
s
e
20
2
0
-
2
0
2
1

8
,
7
9
9
.
1
0

24
.
1
1

46
.
3
3

17
,
3
6
8
.
5
2

47
.
5
8

80
.
9
4

8,8
1
6
.
3
8

24
.
1
5

39
.
3
3

34
,
9
8
4
.
0
0

95
.
8
5

16
6
.
6
0

Av
e
r
a
g
e

C
a
s
e
20
2
1
-
2
0
2
2

8
,
8
2
3
.
1
6

24
.
1
7

46
.
5
1

17
,
4
0
4
.
4
8

47
.
6
8

81
.
3
2

8,8
4
6
.
3
1

24
.
2
4

39
.
5
7

35
,
0
7
3
.
9
4

96
.
0
9

16
7
.
4
0

Av
e
r
a
g
e

C
a
s
e
20
2
2
-
2
0
2
3

8
,
8
7
1
.
9
9

24
.
3
1

46
.
8
6

17
,
3
8
8
.
0
0

47
.
6
4

81
.
5
3

8,8
5
3
.
3
4

24
.
2
6

39
.
7
3

35
,
1
1
3
.
3
3

96
.
2
0

16
8
.
1
2

Av
e
r
a
g
e

C
a
s
e
20
2
3
-
2
0
2
4

8
,
9
6
1
.
2
7

24
.
5
5

47
.
2
3

17
,
5
4
9
.
4
4

48
.
0
8

82
.
2
3

8,9
5
1
.
2
3

24
.
5
2

40
.
1
5

35
,
4
6
1
.
9
5

97
.
1
6

16
9
.
6
1

Av
e
r
a
g
e

C
a
s
e
20
2
4
-
2
0
2
5

8
,
9
5
5
.
6
0

24
.
5
4

47
.
5
1

17
,
4
1
5
.
0
0

47
.
7
1

82
.
1
6

8,8
9
0
.
2
7

24
.
3
6

40
.
1
3

35
,
2
6
0
.
8
8

96
.
6
1

16
9
.
8
0

Av
e
r
a
g
e

C
a
s
e
20
2
5
-
2
0
2
6

8
,
9
9
6
.
4
7

24
.
6
5

47
.
8
4

17
,
3
2
9
.
2
8

47
.
4
8

82
.
2
0

8,8
5
1
.
4
2

24
.
2
5

40
.
1
6

35
,
1
7
7
.
1
7

96
.
3
8

17
0
.
2
1

Av
e
r
a
g
e

C
a
s
e
20
2
6
-
2
0
2
7

9
,
0
3
4
.
4
5

24
.
7
5

48
.
1
6

17
,
2
2
0
.
7
8

47
.
1
8

82
.
1
8

8,8
0
3
.
0
8

24
.
1
2

40
.
1
7

35
,
0
5
8
.
3
2

96
.
0
5

17
0
.
5
1

Av
e
r
a
g
e

C
a
s
e
20
2
7
-
2
0
2
8

9
,
1
1
1
.
2
4

24
.
9
6

48
.
4
8

17
,
1
7
9
.
9
5

47
.
0
7

82
.
3
1

8,7
9
0
.
5
5

24
.
0
8

40
.
2
7

35
,
0
8
1
.
7
4

96
.
1
1

17
1
.
0
6

Av
e
r
a
g
e

C
a
s
e
20
2
8
-
2
0
2
9

9
,
1
0
0
.
1
0

24
.
9
3

48
.
7
7

16
,
9
7
1
.
5
8

46
.
5
0

82
.
0
2

8,6
9
9
.
2
4

23
.
8
3

40
.
1
7

34
,
7
7
0
.
9
3

95
.
2
6

17
0
.
9
7

Av
e
r
a
g
e

C
a
s
e
20
2
9
-
2
0
3
0

9
,
1
2
7
.
3
0

25
.
0
1

49
.
0
5

16
,
8
4
8
.
1
1

46
.
1
6

81
.
9
5

8,6
5
3
.
0
4

23
.
7
1

40
.
2
0

34
,
6
2
8
.
4
5

94
.
8
7

17
1
.
2
0

Av
e
r
a
g
e

C
a
s
e
20
3
0
-
2
0
3
1

9
,
1
5
0
.
7
6

25
.
0
7

49
.
3
2

16
,
7
3
6
.
4
9

45
.
8
5

81
.
9
0

8,6
1
8
.
2
1

23
.
6
1

40
.
2
6

34
,
5
0
5
.
4
6

94
.
5
4

17
1
.
4
8

Av
e
r
a
g
e

C
a
s
e
20
3
1
-
2
0
3
2

9
,
2
1
4
.
6
7

25
.
2
5

49
.
5
7

16
,
7
2
4
.
4
3

45
.
8
2

82
.
2
1

8,6
3
8
.
5
3

23
.
6
7

40
.
5
3

34
,
5
7
7
.
6
2

94
.
7
3

17
2
.
3
0

Av
e
r
a
g
e

C
a
s
e
20
3
2
-
2
0
3
3

9
,
1
8
9
.
2
3

25
.
1
8

49
.
8
0

16
,
5
6
4
.
5
1

45
.
3
8

81
.
9
5

8,5
9
0
.
6
3

23
.
5
4

40
.
5
2

34
,
3
4
4
.
3
8

94
.
0
9

17
2
.
2
6

Av
e
r
a
g
e

C
a
s
e
20
3
3
-
2
0
3
4

9
,
2
0
5
.
4
2

25
.
2
2

50
.
0
2

16
,
5
0
6
.
3
4

45
.
2
2

82
.
0
5

8,5
9
8
.
6
7

23
.
5
6

40
.
7
2

34
,
3
1
0
.
4
3

94
.
0
0

17
2
.
7
9

Av
e
r
a
g
e

C
a
s
e
20
3
4
-
2
0
3
5

9
,
2
2
0
.
2
6

25
.
2
6

50
.
2
4

16
,
4
6
8
.
0
4

45
.
1
2

82
.
2
0

8,6
2
0
.
2
6

23
.
6
2

40
.
9
6

34
,
3
0
8
.
5
6

94
.
0
0

17
3
.
4
0

Av
e
r
a
g
e

C
a
s
e
20
3
5
-
2
0
3
6

9
,
2
7
9
.
2
0

25
.
4
2

50
.
4
6

16
,
5
3
2
.
3
6

45
.
2
9

82
.
7
9

8,6
9
6
.
4
3

23
.
8
3

41
.
4
4

34
,
5
0
8
.
0
0

94
.
5
4

17
4
.
6
9

Av
e
r
a
g
e

C
a
s
e
20
3
6
-
2
0
3
7

9
,
2
4
9
.
0
8

25
.
3
4

50
.
6
6

16
,
4
3
9
.
6
0

45
.
0
4

82
.
6
3

8,6
9
6
.
2
6

23
.
8
3

41
.
5
5

34
,
3
8
4
.
9
4

94
.
2
1

17
4
.
8
4

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 100 of 829
APPENDIX 2.7: ANNUAL DEMAND, AVERAGE DAY DEMAND AND PEAK DAY
DEMAND (NET OF DSM) – CASE HIGH

Sc
e
n
a
r
i
o
Ga
s

Y
e
a
r
An
n
u
a
l

D
e
m
a
n
d
Kla
m
a
t
h

F
a
l
l
s

(M
D
t
h
)
Da
i
l
y

De
m
a
n
d
Kla
m
a
t
h
(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y

Kl
a
m
a
t
h
(M
D
t
h
/
d
a
y
)
An
n
u
a
l

D
e
m
a
n
d
La

G
r
a
n
d
e

(M
D
t
h
)
Da
i
l
y

De
m
a
n
d
La

G
r
a
n
d
e
(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y
La

G
r
a
n
d
e
(M
D
t
h
/
d
a
y
)
An
n
u
a
l

D
e
m
a
n
d
Me
d
f
o
r
d
/
R
o
s
e
b
u
r
g

(M
D
t
h
)
Da
i
l
y

D
e
m
a
n
d
Me
d
f
o
r
d
/
R
o
s
e
b
u
r
g
(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y
Me
d
f
o
r
d
/
R
o
s
e
b
u
r
g
(M
D
t
h
/
d
a
y
)
Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s
20
1
7
-
2
0
1
8
1,
3
5
2
.
1
5

3.7
0

13
.
3
4

85
7
.
1
0

2.3
5

7.
5
9

6,
7
8
9
.
5
3

18
.
6
0

75
.
3
6

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s
20
1
8
-
2
0
1
9
1,
3
6
7
.
6
4

3.7
5

13
.
5
2

87
3
.
3
5

2.3
9

7.
6
8

6,
8
7
2
.
1
0

18
.
8
3

76
.
4
7

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s
20
1
9
-
2
0
2
0
1,
3
9
0
.
1
4

3.8
1

13
.
7
1

89
2
.
0
1

2.4
4

7.
7
7

6,
9
8
1
.
9
9

19
.
1
3

77
.
5
5

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s
20
2
0
-
2
0
2
1
1,
3
9
8
.
9
9

3.8
3

13
.
9
0

90
3
.
7
7

2.4
8

7.
8
6

7,
0
3
3
.
3
5

19
.
2
7

78
.
6
4

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s
20
2
1
-
2
0
2
2
1,
4
1
4
.
6
6

3.8
8

14
.
0
9

91
8
.
8
9

2.5
2

7.
9
5

7,
1
1
4
.
3
6

19
.
4
9

79
.
7
5

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s
20
2
2
-
2
0
2
3
1,
4
3
0
.
5
3

3.9
2

14
.
2
8

93
3
.
7
1

2.5
6

8.
0
4

7,
1
9
4
.
2
1

19
.
7
1

80
.
8
6

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s
20
2
3
-
2
0
2
4
1,
4
5
3
.
3
8

3.9
8

14
.
4
7

95
1
.
7
6

2.6
1

8.
1
2

7,
2
9
6
.
9
0

19
.
9
9

81
.
9
1

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s
20
2
4
-
2
0
2
5
1,
4
5
9
.
7
9

4.0
0

14
.
6
5

96
1
.
3
1

2.6
3

8.
1
9

7,
3
2
4
.
3
0

20
.
0
7

82
.
7
9

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s
20
2
5
-
2
0
2
6
1,
4
7
4
.
4
6

4.0
4

14
.
8
4

97
4
.
6
9

2.6
7

8.
2
7

7,
3
8
8
.
8
5

20
.
2
4

83
.
7
7

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s
20
2
6
-
2
0
2
7
1,
4
8
8
.
4
3

4.0
8

15
.
0
2

98
8
.
2
7

2.7
1

8.
3
5

7,
4
5
1
.
5
1

20
.
4
2

84
.
7
5

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s
20
2
7
-
2
0
2
8
1,
5
0
9
.
1
6

4.1
3

15
.
2
0

1,
0
0
6
.
4
4

2.7
6

8.
4
4

7,
5
4
4
.
6
6

20
.
6
7

85
.
7
2

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s
20
2
8
-
2
0
2
9
1,
5
1
3
.
6
8

4.1
5

15
.
3
7

1,
0
1
7
.
3
8

2.7
9

8.
5
3

7,
5
6
8
.
1
4

20
.
7
3

86
.
6
6

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s
20
2
9
-
2
0
3
0
1,
5
2
4
.
4
9

4.1
8

15
.
5
4

1,
0
3
1
.
9
3

2.8
3

8.
6
2

7,
6
2
1
.
4
1

20
.
8
8

87
.
5
7

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s
20
3
0
-
2
0
3
1
1,
5
3
4
.
7
8

4.2
0

15
.
6
9

1,
0
4
5
.
8
4

2.8
7

8.
7
1

7,
6
7
0
.
4
7

21
.
0
1

88
.
4
4

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s
20
3
1
-
2
0
3
2
1,
5
5
3
.
0
9

4.2
6

15
.
8
5

1,
0
6
3
.
3
7

2.9
1

8.
8
0

7,
7
5
0
.
4
2

21
.
2
3

89
.
2
7

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s
20
3
2
-
2
0
3
3
1,
5
5
5
.
8
2

4.2
6

16
.
0
1

1,
0
7
2
.
1
5

2.9
4

8.
8
8

7,
7
5
8
.
3
3

21
.
2
6

90
.
0
7

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s
20
3
3
-
2
0
3
4
1,
5
6
6
.
5
0

4.2
9

16
.
1
7

1,
0
8
4
.
4
9

2.9
7

8.
9
5

7,
7
9
8
.
8
4

21
.
3
7

90
.
8
5

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s
20
3
4
-
2
0
3
5
1,
5
7
7
.
1
5

4.3
2

16
.
3
3

1,
0
9
6
.
5
9

3.0
0

9.
0
3

7,
8
3
7
.
6
9

21
.
4
7

91
.
6
1

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s
20
3
5
-
2
0
3
6
1,
5
9
6
.
3
3

4.3
7

16
.
4
9

1,
1
1
2
.
6
6

3.0
5

9.
1
1

7,
9
1
1
.
8
4

21
.
6
8

92
.
3
6

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s
20
3
6
-
2
0
3
7
1,
5
9
9
.
2
1

4.3
8

16
.
6
5

1,
1
1
9
.
8
3

3.0
7

9.
1
7

7,
9
1
4
.
3
1

21
.
6
8

93
.
1
0

Sc
e
n
a
r
i
o
Ga
s

Y
e
a
r
An
n
u
a
l

D
e
m
a
n
d
Or
e
g
o
n

(
M
D
t
h
)
Da
i
l
y

De
m
a
n
d
Or
e
g
o
n

(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y
De
m
a
n
d
Or
e
g
o
n
(M
D
t
h
/
d
a
y
)
An
n
u
a
l

D
e
m
a
n
d
Wa
s
h
i
n
g
t
o
n

(M
D
t
h
)
Da
i
l
y

De
m
a
n
d
Wa
s
h
i
n
g
t
o
n
(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y
Wa
s
h
i
n
g
t
o
n
(M
D
t
h
/
d
a
y
)
An
n
u
a
l

D
e
m
a
n
d
Id
a
h
o

(
M
D
t
h
)
Da
i
l
y

D
e
m
a
n
d
Id
a
h
o
(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y
Id
a
h
o
(M
D
t
h
/
d
a
y
)
An
n
u
a
l

D
e
m
a
n
d
To
t
a
l

S
y
s
t
e
m
(M
D
t
h
)
Da
i
l
y

De
m
a
n
d
To
t
a
l

S
y
s
t
e
m
(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y
De
m
a
n
d

To
t
a
l
Sy
s
t
e
m
(M
D
t
h
/
d
a
y
)
Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
1
7
-
2
0
1
8

8
,
9
9
8
.
7
9

24
.
6
5

96
.
2
9

17
,
7
6
4
.
4
6

48
.
6
7

18
9
.
2
8

8,
9
8
1
.
1
2

24
.
6
1

90
.
2
3

35
,
7
4
4
.
3
6

97
.
9
3

37
5
.
8
0

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
1
8
-
2
0
1
9

9
,
1
1
3
.
1
0

24
.
9
7

97
.
6
8

18
,
0
1
4
.
0
8

49
.
3
5

19
2
.
3
3

9,
1
0
8
.
4
1

24
.
9
5

91
.
7
6

36
,
2
3
5
.
5
8

99
.
2
8

38
1
.
7
6

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
1
9
-
2
0
2
0

9
,
2
6
4
.
1
4

25
.
3
8

99
.
0
4

18
,
2
9
9
.
6
8

50
.
1
4

19
5
.
2
9

9,
2
6
7
.
2
8

25
.
3
9

93
.
3
1

36
,
8
3
1
.
1
0

10
0
.
9
1

38
7
.
6
3

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
2
0
-
2
0
2
1

9
,
3
3
6
.
1
0

25
.
5
8

10
0
.
4
1

18
,
4
0
7
.
0
6

50
.
4
3

19
8
.
0
9

9,
3
4
6
.
4
3

25
.
6
1

94
.
8
7

37
,
0
8
9
.
5
9

10
1
.
6
2

39
3
.
3
6

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
2
1
-
2
0
2
2

9
,
4
4
7
.
9
1

25
.
8
8

10
1
.
7
9

18
,
5
4
1
.
7
9

50
.
8
0

20
0
.
6
4

9,
4
4
4
.
6
8

25
.
8
8

96
.
4
2

37
,
4
3
4
.
3
7

10
2
.
5
6

39
8
.
8
5

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
2
2
-
2
0
2
3

9
,
5
5
8
.
4
5

26
.
1
9

10
3
.
1
8

18
,
6
2
9
.
8
7

51
.
0
4

20
3
.
0
2

9,
5
2
1
.
6
0

26
.
0
9

97
.
9
2

37
,
7
0
9
.
9
3

10
3
.
3
1

40
4
.
1
2

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
2
3
-
2
0
2
4

9
,
7
0
2
.
0
4

26
.
5
8

10
4
.
5
0

18
,
8
7
9
.
3
8

51
.
7
2

20
5
.
7
7

9,
6
8
1
.
9
3

26
.
5
3

99
.
5
9

38
,
2
6
3
.
3
5

10
4
.
8
3

40
9
.
8
7

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
2
4
-
2
0
2
5

9
,
7
4
5
.
4
0

26
.
7
0

10
5
.
6
2

18
,
8
2
8
.
2
7

51
.
5
8

20
7
.
5
8

9,
6
7
9
.
7
4

26
.
5
2

10
0
.
7
1

38
,
2
5
3
.
4
1

10
4
.
8
0

41
3
.
9
1

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
2
5
-
2
0
2
6

9
,
8
3
8
.
0
0

26
.
9
5

10
6
.
8
7

18
,
8
2
7
.
9
1

51
.
5
8

20
9
.
6
4

9,
7
0
0
.
2
8

26
.
5
8

10
1
.
9
6

38
,
3
6
6
.
1
8

10
5
.
1
1

41
8
.
4
7

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
2
6
-
2
0
2
7

9
,
9
2
8
.
2
1

27
.
2
0

10
8
.
1
2

18
,
8
0
3
.
9
3

51
.
5
2

21
1
.
6
1

9,
7
1
1
.
4
2

26
.
6
1

10
3
.
1
6

38
,
4
4
3
.
5
7

10
5
.
3
2

42
2
.
8
9

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
2
7
-
2
0
2
8

1
0
,
0
6
0
.
2
6

27
.
5
6

10
9
.
3
6

18
,
8
5
0
.
9
7

51
.
6
5

21
3
.
7
0

9,
7
6
1
.
6
7

26
.
7
4

10
4
.
4
8

38
,
6
7
2
.
9
0

10
5
.
9
5

42
7
.
5
4

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
2
8
-
2
0
2
9

1
0
,
0
9
9
.
2
1

27
.
6
7

11
0
.
5
6

18
,
7
2
1
.
0
1

51
.
2
9

21
5
.
3
5

9,
7
2
8
.
9
9

26
.
6
5

10
5
.
6
1

38
,
5
4
9
.
2
0

10
5
.
6
1

43
1
.
5
2

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
2
9
-
2
0
3
0

1
0
,
1
7
7
.
8
3

27
.
8
8

11
1
.
7
3

18
,
6
7
8
.
9
6

51
.
1
8

21
7
.
1
7

9,
7
4
4
.
7
4

26
.
7
0

10
6
.
8
7

38
,
6
0
1
.
5
4

10
5
.
7
6

43
5
.
7
7

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
3
0
-
2
0
3
1

1
0
,
2
5
1
.
0
9

28
.
0
9

11
2
.
8
5

18
,
6
4
7
.
2
4

51
.
0
9

21
8
.
9
7

9,
7
7
3
.
5
7

26
.
7
8

10
8
.
2
0

38
,
6
7
1
.
9
0

10
5
.
9
5

44
0
.
0
2

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
3
1
-
2
0
3
2

1
0
,
3
6
6
.
8
8

28
.
4
0

11
3
.
9
2

18
,
7
1
9
.
3
9

51
.
2
9

22
1
.
1
0

9,
8
6
3
.
0
1

27
.
0
2

10
9
.
7
7

38
,
9
4
9
.
2
8

10
6
.
7
1

44
4
.
7
9

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
3
2
-
2
0
3
3

1
0
,
3
8
6
.
3
0

28
.
4
6

11
4
.
9
6

18
,
6
3
1
.
7
1

51
.
0
5

22
2
.
6
2

9,
8
7
8
.
9
3

27
.
0
7

11
1
.
0
9

38
,
8
9
6
.
9
4

10
6
.
5
7

44
8
.
6
7

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
3
3
-
2
0
3
4

1
0
,
4
4
9
.
8
2

28
.
6
3

11
5
.
9
7

18
,
6
4
9
.
8
6

51
.
1
0

22
4
.
4
7

9,
9
5
6
.
1
1

27
.
2
8

11
2
.
6
5

39
,
0
5
5
.
7
9

10
7
.
0
0

45
3
.
0
9

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
3
4
-
2
0
3
5

1
0
,
5
1
1
.
4
3

28
.
8
0

11
6
.
9
7

18
,
6
8
6
.
8
6

51
.
2
0

22
6
.
3
4

10
,
0
4
8
.
5
6

27
.
5
3

11
4
.
2
8

39
,
2
4
6
.
8
4

10
7
.
5
3

45
7
.
5
8

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
3
5
-
2
0
3
6

1
0
,
6
2
0
.
8
3

29
.
1
0

11
7
.
9
6

18
,
8
3
2
.
6
3

51
.
6
0

22
8
.
6
4

10
,
2
0
2
.
0
4

27
.
9
5

11
6
.
1
7

39
,
6
5
5
.
5
0

10
8
.
6
5

46
2
.
7
6

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
3
6
-
2
0
3
7

1
0
,
6
3
3
.
3
6

29
.
1
3

11
8
.
9
2

18
,
8
0
7
.
8
1

51
.
5
3

23
0
.
1
7

10
,
2
7
1
.
9
3

28
.
1
4

11
7
.
7
3

39
,
7
1
3
.
0
9

10
8
.
8
0

46
6
.
8
2

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 101 of 829
APPENDIX 2.7: ANNUAL DEMAND, AVERAGE DAY DEMAND AND PEAK DAY
DEMAND (NET OF DSM) – CASE LOW

Sc
e
n
a
r
i
o
Ga
s

Y
e
a
r
An
n
u
a
l

D
e
m
a
n
d
Kla
m
a
t
h

F
a
l
l
s

(M
D
t
h
)
Da
i
l
y

De
m
a
n
d
Kla
m
a
t
h
(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y

Kla
m
a
t
h
(M
D
t
h
/
d
a
y
)
An
n
u
a
l

D
e
m
a
n
d
La

G
r
a
n
d
e

(M
D
t
h
)
Da
i
l
y

De
m
a
n
d
La

G
r
a
n
d
e
(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y
La

G
r
a
n
d
e
(M
D
t
h
/
d
a
y
)
An
n
u
a
l

D
e
m
a
n
d
Me
d
f
o
r
d
/
R
o
s
e
b
u
r
g

(M
D
t
h
)
Da
i
l
y

D
e
m
a
n
d
Me
d
f
o
r
d
/
R
o
s
e
b
u
r
g
(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y
Me
d
f
o
r
d
/
R
o
s
e
b
u
r
g
(M
D
t
h
/
d
a
y
)
Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s
20
1
7
-
2
0
1
8
1,3
2
9
.
1
6

3.6
4

13
.
1
4

84
3
.
6
0

2.
3
1

7.4
7

6,6
8
4
.
2
0

18
.
3
1

74
.
3
3

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s
20
1
8
-
2
0
1
9
1,3
3
1
.
6
6

3.6
5

13
.
2
0

83
5
.
4
9

2.
2
9

7.4
4

6,7
1
0
.
4
7

18
.
3
8

74
.
8
3

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s
20
1
9
-
2
0
2
0
1,3
3
9
.
4
9

3.6
7

13
.
2
5

82
5
.
7
8

2.
2
6

7.4
1

6,7
5
5
.
1
2

18
.
5
1

75
.
1
8

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s
20
2
0
-
2
0
2
1
1,3
3
3
.
9
9

3.6
5

13
.
3
0

81
2
.
1
6

2.
2
3

7.3
6

6,7
4
3
.
2
4

18
.
4
7

75
.
5
5

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s
20
2
1
-
2
0
2
2
1,3
3
0
.
3
5

3.6
4

13
.
2
9

80
2
.
7
1

2.
2
0

7.3
3

6,7
4
0
.
6
7

18
.
4
7

75
.
6
3

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s
20
2
2
-
2
0
2
3
1,3
3
0
.
7
0

3.6
5

13
.
3
4

79
6
.
1
8

2.
1
8

7.3
2

6,7
5
5
.
2
7

18
.
5
1

76
.
0
0

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s
20
2
3
-
2
0
2
4
1,3
3
7
.
8
5

3.6
7

13
.
3
9

79
3
.
6
2

2.
1
7

7.3
2

6,7
9
6
.
0
3

18
.
6
2

76
.
3
6

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s
20
2
4
-
2
0
2
5
1,3
3
0
.
8
1

3.6
5

13
.
4
3

78
4
.
9
7

2.
1
5

7.3
1

6,7
7
2
.
0
1

18
.
5
5

76
.
6
6

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s
20
2
5
-
2
0
2
6
1,3
3
1
.
5
9

3.6
5

13
.
4
9

78
0
.
2
6

2.
1
4

7.3
2

6,7
8
2
.
8
4

18
.
5
8

77
.
0
5

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s
20
2
6
-
2
0
2
7
1,3
3
1
.
9
5

3.6
5

13
.
5
5

77
5
.
9
1

2.
1
3

7.3
2

6,7
9
1
.
4
5

18
.
6
1

77
.
4
4

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s
20
2
7
-
2
0
2
8
1,3
3
8
.
6
4

3.6
7

13
.
6
1

77
4
.
0
4

2.
1
2

7.3
2

6,8
2
7
.
6
4

18
.
7
1

77
.
8
2

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s
20
2
8
-
2
0
2
9
1,3
3
0
.
4
5

3.6
5

13
.
6
5

76
4
.
8
8

2.
1
0

7.3
1

6,7
9
6
.
3
4

18
.
6
2

78
.
1
1

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s
20
2
9
-
2
0
3
0
1,3
2
9
.
7
4

3.6
4

13
.
7
0

75
9
.
7
8

2.
0
8

7.3
0

6,7
9
7
.
5
4

18
.
6
2

78
.
4
5

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s
20
3
0
-
2
0
3
1
1,3
2
8
.
9
2

3.6
4

13
.
7
5

75
5
.
7
1

2.
0
7

7.3
0

6,7
9
6
.
5
2

18
.
6
2

78
.
7
7

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s
20
3
1
-
2
0
3
2
1,3
3
5
.
4
3

3.6
6

13
.
8
1

75
5
.
8
1

2.
0
7

7.3
1

6,8
2
4
.
2
0

18
.
7
0

79
.
0
7

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s
20
3
2
-
2
0
3
3
1,3
2
8
.
4
5

3.6
4

13
.
8
6

74
9
.
6
3

2.
0
5

7.3
0

6,7
8
8
.
7
0

18
.
6
0

79
.
3
6

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s
20
3
3
-
2
0
3
4
1,3
2
8
.
2
0

3.6
4

13
.
9
2

74
6
.
8
6

2.
0
5

7.3
0

6,7
8
2
.
7
2

18
.
5
8

79
.
6
3

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s
20
3
4
-
2
0
3
5
1,3
2
7
.
9
2

3.6
4

13
.
9
7

74
4
.
2
3

2.
0
4

7.3
1

6,7
7
5
.
8
4

18
.
5
6

79
.
8
9

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s
20
3
5
-
2
0
3
6
1,3
3
4
.
7
0

3.6
6

14
.
0
3

74
4
.
9
8

2.
0
4

7.3
2

6,7
9
9
.
7
2

18
.
6
3

80
.
1
5

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s
20
3
6
-
2
0
3
7
1,3
2
7
.
5
1

3.6
4

14
.
0
8

73
9
.
3
2

2.
0
3

7.3
2

6,7
6
1
.
3
2

18
.
5
2

80
.
4
0

Sc
e
n
a
r
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Ga
s

Y
e
a
r
An
n
u
a
l

D
e
m
a
n
d
Or
e
g
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n

(
M
D
t
h
)
Da
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l
y

De
m
a
n
d
Or
e
g
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n

(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y
De
m
a
n
d
Or
e
g
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n
(M
D
t
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/
d
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)
An
n
u
a
l

D
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m
a
n
d
Wa
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(M
D
t
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)
Da
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l
y

De
m
a
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d
Wa
s
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n
(M
D
t
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d
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)
Pe
a
k

D
a
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Wa
s
h
i
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D
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d
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An
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a
l

D
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m
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Id
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M
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y

D
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d
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D
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Pe
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t
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y
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To
t
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m
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)
Lo
w

G
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H
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r
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2
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94
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4

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7
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47
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88
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4
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5

37
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5

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w

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r
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H
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r
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8
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95
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4
8

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6
0
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48
.
2
2

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8,8
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3

24
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89
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1

35
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7
0

96
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6

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2
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6
5

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w

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H
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24
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4

95
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4

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6
9
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48
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4
7

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89
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6

35
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9
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7

97
.
2
4

37
4
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1
8

Lo
w

G
r
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H
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P
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2
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8
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8
8
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3
8

24
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3
5

96
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2
1

17
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6
1
1
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9
3

48
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2
5

18
9
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5
5

8,8
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3
0

24
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2
1

89
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8
0

35
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3
3
8
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6
1

96
.
8
2

37
5
.
5
7

Lo
w

G
r
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&

H
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P
r
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2
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2

8
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7
4

24
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3
1

96
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2
5

17
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5
7
6
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0
4

48
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1
5

19
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2
6

8,8
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0
7

24
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4

90
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35
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6
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8
5

96
.
6
1

37
6
.
5
9

Lo
w

G
r
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h

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H
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P
r
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s

2
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3

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8
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2
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1
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24
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3
3

96
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6
6

17
,
4
9
0
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0
7

47
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9
2

19
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7
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8,7
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4
2

24
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1

90
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3
0

35
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1
3
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6
3

96
.
2
6

37
7
.
7
0

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w

G
r
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h

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H
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P
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2
0
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3
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4

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9
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5
1

24
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4
6

97
.
0
7

17
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5
6
8
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3
2

48
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1
3

19
1
.
7
0

8,8
0
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5
0

24
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1
1

90
.
7
7

35
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2
9
6
.
3
3

96
.
7
0

37
9
.
5
4

Lo
w

G
r
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w
t
h

&

H
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g
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P
r
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s

2
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4
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2
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5

8
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8
8
7
.
7
8

24
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3
5

97
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4
0

17
,
3
7
0
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4
9

47
.
5
9

19
1
.
9
0

8,6
9
2
.
1
6

23
.
8
1

90
.
7
9

34
,
9
5
0
.
4
3

95
.
7
5

38
0
.
0
9

Lo
w

G
r
o
w
t
h

&

H
i
g
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P
r
i
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s

2
0
2
5
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2
0
2
6

8
,
8
9
4
.
7
0

24
.
3
7

97
.
8
6

17
,
2
2
1
.
5
0

47
.
1
8

19
2
.
4
1

8,6
0
5
.
2
4

23
.
5
8

90
.
9
7

34
,
7
2
1
.
4
4

95
.
1
3

38
1
.
2
5

Lo
w

G
r
o
w
t
h

&

H
i
g
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P
r
i
c
e
s

2
0
2
6
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2
0
2
7

8
,
8
9
9
.
3
1

24
.
3
8

98
.
3
2

17
,
0
5
0
.
5
9

46
.
7
1

19
2
.
8
5

8,5
0
9
.
0
5

23
.
3
1

91
.
1
2

34
,
4
5
8
.
9
5

94
.
4
1

38
2
.
2
8

Lo
w

G
r
o
w
t
h

&

H
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g
h

P
r
i
c
e
s

2
0
2
7
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2
0
2
8

8
,
9
4
0
.
3
2

24
.
4
9

98
.
7
5

16
,
9
4
4
.
5
1

46
.
4
2

19
3
.
4
2

8,4
4
5
.
7
7

23
.
1
4

91
.
3
6

34
,
3
3
0
.
6
0

94
.
0
6

38
3
.
5
3

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s

2
0
2
8
-
2
0
2
9

8
,
8
9
1
.
6
7

24
.
3
6

99
.
0
6

16
,
6
6
4
.
9
4

45
.
6
6

19
3
.
3
7

8,3
0
1
.
1
8

22
.
7
4

91
.
3
0

33
,
8
5
7
.
7
9

92
.
7
6

38
3
.
7
4

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s

2
0
2
9
-
2
0
3
0

8
,
8
8
7
.
0
6

24
.
3
5

99
.
4
5

16
,
4
8
1
.
9
2

45
.
1
6

19
3
.
7
2

8,2
0
5
.
9
9

22
.
4
8

91
.
4
6

33
,
5
7
4
.
9
7

91
.
9
9

38
4
.
6
3

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s

2
0
3
0
-
2
0
3
1

8
,
8
8
1
.
1
6

24
.
3
3

99
.
8
2

16
,
3
1
2
.
1
0

44
.
6
9

19
4
.
0
8

8,1
2
1
.
1
5

22
.
2
5

91
.
6
7

33
,
3
1
4
.
4
1

91
.
2
7

38
5
.
5
7

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s

2
0
3
1
-
2
0
3
2

8
,
9
1
5
.
4
4

24
.
4
3

10
0
.
1
8

16
,
2
3
8
.
0
5

44
.
4
9

19
4
.
7
9

8,0
8
6
.
7
4

22
.
1
6

92
.
0
7

33
,
2
4
0
.
2
3

91
.
0
7

38
7
.
0
4

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s

2
0
3
2
-
2
0
3
3

8
,
8
6
6
.
7
8

24
.
2
9

10
0
.
5
2

16
,
0
2
6
.
7
8

43
.
9
1

19
4
.
9
1

7,9
9
0
.
1
0

21
.
8
9

92
.
2
0

32
,
8
8
3
.
6
6

90
.
0
9

38
7
.
6
4

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s

2
0
3
3
-
2
0
3
4

8
,
8
5
7
.
7
8

24
.
2
7

10
0
.
8
5

15
,
9
1
3
.
6
3

43
.
6
0

19
5
.
3
9

7,9
4
4
.
8
2

21
.
7
7

92
.
5
4

32
,
7
1
6
.
2
3

89
.
6
3

38
8
.
7
9

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s

2
0
3
4
-
2
0
3
5

8
,
8
4
7
.
9
9

24
.
2
4

10
1
.
1
7

15
,
8
2
1
.
2
7

43
.
3
5

19
5
.
9
1

7,9
1
2
.
1
1

21
.
6
8

92
.
9
3

32
,
5
8
1
.
3
7

89
.
2
6

39
0
.
0
1

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s

2
0
3
5
-
2
0
3
6

8
,
8
7
9
.
3
9

24
.
3
3

10
1
.
4
9

15
,
8
2
6
.
2
3

43
.
3
6

19
6
.
8
7

8,0
5
3
.
3
4

22
.
0
6

91
.
4
0

32
,
7
5
8
.
9
6

89
.
7
5

38
9
.
7
6

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s

2
0
3
6
-
2
0
3
7

8
,
8
2
8
.
1
6

24
.
1
9

10
1
.
8
0

15
,
6
8
6
.
0
5

42
.
9
8

19
7
.
0
7

7,7
5
1
.
3
8

21
.
2
4

90
.
7
0

32
,
2
6
5
.
5
9

88
.
4
0

38
9
.
5
7

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 102 of 829
APPENDIX 2.7: ANNUAL DEMAND, AVERAGE DAY DEMAND AND PEAK DAY
DEMAND (NET OF DSM) – CASE COLDEST IN 20

Sc
e
n
a
r
i
o
Ga
s

Y
e
a
r
An
n
u
a
l

D
e
m
a
n
d
Kla
m
a
t
h

F
a
l
l
s

(M
D
t
h
)
Da
i
l
y

De
m
a
n
d
Kla
m
a
t
h
(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y

Kl
a
m
a
t
h
(M
D
t
h
/
d
a
y
)
An
n
u
a
l

D
e
m
a
n
d
La

G
r
a
n
d
e

(M
D
t
h
)
Da
i
l
y

De
m
a
n
d
La

G
r
a
n
d
e
(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y
La

G
r
a
n
d
e
(M
D
t
h
/
d
a
y
)
An
n
u
a
l

D
e
m
a
n
d
Me
d
f
o
r
d
/
R
o
s
e
b
u
r
g

(M
D
t
h
)
Da
i
l
y

D
e
m
a
n
d
Me
d
f
o
r
d
/
R
o
s
e
b
u
r
g
(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y
Me
d
f
o
r
d
/
R
o
s
e
b
u
r
g
(M
D
t
h
/
d
a
y
)
Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d
20
1
7
-
2
0
1
8
1,
3
4
0
.
6
9

3.6
7

13
.
2
4

84
2
.
5
6

2.3
1

6.
7
4

6,
6
8
3
.
4
9

18
.
3
1

65
.
0
2

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d
20
1
8
-
2
0
1
9
1,
3
4
9
.
5
8

3.7
0

13
.
3
6

84
7
.
7
9

2.3
2

6.
7
7

6,
7
3
7
.
0
7

18
.
4
6

65
.
7
1

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d
20
1
9
-
2
0
2
0
1,
3
6
5
.
6
4

3.7
4

13
.
4
9

85
3
.
0
7

2.3
4

6.
8
0

6,
8
1
8
.
0
2

18
.
6
8

66
.
3
8

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d
20
2
0
-
2
0
2
1
1,
3
6
8
.
0
8

3.7
5

13
.
6
2

85
1
.
2
1

2.3
3

6.
8
2

6,
8
4
0
.
7
5

18
.
7
4

67
.
0
6

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d
20
2
1
-
2
0
2
2
1,
3
7
0
.
7
5

3.7
6

13
.
6
7

84
9
.
6
6

2.3
3

6.
8
2

6,
8
6
4
.
9
0

18
.
8
1

67
.
3
7

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d
20
2
2
-
2
0
2
3
1,
3
7
8
.
1
7

3.7
8

13
.
7
8

84
9
.
9
9

2.3
3

6.
8
4

6,
9
0
8
.
4
0

18
.
9
3

67
.
9
7

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d
20
2
3
-
2
0
2
4
1,
3
9
3
.
4
9

3.8
2

13
.
9
1

85
3
.
9
6

2.3
4

6.
8
6

6,
9
8
0
.
9
8

19
.
1
3

68
.
6
0

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d
20
2
4
-
2
0
2
5
1,
3
9
3
.
0
3

3.8
2

14
.
0
2

85
0
.
2
5

2.3
3

6.
8
7

6,
9
8
1
.
5
9

19
.
1
3

69
.
0
9

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d
20
2
5
-
2
0
2
6
1,
4
0
0
.
4
6

3.8
4

14
.
1
4

85
0
.
2
6

2.3
3

6.
9
0

7,
0
1
7
.
4
9

19
.
2
3

69
.
6
7

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d
20
2
6
-
2
0
2
7
1,
4
0
7
.
3
1

3.8
6

14
.
2
6

85
0
.
0
9

2.3
3

6.
9
2

7,
0
5
1
.
2
6

19
.
3
2

70
.
2
4

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d
20
2
7
-
2
0
2
8
1,
4
2
0
.
6
6

3.8
9

14
.
3
7

85
3
.
2
9

2.3
4

6.
9
4

7,
1
1
3
.
9
3

19
.
4
9

70
.
8
0

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d
20
2
8
-
2
0
2
9
1,
4
1
9
.
0
4

3.8
9

14
.
4
8

84
9
.
6
0

2.3
3

6.
9
6

7,
1
1
0
.
4
9

19
.
4
8

71
.
3
4

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d
20
2
9
-
2
0
3
0
1,
4
2
3
.
7
6

3.9
0

14
.
5
9

84
9
.
1
4

2.3
3

6.
9
9

7,
1
3
5
.
7
4

19
.
5
5

71
.
8
6

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d
20
3
0
-
2
0
3
1
1,
4
2
8
.
1
5

3.9
1

14
.
6
9

84
8
.
4
2

2.3
2

7.
0
1

7,
1
5
7
.
7
7

19
.
6
1

72
.
3
5

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d
20
3
1
-
2
0
3
2
1,
4
3
9
.
8
6

3.9
4

14
.
7
9

85
1
.
0
0

2.3
3

7.
0
3

7,
2
0
9
.
5
4

19
.
7
5

72
.
8
2

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d
20
3
2
-
2
0
3
3
1,
4
3
6
.
8
5

3.9
4

14
.
8
9

84
6
.
3
7

2.3
2

7.
0
5

7,
1
9
3
.
8
5

19
.
7
1

73
.
2
6

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d
20
3
3
-
2
0
3
4
1,
4
4
1
.
1
4

3.9
5

15
.
0
0

84
5
.
0
5

2.3
2

7.
0
6

7,
2
0
9
.
1
1

19
.
7
5

73
.
6
9

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d
20
3
4
-
2
0
3
5
1,
4
4
5
.
3
9

3.9
6

15
.
1
0

84
3
.
6
8

2.3
1

7.
0
8

7,
2
2
3
.
0
9

19
.
7
9

74
.
1
0

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d
20
3
5
-
2
0
3
6
1,
4
5
7
.
3
8

3.9
9

15
.
2
0

84
5
.
7
5

2.3
2

7.
1
1

7,
2
6
9
.
9
6

19
.
9
2

74
.
5
1

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d
20
3
6
-
2
0
3
7
1,
4
5
4
.
2
8

3.9
8

15
.
3
0

84
0
.
6
5

2.3
0

7.
1
1

7,
2
5
0
.
0
3

19
.
8
6

74
.
9
2

Sc
e
n
a
r
i
o
Ga
s

Y
e
a
r
An
n
u
a
l

D
e
m
a
n
d
Or
e
g
o
n

(
M
D
t
h
)
Da
i
l
y

De
m
a
n
d
Or
e
g
o
n

(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y
De
m
a
n
d
Or
e
g
o
n
(M
D
t
h
/
d
a
y
)
An
n
u
a
l

D
e
m
a
n
d
Wa
s
h
i
n
g
t
o
n

(M
D
t
h
)
Da
i
l
y

De
m
a
n
d
Wa
s
h
i
n
g
t
o
n
(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y
Wa
s
h
i
n
g
t
o
n
(M
D
t
h
/
d
a
y
)
An
n
u
a
l

D
e
m
a
n
d
Id
a
h
o

(
M
D
t
h
)
Da
i
l
y

D
e
m
a
n
d
Id
a
h
o
(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y
Id
a
h
o
(M
D
t
h
/
d
a
y
)
An
n
u
a
l

D
e
m
a
n
d
To
t
a
l

S
y
s
t
e
m
(M
D
t
h
)
Da
i
l
y

De
m
a
n
d
To
t
a
l

S
y
s
t
e
m
(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y
De
m
a
n
d

To
t
a
l
Sy
s
t
e
m
(M
D
t
h
/
d
a
y
)
Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d

2
0
1
7
-
2
0
1
8

8
,
8
6
6
.
7
4

24
.
2
9

85
.
0
0

17
,
5
7
7
.
6
5

48
.
1
6

17
5
.
1
1

8,
8
7
3
.
2
5

24
.
3
1

83
.
4
1

35
,
3
1
7
.
6
5

96
.
7
6

34
3
.
5
2

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d

2
0
1
8
-
2
0
1
9

8
,
9
3
4
.
4
3

24
.
4
8

85
.
8
4

17
,
7
5
0
.
6
8

48
.
6
3

17
7
.
1
9

8,
9
5
2
.
1
7

24
.
5
3

84
.
3
7

35
,
6
3
7
.
2
9

97
.
6
4

34
7
.
4
1

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d

2
0
1
9
-
2
0
2
0

9
,
0
3
6
.
7
4

24
.
7
6

86
.
6
7

17
,
9
2
6
.
5
0

49
.
1
1

17
8
.
8
0

9,
0
5
8
.
0
7

24
.
8
2

85
.
3
3

36
,
0
2
1
.
3
2

98
.
6
9

35
0
.
8
0

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d

2
0
2
0
-
2
0
2
1

9
,
0
6
0
.
0
5

24
.
8
2

87
.
5
0

17
,
9
2
3
.
0
3

49
.
1
0

18
0
.
2
1

9,
0
8
2
.
2
6

24
.
8
8

86
.
2
7

36
,
0
6
5
.
3
4

98
.
8
1

35
3
.
9
8

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d

2
0
2
1
-
2
0
2
2

9
,
0
8
5
.
3
1

24
.
8
9

87
.
8
6

17
,
9
6
4
.
8
1

49
.
2
2

18
1
.
6
2

9,
1
1
5
.
4
8

24
.
9
7

87
.
0
8

36
,
1
6
5
.
6
0

99
.
0
8

35
6
.
5
6

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d

2
0
2
2
-
2
0
2
3

9
,
1
3
6
.
5
5

25
.
0
3

88
.
5
9

17
,
9
5
3
.
7
0

49
.
1
9

18
2
.
7
8

9,
1
2
5
.
8
1

25
.
0
0

87
.
8
2

36
,
2
1
6
.
0
7

99
.
2
2

35
9
.
1
9

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d

2
0
2
3
-
2
0
2
4

9
,
2
2
8
.
4
3

25
.
2
8

89
.
3
7

18
,
1
2
1
.
2
6

49
.
6
5

18
4
.
5
7

9,
2
2
7
.
1
8

25
.
2
8

88
.
8
4

36
,
5
7
6
.
8
7

10
0
.
2
1

36
2
.
7
8

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d

2
0
2
4
-
2
0
2
5

9
,
2
2
4
.
8
7

25
.
2
7

89
.
9
8

17
,
9
9
1
.
9
2

49
.
2
9

18
5
.
4
1

9,
1
6
9
.
0
7

25
.
1
2

89
.
3
2

36
,
3
8
5
.
8
5

99
.
6
9

36
4
.
7
1

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d

2
0
2
5
-
2
0
2
6

9
,
2
6
8
.
2
1

25
.
3
9

90
.
7
1

17
,
9
1
2
.
1
7

49
.
0
7

18
6
.
5
1

9,
1
3
3
.
5
3

25
.
0
2

89
.
9
3

36
,
3
1
3
.
9
1

99
.
4
9

36
7
.
1
5

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d

2
0
2
6
-
2
0
2
7

9
,
3
0
8
.
6
6

25
.
5
0

91
.
4
2

17
,
8
0
9
.
5
3

48
.
7
9

18
7
.
5
3

9,
0
8
8
.
4
6

24
.
9
0

90
.
5
1

36
,
2
0
6
.
6
6

99
.
2
0

36
9
.
4
6

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d

2
0
2
7
-
2
0
2
8

9
,
3
8
7
.
8
9

25
.
7
2

92
.
1
2

17
,
7
7
4
.
4
4

48
.
7
0

18
8
.
6
8

9,
0
7
9
.
2
1

24
.
8
7

91
.
1
9

36
,
2
4
1
.
5
5

99
.
2
9

37
1
.
9
9

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d

2
0
2
8
-
2
0
2
9

9
,
3
7
9
.
1
3

25
.
7
0

92
.
7
9

17
,
5
7
1
.
7
1

48
.
1
4

18
9
.
3
9

8,
9
9
1
.
2
2

24
.
6
3

91
.
6
7

35
,
9
4
2
.
0
5

98
.
4
7

37
3
.
8
5

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d

2
0
2
9
-
2
0
3
0

9
,
4
0
8
.
6
4

25
.
7
8

93
.
4
3

17
,
4
5
3
.
7
4

47
.
8
2

19
0
.
3
0

8,
9
4
8
.
3
3

24
.
5
2

92
.
2
8

35
,
8
1
0
.
7
1

98
.
1
1

37
6
.
0
0

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d

2
0
3
0
-
2
0
3
1

9
,
4
3
4
.
3
4

25
.
8
5

94
.
0
5

17
,
3
4
7
.
4
9

47
.
5
3

19
1
.
2
0

8,
9
1
6
.
8
7

24
.
4
3

92
.
9
3

35
,
6
9
8
.
7
0

97
.
8
0

37
8
.
1
8

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d

2
0
3
1
-
2
0
3
2

9
,
5
0
0
.
4
0

26
.
0
3

94
.
6
4

17
,
3
4
0
.
6
7

47
.
5
1

19
2
.
4
5

8,
9
4
0
.
6
4

24
.
4
9

93
.
8
0

35
,
7
8
1
.
7
1

98
.
0
3

38
0
.
8
9

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d

2
0
3
2
-
2
0
3
3

9
,
4
7
7
.
0
6

25
.
9
6

95
.
2
0

17
,
1
8
5
.
9
0

47
.
0
8

19
3
.
1
0

8,
8
9
6
.
2
5

24
.
3
7

94
.
4
1

35
,
5
5
9
.
2
1

97
.
4
2

38
2
.
7
1

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d

2
0
3
3
-
2
0
3
4

9
,
4
9
5
.
3
1

26
.
0
1

95
.
7
5

17
,
1
3
2
.
7
5

46
.
9
4

19
4
.
0
9

8,
9
0
7
.
8
6

24
.
4
1

95
.
2
3

35
,
5
3
5
.
9
2

97
.
3
6

38
5
.
0
7

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d

2
0
3
4
-
2
0
3
5

9
,
5
1
2
.
1
6

26
.
0
6

96
.
2
8

17
,
0
9
9
.
3
8

46
.
8
5

19
5
.
1
2

8,
9
3
3
.
0
7

24
.
4
7

96
.
1
1

35
,
5
4
4
.
6
1

97
.
3
8

38
7
.
5
1

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d

2
0
3
5
-
2
0
3
6

9
,
5
7
3
.
0
9

26
.
2
3

96
.
8
2

17
,
1
6
8
.
5
7

47
.
0
4

19
6
.
5
7

9,
0
1
2
.
9
4

24
.
6
9

97
.
2
4

35
,
7
5
4
.
6
1

97
.
9
6

39
0
.
6
3

Co
l
d

D
a
y

2
0
Y
r

W
e
a
t
h
e
r

S
t
d

2
0
3
6
-
2
0
3
7

9
,
5
4
4
.
9
5

26
.
1
5

97
.
3
3

17
,
0
8
0
.
6
3

46
.
8
0

19
7
.
2
7

9,
0
1
6
.
5
2

24
.
7
0

98
.
0
1

35
,
6
4
2
.
1
0

97
.
6
5

39
2
.
6
1

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 103 of 829
APPENDIX 2.7: ANNUAL DEMAND, AVERAGE DAY DEMAND AND PEAK DAY
DEMAND (NET OF DSM) – CASE 80% BELOW 1990 EMISSIONS

Sc
e
n
a
r
i
o
Ga
s

Y
e
a
r
An
n
u
a
l

D
e
m
a
n
d
Kla
m
a
t
h

F
a
l
l
s

(M
D
t
h
)
Da
i
l
y

De
m
a
n
d
Kla
m
a
t
h
(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y

Kla
m
a
t
h
(M
D
t
h
/
d
a
y
)
An
n
u
a
l

D
e
m
a
n
d
La

G
r
a
n
d
e

(M
D
t
h
)
Da
i
l
y

De
m
a
n
d
La

G
r
a
n
d
e
(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y
La

G
r
a
n
d
e
(M
D
t
h
/
d
a
y
)
An
n
u
a
l

D
e
m
a
n
d
Me
d
f
o
r
d
/
R
o
s
e
b
u
r
g

(M
D
t
h
)
Da
i
l
y

D
e
m
a
n
d
Me
d
f
o
r
d
/
R
o
s
e
b
u
r
g
(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y
Me
d
f
o
r
d
/
R
o
s
e
b
u
r
g
(M
D
t
h
/
d
a
y
)
80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s
20
1
7
-
2
0
1
8
1,3
0
7
.
4
3

3.
5
8

12
.
9
1

82
9
.
5
3

2.2
7

7.
3
4

6,
5
6
9
.
6
5

18
.
0
0

72
.
9
9

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s
20
1
8
-
2
0
1
9
1,2
6
8
.
0
0

3.
4
7

12
.
5
6

80
4
.
8
5

2.2
1

7.
1
0

6,
3
8
0
.
5
9

17
.
4
8

71
.
1
1

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s
20
1
9
-
2
0
2
0
1,2
3
0
.
6
2

3.
3
7

12
.
1
7

77
7
.
2
9

2.1
3

6.
8
5

6,
1
9
3
.
2
5

16
.
9
7

68
.
9
4

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s
20
2
0
-
2
0
2
1
1,1
9
1
.
5
7

3.
2
6

11
.
8
8

75
0
.
1
2

2.0
6

6.
6
5

6,
0
0
6
.
4
9

16
.
4
6

67
.
3
7

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s
20
2
1
-
2
0
2
2
1,1
4
7
.
7
9

3.
1
4

11
.
4
8

72
0
.
2
1

1.9
7

6.
4
0

5,
7
9
5
.
2
7

15
.
8
8

65
.
1
5

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s
20
2
2
-
2
0
2
3
1,1
0
9
.
3
4

3.
0
4

11
.
1
4

69
2
.
8
1

1.9
0

6.
1
8

5,
6
0
6
.
0
4

15
.
3
6

63
.
2
9

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s
20
2
3
-
2
0
2
4
1,0
7
1
.
8
3

2.
9
4

10
.
7
6

66
5
.
5
2

1.8
2

5.
9
4

5,
4
1
3
.
5
2

14
.
8
3

61
.
1
5

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s
20
2
4
-
2
0
2
5
1,0
3
1
.
9
9

2.
8
3

10
.
4
7

63
8
.
6
6

1.7
5

5.
7
4

5,
2
1
5
.
0
7

14
.
2
9

59
.
4
6

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s
20
2
5
-
2
0
2
6
99
3
.
2
1

2.
7
2

10
.
1
3

61
1
.
9
0

1.6
8

5.
5
3

5,
0
1
8
.
7
7

13
.
7
5

57
.
5
6

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s
20
2
6
-
2
0
2
7
95
3
.
9
2

2.
6
1

9.8
0

58
5
.
2
7

1.6
0

5.
3
2

4,
8
2
0
.
6
1

13
.
2
1

55
.
6
6

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s
20
2
7
-
2
0
2
8
91
4
.
6
6

2.
5
1

9.4
2

55
8
.
5
5

1.5
3

5.
0
9

4,
6
2
0
.
1
0

12
.
6
6

53
.
5
1

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s
20
2
8
-
2
0
2
9
87
3
.
9
1

2.
3
9

9.1
2

53
2
.
6
5

1.4
6

4.
9
0

4,
4
1
8
.
4
3

12
.
1
1

51
.
8
2

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s
20
2
9
-
2
0
3
0
83
3
.
3
1

2.
2
8

8.7
8

50
6
.
6
0

1.3
9

4.
7
0

4,
2
1
5
.
2
9

11
.
5
5

49
.
9
0

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s
20
3
0
-
2
0
3
1
79
2
.
6
8

2.
1
7

8.4
3

48
0
.
7
0

1.3
2

4.
5
0

4,
0
1
1
.
1
0

10
.
9
9

47
.
9
7

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s
20
3
1
-
2
0
3
2
75
2
.
6
1

2.
0
6

8.0
6

45
4
.
7
3

1.2
5

4.
2
9

3,
8
0
5
.
8
4

10
.
4
3

45
.
8
2

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s
20
3
2
-
2
0
3
3
71
1
.
6
5

1.
9
5

7.7
5

42
9
.
3
2

1.1
8

4.
1
0

3,
6
0
0
.
0
9

9.
8
6

44
.
0
8

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s
20
3
3
-
2
0
3
4
67
1
.
1
5

1.
8
4

7.4
1

40
3
.
7
8

1.1
1

3.
9
0

3,
3
9
3
.
7
7

9.
3
0

42
.
1
3

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s
20
3
4
-
2
0
3
5
63
0
.
6
4

1.
7
3

7.0
7

37
8
.
4
1

1.0
4

3.
7
1

3,
1
8
7
.
2
9

8.
7
3

40
.
1
7

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s
20
3
5
-
2
0
3
6
59
0
.
5
5

1.
6
2

6.7
0

35
2
.
9
5

0.9
7

3.
5
0

2,
9
8
0
.
5
9

8.
1
7

38
.
0
4

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s
20
3
6
-
2
0
3
7
54
9
.
7
3

1.
5
1

6.3
9

32
7
.
9
9

0.9
0

3.
3
2

2,
7
7
4
.
6
8

7.
6
0

36
.
2
6

Sc
e
n
a
r
i
o
Ga
s

Y
e
a
r
An
n
u
a
l

D
e
m
a
n
d
Or
e
g
o
n

(
M
D
t
h
)
Da
i
l
y

De
m
a
n
d
Or
e
g
o
n

(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y
De
m
a
n
d
Or
e
g
o
n
(M
D
t
h
/
d
a
y
)
An
n
u
a
l

D
e
m
a
n
d
Wa
s
h
i
n
g
t
o
n

(M
D
t
h
)
Da
i
l
y

De
m
a
n
d
Wa
s
h
i
n
g
t
o
n
(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y
Wa
s
h
i
n
g
t
o
n
(M
D
t
h
/
d
a
y
)
An
n
u
a
l

D
e
m
a
n
d
Id
a
h
o

(
M
D
t
h
)
Da
i
l
y

D
e
m
a
n
d
Id
a
h
o
(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y
Id
a
h
o
(M
D
t
h
/
d
a
y
)
An
n
u
a
l

D
e
m
a
n
d
To
t
a
l

S
y
s
t
e
m
(M
D
t
h
)
Da
i
l
y

De
m
a
n
d
To
t
a
l

S
y
s
t
e
m
(M
D
t
h
/
d
a
y
)
Pe
a
k

D
a
y
De
m
a
n
d

To
t
a
l
Sy
s
t
e
m
(M
D
t
h
/
d
a
y
)
80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
1
7
-
2
0
1
8

8
,
7
0
6
.
6
0

23
.
8
5

93
.
2
5

17
,
1
9
5
.
1
6

47
.
1
1

18
3
.
2
7

8,
8
9
8
.
3
3

24
.
3
8

89
.
4
2

34
,
8
0
0
.
0
9

95
.
3
4

36
5
.
9
5

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
1
8
-
2
0
1
9

8
,
4
5
3
.
4
4

23
.
1
6

90
.
7
7

16
,
6
8
8
.
8
5

45
.
7
2

17
8
.
3
0

8,
9
7
7
.
5
8

24
.
6
0

90
.
4
7

34
,
1
1
9
.
8
6

93
.
4
8

35
9
.
5
5

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
1
9
-
2
0
2
0

8
,
2
0
1
.
1
5

22
.
4
7

87
.
9
6

16
,
1
4
7
.
7
1

44
.
2
4

17
2
.
5
4

9,
0
8
3
.
8
0

24
.
8
9

91
.
5
1

33
,
4
3
2
.
6
7

91
.
6
0

35
2
.
0
0

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
2
0
-
2
0
2
1

7
,
9
4
8
.
1
8

21
.
7
8

85
.
9
1

15
,
5
8
0
.
0
8

42
.
6
9

16
8
.
0
2

9,
1
0
8
.
3
4

24
.
9
5

92
.
5
3

32
,
6
3
6
.
6
0

89
.
4
2

34
6
.
4
6

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
2
1
-
2
0
2
2

7
,
6
6
3
.
2
6

21
.
0
0

83
.
0
2

14
,
9
9
4
.
6
9

41
.
0
8

16
2
.
9
5

9,
1
4
9
.
2
4

25
.
0
7

93
.
5
1

31
,
8
0
7
.
2
0

87
.
1
4

33
9
.
4
7

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
2
2
-
2
0
2
3

7
,
4
0
8
.
1
9

20
.
3
0

80
.
6
0

14
,
3
6
7
.
7
6

39
.
3
6

15
7
.
7
4

9,
1
6
7
.
6
4

25
.
1
2

94
.
4
3

30
,
9
4
3
.
6
0

84
.
7
8

33
2
.
7
7

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
2
3
-
2
0
2
4

7
,
1
5
0
.
8
8

19
.
5
9

77
.
8
5

13
,
8
2
4
.
9
4

37
.
8
8

15
2
.
3
0

9,
2
6
9
.
6
0

25
.
4
0

95
.
5
3

30
,
2
4
5
.
4
2

82
.
8
6

32
5
.
6
8

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
2
4
-
2
0
2
5

6
,
8
8
5
.
7
2

18
.
8
6

75
.
6
7

13
,
1
5
0
.
1
7

36
.
0
3

14
7
.
2
9

9,
2
1
3
.
9
2

25
.
2
4

96
.
1
1

29
,
2
4
9
.
8
2

80
.
1
4

31
9
.
0
6

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
2
5
-
2
0
2
6

6
,
6
2
3
.
8
9

18
.
1
5

73
.
2
2

12
,
4
4
2
.
8
1

34
.
0
9

14
1
.
8
6

9,
1
7
8
.
9
1

25
.
1
5

96
.
8
0

28
,
2
4
5
.
6
0

77
.
3
9

31
1
.
8
8

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
2
6
-
2
0
2
7

6
,
3
5
9
.
8
0

17
.
4
2

70
.
7
7

11
,
7
1
6
.
2
5

32
.
1
0

13
6
.
3
7

9,
1
3
4
.
3
7

25
.
0
3

97
.
4
6

27
,
2
1
0
.
4
2

74
.
5
5

30
4
.
6
0

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
2
7
-
2
0
2
8

6
,
0
9
3
.
3
2

16
.
6
9

68
.
0
2

10
,
9
8
0
.
2
5

30
.
0
8

13
0
.
5
0

9,
1
2
5
.
7
4

25
.
0
0

98
.
2
1

26
,
1
9
9
.
3
0

71
.
7
8

29
6
.
7
3

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
2
8
-
2
0
2
9

5
,
8
2
4
.
9
9

15
.
9
6

65
.
8
5

10
,
2
4
1
.
9
2

28
.
0
6

12
5
.
3
4

9,
0
3
8
.
1
9

24
.
7
6

98
.
7
8

25
,
1
0
5
.
0
9

68
.
7
8

28
9
.
9
7

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
2
9
-
2
0
3
0

5
,
5
5
5
.
2
0

15
.
2
2

63
.
3
7

9,
5
1
1
.
6
3

26
.
0
6

11
9
.
8
6

8,
9
9
5
.
8
3

24
.
6
5

99
.
4
6

24
,
0
6
2
.
6
7

65
.
9
3

28
2
.
7
0

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
3
0
-
2
0
3
1

5
,
2
8
4
.
4
8

14
.
4
8

60
.
9
0

9,
0
4
0
.
1
6

24
.
7
7

11
0
.
0
9

8,
9
6
4
.
9
3

24
.
5
6

10
0
.
2
0

23
,
2
8
9
.
5
6

63
.
8
1

27
1
.
1
9

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
3
1
-
2
0
3
2

5
,
0
1
3
.
1
8

13
.
7
3

58
.
1
7

8,
1
2
6
.
3
9

22
.
2
6

10
4
.
2
8

8,
9
8
9
.
3
3

24
.
6
3

10
1
.
1
5

22
,
1
2
8
.
8
9

60
.
6
3

26
3
.
6
0

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
3
2
-
2
0
3
3

4
,
7
4
1
.
0
6

12
.
9
9

55
.
9
3

7,
4
5
2
.
4
7

20
.
4
2

98
.
5
9

8,
9
4
5
.
4
3

24
.
5
1

10
1
.
8
5

21
,
1
3
8
.
9
5

57
.
9
1

25
6
.
3
7

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
3
3
-
2
0
3
4

4
,
4
6
8
.
7
0

12
.
2
4

53
.
4
4

6,
8
0
1
.
1
9

18
.
6
3

92
.
9
9

8,
9
5
7
.
6
1

24
.
5
4

10
2
.
7
6

20
,
2
2
7
.
5
0

55
.
4
2

24
9
.
1
9

80
%

B
e
l
o
w

1
9
9
0

E
m
i
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Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 104 of 829
APPENDIX 2.8: PEAK DAY DEMAND BEFORE AND AFTER DSM
WASHINGTON

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 105 of 829
APPENDIX 2.8: PEAK DAY DEMAND BEFORE AND AFTER DSM
IDAHO

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 106 of 829
APPENDIX 2.8: PEAK DAY DEMAND BEFORE AND AFTER DSM
MEDFORD/ROSEBURG

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 107 of 829
APPENDIX 2.8: PEAK DAY DEMAND BEFORE AND AFTER DSM
KLAMATH FALLS

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 108 of 829
APPENDIX 2.8: PEAK DAY DEMAND BEFORE AND AFTER DSM
LA GRANDE

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 109 of 829
APPENDIX 2.9: DETAILED DEMAND DATA
EXPECTED MIX

Area
2017-2018:
Residential
2017-2018:
Commercial
2017-2018:
Ind
FirmSale
2017-2018:
Total
2018-2019:
Residential
2018-2019:
Commercial
2018-2019:
Ind
FirmSale
2018-2019:
Total
2019-2020:
Residential
2019-2020:
Commercial
2019-2020:
Ind
FirmSale
2019-2020:
Total
Klamath Falls 874.44 452.24 14.01 1,340.69 882.77 452.95 13.86 1,349.58 895.08 456.78 13.78 1,365.64
La Grande 485.62 311.25 53.19 850.05 487.04 311.62 56.66 855.32 490.38 313.30 56.98 860.65
Medford GTN 2,301.32 1,432.79 18.61 3,752.73 2,323.88 1,443.20 18.40 3,785.48 2,356.55 1,458.85 18.28 3,833.68
Medford NWP 1,033.93 643.72 8.36 1,686.01 1,044.06 648.39 8.27 1,700.72 1,058.74 655.43 8.21 1,722.38
Roseburg 719.67 575.98 2.37 1,298.02 725.91 576.49 2.35 1,304.75 735.20 578.92 2.34 1,316.45
OR Sub-Total 5,414.98 3,415.97 96.54 8,927.50 5,463.67 3,432.66 99.53 8,995.85 5,535.95 3,463.28 99.58 9,098.81
Washington Both 6,319.09 3,750.78 156.12 10,225.98 6,403.56 3,768.84 154.35 10,326.75 6,482.26 3,793.71 153.08 10,429.05
Washington GTN 871.60 517.35 21.53 1,410.48 883.25 519.84 21.29 1,424.38 894.10 523.27 21.11 1,438.49
Washington NWP 3,704.29 2,198.73 91.52 5,994.54 3,753.81 2,209.32 90.48 6,053.61 3,799.94 2,223.90 89.74 6,113.58
WA Sub-Total 10,894.98 6,466.85 269.16 17,631.00 11,040.62 6,498.00 266.12 17,804.74 11,176.31 6,540.87 263.93 17,981.11
Idaho Both 3,173.24 1,838.79 149.00 5,161.03 3,212.59 1,843.92 150.48 5,206.99 3,262.14 1,855.12 151.35 5,268.61
Idaho GTN 437.69 253.63 20.55 711.87 443.12 254.33 20.76 718.21 449.95 255.88 20.88 726.70
Idaho NWP 1,860.17 1,077.91 87.35 3,025.43 1,883.24 1,080.92 88.21 3,052.38 1,912.29 1,087.48 88.72 3,088.49
ID Sub-Total 5,471.10 3,170.33 256.90 8,898.33 5,538.95 3,179.18 259.45 8,977.58 5,624.37 3,198.48 260.95 9,083.80
Case Total 21,781.06 13,053.16 622.61 35,456.83 22,043.24 13,109.83 625.10 35,778.17 22,336.62 13,202.64 624.46 36,163.73
Area 2020-2021: Residential 2020-2021: Commercial
2020-2021:
Ind FirmSale 2020-2021: Total 2021-2022: Residential 2021-2022: Commercial
2021-2022:
Ind FirmSale 2021-2022: Total 2022-2023: Residential 2022-2023: Commercial
2022-2023:
Ind FirmSale 2022-2023: Total
Klamath Falls 898.47 455.98 13.63 1,368.08 902.04 455.18 13.53 1,370.75 908.77 455.95 13.45 1,378.17
La Grande 489.73 312.39 56.72 858.83 489.10 311.73 56.45 857.28 489.67 311.82 56.14 857.64
Medford GTN 2,368.38 1,462.78 18.10 3,849.26 2,380.10 1,467.46 17.98 3,865.54 2,398.70 1,475.78 17.88 3,892.36
Medford NWP 1,064.05 657.19 8.13 1,729.38 1,069.32 659.29 8.08 1,736.69 1,077.68 663.03 8.03 1,748.74
Roseburg 738.24 576.67 2.31 1,317.21 741.21 574.54 2.29 1,318.04 746.74 574.19 2.28 1,323.21
OR Sub-Total 5,558.86 3,465.01 98.89 9,122.76 5,581.77 3,468.19 98.34 9,148.30 5,621.57 3,480.76 97.78 9,200.11
Washington Both 6,493.07 3,783.53 150.74 10,427.34 6,515.92 3,786.89 149.10 10,451.91 6,515.13 3,783.17 147.47 10,445.77
Washington GTN 895.60 521.87 20.79 1,438.25 898.75 522.33 20.57 1,441.64 898.64 521.82 20.34 1,440.80
Washington NWP 3,806.28 2,217.93 88.36 6,112.58 3,819.68 2,219.90 87.40 6,126.98 3,819.21 2,217.72 86.45 6,123.38
WA Sub-Total 11,194.95 6,523.34 259.89 17,978.18 11,234.34 6,529.12 257.07 18,020.53 11,232.98 6,522.71 254.26 18,009.95
Idaho Both 3,281.97 1,850.24 150.63 5,282.84 3,302.73 1,849.26 150.29 5,302.28 3,313.10 1,845.47 149.89 5,308.47
Idaho GTN 452.69 255.21 20.78 728.67 455.55 255.07 20.73 731.35 456.98 254.55 20.67 732.20
Idaho NWP 1,923.91 1,084.62 88.30 3,096.83 1,936.09 1,084.05 88.10 3,108.24 1,942.16 1,081.83 87.87 3,111.86
ID Sub-Total 5,658.57 3,190.06 259.70 9,108.34 5,694.37 3,188.38 259.12 9,141.87 5,712.24 3,181.85 258.43 9,152.53
Case Total 22,412.38 13,178.41 618.48 36,209.27 22,510.48 13,185.70 614.52 36,310.70 22,566.79 13,185.32 610.48 36,362.59
Area
2023-2024:
Residential
2023-2024:
Commercial
2023-2024:
Ind
FirmSale
2023-2024:
Total
2024-2025:
Residential
2024-2025:
Commercial
2024-2025:
Ind
FirmSale
2024-2025:
Total
2025-2026:
Residential
2025-2026:
Commercial
2025-2026:
Ind
FirmSale
2025-2026:
Total
Klamath Falls 920.88 459.21 13.40 1,393.49 922.26 457.51 13.25 1,393.03 929.01 458.31 13.14 1,400.46
La Grande 492.43 313.35 55.86 861.65 490.63 311.98 55.36 857.97 491.03 312.08 54.91 858.01
Medford GTN 2,426.77 1,490.06 17.81 3,934.63 2,428.47 1,490.18 17.63 3,936.28 2,442.96 1,497.29 17.49 3,957.73
Medford NWP 1,090.29 669.45 8.00 1,767.73 1,091.05 669.50 7.92 1,768.47 1,097.56 672.69 7.86 1,778.11
Roseburg 756.21 576.61 2.27 1,335.09 758.04 573.49 2.24 1,333.78 763.73 573.18 2.23 1,339.13
OR Sub-Total 5,686.58 3,508.68 97.34 9,292.60 5,690.46 3,502.66 96.41 9,289.52 5,724.29 3,513.54 95.62 9,333.44
Washington Both 6,601.83 3,794.96 146.51 10,543.30 6,559.37 3,764.84 144.37 10,468.58 6,526.49 3,753.27 142.91 10,422.67
Washington GTN 910.60 523.44 20.21 1,454.25 904.74 519.29 19.91 1,443.94 900.20 517.69 19.71 1,437.61
Washington NWP 3,870.04 2,224.63 85.89 6,180.56 3,845.15 2,206.97 84.63 6,136.75 3,825.87 2,200.19 83.78 6,109.84
WA Sub-Total 11,382.46 6,543.04 252.61 18,178.11 11,309.26 6,491.10 248.92 18,049.28 11,252.56 6,471.16 246.40 17,970.12
Idaho Both 3,369.35 1,847.98 150.13 5,367.45 3,353.83 1,831.01 149.07 5,333.91 3,342.07 1,822.70 148.71 5,313.48
Idaho GTN 464.74 254.89 20.71 740.34 462.60 252.55 20.56 735.71 460.98 251.41 20.51 732.89
Idaho NWP 1,975.14 1,083.30 88.00 3,146.44 1,966.04 1,073.35 87.39 3,126.77 1,959.14 1,068.48 87.18 3,114.80
ID Sub-Total 5,809.22 3,186.17 258.84 9,254.23 5,782.46 3,156.91 257.02 9,196.40 5,762.19 3,142.59 256.40 9,161.18
Case Total 22,878.27 13,237.89 608.79 36,724.94 22,782.18 13,150.66 602.35 36,535.20 22,739.04 13,127.28 598.42 36,464.74
Area
2026-2027:
Residential
2026-2027:
Commercial
2026-2027:
Ind
FirmSale
2026-2027:
Total
2027-2028:
Residential
2027-2028:
Commercial
2027-2028:
Ind
FirmSale
2027-2028:
Total
2028-2029:
Residential
2028-2029:
Commercial
2028-2029:
Ind
FirmSale
2028-2029:
Total
Klamath Falls 935.30 458.98 13.02 1,407.31 945.90 461.83 12.93 1,420.66 946.12 460.20 12.72 1,419.04
La Grande 491.39 312.11 54.39 857.89 493.84 313.39 53.89 861.13 492.31 312.02 53.14 857.47
Medford GTN 2,456.53 1,503.96 17.32 3,977.81 2,480.18 1,516.53 17.19 4,013.89 2,479.88 1,516.16 16.93 4,012.97
Medford NWP 1,103.66 675.69 7.78 1,787.13 1,114.28 681.34 7.72 1,803.34 1,114.15 681.17 7.61 1,802.93
Roseburg 769.36 572.78 2.21 1,344.34 778.26 574.79 2.19 1,355.25 779.82 571.68 2.16 1,353.66
OR Sub-Total 5,756.24 3,523.51 94.72 9,374.47 5,812.47 3,547.88 93.92 9,454.27 5,812.28 3,541.24 92.55 9,446.08
Washington Both 6,482.38 3,739.61 141.49 10,363.48 6,460.16 3,742.67 140.63 10,343.45 6,375.69 3,711.75 138.75 10,226.19
Washington GTN 894.12 515.81 19.52 1,429.44 891.06 516.23 19.40 1,426.68 879.40 511.97 19.14 1,410.51
Washington NWP 3,800.02 2,192.18 82.94 6,075.14 3,786.99 2,193.98 82.44 6,063.40 3,737.47 2,175.85 81.34 5,994.66
WA Sub-Total 11,176.52 6,447.60 243.94 17,868.06 11,138.21 6,452.87 242.46 17,833.54 10,992.56 6,399.57 239.23 17,631.36
Idaho Both 3,325.06 1,814.10 148.37 5,287.53 3,320.27 1,813.45 148.64 5,282.35 3,286.22 1,797.53 147.75 5,231.50
Idaho GTN 458.63 250.22 20.46 729.31 457.97 250.13 20.50 728.60 453.27 247.93 20.38 721.59
Idaho NWP 1,949.17 1,063.44 86.97 3,099.59 1,946.36 1,063.06 87.13 3,096.55 1,926.41 1,053.72 86.61 3,066.74
ID Sub-Total 5,732.86 3,127.77 255.80 9,116.43 5,724.60 3,126.63 256.27 9,107.50 5,665.90 3,099.18 254.74 9,019.82
Case Total 22,665.62 13,098.88 594.46 36,358.96 22,675.27 13,127.39 592.65 36,395.31 22,470.74 13,039.99 586.53 36,097.26
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 110 of 829
APPENDIX 2.9: DETAILED DEMAND DATA
EXPECTED MIX

Area
2029-2030:
Residential
2029-2030:
Commercial
2029-2030:
Ind
FirmSale
2029-2030:
Total
2030-2031:
Residential
2030-2031:
Commercial
2030-2031:
Ind
FirmSale
2030-2031:
Total
2031-2032:
Residential
2031-2032:
Commercial
2031-2032:
Ind
FirmSale
2031-2032:
Total
Klamath Falls 950.47 460.73 12.56 1,423.76 954.48 461.28 12.39 1,428.15 963.58 464.03 12.25 1,439.86
La Grande 492.64 311.94 52.48 857.06 492.80 311.83 51.75 856.38 494.90 313.04 51.06 859.00
Medford GTN 2,489.65 1,521.73 16.72 4,028.11 2,498.28 1,526.98 16.49 4,041.75 2,517.50 1,538.42 16.29 4,072.21
Medford NWP 1,118.54 683.68 7.51 1,809.73 1,122.42 686.03 7.41 1,815.86 1,131.05 691.17 7.32 1,829.54
Roseburg 784.40 570.95 2.13 1,357.48 788.14 569.98 2.10 1,360.23 794.90 571.34 2.08 1,368.32
OR Sub-Total 5,835.71 3,549.03 91.40 9,476.13 5,856.12 3,556.11 90.14 9,502.37 5,901.93 3,578.00 88.99 9,568.92
Washington Both 6,321.09 3,699.55 137.44 10,158.08 6,272.26 3,688.35 136.16 10,096.76 6,261.52 3,696.18 135.41 10,093.11
Washington GTN 871.87 510.28 18.96 1,401.11 865.14 508.74 18.78 1,392.66 863.66 509.82 18.68 1,392.15
Washington NWP 3,705.47 2,168.70 80.57 5,954.74 3,676.84 2,162.13 79.82 5,918.79 3,670.55 2,166.72 79.38 5,916.65
WA Sub-Total 10,898.44 6,378.53 236.97 17,513.94 10,814.24 6,359.22 234.76 17,408.21 10,795.73 6,372.72 233.47 17,401.91
Idaho Both 3,268.76 1,790.57 147.48 5,206.81 3,256.81 1,784.71 147.24 5,188.76 3,266.97 1,788.16 147.60 5,202.73
Idaho GTN 450.86 246.98 20.34 718.18 449.22 246.17 20.31 715.69 450.62 246.64 20.36 717.62
Idaho NWP 1,916.17 1,049.65 86.46 3,052.27 1,909.16 1,046.21 86.31 3,041.69 1,915.12 1,048.23 86.52 3,049.88
ID Sub-Total 5,635.79 3,087.19 254.28 8,977.26 5,615.19 3,077.09 253.85 8,946.13 5,632.71 3,083.04 254.48 8,970.23
Case Total 22,369.93 13,014.75 582.64 35,967.33 22,285.55 12,992.41 578.75 35,856.71 22,330.37 13,033.76 576.94 35,941.07
Area 2032-2033: Residential 2032-2033: Commercial
2032-2033: Ind FirmSale 2032-2033: Total 2033-2034: Residential 2033-2034: Commercial
2033-2034: Ind FirmSale 2033-2034: Total 2034-2035: Residential 2034-2035: Commercial
2034-2035: Ind FirmSale 2034-2035: Total
Klamath Falls 962.62 462.23 12.00 1,436.85 966.73 462.63 11.78 1,441.14 970.81 463.02 11.56 1,445.39
La Grande 492.75 311.56 50.11 854.41 492.54 311.37 49.21 853.13 492.28 311.24 48.28 851.79
Medford GTN 2,512.39 1,536.46 15.97 4,064.82 2,518.22 1,540.79 15.68 4,074.69 2,523.44 1,544.92 15.39 4,083.75
Medford NWP 1,128.75 690.29 7.17 1,826.22 1,131.38 692.24 7.05 1,830.66 1,133.72 694.09 6.92 1,834.73
Roseburg 794.19 567.56 2.03 1,363.78 796.93 566.24 2.00 1,365.17 799.57 564.93 1.96 1,366.46
OR Sub-Total 5,890.69 3,568.10 87.28 9,546.08 5,905.80 3,573.27 85.72 9,564.79 5,919.81 3,578.20 84.11 9,582.11 Washington Both 6,198.50 3,671.47 133.67 10,003.64 6,172.03 3,668.62 132.45 9,973.10 6,153.87 3,668.91 131.24 9,954.03
Washington GTN 854.97 506.41 18.44 1,379.81 851.32 506.02 18.27 1,375.60 848.81 506.06 18.10 1,372.97
Washington NWP 3,633.60 2,152.24 78.36 5,864.20 3,618.09 2,150.57 77.64 5,846.30 3,607.44 2,150.74 76.94 5,835.12
WA Sub-Total 10,687.07 6,330.12 230.46 17,247.65 10,641.44 6,325.20 228.36 17,195.00 10,610.13 6,325.70 226.28 17,162.11
Idaho Both 3,253.17 1,777.22 146.80 5,177.19 3,260.50 1,777.02 146.61 5,184.12 3,274.00 1,778.52 146.42 5,198.95
Idaho GTN 448.71 245.13 20.25 714.10 449.72 245.11 20.22 715.05 451.59 245.31 20.20 717.10
Idaho NWP 1,907.03 1,041.82 86.05 3,034.90 1,911.33 1,041.70 85.94 3,038.97 1,919.24 1,042.58 85.83 3,047.66
ID Sub-Total 5,608.92 3,064.18 253.10 8,926.19 5,621.56 3,063.82 252.77 8,938.15 5,644.83 3,066.42 252.46 8,963.71
Case Total 22,186.68 12,962.40 570.83 35,719.91 22,168.80 12,962.29 566.85 35,697.94 22,174.77 12,970.32 562.85 35,707.94
Area
2035-2036:
Residential
2035-2036:
Commercial
2035-2036:
Ind
FirmSale
2035-2036:
Total
2036-2037:
Residential
2036-2037:
Commercial
2036-2037:
Ind
FirmSale
2036-2037:
Total
Klamath Falls 980.21 465.79 11.38 1,457.38 979.29 463.88 11.11 1,454.28
La Grande 494.06 312.43 47.42 853.91 491.65 310.80 46.39 848.83
Medford GTN 2,540.44 1,555.58 15.14 4,111.16 2,533.52 1,552.82 14.79 4,101.13
Medford NWP 1,141.36 698.88 6.80 1,847.04 1,138.25 697.64 6.65 1,842.54
Roseburg 805.94 566.14 1.93 1,374.01 804.96 562.19 1.88 1,369.04
OR Sub-Total 5,962.01 3,598.83 82.67 9,643.50 5,947.66 3,587.34 80.82 9,615.82
Washington Both 6,174.01 3,689.88 130.55 9,994.44 6,137.04 3,677.80 128.87 9,943.70
Washington GTN 851.59 508.95 18.01 1,378.54 846.49 507.28 17.77 1,371.55
Washington NWP 3,619.25 2,163.03 76.53 5,858.81 3,597.57 2,155.95 75.54 5,829.07
WA Sub-Total 10,644.85 6,361.86 225.08 17,231.79 10,581.10 6,341.03 222.18 17,144.32
Idaho Both 3,308.89 1,789.76 146.84 5,245.48 3,315.58 1,786.11 146.08 5,247.77
Idaho GTN 456.40 246.86 20.25 723.52 457.32 246.36 20.15 723.83
Idaho NWP 1,939.69 1,049.17 86.08 3,074.94 1,943.62 1,047.03 85.63 3,076.28
ID Sub-Total 5,704.98 3,085.79 253.17 9,043.94 5,716.52 3,079.50 251.86 9,047.89
Case Total 22,311.83 13,046.47 560.92 35,919.23 22,245.28 13,007.87 554.86 35,808.02
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 111 of 829
APPENDIX 2.9: DETAILED DEMAND DATA
LOW GROWTH HIGH PRICE

Area
2017-2018:
Residential
2017-2018:
Commercial
2017-2018:
Ind
FirmSale
2017-2018:
Total
2018-2019:
Residential
2018-2019:
Commercial
2018-2019:
Ind
FirmSale
2018-2019:
Total
2019-2020:
Residential
2019-2020:
Commercial
2019-2020:
Ind
FirmSale
2019-2020:
Total
Klamath Falls 867.19 448.44 13.52 1,329.16 871.85 447.30 12.51 1,331.66 879.21 448.75 11.53 1,339.49
La Grande 481.35 308.50 53.76 843.60 480.73 307.57 47.19 835.49 481.59 307.72 36.47 825.78
Medford GTN 2,283.52 1,421.48 18.29 3,723.29 2,296.93 1,426.25 17.44 3,740.63 2,317.07 1,434.65 16.69 3,768.41
Medford NWP 1,025.93 638.64 8.22 1,672.78 1,031.96 640.78 7.84 1,680.57 1,041.00 644.55 7.50 1,693.05
Roseburg 714.37 571.66 2.10 1,288.12 717.79 569.97 1.50 1,289.27 723.19 569.55 0.91 1,293.65
OR Sub-Total 5,372.37 3,388.70 95.89 8,856.96 5,399.26 3,391.87 86.49 8,877.62 5,442.07 3,405.22 73.09 8,920.39
Washington Both 6,271.88 3,722.51 154.41 10,148.80 6,332.03 3,726.53 150.46 10,209.02 6,380.77 3,734.51 146.81 10,262.09
Washington GTN 865.09 513.45 21.30 1,399.83 873.38 514.00 20.75 1,408.14 880.11 515.10 20.25 1,415.46
Washington NWP 3,676.62 2,182.16 90.51 5,949.30 3,711.88 2,184.52 88.20 5,984.60 3,740.45 2,189.20 86.06 6,015.71
WA Sub-Total 10,813.59 6,418.12 266.22 17,497.93 10,917.29 6,425.05 259.41 17,601.75 11,001.32 6,438.81 253.13 17,693.26
Idaho Both 3,143.30 1,821.15 146.23 5,110.68 3,166.01 1,816.90 142.74 5,125.65 3,192.94 1,816.20 139.71 5,148.85
Idaho GTN 433.56 251.19 20.17 704.92 436.69 250.61 19.69 706.99 440.41 250.51 19.27 710.19
Idaho NWP 1,842.62 1,067.57 85.72 2,995.92 1,855.93 1,065.08 83.68 3,004.69 1,871.72 1,064.67 81.90 3,018.29
ID Sub-Total 5,419.48 3,139.91 252.12 8,811.52 5,458.63 3,132.59 246.11 8,837.33 5,505.07 3,131.37 240.88 8,877.32
Case Total 21,605.44 12,946.74 614.22 35,166.40 21,775.18 12,949.51 592.01 35,316.70 21,948.46 12,975.40 567.10 35,490.97
Area 2020-2021: Residential 2020-2021: Commercial
2020-2021: Ind FirmSale 2020-2021: Total 2021-2022: Residential 2021-2022: Commercial
2021-2022: Ind FirmSale 2021-2022: Total 2022-2023: Residential 2022-2023: Commercial
2022-2023: Ind FirmSale 2022-2023: TotalKlamath Falls 877.85 445.67 10.47 1,333.99 877.82 443.10 9.44 1,330.35 880.40 441.87 8.42 1,330.70
La Grande 478.65 305.40 28.10 812.16 476.32 303.66 22.73 802.71 475.08 302.60 18.50 796.18
Medford GTN 2,317.02 1,431.68 15.88 3,764.58 2,319.86 1,430.90 15.14 3,765.91 2,328.62 1,433.33 14.41 3,776.36
Medford NWP 1,040.98 643.22 7.14 1,691.33 1,042.26 642.87 6.80 1,691.93 1,046.19 643.96 6.48 1,696.63
Roseburg 722.47 564.55 0.30 1,287.32 722.56 560.27 - 1,282.83 724.78 557.51 - 1,282.28
OR Sub-Total 5,436.97 3,390.52 61.89 8,889.38 5,438.82 3,380.80 54.12 8,873.74 5,455.07 3,379.27 47.81 8,882.14
Washington Both 6,363.95 3,708.85 142.12 10,214.92 6,359.17 3,696.87 138.06 10,194.10 6,331.78 3,678.47 133.99 10,144.24
Washington GTN 877.79 511.57 19.60 1,408.95 877.13 509.91 19.04 1,406.08 873.35 507.38 18.48 1,399.21
Washington NWP 3,730.59 2,174.15 83.31 5,988.06 3,727.79 2,167.13 80.93 5,975.85 3,711.73 2,156.35 78.55 5,946.62
WA Sub-Total 10,972.33 6,394.57 245.04 17,611.93 10,964.09 6,373.91 238.04 17,576.04 10,916.86 6,342.19 231.02 17,490.07
Idaho Both 3,190.35 1,799.69 135.59 5,125.63 3,190.43 1,787.98 132.01 5,110.42 3,180.13 1,773.65 128.42 5,082.20
Idaho GTN 440.05 248.23 18.70 706.98 440.06 246.62 18.21 704.89 438.64 244.64 17.71 700.99
Idaho NWP 1,870.20 1,054.99 79.49 3,004.68 1,870.25 1,048.13 77.38 2,995.77 1,864.21 1,039.72 75.28 2,979.22
ID Sub-Total 5,500.60 3,102.92 233.78 8,837.30 5,500.75 3,082.73 227.60 8,811.07 5,482.98 3,058.01 221.42 8,762.42
Case Total 21,909.90 12,888.00 540.71 35,338.61 21,903.66 12,837.44 519.75 35,260.85 21,854.91 12,779.47 500.24 35,134.63
Area
2023-2024:
Residential
2023-2024:
Commercial
2023-2024:
Ind
FirmSale
2023-2024:
Total
2024-2025:
Residential
2024-2025:
Commercial
2024-2025:
Ind
FirmSale
2024-2025:
Total
2025-2026:
Residential
2025-2026:
Commercial
2025-2026:
Ind
FirmSale
2025-2026:
Total
Klamath Falls 887.60 442.82 7.43 1,337.85 885.12 439.29 6.40 1,330.81 887.96 438.25 5.39 1,331.59
La Grande 475.80 302.87 14.95 793.62 472.50 300.55 11.92 784.97 471.52 299.77 8.98 780.26
Medford GTN 2,345.88 1,441.33 13.70 3,800.92 2,339.53 1,436.54 12.91 3,788.98 2,345.76 1,438.63 12.14 3,796.53
Medford NWP 1,053.95 647.55 6.16 1,707.66 1,051.09 645.40 5.80 1,702.30 1,053.89 646.34 5.46 1,705.69
Roseburg 730.31 557.15 - 1,287.46 728.96 551.77 - 1,280.73 731.42 549.20 - 1,280.62
OR Sub-Total 5,493.54 3,391.72 42.25 8,927.51 5,477.20 3,373.56 37.02 8,887.78 5,490.55 3,372.19 31.96 8,894.70
Washington Both 6,386.36 3,672.84 130.43 10,189.63 6,319.52 3,629.49 125.88 10,074.88 6,261.94 3,604.62 121.91 9,988.47
Washington GTN 880.88 506.60 17.99 1,405.47 871.66 500.62 17.36 1,389.64 863.72 497.19 16.82 1,377.72
Washington NWP 3,743.73 2,153.04 76.46 5,973.23 3,704.54 2,127.63 73.79 5,905.97 3,670.80 2,113.05 71.46 5,855.31
WA Sub-Total 11,010.96 6,332.48 224.89 17,568.32 10,895.72 6,257.74 217.03 17,370.49 10,796.46 6,214.86 210.19 17,221.50
Idaho Both 3,213.90 1,765.04 125.35 5,104.29 3,180.85 1,739.35 121.26 5,041.45 3,151.09 1,722.19 117.76 4,991.04
Idaho GTN 443.30 243.45 17.29 704.04 438.74 239.91 16.73 695.37 434.63 237.54 16.24 688.42
Idaho NWP 1,884.01 1,034.68 73.48 2,992.17 1,864.63 1,019.62 71.08 2,955.33 1,847.19 1,009.56 69.03 2,925.78
ID Sub-Total 5,541.21 3,043.17 216.13 8,800.50 5,484.22 2,998.87 209.07 8,692.16 5,432.92 2,969.30 203.03 8,605.24
Case Total 22,045.71 12,767.36 483.26 35,296.33 21,857.14 12,630.17 463.12 34,950.43 21,719.92 12,556.34 445.18 34,721.44
Area
2026-2027:
Residential
2026-2027:
Commercial
2026-2027:
Ind
FirmSale
2026-2027:
Total
2027-2028:
Residential
2027-2028:
Commercial
2027-2028:
Ind
FirmSale
2027-2028:
Total
2028-2029:
Residential
2028-2029:
Commercial
2028-2029:
Ind
FirmSale
2028-2029:
Total
Klamath Falls 890.42 437.15 4.38 1,331.95 897.08 438.17 3.38 1,338.64 893.33 434.75 2.36 1,330.45
La Grande 470.30 298.80 6.81 775.91 470.65 298.74 4.65 774.04 466.58 295.81 2.49 764.88
Medford GTN 2,351.10 1,440.30 11.35 3,802.75 2,366.09 1,447.64 10.58 3,824.31 2,356.52 1,441.84 9.71 3,808.07
Medford NWP 1,056.29 647.09 5.10 1,708.48 1,063.03 650.39 4.75 1,718.17 1,058.73 647.78 4.36 1,710.87
Roseburg 733.73 546.50 - 1,280.22 739.08 546.09 - 1,285.16 736.90 540.50 - 1,277.40
OR Sub-Total 5,501.84 3,369.83 27.65 8,899.31 5,535.92 3,381.04 23.36 8,940.32 5,512.06 3,360.69 18.92 8,891.67
Washington Both 6,193.46 3,577.92 117.96 9,889.34 6,145.86 3,567.48 114.47 9,827.81 6,033.46 3,522.11 110.09 9,665.67
Washington GTN 854.27 493.51 16.27 1,364.05 847.70 492.07 15.79 1,355.56 832.20 485.81 15.18 1,333.20
Washington NWP 3,630.65 2,097.40 69.15 5,797.20 3,602.75 2,091.28 67.10 5,761.13 3,536.86 2,064.69 64.54 5,666.08
WA Sub-Total 10,678.37 6,168.84 203.38 17,050.59 10,596.31 6,150.83 197.36 16,944.51 10,402.52 6,072.61 189.81 16,664.94
Idaho Both 3,116.09 1,704.88 114.27 4,935.25 3,092.23 1,695.07 111.25 4,898.55 3,037.64 1,669.72 107.33 4,814.68
Idaho GTN 429.81 235.16 15.76 680.72 426.51 233.80 15.34 675.66 418.98 230.31 14.80 664.09
Idaho NWP 1,826.68 999.42 66.98 2,893.08 1,812.69 993.66 65.22 2,871.56 1,780.68 978.80 62.92 2,822.40
ID Sub-Total 5,372.58 2,939.46 197.01 8,509.05 5,331.44 2,922.53 191.81 8,445.77 5,237.30 2,878.83 185.05 8,301.18
Case Total 21,552.79 12,478.12 428.04 34,458.95 21,463.66 12,454.40 412.54 34,330.60 21,151.88 12,312.13 393.78 33,857.79
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 112 of 829
APPENDIX 2.9: DETAILED DEMAND DATA
LOW GROWTH HIGH PRICE

Area
2029-2030:
Residential
2029-2030:
Commercial
2029-2030:
Ind
FirmSale
2029-2030:
Total
2030-2031:
Residential
2030-2031:
Commercial
2030-2031:
Ind
FirmSale
2030-2031:
Total
2031-2032:
Residential
2031-2032:
Commercial
2031-2032:
Ind
FirmSale
2031-2032:
Total
Klamath Falls 894.55 433.84 1.36 1,329.74 895.54 433.01 0.37 1,328.92 901.22 434.21 - 1,335.43
La Grande 464.65 294.31 0.81 759.78 462.78 292.93 - 755.71 462.91 292.90 - 755.81
Medford GTN 2,358.43 1,442.63 8.87 3,809.94 2,359.40 1,443.20 8.02 3,810.62 2,370.52 1,449.72 7.17 3,827.41
Medford NWP 1,059.59 648.14 3.99 1,711.71 1,060.02 648.40 3.60 1,712.02 1,065.02 651.32 3.22 1,719.56
Roseburg 738.26 537.64 - 1,275.90 739.10 534.78 - 1,273.88 742.96 534.26 - 1,277.22
OR Sub-Total 5,515.48 3,356.56 15.02 8,887.06 5,516.85 3,352.32 11.99 8,881.16 5,542.63 3,362.42 10.39 8,915.44
Washington Both 5,955.52 3,497.77 106.22 9,559.51 5,883.84 3,474.80 102.38 9,461.02 5,848.95 3,470.19 98.93 9,418.07
Washington GTN 821.45 482.45 14.65 1,318.55 811.56 479.28 14.12 1,304.97 806.75 478.65 13.65 1,299.04
Washington NWP 3,491.17 2,050.42 62.27 5,603.85 3,449.15 2,036.95 60.02 5,546.11 3,428.70 2,034.25 57.99 5,520.94
WA Sub-Total 10,268.13 6,030.64 183.15 16,481.92 10,144.55 5,991.03 176.52 16,312.10 10,084.40 5,983.08 170.57 16,238.05
Idaho Both 3,001.46 1,654.09 103.92 4,759.48 2,970.30 1,639.44 100.53 4,710.27 2,959.42 1,633.33 97.55 4,690.31
Idaho GTN 414.00 228.15 14.33 656.48 409.70 226.13 13.87 649.69 408.20 225.29 13.46 646.94
Idaho NWP 1,759.48 969.64 60.92 2,790.04 1,741.21 961.05 58.93 2,761.19 1,734.83 957.47 57.19 2,749.49
ID Sub-Total 5,174.94 2,851.89 179.17 8,205.99 5,121.20 2,826.62 173.32 8,121.15 5,102.45 2,816.09 168.20 8,086.74
Case Total 20,958.55 12,239.08 377.34 33,574.97 20,782.61 12,169.97 361.83 33,314.41 20,729.48 12,161.58 349.16 33,240.23
Area 2032-2033: Residential 2032-2033: Commercial
2032-2033: Ind FirmSale 2032-2033: Total 2033-2034: Residential 2033-2034: Commercial
2033-2034: Ind FirmSale 2033-2034: Total 2034-2035: Residential 2034-2035: Commercial
2034-2035: Ind FirmSale 2034-2035: Total
Klamath Falls 897.36 431.09 - 1,328.45 898.18 430.02 - 1,328.20 898.98 428.94 - 1,327.92
La Grande 459.19 290.44 - 749.63 457.53 289.33 - 746.86 455.90 288.34 - 744.23
Medford GTN 2,358.79 1,443.66 6.25 3,808.70 2,357.52 1,443.60 5.34 3,806.46 2,355.79 1,443.42 4.42 3,803.63
Medford NWP 1,059.75 648.60 2.81 1,711.16 1,059.18 648.57 2.40 1,710.15 1,058.40 648.49 1.99 1,708.88
Roseburg 739.87 528.97 - 1,268.85 740.07 526.04 - 1,266.11 740.19 523.14 - 1,263.33
OR Sub-Total 5,514.97 3,342.76 9.05 8,866.78 5,512.48 3,337.56 7.74 8,857.78 5,509.25 3,332.33 6.41 8,847.99 Washington Both 5,765.54 3,435.25 94.74 9,295.53 5,717.44 3,421.52 90.95 9,229.91 5,677.98 3,411.19 87.17 9,176.34
Washington GTN 795.25 473.83 13.07 1,282.14 788.61 471.93 12.54 1,273.09 783.17 470.51 12.02 1,265.70
Washington NWP 3,379.80 2,013.77 55.54 5,449.10 3,351.60 2,005.72 53.32 5,410.64 3,328.47 1,999.67 51.10 5,379.23
WA Sub-Total 9,940.59 5,922.84 163.35 16,026.78 9,857.65 5,899.17 156.81 15,913.63 9,789.62 5,881.37 150.29 15,821.27
Idaho Both 2,926.48 1,613.97 93.81 4,634.26 2,912.92 1,604.60 90.48 4,607.99 2,905.00 1,596.87 87.15 4,589.02
Idaho GTN 403.65 222.62 12.94 639.21 401.78 221.32 12.48 635.59 400.69 220.26 12.02 632.97
Idaho NWP 1,715.52 946.12 54.99 2,716.63 1,707.57 940.63 53.04 2,701.24 1,702.93 936.09 51.09 2,690.12
ID Sub-Total 5,045.66 2,782.70 161.74 7,990.10 5,022.27 2,766.56 155.99 7,944.82 5,008.62 2,753.22 150.26 7,912.11
Case Total 20,501.21 12,048.31 334.14 32,883.66 20,392.40 12,003.29 320.54 32,716.23 20,307.49 11,966.92 306.96 32,581.37
Area
2035-2036:
Residential
2035-2036:
Commercial
2035-2036:
Ind
FirmSale
2035-2036:
Total
2036-2037:
Residential
2036-2037:
Commercial
2036-2037:
Ind
FirmSale
2036-2037:
Total
Klamath Falls 904.66 430.04 - 1,334.70 900.71 426.79 - 1,327.51
La Grande 456.31 288.67 - 744.98 452.91 286.41 - 739.32
Medford GTN 2,365.13 1,449.38 3.51 3,818.02 2,352.12 1,442.77 2.57 3,797.46
Medford NWP 1,062.59 651.17 1.58 1,715.34 1,056.75 648.20 1.16 1,706.11
Roseburg 743.76 522.59 - 1,266.35 740.50 517.26 - 1,257.76
OR Sub-Total 5,532.45 3,341.85 5.09 8,879.39 5,502.99 3,321.44 3.73 8,828.16
Washington Both 5,674.94 3,420.56 83.72 9,179.21 5,619.00 3,399.29 79.62 9,097.91
Washington GTN 782.75 471.80 11.55 1,266.10 775.03 468.87 10.98 1,254.88
Washington NWP 3,326.69 2,005.15 49.07 5,380.92 3,293.90 1,992.69 46.67 5,333.26
WA Sub-Total 9,784.38 5,897.51 144.34 15,826.23 9,687.93 5,860.84 137.28 15,686.05
Idaho Both 2,988.78 1,597.98 84.18 4,670.94 2,829.63 1,585.64 80.53 4,495.80
Idaho GTN 412.25 220.41 11.61 644.27 390.29 218.71 11.11 620.11
Idaho NWP 1,752.04 936.75 49.35 2,738.14 1,658.75 929.51 47.20 2,635.47
ID Sub-Total 5,153.06 2,755.13 145.14 8,053.34 4,878.67 2,733.87 138.84 7,751.38
Case Total 20,469.89 11,994.50 294.57 32,758.96 20,069.60 11,916.15 279.84 32,265.59
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 113 of 829
APPENDIX 2.9: DETAILED DEMAND DATA
HIGH GROWTH LOW PRICE

Area
2017-2018:
Residential
2017-2018:
Commercial
2017-2018:
Ind
FirmSale
2017-2018:
Total
2018-2019:
Residential
2018-2019:
Commercial
2018-2019:
Ind
FirmSale
2018-2019:
Total
2019-2020:
Residential
2019-2020:
Commercial
2019-2020:
Ind
FirmSale
2019-2020:
Total
Klamath Falls 881.72 456.05 14.37 1,352.15 893.78 458.64 15.22 1,367.64 909.69 464.28 16.16 1,390.14
La Grande 489.91 314.01 53.19 857.10 493.41 315.71 64.23 873.35 498.66 318.60 74.75 892.01
Medford GTN 2,319.19 1,444.15 18.94 3,782.28 2,351.04 1,460.29 19.35 3,830.68 2,393.03 1,481.67 19.86 3,894.57
Medford NWP 1,041.96 648.82 8.51 1,699.28 1,056.26 656.07 8.69 1,721.03 1,075.13 665.68 8.92 1,749.73
Roseburg 724.99 580.32 2.67 1,307.97 734.09 583.06 3.24 1,320.40 746.20 587.66 3.83 1,337.69
OR Sub-Total 5,457.76 3,443.35 97.68 8,998.79 5,528.58 3,473.77 110.74 9,113.10 5,622.71 3,517.90 123.53 9,264.14
Washington Both 6,366.46 3,779.14 157.78 10,303.39 6,475.63 3,811.46 161.07 10,448.16 6,591.71 3,857.14 164.97 10,613.82
Washington GTN 878.13 521.26 21.76 1,421.16 893.19 525.72 22.22 1,441.13 909.20 532.02 22.75 1,463.97
Washington NWP 3,732.06 2,215.36 92.49 6,039.92 3,796.06 2,234.30 94.42 6,124.79 3,864.11 2,261.08 96.70 6,221.89
WA Sub-Total 10,976.66 6,515.77 272.04 17,764.46 11,164.88 6,571.48 277.72 18,014.08 11,365.02 6,650.24 284.42 18,299.68
Idaho Both 3,203.31 1,856.52 149.22 5,209.05 3,259.62 1,871.21 152.04 5,282.88 3,327.18 1,892.37 155.47 5,375.02
Idaho GTN 441.84 256.07 20.58 718.49 449.60 258.10 20.97 728.67 458.92 261.02 21.44 741.38
Idaho NWP 1,877.80 1,088.30 87.47 3,053.58 1,910.81 1,096.92 89.13 3,096.86 1,950.42 1,109.32 91.13 3,150.87
ID Sub-Total 5,522.95 3,200.89 257.27 8,981.12 5,620.04 3,226.23 262.14 9,108.41 5,736.52 3,262.71 268.04 9,267.28
Case Total 21,957.37 13,160.00 626.99 35,744.36 22,313.50 13,271.48 650.59 36,235.58 22,724.25 13,430.85 676.00 36,831.10
Area 2020-2021: Residential 2020-2021: Commercial
2020-2021: Ind FirmSale 2020-2021: Total 2021-2022: Residential 2021-2022: Commercial
2021-2022: Ind FirmSale 2021-2022: Total 2022-2023: Residential 2022-2023: Commercial
2022-2023: Ind FirmSale 2022-2023: TotalKlamath Falls 916.68 465.28 17.02 1,398.99 928.46 468.24 17.96 1,414.66 940.24 471.40 18.90 1,430.53
La Grande 499.82 318.85 85.10 903.77 502.84 320.36 95.70 918.89 505.62 321.81 106.29 933.71
Medford GTN 2,414.05 1,491.25 20.30 3,925.60 2,445.49 1,506.64 20.83 3,972.97 2,476.06 1,521.92 21.36 4,019.33
Medford NWP 1,084.57 669.98 9.12 1,763.67 1,098.70 676.90 9.36 1,784.96 1,112.43 683.76 9.60 1,805.79
Roseburg 752.10 587.58 4.40 1,344.08 761.53 589.92 4.99 1,356.44 771.08 592.44 5.57 1,369.09
OR Sub-Total 5,667.22 3,532.94 135.94 9,336.10 5,737.02 3,562.05 148.84 9,447.91 5,805.42 3,591.33 161.71 9,558.45
Washington Both 6,640.57 3,867.88 167.65 10,676.09 6,694.80 3,888.52 170.92 10,754.24 6,727.91 3,903.22 174.19 10,805.33
Washington GTN 915.94 533.50 23.12 1,472.56 923.42 536.35 23.58 1,483.34 927.99 538.38 24.03 1,490.39
Washington NWP 3,892.75 2,267.38 98.27 6,258.40 3,924.54 2,279.48 100.19 6,304.21 3,943.95 2,288.10 102.11 6,334.16
WA Sub-Total 11,449.25 6,668.76 289.04 18,407.06 11,542.76 6,704.34 294.69 18,541.79 11,599.84 6,729.69 300.33 18,629.87
Idaho Both 3,365.66 1,897.60 157.67 5,420.93 3,409.08 1,908.36 160.47 5,477.91 3,442.83 1,916.43 163.26 5,522.53
Idaho GTN 464.23 261.74 21.75 747.71 470.22 263.22 22.13 755.57 474.87 264.34 22.52 761.73
Idaho NWP 1,972.97 1,112.39 92.43 3,177.79 1,998.43 1,118.69 94.07 3,211.19 2,018.21 1,123.43 95.71 3,237.34
ID Sub-Total 5,802.86 3,271.72 271.85 9,346.43 5,877.73 3,290.27 276.68 9,444.68 5,935.92 3,304.19 281.49 9,521.60
Case Total 22,919.33 13,473.42 696.84 37,089.59 23,157.51 13,556.66 720.21 37,434.37 23,341.18 13,625.21 743.53 37,709.93
Area
2023-2024:
Residential
2023-2024:
Commercial
2023-2024:
Ind
FirmSale
2023-2024:
Total
2024-2025:
Residential
2024-2025:
Commercial
2024-2025:
Ind
FirmSale
2024-2025:
Total
2025-2026:
Residential
2025-2026:
Commercial
2025-2026:
Ind
FirmSale
2025-2026:
Total
Klamath Falls 956.74 476.75 19.89 1,453.38 962.10 476.95 20.73 1,459.79 973.09 479.74 21.63 1,474.46
La Grande 510.18 324.49 117.08 951.76 509.91 324.09 127.31 961.31 511.79 325.13 137.76 974.69
Medford GTN 2,513.57 1,541.89 21.93 4,077.39 2,523.51 1,547.06 22.36 4,092.93 2,546.87 1,559.56 22.84 4,129.28
Medford NWP 1,129.29 692.73 9.85 1,831.87 1,133.75 695.06 10.05 1,838.85 1,144.25 700.67 10.26 1,855.18
Roseburg 784.06 597.39 6.19 1,387.64 789.18 596.61 6.73 1,392.52 798.35 598.73 7.31 1,404.39
OR Sub-Total 5,893.85 3,633.26 174.93 9,702.04 5,918.45 3,639.76 187.18 9,745.40 5,974.36 3,663.82 199.82 9,838.00
Washington Both 6,841.93 3,930.00 178.11 10,950.04 6,825.75 3,914.06 180.58 10,920.40 6,819.52 3,916.83 183.83 10,920.19
Washington GTN 943.71 542.07 24.57 1,510.35 941.48 539.87 24.91 1,506.26 940.62 540.25 25.36 1,506.23
Washington NWP 4,010.79 2,303.79 104.41 6,418.99 4,001.30 2,294.45 105.86 6,401.61 3,997.65 2,296.07 107.76 6,401.49
WA Sub-Total 11,796.43 6,775.86 307.09 18,879.38 11,768.53 6,748.38 311.35 18,828.27 11,757.80 6,753.16 316.95 18,827.91
Idaho Both 3,519.47 1,929.35 166.71 5,615.52 3,523.41 1,922.09 168.75 5,614.25 3,531.17 1,923.46 171.54 5,626.16
Idaho GTN 485.44 266.12 22.99 774.55 485.99 265.12 23.28 774.38 487.06 265.30 23.66 776.02
Idaho NWP 2,063.14 1,131.00 97.72 3,291.86 2,065.45 1,126.74 98.92 3,291.11 2,070.00 1,127.54 100.56 3,298.10
ID Sub-Total 6,068.04 3,326.46 287.42 9,681.93 6,074.85 3,313.95 290.94 9,679.74 6,088.22 3,316.31 295.75 9,700.28
Case Total 23,758.33 13,735.58 769.44 38,263.35 23,761.83 13,702.10 789.47 38,253.41 23,820.38 13,733.28 812.52 38,366.18
Area
2026-2027:
Residential
2026-2027:
Commercial
2026-2027:
Ind
FirmSale
2026-2027:
Total
2027-2028:
Residential
2027-2028:
Commercial
2027-2028:
Ind
FirmSale
2027-2028:
Total
2028-2029:
Residential
2028-2029:
Commercial
2028-2029:
Ind
FirmSale
2028-2029:
Total
Klamath Falls 983.55 482.35 22.52 1,488.43 998.48 487.20 23.47 1,509.16 1,002.24 487.20 24.25 1,513.68
La Grande 513.87 326.25 148.15 988.27 518.61 328.98 158.85 1,006.44 519.52 329.15 168.72 1,017.38
Medford GTN 2,569.36 1,571.63 23.31 4,164.29 2,602.41 1,589.87 23.82 4,216.09 2,610.31 1,594.51 24.17 4,228.98
Medford NWP 1,154.35 706.09 10.47 1,870.91 1,169.20 714.29 10.70 1,894.19 1,172.75 716.37 10.86 1,899.98
Roseburg 807.59 600.83 7.89 1,416.31 820.37 605.50 8.51 1,434.38 825.42 604.72 9.04 1,439.18
OR Sub-Total 6,028.72 3,687.15 212.34 9,928.21 6,109.07 3,725.84 225.35 10,060.26 6,130.23 3,731.95 237.03 10,099.21
Washington Both 6,801.89 3,917.29 187.10 10,906.28 6,807.40 3,935.06 191.10 10,933.56 6,747.51 3,916.96 193.72 10,858.18
Washington GTN 938.19 540.32 25.81 1,504.31 938.95 542.77 26.36 1,508.08 930.69 540.27 26.72 1,497.68
Washington NWP 3,987.32 2,296.34 109.68 6,393.34 3,990.54 2,306.76 112.03 6,409.33 3,955.44 2,296.15 113.56 6,365.14
WA Sub-Total 11,727.40 6,753.94 322.59 18,803.93 11,736.90 6,784.59 329.49 18,850.97 11,633.64 6,753.38 333.99 18,721.01
Idaho Both 3,533.81 1,924.47 174.34 5,632.63 3,549.95 1,933.95 177.88 5,661.77 3,535.49 1,927.29 180.03 5,642.81
Idaho GTN 487.42 265.44 24.05 776.91 489.65 266.75 24.53 780.93 487.65 265.83 24.83 778.32
Idaho NWP 2,071.55 1,128.14 102.20 3,301.88 2,081.00 1,133.69 104.27 3,318.97 2,072.53 1,129.79 105.53 3,307.86
ID Sub-Total 6,092.78 3,318.05 300.59 9,711.42 6,120.60 3,334.39 306.68 9,761.67 6,095.67 3,322.92 310.40 9,728.99
Case Total 23,848.90 13,759.14 835.52 38,443.57 23,966.56 13,844.82 861.52 38,672.90 23,859.53 13,808.25 881.42 38,549.20
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 114 of 829
APPENDIX 2.9: DETAILED DEMAND DATA
HIGH GROWTH LOW PRICE

Area
2029-2030:
Residential
2029-2030:
Commercial
2029-2030:
Ind
FirmSale
2029-2030:
Total
2030-2031:
Residential
2030-2031:
Commercial
2030-2031:
Ind
FirmSale
2030-2031:
Total
2031-2032:
Residential
2031-2032:
Commercial
2031-2032:
Ind
FirmSale
2031-2032:
Total
Klamath Falls 1,010.07 489.32 25.10 1,524.49 1,017.43 491.41 25.94 1,534.78 1,030.34 495.89 26.86 1,553.09
La Grande 522.35 330.63 178.96 1,031.93 524.76 331.93 189.14 1,045.84 529.08 334.53 199.76 1,063.37
Medford GTN 2,628.70 1,605.31 24.58 4,258.60 2,645.77 1,615.70 24.98 4,286.45 2,673.93 1,632.56 25.43 4,331.91
Medford NWP 1,181.01 721.23 11.04 1,913.28 1,188.68 725.90 11.22 1,925.80 1,201.33 733.47 11.43 1,946.22
Roseburg 833.56 606.36 9.61 1,449.53 840.53 607.50 10.18 1,458.21 850.51 610.96 10.80 1,472.28
OR Sub-Total 6,175.69 3,752.85 249.30 10,177.83 6,217.18 3,772.44 261.47 10,251.09 6,285.19 3,807.41 274.28 10,366.88
Washington Both 6,718.62 3,918.12 197.06 10,833.80 6,695.04 3,919.93 200.43 10,815.40 6,711.10 3,941.56 204.58 10,857.25
Washington GTN 926.71 540.43 27.18 1,494.32 923.45 540.68 27.65 1,491.78 925.67 543.66 28.22 1,497.55
Washington NWP 3,938.50 2,296.83 115.52 6,350.85 3,924.68 2,297.89 117.50 6,340.06 3,934.09 2,310.57 119.93 6,364.59
WA Sub-Total 11,583.83 6,755.37 339.77 18,678.96 11,543.17 6,758.50 345.58 18,647.24 11,570.86 6,795.80 352.73 18,719.39
Idaho Both 3,538.90 1,930.14 182.91 5,651.95 3,548.56 1,934.29 185.82 5,668.67 3,582.42 1,948.63 189.49 5,720.55
Idaho GTN 488.12 266.23 25.23 779.58 489.46 266.80 25.63 781.89 494.13 268.78 26.14 789.04
Idaho NWP 2,074.53 1,131.46 107.23 3,313.21 2,080.19 1,133.89 108.93 3,323.01 2,100.04 1,142.30 111.08 3,353.42
ID Sub-Total 6,101.55 3,327.82 315.37 9,744.74 6,118.21 3,334.98 320.38 9,773.57 6,176.59 3,359.71 326.71 9,863.01
Case Total 23,861.06 13,836.04 904.43 38,601.54 23,878.56 13,865.92 927.42 38,671.90 24,032.64 13,962.92 953.72 38,949.28
Area 2032-2033: Residential 2032-2033: Commercial
2032-2033: Ind FirmSale 2032-2033: Total 2033-2034: Residential 2033-2034: Commercial
2033-2034: Ind FirmSale 2033-2034: Total 2034-2035: Residential 2034-2035: Commercial
2034-2035: Ind FirmSale 2034-2035: Total
Klamath Falls 1,032.66 495.59 27.57 1,555.82 1,040.47 497.65 28.37 1,566.50 1,048.27 499.71 29.16 1,577.15
La Grande 528.69 334.15 209.31 1,072.15 530.15 335.01 219.32 1,084.49 531.43 335.86 229.30 1,096.59
Medford GTN 2,676.20 1,635.18 25.71 4,337.09 2,689.97 1,644.38 26.05 4,360.41 2,702.98 1,653.33 26.39 4,382.70
Medford NWP 1,202.35 734.64 11.55 1,948.55 1,208.54 738.78 11.71 1,959.02 1,214.38 742.80 11.86 1,969.04
Roseburg 852.49 608.90 11.31 1,472.70 858.11 609.42 11.88 1,479.40 863.61 609.90 12.44 1,485.95
OR Sub-Total 6,292.39 3,808.46 285.46 10,386.30 6,327.24 3,825.24 297.33 10,449.82 6,360.67 3,841.61 309.14 10,511.43 Washington Both 6,670.86 3,928.30 207.23 10,806.39 6,668.63 3,937.64 210.65 10,816.92 6,674.42 3,949.89 214.08 10,838.38
Washington GTN 920.12 541.84 28.58 1,490.54 919.81 543.12 29.06 1,491.99 920.61 544.81 29.53 1,494.95
Washington NWP 3,910.50 2,302.80 121.48 6,334.78 3,909.20 2,308.27 123.48 6,340.95 3,912.59 2,315.45 125.49 6,353.53
WA Sub-Total 11,501.48 6,772.94 357.29 18,631.71 11,497.64 6,789.03 363.19 18,649.86 11,507.61 6,810.15 369.10 18,686.86
Idaho Both 3,590.58 1,947.51 191.68 5,729.78 3,621.92 1,957.98 194.65 5,774.55 3,660.20 1,970.35 197.62 5,828.16
Idaho GTN 495.25 268.62 26.44 790.31 499.58 270.07 26.85 796.49 504.86 271.77 27.26 803.88
Idaho NWP 2,104.83 1,141.64 112.37 3,358.84 2,123.20 1,147.78 114.10 3,385.08 2,145.64 1,155.03 115.84 3,416.51
ID Sub-Total 6,190.66 3,357.77 330.49 9,878.93 6,244.70 3,375.82 335.60 9,956.11 6,310.69 3,397.15 340.72 10,048.56
Case Total 23,984.53 13,939.17 973.24 38,896.94 24,069.58 13,990.10 996.11 39,055.79 24,178.98 14,048.90 1,018.96 39,246.84
Area
2035-2036:
Residential
2035-2036:
Commercial
2035-2036:
Ind
FirmSale
2035-2036:
Total
2036-2037:
Residential
2036-2037:
Commercial
2036-2037:
Ind
FirmSale
2036-2037:
Total
Klamath Falls 1,061.91 504.37 30.05 1,596.33 1,064.46 504.01 30.74 1,599.21
La Grande 534.76 338.04 239.86 1,112.66 533.50 337.12 249.22 1,119.83
Medford GTN 2,728.57 1,669.26 26.79 4,424.62 2,728.57 1,670.86 27.04 4,426.47
Medford NWP 1,225.88 749.96 12.04 1,987.87 1,225.88 750.67 12.15 1,988.70
Roseburg 873.16 613.12 13.06 1,499.34 874.80 610.79 13.56 1,499.14
OR Sub-Total 6,424.27 3,874.75 321.81 10,620.83 6,427.20 3,873.46 332.70 10,633.36
Washington Both 6,720.65 3,983.94 218.33 10,922.92 6,705.23 3,982.33 220.96 10,908.53
Washington GTN 926.99 549.51 30.11 1,506.61 924.86 549.29 30.48 1,504.62
Washington NWP 3,939.69 2,335.42 127.99 6,403.09 3,930.65 2,334.47 129.53 6,394.65
WA Sub-Total 11,587.32 6,868.87 376.43 18,832.63 11,560.75 6,866.09 380.97 18,807.81
Idaho Both 3,722.33 1,993.46 201.39 5,917.19 3,753.85 2,000.30 203.58 5,957.72
Idaho GTN 513.42 274.96 27.78 816.16 517.77 275.90 28.08 821.75
Idaho NWP 2,182.05 1,168.58 118.06 3,468.69 2,200.53 1,172.59 119.34 3,492.45
ID Sub-Total 6,417.81 3,437.01 347.23 10,202.04 6,472.15 3,448.79 350.99 10,271.93
Case Total 24,429.40 14,180.62 1,045.47 39,655.50 24,460.09 14,188.34 1,064.66 39,713.09
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 115 of 829
APPENDIX 2.9: DETAILED DEMAND DATA
AVERAGE MIX

Area
2017-2018:
Residential
2017-2018:
Commercial
2017-2018:
Ind
FirmSale
2017-2018:
Total
2018-2019:
Residential
2018-2019:
Commercial
2018-2019:
Ind
FirmSale
2018-2019:
Total
2019-2020:
Residential
2019-2020:
Commercial
2019-2020:
Ind
FirmSale
2019-2020:
Total
Klamath Falls 848.68 440.78 13.86 1,303.32 856.66 441.43 13.71 1,311.79 868.65 445.18 13.63 1,327.47
La Grande 468.70 301.02 53.19 822.90 470.01 301.34 56.66 828.02 473.24 302.97 56.98 833.19
Medford GTN 2,210.25 1,389.32 18.51 3,618.08 2,231.59 1,399.25 18.29 3,649.14 2,263.10 1,414.44 18.17 3,695.71
Medford NWP 993.01 624.19 8.31 1,625.51 1,002.60 628.65 8.22 1,639.47 1,016.75 635.47 8.16 1,660.39
Roseburg 686.98 554.98 2.33 1,244.29 692.85 555.39 2.30 1,250.54 701.76 557.74 2.29 1,261.79
OR Sub-Total 5,207.61 3,310.29 96.19 8,614.10 5,253.72 3,326.06 99.18 8,678.95 5,323.51 3,355.80 99.23 8,778.54
Washington Both 6,102.55 3,628.54 153.06 9,884.15 6,183.26 3,645.57 151.33 9,980.17 6,259.05 3,669.73 150.10 10,078.87
Washington GTN 841.73 500.49 21.11 1,363.33 852.86 502.84 20.87 1,376.57 863.32 506.17 20.70 1,390.19
Washington NWP 3,577.36 2,127.07 89.73 5,794.16 3,624.67 2,137.06 88.71 5,850.44 3,669.10 2,151.22 87.99 5,908.30
WA Sub-Total 10,521.64 6,256.10 263.90 17,041.64 10,660.80 6,285.47 260.92 17,207.18 10,791.46 6,327.12 258.79 17,377.37
Idaho Both 3,065.38 1,786.48 146.36 4,998.22 3,102.96 1,791.28 147.81 5,042.05 3,150.70 1,802.15 148.67 5,101.51
Idaho GTN 422.81 246.41 20.19 689.41 427.99 247.07 20.39 695.45 434.58 248.57 20.51 703.66
Idaho NWP 1,796.95 1,047.25 85.80 2,929.99 1,818.98 1,050.06 86.65 2,955.68 1,846.96 1,056.43 87.15 2,990.54
ID Sub-Total 5,285.13 3,080.13 252.35 8,617.62 5,349.93 3,088.41 254.84 8,693.19 5,432.24 3,107.15 256.32 8,795.71
Case Total 21,014.38 12,646.52 612.45 34,273.35 21,264.44 12,699.94 614.94 34,579.32 21,547.20 12,790.07 614.34 34,951.61
Area
2020-2021:
Residential
2020-2021:
Commercial
2020-2021:
Ind
FirmSale
2020-2021:
Total
2021-2022:
Residential
2021-2022:
Commercial
2021-2022:
Ind
FirmSale
2021-2022:
Total
2022-2023:
Residential
2022-2023:
Commercial
2022-2023:
Ind
FirmSale
2022-2023:
Total
Klamath Falls 871.72 444.30 13.48 1,329.51 875.13 443.49 13.38 1,332.01 881.57 444.20 13.30 1,339.08
La Grande 472.49 302.01 56.72 831.22 471.86 301.36 56.45 829.67 472.37 301.41 56.14 829.92
Medford GTN 2,273.76 1,417.90 17.99 3,709.65 2,284.87 1,422.37 17.88 3,725.12 2,302.43 1,430.29 17.77 3,750.49
Medford NWP 1,021.54 637.03 8.08 1,666.65 1,026.53 639.04 8.03 1,673.60 1,034.43 642.59 7.98 1,685.00
Roseburg 704.41 555.40 2.26 1,262.07 707.19 553.32 2.24 1,262.75 712.36 552.90 2.23 1,267.49
OR Sub-Total 5,343.93 3,356.64 98.54 8,799.10 5,365.59 3,359.58 97.99 8,823.16 5,403.16 3,371.40 97.43 8,871.99
Washington Both 6,267.13 3,658.83 147.79 10,073.74 6,287.10 3,661.32 146.18 10,094.60 6,283.66 3,656.81 144.58 10,085.04
Washington GTN 864.43 504.67 20.38 1,389.48 867.19 505.01 20.16 1,392.36 866.71 504.39 19.94 1,391.04
Washington NWP 3,673.83 2,144.83 86.63 5,905.30 3,685.54 2,146.29 85.69 5,917.52 3,683.52 2,143.65 84.75 5,911.92
WA Sub-Total 10,805.39 6,308.32 254.81 17,368.52 10,839.83 6,312.62 252.03 17,404.48 10,833.89 6,304.84 249.27 17,388.00
Idaho Both 3,168.64 1,796.92 147.94 5,113.50 3,187.60 1,795.66 147.60 5,130.86 3,196.15 1,791.59 147.21 5,134.94
Idaho GTN 437.05 247.85 20.41 705.31 439.67 247.68 20.36 707.70 440.85 247.12 20.30 708.27
Idaho NWP 1,857.48 1,053.37 86.72 2,997.57 1,868.59 1,052.63 86.52 3,007.75 1,873.60 1,050.24 86.29 3,010.14
ID Sub-Total 5,463.18 3,098.14 255.07 8,816.38 5,495.86 3,095.97 254.48 8,846.31 5,510.60 3,088.94 253.80 8,853.34
Case Total 21,612.49 12,763.10 608.41 34,984.00 21,701.28 12,768.16 604.50 35,073.94 21,747.65 12,765.18 600.50 35,113.33
Area
2023-2024:
Residential
2023-2024:
Commercial
2023-2024:
Ind
FirmSale
2023-2024:
Total
2024-2025:
Residential
2024-2025:
Commercial
2024-2025:
Ind
FirmSale
2024-2025:
Total
2025-2026:
Residential
2025-2026:
Commercial
2025-2026:
Ind
FirmSale
2025-2026:
Total
Klamath Falls 893.36 447.38 13.25 1,354.00 894.46 445.63 13.11 1,353.20 900.89 446.35 13.00 1,360.24
La Grande 475.04 302.90 55.86 833.79 473.16 301.49 55.36 830.01 473.47 301.53 54.91 829.91
Medford GTN 2,329.44 1,444.13 17.70 3,791.27 2,330.30 1,443.89 17.52 3,791.72 2,343.81 1,450.58 17.38 3,811.76
Medford NWP 1,046.56 648.81 7.95 1,703.32 1,046.95 648.70 7.87 1,703.53 1,053.01 651.71 7.81 1,712.53
Roseburg 721.42 555.25 2.23 1,278.89 722.89 552.06 2.20 1,277.15 728.17 551.67 2.18 1,282.02
OR Sub-Total 5,465.81 3,398.47 96.99 8,961.27 5,467.77 3,391.77 96.06 8,955.60 5,499.36 3,401.84 95.27 8,996.47
Washington Both 6,367.41 3,667.63 143.64 10,178.68 6,322.41 3,636.76 141.53 10,100.70 6,286.64 3,624.26 140.09 10,050.98
Washington GTN 878.26 505.88 19.81 1,403.96 872.06 501.62 19.52 1,393.20 867.12 499.90 19.32 1,386.34
Washington NWP 3,732.62 2,149.99 84.20 5,966.81 3,706.24 2,131.90 82.96 5,921.10 3,685.27 2,124.56 82.12 5,891.95
WA Sub-Total 10,978.29 6,323.50 247.65 17,549.44 10,900.71 6,270.28 244.01 17,415.00 10,839.03 6,248.72 241.53 17,329.28
Idaho Both 3,250.52 1,793.75 147.44 5,191.71 3,233.42 1,776.54 146.39 5,156.36 3,219.89 1,767.90 146.03 5,133.83
Idaho GTN 448.35 247.41 20.34 716.10 445.99 245.04 20.19 711.22 444.12 243.85 20.14 708.11
Idaho NWP 1,905.48 1,051.51 86.43 3,043.42 1,895.46 1,041.42 85.82 3,022.69 1,887.52 1,036.36 85.60 3,009.48
ID Sub-Total 5,604.35 3,092.67 254.21 8,951.23 5,574.87 3,063.00 252.40 8,890.27 5,551.54 3,048.11 251.78 8,851.42
Case Total 22,048.45 12,814.64 598.85 35,461.95 21,943.35 12,725.06 592.47 35,260.88 21,889.93 12,698.66 588.58 35,177.17
Area
2026-2027:
Residential
2026-2027:
Commercial
2026-2027:
Ind
FirmSale
2026-2027:
Total
2027-2028:
Residential
2027-2028:
Commercial
2027-2028:
Ind
FirmSale
2027-2028:
Total
2028-2029:
Residential
2028-2029:
Commercial
2028-2029:
Ind
FirmSale
2028-2029:
Total
Klamath Falls 906.87 446.95 12.87 1,366.70 917.16 449.73 12.78 1,379.67 917.08 448.02 12.58 1,377.68
La Grande 473.75 301.51 54.39 829.65 476.10 302.75 53.89 832.74 474.46 301.33 53.14 828.93
Medford GTN 2,356.41 1,456.83 17.21 3,830.45 2,379.11 1,468.98 17.08 3,865.17 2,377.88 1,468.21 16.82 3,862.92
Medford NWP 1,058.68 654.52 7.73 1,720.93 1,068.87 659.98 7.67 1,736.53 1,068.32 659.63 7.56 1,735.51
Roseburg 733.39 551.18 2.16 1,286.73 741.88 553.11 2.15 1,297.13 743.04 549.91 2.11 1,295.06
OR Sub-Total 5,529.10 3,410.99 94.37 9,034.45 5,583.12 3,434.54 93.58 9,111.24 5,580.79 3,427.10 92.21 9,100.10
Washington Both 6,239.70 3,609.67 138.68 9,988.05 6,214.69 3,611.84 137.84 9,964.37 6,127.48 3,580.05 135.99 9,843.52
Washington GTN 860.65 497.89 19.13 1,377.66 857.20 498.18 19.01 1,374.40 845.17 493.80 18.76 1,357.73
Washington NWP 3,657.75 2,116.02 81.30 5,855.07 3,643.09 2,117.28 80.80 5,841.18 3,591.97 2,098.65 79.72 5,770.34
WA Sub-Total 10,758.10 6,223.58 239.11 17,220.78 10,714.98 6,227.31 237.66 17,179.95 10,564.63 6,172.50 234.46 16,971.58
Idaho Both 3,201.12 1,758.98 145.68 5,105.79 3,194.58 1,757.99 145.95 5,098.52 3,158.76 1,741.74 145.07 5,045.56
Idaho GTN 441.53 242.62 20.09 704.25 440.63 242.48 20.13 703.24 435.69 240.24 20.01 695.94
Idaho NWP 1,876.52 1,031.13 85.40 2,993.05 1,872.68 1,030.55 85.56 2,988.79 1,851.68 1,021.02 85.04 2,957.74
ID Sub-Total 5,519.18 3,032.73 251.18 8,803.08 5,507.89 3,031.02 251.64 8,790.55 5,446.13 3,002.99 250.12 8,699.24
Case Total 21,806.38 12,667.29 584.66 35,058.32 21,806.00 12,692.87 582.88 35,081.74 21,591.55 12,602.59 576.79 34,770.93
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 116 of 829
APPENDIX 2.9: DETAILED DEMAND DATA
AVERAGE MIX

Area
2029-2030:
Residential
2029-2030:
Commercial
2029-2030:
Ind
FirmSale
2029-2030:
Total
2030-2031:
Residential
2030-2031:
Commercial
2030-2031:
Ind
FirmSale
2030-2031:
Total
2031-2032:
Residential
2031-2032:
Commercial
2031-2032:
Ind
FirmSale
2031-2032:
Total
Klamath Falls 921.16 448.47 12.42 1,382.05 924.90 448.95 12.24 1,386.09 933.73 451.63 12.10 1,397.46
La Grande 474.69 301.19 52.48 828.36 474.75 301.03 51.75 827.54 476.76 302.19 51.06 830.01
Medford GTN 2,386.76 1,473.38 16.61 3,876.75 2,394.53 1,478.22 16.38 3,889.13 2,412.92 1,489.27 16.18 3,918.38
Medford NWP 1,072.31 661.95 7.46 1,741.73 1,075.80 664.13 7.36 1,747.29 1,084.07 669.09 7.27 1,760.43
Roseburg 747.22 549.10 2.08 1,298.41 750.60 548.05 2.05 1,300.71 757.02 549.34 2.03 1,308.39
OR Sub-Total 5,602.15 3,434.10 91.05 9,127.30 5,620.58 3,440.38 89.79 9,150.76 5,664.50 3,461.52 88.65 9,214.67
Washington Both 6,070.21 3,567.00 134.70 9,771.91 6,018.75 3,554.98 133.43 9,707.17 6,005.44 3,562.02 132.71 9,700.17
Washington GTN 837.27 492.00 18.58 1,347.85 830.17 490.34 18.40 1,338.92 828.34 491.31 18.30 1,337.95
Washington NWP 3,558.40 2,091.00 78.96 5,728.36 3,528.23 2,083.95 78.22 5,690.41 3,520.43 2,088.08 77.79 5,686.30
WA Sub-Total 10,465.88 6,150.00 232.24 16,848.11 10,377.16 6,129.27 230.06 16,736.49 10,354.21 6,141.41 228.80 16,724.43
Idaho Both 3,139.51 1,734.45 144.80 5,018.76 3,125.75 1,728.25 144.55 4,998.56 3,134.06 1,731.37 144.91 5,010.35
Idaho GTN 433.04 239.23 19.97 692.24 431.14 238.38 19.94 689.46 432.28 238.81 19.99 691.08
Idaho NWP 1,840.40 1,016.75 84.88 2,942.03 1,832.34 1,013.11 84.74 2,930.19 1,837.21 1,014.94 84.95 2,937.10
ID Sub-Total 5,412.95 2,990.43 249.66 8,653.04 5,389.23 2,979.75 249.23 8,618.21 5,403.55 2,985.12 249.85 8,638.53
Case Total 21,480.98 12,574.53 572.94 34,628.45 21,386.97 12,549.41 569.08 34,505.46 21,422.26 12,588.05 567.31 34,577.62
Area 2032-2033: Residential 2032-2033: Commercial
2032-2033: Ind FirmSale 2032-2033: Total 2033-2034: Residential 2033-2034: Commercial
2033-2034: Ind FirmSale 2033-2034: Total 2034-2035: Residential 2034-2035: Commercial
2034-2035: Ind FirmSale 2034-2035: Total
Klamath Falls 932.49 449.75 11.85 1,394.09 936.33 450.07 11.64 1,398.04 940.13 450.39 11.41 1,401.94
La Grande 474.51 300.66 50.11 825.27 474.22 300.43 49.21 823.86 473.86 300.24 48.28 822.38
Medford GTN 2,407.02 1,486.93 15.86 3,909.81 2,412.09 1,490.88 15.58 3,918.54 2,416.56 1,494.64 15.29 3,926.49
Medford NWP 1,081.41 668.04 7.13 1,756.58 1,083.69 669.81 7.00 1,760.51 1,085.70 671.50 6.87 1,764.07
Roseburg 755.99 545.50 1.99 1,303.47 758.41 544.11 1.95 1,304.47 760.73 542.73 1.91 1,305.38
OR Sub-Total 5,651.42 3,450.88 86.93 9,189.23 5,664.74 3,455.30 85.38 9,205.42 5,677.00 3,459.50 83.76 9,220.26 Washington Both 5,939.90 3,536.54 130.98 9,607.42 5,910.96 3,532.94 129.78 9,573.68 5,890.36 3,532.50 128.60 9,551.46
Washington GTN 819.30 487.80 18.07 1,325.16 815.30 487.30 17.90 1,320.51 812.46 487.24 17.74 1,317.44
Washington NWP 3,482.01 2,073.15 76.78 5,631.93 3,465.04 2,071.03 76.08 5,612.16 3,452.97 2,070.78 75.39 5,599.13
WA Sub-Total 10,241.20 6,097.49 225.83 16,564.51 10,191.30 6,091.27 223.76 16,506.34 10,155.80 6,090.52 221.72 16,468.04
Idaho Both 3,118.37 1,720.08 144.12 4,982.57 3,123.77 1,719.53 143.92 4,987.23 3,135.31 1,720.69 143.74 4,999.75
Idaho GTN 430.12 237.25 19.88 687.25 430.87 237.18 19.85 687.89 432.46 237.34 19.83 689.62
Idaho NWP 1,828.01 1,008.33 84.48 2,920.82 1,831.18 1,008.00 84.37 2,923.55 1,837.94 1,008.68 84.26 2,930.89
ID Sub-Total 5,376.49 2,965.66 248.48 8,590.63 5,385.81 2,964.71 248.15 8,598.67 5,405.71 2,966.71 247.83 8,620.26
Case Total 21,269.11 12,514.03 561.23 34,344.38 21,241.86 12,511.29 557.29 34,310.43 21,238.51 12,516.73 553.32 34,308.56
Area
2035-2036:
Residential
2035-2036:
Commercial
2035-2036:
Ind
FirmSale
2035-2036:
Total
2036-2037:
Residential
2036-2037:
Commercial
2036-2037:
Ind
FirmSale
2036-2037:
Total
Klamath Falls 949.26 453.08 11.23 1,413.58 948.06 451.10 10.96 1,410.12
La Grande 475.56 301.38 47.42 824.36 473.07 299.70 46.39 819.16
Medford GTN 2,432.84 1,504.94 15.03 3,952.81 2,425.20 1,501.80 14.69 3,941.69
Medford NWP 1,093.02 676.13 6.75 1,775.90 1,089.58 674.72 6.60 1,770.91
Roseburg 766.79 543.87 1.89 1,312.56 765.50 539.86 1.84 1,307.20
OR Sub-Total 5,717.48 3,479.40 82.32 9,279.20 5,701.42 3,467.19 80.47 9,249.08
Washington Both 5,908.09 3,552.76 127.92 9,588.77 5,868.74 3,539.97 126.26 9,534.97
Washington GTN 814.91 490.04 17.64 1,322.59 809.48 488.27 17.42 1,315.17
Washington NWP 3,463.37 2,082.65 74.99 5,621.00 3,440.30 2,075.15 74.01 5,589.46
WA Sub-Total 10,186.37 6,125.44 220.55 16,532.36 10,118.52 6,103.39 217.69 16,439.60
Idaho Both 3,168.20 1,731.57 144.16 5,043.93 3,172.86 1,727.57 143.40 5,043.83
Idaho GTN 436.99 238.84 19.88 695.71 437.64 238.29 19.78 695.70
Idaho NWP 1,857.22 1,015.06 84.51 2,956.79 1,859.95 1,012.72 84.06 2,956.73
ID Sub-Total 5,462.41 2,985.47 248.55 8,696.43 5,470.45 2,978.57 247.24 8,696.26
Case Total 21,366.26 12,590.31 551.42 34,508.00 21,290.39 12,549.16 545.40 34,384.94
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 117 of 829
APPENDIX 2.9: DETAILED DEMAND DATA
COLDEST IN 20 YEARS

Area
2017-2018:
Residential
2017-2018:
Commercial
2017-2018:
Ind
FirmSale
2017-2018:
Total
2018-2019:
Residential
2018-2019:
Commercial
2018-2019:
Ind
FirmSale
2018-2019:
Total
2019-2020:
Residential
2019-2020:
Commercial
2019-2020:
Ind
FirmSale
2019-2020:
Total
Klamath Falls 874.44 452.24 14.01 1,340.69 882.77 452.95 13.86 1,349.58 895.08 456.78 13.78 1,365.64
La Grande 480.97 308.40 53.19 842.56 482.37 308.76 56.66 847.79 485.67 310.42 56.98 853.07
Medford GTN 2,282.45 1,423.79 18.59 3,724.84 2,304.76 1,434.10 18.37 3,757.23 2,337.18 1,449.66 18.25 3,805.10
Medford NWP 1,025.45 639.68 8.35 1,673.48 1,035.47 644.31 8.26 1,688.03 1,050.04 651.30 8.20 1,709.54
Roseburg 711.76 571.05 2.37 1,285.17 717.92 571.55 2.34 1,291.80 727.11 573.95 2.33 1,303.39
OR Sub-Total 5,375.07 3,395.16 96.50 8,866.74 5,423.28 3,411.66 99.49 8,934.43 5,495.09 3,442.11 99.54 9,036.74
Washington Both 6,299.68 3,739.54 155.81 10,195.04 6,383.84 3,757.51 154.05 10,295.40 6,462.27 3,782.32 152.78 10,397.37
Washington GTN 868.92 515.80 21.49 1,406.21 880.53 518.28 21.25 1,420.05 891.35 521.70 21.07 1,434.12
Washington NWP 3,692.92 2,192.15 91.34 5,976.40 3,742.25 2,202.68 90.30 6,035.23 3,788.23 2,217.22 89.56 6,095.01
WA Sub-Total 10,861.52 6,447.49 268.64 17,577.65 11,006.61 6,478.47 265.60 17,750.68 11,141.84 6,521.24 263.42 17,926.50
Idaho Both 3,163.71 1,834.05 148.72 5,146.49 3,202.90 1,839.15 150.20 5,192.26 3,252.29 1,850.32 151.07 5,253.68
Idaho GTN 436.37 252.97 20.51 709.86 441.78 253.68 20.72 716.17 448.59 255.22 20.84 724.65
Idaho NWP 1,854.59 1,075.13 87.18 3,016.91 1,877.56 1,078.12 88.05 3,043.74 1,906.52 1,084.67 88.56 3,079.75
ID Sub-Total 5,454.67 3,162.16 256.42 8,873.25 5,522.25 3,170.96 258.97 8,952.17 5,607.40 3,190.21 260.47 9,058.07
Case Total 21,691.27 13,004.82 621.56 35,317.65 21,952.14 13,061.09 624.06 35,637.29 22,244.33 13,153.56 623.42 36,021.32
Area 2020-2021: Residential 2020-2021: Commercial
2020-2021: Ind FirmSale 2020-2021: Total 2021-2022: Residential 2021-2022: Commercial
2021-2022: Ind FirmSale 2021-2022: Total 2022-2023: Residential 2022-2023: Commercial
2022-2023: Ind FirmSale 2022-2023: TotalKlamath Falls 898.47 455.98 13.63 1,368.08 902.04 455.18 13.53 1,370.75 908.77 455.95 13.45 1,378.17
La Grande 484.99 309.50 56.72 851.21 484.36 308.84 56.45 849.66 484.92 308.92 56.14 849.99
Medford GTN 2,348.77 1,453.49 18.07 3,820.33 2,360.37 1,458.12 17.96 3,836.45 2,378.76 1,466.36 17.85 3,862.97
Medford NWP 1,055.24 653.02 8.12 1,716.38 1,060.46 655.10 8.07 1,723.62 1,068.72 658.80 8.02 1,735.54
Roseburg 730.06 571.68 2.30 1,304.03 732.98 569.56 2.28 1,304.83 738.43 569.19 2.27 1,309.89
OR Sub-Total 5,517.53 3,443.67 98.85 9,060.05 5,540.21 3,446.80 98.30 9,085.31 5,579.59 3,459.23 97.74 9,136.55
Washington Both 6,472.83 3,772.08 150.44 10,395.36 6,495.43 3,775.36 148.81 10,419.59 6,494.40 3,771.56 147.18 10,413.15
Washington GTN 892.80 520.29 20.75 1,433.84 895.92 520.74 20.53 1,437.19 895.78 520.22 20.30 1,436.30
Washington NWP 3,794.42 2,211.22 88.19 6,093.83 3,807.66 2,213.14 87.23 6,108.04 3,807.06 2,210.92 86.28 6,104.26
WA Sub-Total 11,160.06 6,503.58 259.38 17,923.03 11,199.01 6,509.23 256.57 17,964.81 11,197.24 6,502.69 253.76 17,953.70
Idaho Both 3,271.96 1,845.41 150.35 5,267.71 3,292.56 1,844.41 150.01 5,286.98 3,302.77 1,840.59 149.61 5,292.97
Idaho GTN 451.30 254.54 20.74 726.58 454.15 254.40 20.69 729.24 455.55 253.87 20.64 730.07
Idaho NWP 1,918.04 1,081.79 88.13 3,087.97 1,930.12 1,081.20 87.93 3,099.26 1,936.11 1,078.97 87.70 3,102.78
ID Sub-Total 5,641.31 3,181.74 259.22 9,082.26 5,676.83 3,180.01 258.63 9,115.48 5,694.43 3,173.44 257.95 9,125.81
Case Total 22,318.90 13,128.99 617.45 36,065.34 22,416.06 13,136.05 613.49 36,165.60 22,471.26 13,135.35 609.45 36,216.07
Area
2023-2024:
Residential
2023-2024:
Commercial
2023-2024:
Ind
FirmSale
2023-2024:
Total
2024-2025:
Residential
2024-2025:
Commercial
2024-2025:
Ind
FirmSale
2024-2025:
Total
2025-2026:
Residential
2025-2026:
Commercial
2025-2026:
Ind
FirmSale
2025-2026:
Total
Klamath Falls 920.88 459.21 13.40 1,393.49 922.26 457.51 13.25 1,393.03 929.01 458.31 13.14 1,400.46
La Grande 487.66 310.45 55.86 853.96 485.83 309.06 55.36 850.25 486.20 309.14 54.91 850.26
Medford GTN 2,406.60 1,480.55 17.78 3,904.93 2,408.13 1,480.59 17.60 3,906.33 2,422.41 1,487.61 17.46 3,927.48
Medford NWP 1,081.22 665.17 7.99 1,754.39 1,081.91 665.19 7.91 1,755.02 1,088.33 668.35 7.85 1,764.52
Roseburg 747.80 571.60 2.27 1,321.66 749.54 568.46 2.24 1,320.25 755.13 568.13 2.22 1,325.48
OR Sub-Total 5,644.16 3,486.97 97.30 9,228.43 5,647.68 3,480.82 96.37 9,224.87 5,681.09 3,491.54 95.58 9,268.21
Washington Both 6,580.84 3,783.27 146.23 10,510.33 6,538.15 3,753.07 144.09 10,435.31 6,505.01 3,741.42 142.63 10,389.06
Washington GTN 907.70 521.83 20.17 1,449.70 901.81 517.66 19.87 1,439.35 897.24 516.06 19.67 1,432.97
Washington NWP 3,857.73 2,217.78 85.72 6,161.23 3,832.71 2,200.08 84.47 6,117.25 3,813.28 2,193.25 83.61 6,090.14
WA Sub-Total 11,346.27 6,522.87 252.11 18,121.26 11,272.68 6,470.81 248.43 17,991.92 11,215.53 6,450.72 245.91 17,912.17
Idaho Both 3,358.85 1,843.07 149.84 5,351.76 3,343.19 1,826.07 148.79 5,318.06 3,331.28 1,817.74 148.43 5,297.45
Idaho GTN 463.29 254.22 20.67 738.17 461.13 251.87 20.52 733.53 459.49 250.72 20.47 730.68
Idaho NWP 1,968.98 1,080.42 87.84 3,137.24 1,959.80 1,070.46 87.22 3,117.48 1,952.82 1,065.57 87.01 3,105.40
ID Sub-Total 5,791.12 3,177.70 258.35 9,227.18 5,764.12 3,148.40 256.54 9,169.07 5,743.58 3,134.03 255.92 9,133.53
Case Total 22,781.55 13,187.55 607.77 36,576.87 22,684.48 13,100.04 601.34 36,385.85 22,640.20 13,076.29 597.41 36,313.91
Area
2026-2027:
Residential
2026-2027:
Commercial
2026-2027:
Ind
FirmSale
2026-2027:
Total
2027-2028:
Residential
2027-2028:
Commercial
2027-2028:
Ind
FirmSale
2027-2028:
Total
2028-2029:
Residential
2028-2029:
Commercial
2028-2029:
Ind
FirmSale
2028-2029:
Total
Klamath Falls 935.30 458.98 13.02 1,407.31 945.90 461.83 12.93 1,420.66 946.12 460.20 12.72 1,419.04
La Grande 486.54 309.16 54.39 850.09 488.97 310.43 53.89 853.29 487.40 309.05 53.14 849.60
Medford GTN 2,435.78 1,494.20 17.30 3,947.28 2,459.24 1,506.68 17.16 3,983.08 2,458.74 1,506.23 16.90 3,981.88
Medford NWP 1,094.34 671.31 7.77 1,773.41 1,104.87 676.91 7.71 1,789.50 1,104.65 676.71 7.59 1,788.96
Roseburg 760.66 567.71 2.20 1,330.57 769.46 569.71 2.19 1,341.35 770.93 566.57 2.15 1,339.65
OR Sub-Total 5,712.63 3,501.36 94.68 9,308.66 5,768.44 3,525.57 93.88 9,387.89 5,767.85 3,518.77 92.51 9,379.13
Washington Both 6,460.65 3,727.67 141.21 10,329.53 6,438.18 3,730.65 140.35 10,309.18 6,353.46 3,699.65 138.48 10,191.59
Washington GTN 891.12 514.16 19.48 1,424.76 888.02 514.57 19.36 1,421.96 876.34 510.30 19.10 1,405.74
Washington NWP 3,787.28 2,185.19 82.78 6,055.24 3,774.11 2,186.93 82.27 6,043.31 3,724.44 2,168.76 81.18 5,974.38
WA Sub-Total 11,139.05 6,427.02 243.46 17,809.53 11,100.31 6,432.15 241.98 17,774.44 10,954.24 6,378.71 238.75 17,571.71
Idaho Both 3,314.11 1,809.11 148.09 5,271.31 3,309.16 1,808.42 148.36 5,265.94 3,274.96 1,792.47 147.47 5,214.90
Idaho GTN 457.12 249.53 20.43 727.08 456.44 249.44 20.46 726.34 451.72 247.24 20.34 719.30
Idaho NWP 1,942.75 1,060.51 86.81 3,090.08 1,939.85 1,060.11 86.97 3,086.93 1,919.81 1,050.76 86.45 3,057.01
ID Sub-Total 5,713.98 3,119.16 255.32 9,088.46 5,705.46 3,117.97 255.79 9,079.21 5,646.49 3,090.47 254.26 8,991.22
Case Total 22,565.66 13,047.54 593.46 36,206.66 22,574.21 13,075.69 591.65 36,241.55 22,368.58 12,987.95 585.53 35,942.05
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 118 of 829
APPENDIX 2.9: DETAILED DEMAND DATA
COLDEST IN 20 YEARS

Area
2029-2030:
Residential
2029-2030:
Commercial
2029-2030:
Ind
FirmSale
2029-2030:
Total
2030-2031:
Residential
2030-2031:
Commercial
2030-2031:
Ind
FirmSale
2030-2031:
Total
2031-2032:
Residential
2031-2032:
Commercial
2031-2032:
Ind
FirmSale
2031-2032:
Total
Klamath Falls 950.47 460.73 12.56 1,423.76 954.48 461.28 12.39 1,428.15 963.58 464.03 12.25 1,439.86
La Grande 487.71 308.95 52.48 849.14 487.84 308.83 51.75 848.42 489.92 310.03 51.06 851.00
Medford GTN 2,468.33 1,511.72 16.69 3,996.74 2,476.78 1,516.88 16.46 4,010.13 2,495.83 1,528.24 16.27 4,040.33
Medford NWP 1,108.96 679.18 7.50 1,795.64 1,112.76 681.50 7.40 1,801.65 1,121.31 686.60 7.31 1,815.22
Roseburg 775.41 565.83 2.12 1,343.36 779.06 564.84 2.09 1,346.00 785.74 566.18 2.07 1,353.99
OR Sub-Total 5,790.88 3,526.40 91.36 9,408.64 5,810.92 3,533.32 90.10 9,434.34 5,856.37 3,555.07 88.95 9,500.40
Washington Both 6,298.63 3,687.37 137.17 10,123.17 6,249.56 3,676.10 135.89 10,061.54 6,238.59 3,683.85 135.14 10,057.59
Washington GTN 868.78 508.60 18.92 1,396.30 862.01 507.05 18.74 1,387.80 860.50 508.12 18.64 1,387.25
Washington NWP 3,692.30 2,161.56 80.41 5,934.27 3,663.54 2,154.95 79.66 5,898.15 3,657.11 2,159.50 79.22 5,895.83
WA Sub-Total 10,859.71 6,357.54 236.50 17,453.74 10,775.10 6,338.09 234.29 17,347.49 10,756.20 6,351.47 233.00 17,340.67
Idaho Both 3,257.34 1,785.49 147.20 5,190.03 3,245.23 1,779.60 146.95 5,171.79 3,255.23 1,783.02 147.32 5,185.57
Idaho GTN 449.29 246.27 20.30 715.87 447.62 245.46 20.27 713.35 449.00 245.93 20.32 715.25
Idaho NWP 1,909.47 1,046.67 86.29 3,042.43 1,902.38 1,043.21 86.15 3,031.74 1,908.24 1,045.22 86.36 3,039.82
ID Sub-Total 5,616.10 3,078.43 253.80 8,948.33 5,595.23 3,068.27 253.37 8,916.87 5,612.47 3,074.17 253.99 8,940.64
Case Total 22,266.69 12,962.37 581.65 35,810.71 22,181.25 12,939.69 577.76 35,698.70 22,225.04 12,980.72 575.95 35,781.71
Area 2032-2033: Residential 2032-2033: Commercial
2032-2033: Ind FirmSale 2032-2033: Total 2033-2034: Residential 2033-2034: Commercial
2033-2034: Ind FirmSale 2033-2034: Total 2034-2035: Residential 2034-2035: Commercial
2034-2035: Ind FirmSale 2034-2035: Total
Klamath Falls 962.62 462.23 12.00 1,436.85 966.73 462.63 11.78 1,441.14 970.81 463.02 11.56 1,445.39
La Grande 487.74 308.53 50.11 846.37 487.51 308.33 49.21 845.05 487.22 308.18 48.28 843.68
Medford GTN 2,490.55 1,526.20 15.94 4,032.70 2,496.23 1,530.45 15.66 4,042.33 2,501.29 1,534.50 15.37 4,051.16
Medford NWP 1,118.94 685.69 7.16 1,811.79 1,121.49 687.59 7.04 1,816.12 1,123.77 689.41 6.90 1,820.08
Roseburg 784.95 562.39 2.03 1,349.36 787.61 561.05 1.99 1,350.66 790.17 559.72 1.95 1,351.85
OR Sub-Total 5,844.79 3,545.03 87.24 9,477.06 5,859.57 3,550.05 85.68 9,495.31 5,873.25 3,554.84 84.07 9,512.16 Washington Both 6,175.35 3,659.08 133.40 9,967.82 6,148.66 3,656.15 132.18 9,937.00 6,130.28 3,656.38 130.98 9,917.64
Washington GTN 851.77 504.70 18.40 1,374.87 848.09 504.30 18.23 1,370.62 845.56 504.33 18.07 1,367.95
Washington NWP 3,620.03 2,144.98 78.20 5,843.21 3,604.39 2,143.26 77.49 5,825.14 3,593.61 2,143.39 76.78 5,813.79
WA Sub-Total 10,647.15 6,308.76 229.99 17,185.90 10,601.14 6,303.71 227.90 17,132.75 10,569.45 6,304.10 225.83 17,099.38
Idaho Both 3,241.26 1,772.05 146.52 5,159.83 3,248.42 1,771.81 146.33 5,166.56 3,261.75 1,773.29 146.14 5,181.18
Idaho GTN 447.07 244.42 20.21 711.70 448.06 244.39 20.18 712.63 449.90 244.59 20.16 714.65
Idaho NWP 1,900.05 1,038.79 85.89 3,024.73 1,904.25 1,038.65 85.78 3,028.67 1,912.06 1,039.51 85.67 3,037.24
ID Sub-Total 5,588.38 3,055.25 252.62 8,896.25 5,600.73 3,054.84 252.29 8,907.86 5,623.71 3,057.39 251.97 8,933.07
Case Total 22,080.32 12,909.04 569.85 35,559.21 22,061.44 12,908.61 565.87 35,535.92 22,066.41 12,916.33 561.87 35,544.61
Area
2035-2036:
Residential
2035-2036:
Commercial
2035-2036:
Ind
FirmSale
2035-2036:
Total
2036-2037:
Residential
2036-2037:
Commercial
2036-2037:
Ind
FirmSale
2036-2037:
Total
Klamath Falls 980.21 465.79 11.38 1,457.38 979.29 463.88 11.11 1,454.28
La Grande 488.98 309.36 47.42 845.75 486.55 307.72 46.39 840.65
Medford GTN 2,518.14 1,545.09 15.12 4,078.35 2,511.07 1,542.25 14.77 4,068.09
Medford NWP 1,131.34 694.17 6.79 1,832.30 1,128.16 692.90 6.64 1,827.69
Roseburg 796.47 560.91 1.93 1,359.31 795.41 556.96 1.88 1,354.25
OR Sub-Total 5,915.14 3,575.33 82.63 9,573.09 5,900.48 3,563.70 80.78 9,544.95
Washington Both 6,150.20 3,677.29 130.28 9,957.77 6,113.02 3,665.14 128.60 9,906.76
Washington GTN 848.30 507.21 17.97 1,373.49 843.18 505.54 17.74 1,366.45
Washington NWP 3,605.29 2,155.65 76.37 5,837.31 3,583.49 2,148.53 75.39 5,807.41
WA Sub-Total 10,603.80 6,340.15 224.63 17,168.57 10,539.69 6,319.20 221.73 17,080.63
Idaho Both 3,296.46 1,784.49 146.56 5,227.51 3,302.97 1,780.81 145.80 5,229.58
Idaho GTN 454.68 246.14 20.22 721.04 455.58 245.63 20.11 721.32
Idaho NWP 1,932.41 1,046.08 85.91 3,064.40 1,936.23 1,043.92 85.47 3,065.62
ID Sub-Total 5,683.55 3,076.70 252.69 9,012.94 5,694.78 3,070.36 251.38 9,016.52
Case Total 22,202.49 12,992.17 559.94 35,754.61 22,134.95 12,953.27 553.89 35,642.10
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 119 of 829
APPENDIX 2.9: DETAILED DEMAND DATA
80% BELOW 1990 LEVELS

Area
2017-2018:
Residential
2017-2018:
Commercial
2017-2018:
Ind
FirmSale
2017-2018:
Total
2018-2019:
Residential
2018-2019:
Commercial
2018-2019:
Ind
FirmSale
2018-2019:
Total
2019-2020:
Residential
2019-2020:
Commercial
2019-2020:
Ind
FirmSale
2019-2020:
Total
Klamath Falls 852.74 441.03 13.66 1,307.43 829.40 425.59 13.01 1,268.00 806.59 411.64 12.39 1,230.62
La Grande 473.57 303.53 52.43 829.53 457.61 292.80 54.44 804.85 441.92 282.34 53.03 777.29
Medford GTN 2,244.22 1,397.27 18.15 3,659.64 2,183.42 1,356.03 17.27 3,556.72 2,123.66 1,314.67 16.43 3,454.76
Medford NWP 1,008.27 627.76 8.15 1,644.19 980.96 609.23 7.76 1,597.95 954.11 590.65 7.38 1,552.14
Roseburg 701.81 561.70 2.31 1,265.82 682.03 541.68 2.20 1,225.92 662.52 521.72 2.10 1,186.35
OR Sub-Total 5,280.60 3,331.30 94.70 8,706.60 5,133.43 3,225.33 94.68 8,453.44 4,988.81 3,121.02 91.33 8,201.15
Washington Both 6,162.85 3,658.08 152.26 9,973.19 6,002.06 3,532.77 144.70 9,679.53 5,820.95 3,407.21 137.52 9,365.67
Washington GTN 850.05 504.56 21.00 1,375.61 827.87 487.28 19.96 1,335.11 802.89 469.96 18.97 1,291.82
Washington NWP 3,612.71 2,144.39 89.26 5,846.35 3,518.45 2,070.93 84.83 5,674.21 3,412.28 1,997.33 80.61 5,490.22
WA Sub-Total 10,625.61 6,307.03 262.52 17,195.16 10,348.37 6,090.98 249.49 16,688.85 10,036.12 5,874.50 237.10 16,147.71
Idaho Both 3,173.24 1,838.79 149.00 5,161.03 3,212.59 1,843.92 150.48 5,206.99 3,262.14 1,855.12 151.35 5,268.61
Idaho GTN 437.69 253.63 20.55 711.87 443.12 254.33 20.76 718.21 449.95 255.88 20.88 726.70
Idaho NWP 1,860.17 1,077.91 87.35 3,025.43 1,883.24 1,080.92 88.21 3,052.38 1,912.29 1,087.48 88.72 3,088.49
ID Sub-Total 5,471.10 3,170.33 256.90 8,898.33 5,538.95 3,179.18 259.45 8,977.58 5,624.37 3,198.48 260.95 9,083.80
Case Total 21,377.32 12,808.66 614.12 34,800.09 21,020.74 12,495.49 603.62 34,119.86 20,649.30 12,193.99 589.38 33,432.67
Area 2020-2021: Residential 2020-2021: Commercial
2020-2021: Ind FirmSale 2020-2021: Total 2021-2022: Residential 2021-2022: Commercial
2021-2022: Ind FirmSale 2021-2022: Total 2022-2023: Residential 2022-2023: Commercial
2022-2023: Ind FirmSale 2022-2023: TotalKlamath Falls 782.59 397.15 11.83 1,191.57 755.41 381.11 11.27 1,147.79 731.68 366.92 10.74 1,109.34
La Grande 426.60 272.09 51.43 750.12 409.64 261.02 49.54 720.21 394.22 250.91 47.68 692.81
Medford GTN 2,063.06 1,274.05 15.71 3,352.82 1,993.44 1,228.72 14.98 3,237.14 1,931.43 1,187.50 14.28 3,133.22
Medford NWP 926.88 572.40 7.06 1,506.34 895.61 552.03 6.73 1,454.37 867.75 533.51 6.42 1,407.68
Roseburg 643.04 502.29 2.00 1,147.33 620.75 481.09 1.91 1,103.75 601.24 462.09 1.82 1,065.15
OR Sub-Total 4,842.16 3,017.99 88.02 7,948.18 4,674.85 2,903.98 84.44 7,663.26 4,526.32 2,800.93 80.94 7,408.19
Washington Both 5,625.95 3,279.74 130.75 9,036.45 5,419.39 3,153.19 124.34 8,696.92 5,192.55 3,022.57 118.19 8,333.30
Washington GTN 775.99 452.38 18.03 1,246.41 747.50 434.92 17.15 1,199.58 716.21 416.91 16.30 1,149.42
Washington NWP 3,297.97 1,922.61 76.65 5,297.23 3,176.88 1,848.42 72.89 5,098.20 3,043.91 1,771.85 69.28 4,885.04
WA Sub-Total 9,699.92 5,654.73 225.44 15,580.08 9,343.77 5,436.54 214.38 14,994.69 8,952.67 5,211.33 203.77 14,367.76
Idaho Both 3,281.97 1,850.24 150.63 5,282.84 3,305.69 1,850.52 150.34 5,306.56 3,319.19 1,848.04 150.01 5,317.23
Idaho GTN 452.69 255.21 20.78 728.67 455.96 255.24 20.74 731.94 457.82 254.90 20.69 733.41
Idaho NWP 1,923.91 1,084.62 88.30 3,096.83 1,937.82 1,084.79 88.13 3,110.74 1,945.73 1,083.33 87.93 3,117.00
ID Sub-Total 5,658.57 3,190.06 259.70 9,108.34 5,699.47 3,190.56 259.21 9,149.24 5,722.73 3,186.28 258.63 9,167.64
Case Total 20,200.65 11,862.78 573.17 32,636.60 19,718.09 11,531.08 558.03 31,807.20 19,201.73 11,198.53 543.34 30,943.60
Area
2023-2024:
Residential
2023-2024:
Commercial
2023-2024:
Ind
FirmSale
2023-2024:
Total
2024-2025:
Residential
2024-2025:
Commercial
2024-2025:
Ind
FirmSale
2024-2025:
Total
2025-2026:
Residential
2025-2026:
Commercial
2025-2026:
Ind
FirmSale
2025-2026:
Total
Klamath Falls 708.55 353.08 10.21 1,071.83 683.54 338.76 9.69 1,031.99 659.25 324.80 9.17 993.21
La Grande 378.87 240.92 45.74 665.52 363.60 230.98 44.08 638.66 348.40 221.15 42.35 611.90
Medford GTN 1,867.51 1,145.63 13.56 3,026.70 1,800.29 1,103.36 12.89 2,916.54 1,734.13 1,061.22 12.19 2,807.55
Medford NWP 839.03 514.70 6.09 1,359.82 808.82 495.71 5.79 1,310.33 779.10 476.78 5.48 1,261.36
Roseburg 581.88 443.39 1.73 1,027.00 561.88 424.68 1.64 988.20 542.04 406.27 1.55 949.86
OR Sub-Total 4,375.83 2,697.72 77.33 7,150.88 4,218.13 2,593.49 74.10 6,885.72 4,062.92 2,490.23 70.74 6,623.89
Washington Both 5,017.65 2,888.63 112.19 8,018.46 4,772.84 2,747.85 106.41 7,627.10 4,506.78 2,609.20 100.85 7,216.83
Washington GTN 692.09 398.43 15.47 1,105.99 658.32 379.01 14.68 1,052.01 621.62 359.89 13.91 995.42
Washington NWP 2,941.38 1,693.33 65.77 4,700.48 2,797.87 1,610.81 62.38 4,471.06 2,641.90 1,529.53 59.12 4,230.55
WA Sub-Total 8,651.11 4,980.39 193.43 13,824.94 8,229.03 4,737.68 183.47 13,150.17 7,770.30 4,498.62 173.88 12,442.81
Idaho Both 3,375.56 1,850.57 150.24 5,376.37 3,360.92 1,833.95 149.20 5,344.07 3,349.27 1,825.66 148.84 5,323.77
Idaho GTN 465.59 255.25 20.72 741.57 463.58 252.96 20.58 737.11 461.97 251.81 20.53 734.31
Idaho NWP 1,978.78 1,084.82 88.07 3,151.67 1,970.20 1,075.07 87.46 3,132.73 1,963.37 1,070.21 87.25 3,120.83
ID Sub-Total 5,819.93 3,190.64 259.03 9,269.60 5,794.70 3,161.98 257.25 9,213.92 5,774.61 3,147.68 256.62 9,178.91
Case Total 18,846.87 10,868.76 529.79 30,245.42 18,241.86 10,493.14 514.82 29,249.82 17,607.83 10,136.53 501.24 28,245.60
Area
2026-2027:
Residential
2026-2027:
Commercial
2026-2027:
Ind
FirmSale
2026-2027:
Total
2027-2028:
Residential
2027-2028:
Commercial
2027-2028:
Ind
FirmSale
2027-2028:
Total
2028-2029:
Residential
2028-2029:
Commercial
2028-2029:
Ind
FirmSale
2028-2029:
Total
Klamath Falls 634.46 310.83 8.64 953.92 609.57 297.00 8.09 914.66 583.33 283.04 7.55 873.91
La Grande 333.27 211.35 40.64 585.27 318.16 201.53 38.86 558.55 303.42 191.90 37.33 532.65
Medford GTN 1,667.11 1,018.74 11.49 2,697.34 1,599.25 975.66 10.75 2,585.66 1,530.12 933.11 10.04 2,473.27
Medford NWP 748.99 457.69 5.16 1,211.85 718.50 438.34 4.83 1,161.67 687.45 419.23 4.51 1,111.18
Roseburg 522.00 387.96 1.46 911.43 501.69 369.71 1.37 872.78 481.02 351.68 1.28 833.97
OR Sub-Total 3,905.84 2,386.57 67.39 6,359.80 3,747.17 2,282.24 63.90 6,093.32 3,585.32 2,178.95 60.71 5,824.99
Washington Both 4,230.09 2,469.85 95.49 6,795.43 3,946.37 2,331.89 90.28 6,368.55 3,660.16 2,194.80 85.36 5,940.31
Washington GTN 583.46 340.67 13.17 937.30 544.33 321.64 12.45 878.42 504.85 302.73 11.77 819.35
Washington NWP 2,479.71 1,447.84 55.98 3,983.53 2,313.39 1,366.97 52.93 3,733.29 2,145.61 1,286.61 50.04 3,482.25
WA Sub-Total 7,293.25 4,258.36 164.64 11,716.25 6,804.09 4,020.50 155.66 10,980.25 6,310.62 3,784.13 147.16 10,241.92
Idaho Both 3,332.36 1,817.08 148.50 5,297.93 3,327.71 1,816.45 148.77 5,292.93 3,293.73 1,800.54 147.88 5,242.15
Idaho GTN 459.64 250.63 20.48 730.75 458.99 250.55 20.52 730.06 454.31 248.35 20.40 723.06
Idaho NWP 1,953.45 1,065.18 87.05 3,105.69 1,950.73 1,064.82 87.21 3,102.75 1,930.81 1,055.49 86.69 3,072.98
ID Sub-Total 5,745.45 3,132.89 256.03 9,134.37 5,737.43 3,131.82 256.49 9,125.74 5,678.85 3,104.37 254.96 9,038.19
Case Total 16,944.54 9,777.82 488.05 27,210.42 16,288.68 9,434.56 476.06 26,199.30 15,574.79 9,067.46 462.84 25,105.09
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 120 of 829
APPENDIX 2.9: DETAILED DEMAND DATA
80% BELOW 1990 LEVELS

Area
2029-2030:
Residential
2029-2030:
Commercial
2029-2030:
Ind
FirmSale
2029-2030:
Total
2030-2031:
Residential
2030-2031:
Commercial
2030-2031:
Ind
FirmSale
2030-2031:
Total
2031-2032:
Residential
2031-2032:
Commercial
2031-2032:
Ind
FirmSale
2031-2032:
Total
Klamath Falls 557.05 269.25 7.00 833.31 530.62 255.60 6.46 792.68 504.62 242.10 5.89 752.61
La Grande 288.57 182.30 35.73 506.60 273.75 172.79 34.16 480.70 258.88 163.31 32.54 454.73
Medford GTN 1,460.53 890.20 9.32 2,360.05 1,390.50 847.28 8.59 2,246.38 1,320.24 804.08 7.84 2,132.15
Medford NWP 656.18 399.94 4.19 1,060.31 624.72 380.66 3.86 1,009.24 593.15 361.25 3.52 957.92
Roseburg 460.01 333.74 1.19 794.94 438.50 315.88 1.10 755.48 416.68 298.08 1.00 715.77
OR Sub-Total 3,422.33 2,075.44 57.43 5,555.20 3,258.08 1,972.23 54.17 5,284.48 3,093.57 1,868.82 50.80 5,013.18
Washington Both 3,375.09 2,061.09 80.56 5,516.74 3,237.53 1,929.82 75.94 5,243.29 2,840.23 1,801.64 71.43 4,713.30
Washington GTN 465.53 284.29 11.11 760.93 446.56 266.18 10.47 723.21 391.76 248.50 9.85 650.11
Washington NWP 1,978.50 1,208.22 47.23 3,233.95 1,897.86 1,131.27 44.52 3,073.65 1,664.96 1,056.13 41.88 2,762.97
WA Sub-Total 5,819.13 3,553.60 138.90 9,511.63 5,581.95 3,327.27 130.93 9,040.16 4,896.95 3,106.27 123.16 8,126.39
Idaho Both 3,276.37 1,793.60 147.61 5,217.58 3,264.53 1,787.76 147.36 5,199.66 3,274.84 1,791.24 147.73 5,213.81
Idaho GTN 451.91 247.39 20.36 719.67 450.28 246.59 20.33 717.19 451.70 247.07 20.38 719.15
Idaho NWP 1,920.63 1,051.42 86.53 3,058.58 1,913.69 1,048.00 86.39 3,048.07 1,919.73 1,050.04 86.60 3,056.37
ID Sub-Total 5,648.92 3,092.41 254.50 8,995.83 5,628.51 3,082.34 254.08 8,964.93 5,646.28 3,088.35 254.70 8,989.33
Case Total 14,890.38 8,721.45 450.83 24,062.67 14,468.54 8,381.84 439.18 23,289.56 13,636.80 8,063.43 428.66 22,128.89
Area 2032-2033: Residential 2032-2033: Commercial
2032-2033: Ind FirmSale 2032-2033: Total 2033-2034: Residential 2033-2034: Commercial
2033-2034: Ind FirmSale 2033-2034: Total 2034-2035: Residential 2034-2035: Commercial
2034-2035: Ind FirmSale 2034-2035: Total
Klamath Falls 477.85 228.47 5.33 711.65 451.44 214.95 4.76 671.15 424.97 201.48 4.19 630.64
La Grande 244.22 153.98 31.12 429.32 229.50 144.64 29.64 403.78 214.84 135.38 28.19 378.41
Medford GTN 1,249.22 761.24 7.10 2,017.56 1,178.14 718.07 6.35 1,902.56 1,106.93 674.85 5.59 1,787.38
Medford NWP 561.24 342.00 3.19 906.44 529.31 322.61 2.85 854.77 497.32 303.20 2.51 803.02
Roseburg 394.71 280.48 0.91 676.09 372.66 262.96 0.81 636.43 350.57 245.60 0.71 596.89
OR Sub-Total 2,927.24 1,766.16 47.66 4,741.06 2,761.06 1,663.22 44.42 4,468.70 2,594.63 1,560.51 41.20 4,196.34 Washington Both 2,578.68 1,676.60 67.15 4,322.43 2,324.20 1,557.52 62.96 3,944.69 2,078.22 1,442.66 58.91 3,579.79
Washington GTN 355.68 231.26 9.26 596.20 320.58 214.83 8.68 544.10 286.65 198.99 8.13 493.76
Washington NWP 1,511.64 982.84 39.36 2,533.84 1,362.46 913.03 36.91 2,312.40 1,218.27 845.70 34.53 2,098.50
WA Sub-Total 4,446.00 2,890.69 115.77 7,452.47 4,007.25 2,685.38 108.56 6,801.19 3,583.14 2,487.35 101.56 6,172.05
Idaho Both 3,261.12 1,780.30 146.93 5,188.35 3,268.56 1,780.12 146.74 5,195.41 3,282.18 1,781.64 146.55 5,210.38
Idaho GTN 449.81 245.56 20.27 715.63 450.84 245.53 20.24 716.61 452.71 245.74 20.21 718.67
Idaho NWP 1,911.69 1,043.63 86.13 3,041.44 1,916.05 1,043.52 86.02 3,045.59 1,924.04 1,044.41 85.91 3,054.36
ID Sub-Total 5,622.61 3,069.49 253.32 8,945.43 5,635.45 3,069.17 252.99 8,957.61 5,658.93 3,071.80 252.68 8,983.41
Case Total 12,995.86 7,726.34 416.75 21,138.95 12,403.76 7,417.77 405.97 20,227.50 11,836.69 7,119.66 395.44 19,351.80
Area
2035-2036:
Residential
2035-2036:
Commercial
2035-2036:
Ind
FirmSale
2035-2036:
Total
2036-2037:
Residential
2036-2037:
Commercial
2036-2037:
Ind
FirmSale
2036-2037:
Total
Klamath Falls 398.81 188.13 3.61 590.55 372.02 174.65 3.06 549.73
La Grande 200.15 126.11 26.68 352.95 185.74 116.91 25.34 327.99
Medford GTN 1,035.86 631.31 4.82 1,672.00 964.76 588.17 4.09 1,557.02
Medford NWP 465.39 283.63 2.17 751.19 433.44 264.25 1.84 699.53
Roseburg 328.47 228.32 0.62 557.41 306.41 211.20 0.52 518.13
OR Sub-Total 2,428.68 1,457.51 37.90 3,924.09 2,262.38 1,355.18 34.84 3,652.40
Washington Both 1,988.12 1,331.66 54.93 3,374.72 1,250.54 1,223.77 51.13 2,525.44
Washington GTN 274.22 183.68 7.58 465.48 172.49 168.80 7.05 348.34
Washington NWP 1,165.45 780.63 32.20 1,978.29 733.08 717.38 29.97 1,480.43
WA Sub-Total 3,427.80 2,295.97 94.72 5,818.49 2,156.10 2,109.95 88.16 4,354.21
Idaho Both 3,317.22 1,792.91 146.97 5,257.10 3,323.99 1,789.27 146.21 5,259.47
Idaho GTN 457.55 247.30 20.27 725.12 458.48 246.80 20.17 725.44
Idaho NWP 1,944.58 1,051.02 86.15 3,081.75 1,948.55 1,048.88 85.71 3,083.14
ID Sub-Total 5,719.34 3,091.23 253.40 9,063.96 5,731.03 3,084.95 252.09 9,068.06
Case Total 11,575.82 6,844.71 386.01 18,806.54 10,149.50 6,550.08 375.08 17,074.67
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 121 of 829

Energy Solutions. Delivered.

This work was performed by
Applied Energy Group, Inc.
211 Broad Street, Suite 206
Red Bank, NJ 07701
Executive-in-Charge: I. Rohmund
Report prepared for:
AVISTA UTILITIES

2018 AVISTA UTILITIES NATURAL GAS
CONSERVATION POTENTIAL ASSESSMENT
Volume 1, Final Report
August 7, 2018
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 122 of 829
This work was performed by:
Applied Energy Group, Inc.
500 Ygnacio Valley Road, Suite 250
Walnut Creek, CA 94596

Project Director: I. Rohmund
Project Manager: K. Kolnowski
Lead Analyst: F. Nguyen

AEG would also like to acknowledge the valuable contributions of
Avista Utilities
1411 E Mission MSC-15
Spokane, WA 99220

Project Team: Amber Gifford
Ryan Finesilver
Tom Pardee
Kaylene Schultz

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 123 of 829
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 124 of 829
EXECUTIVE SUMMARY
In the winter of 2017, Avista Utilities (Avista) contracted with Applied Energy Group (AEG) to conduct this
Conservation Potential Assessment (CPA) in support of their conservation and resource planning activities.
This report documents this effort and provides estimates of the potential reductions in annual energy
usage for natural gas customers in Avista’s Washington and Idaho service territories from energy
conservation efforts in the time period of 2018 to 2038. To produce a reliable and transparent estimate of
energy efficiency (EE) resource potential, the AEG team performed the following tasks to meet Avista’s key
objectives:
 Used information and data from Avista, as well as secondary data sources, to describe how customers
currently use gas by sector, segment, end use and technology.
 Developed a baseline projection of how customers are likely to use gas in absence of future EE
programs. This defines the metric against which future program savings are measured. This projection
used up-to-date technology data, modeling assumptions, and energy baselines that reflect both
current and anticipated federal, state, and local energy efficiency legislation that will impact energy
EE potential.
 Estimated the technical, achievable technical, and achievable economic potential at the measure level
for energy efficiency within Avista’s service territory over the 2018 to 2038 planning horizon.
 Delivered a fully configured end-use conservation planning model, LoadMAP, for Avista to use in
future potential and resource planning initiatives
In summary, the potential study provided a solid foundation for the development of Avista’s energy
savings targets.
Table ES-1 summarizes the results for Avista’s Washington territory at a high level. AEG analyzed potential
for the residential, commercial, and industrial market sectors. First-year utility cost test (UCT) achievable
economic potential in Washington is 61,279 dekatherms. This increases to a cumulative total of 133,576
dekatherms in the second year and 1,916,441 dekatherms by the eleventh year.
Table ES-1 Washington Conservation Potential by Case, Selected Years (dekatherms)
Scenario 2018 2019 2022 2028 2038
Baseline Projection (Dth) 17,221,900 17,418,177 17,878,550 18,517,630 19,498,948
Cumulative Savings (Dth)
UCT Achievable Economic Potential 61,279 133,576 500,422 1,916,441 4,139,016
Achievable Technical Potential 86,389 186,065 655,389 2,405,890 4,901,043
Technical Potential 217,202 434,037 1,189,331 3,251,362 5,804,041
Cumulative Savings (% of Baseline)
UCT Achievable Economic Potential 0.4% 0.8% 2.8% 10.3% 21.2%
Achievable Technical Potential 0.5% 1.1% 3.7% 13.0% 25.1%
Technical Potential 1.3% 2.5% 6.7% 17.6% 29.8%

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 125 of 829
Table ES-2 summarizes the results for Avista’s Idaho territory at a high level. First-year utility cost test
(UCT) achievable economic potential in Idaho is 26,340 dekatherms. This increases to a cumulative total
of 58,352 dekatherms in the second year and 965,825 dekatherms by the eleventh year.
Table ES-2 Idaho Conservation Potential by Case, Selected Years (dekatherms)
Scenario 2018 2019 2022 2028 2038
Baseline Projection (Dth) 8,557,178 8,667,149 8,958,733 9,352,011 9,975,077
Cumulative Savings (Dth)
UCT Achievable Economic Potential 26,340 58,352 235,414 965,825 2,107,684
Achievable Technical Potential 37,324 81,526 310,222 1,218,944 2,514,049
Technical Potential 103,071 206,214 582,638 1,660,809 2,993,151
Cumulative Savings (% of Baseline)
UCT Achievable Economic Potential 0.3% 0.7% 2.6% 10.3% 21.1%
Achievable Technical Potential 0.4% 0.9% 3.5% 13.0% 25.2%
Technical Potential 1.2% 2.4% 6.5% 17.8% 30.0%
As part of this study, we also estimated total resource cost (TRC) potential, with the focus of fully balancing
non-energy impacts. This includes the use of full measure costs as well as quantified and monetizable
non-energy impacts and non-gas fuel impacts (e.g. electric cooling or wood secondary heating) consistent
with methodology within the Seventh Northwest Conservation and Electric Power Plan (Seventh Plan). We
explore this potential in more detail throughout the report.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 126 of 829
CONTENTS
Executive Summary ................................................................................................................... i
1 INTRODUCTION .............................................................................................. 1
Goals of the Conservation Potential Assessment .................................................................. 1
Summary of Report Contents .................................................................................................. 2
Abbreviations and Acronyms .................................................................................................. 4
2 ANALYSIS APPROACH AND DATA DEVELOPMENT .............................................. 5
Overview of Analysis Approach .............................................................................................. 5
Comparison with Northwest Power & Conservation Council Methodology .......... 5
LoadMAP Model .......................................................................................................... 6
Definitions of Potential ................................................................................................ 7
Market Characterization............................................................................................. 9
Baseline Projection .................................................................................................... 10
Energy Efficiency Measure Development ............................................................... 11
Calculation of Energy Conservation Potential ....................................................... 14
Data Development ................................................................................................................ 16
Data Sources.............................................................................................................. 16
Application of Data to the Analysis ......................................................................... 19
3 MARKET CHARACTERIZATION AND MARKET PROFILES ...................................... 25
Overall Energy Use Summary ................................................................................................. 25
Residential Sector ................................................................................................................... 27
Washington Characterization .................................................................................. 27
Idaho Characterization ............................................................................................ 29
Commercial Sector ................................................................................................................ 32
Washington Characterization .................................................................................. 32
Idaho Characterization ............................................................................................ 35
Industrial Sector ...................................................................................................................... 38
Washington Characterization .................................................................................. 38
Idaho Characterization ............................................................................................ 39
4 BASELINE PROJECTION ................................................................................. 41
Overall Baseline Projection .................................................................................................... 42
Washington Projection .............................................................................................. 42
Idaho Projection ........................................................................................................ 43
Residential Sector ................................................................................................................... 44
Washington Projection .............................................................................................. 44
Idaho Projection ........................................................................................................ 45
Commercial Sector ................................................................................................................ 46
Washington Projection .............................................................................................. 46
Idaho Projection ........................................................................................................ 47
Industrial Sector ...................................................................................................................... 48
Washington Projection .............................................................................................. 48
Idaho Projection ........................................................................................................ 49
5 OVERALL ENERGY EFFICIENCY POTENTIAL ...................................................... 50
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 127 of 829
Overall Energy Efficiency Potential ...................................................................................... 50
Washington Potential ................................................................................................ 50
Idaho Potential .......................................................................................................... 54
6 SECTOR-LEVEL ENERGY EFFICIENCY POTENTIAL ............................................... 57
Residential Sector ................................................................................................................... 57
Washington Potential ................................................................................................ 57
Idaho Potential .......................................................................................................... 60
Commercial Sector ................................................................................................................ 63
Washington Potential ................................................................................................ 63
Idaho Potential .......................................................................................................... 66
Industrial Sector ...................................................................................................................... 69
Washington Potential ................................................................................................ 69
Idaho Potential .......................................................................................................... 72
Incorporating the Total Resource Cost Test ......................................................................... 75
7 COMPARISON WITH CURRENT PROGRAMS ...................................................... 76
Washington Comparison with 2017 Programs and 2018 Plan ............................................ 76
Residential Sector ...................................................................................................... 76
Commercial and Industrial Sectors .......................................................................... 77
Idaho Comparison with 2017 Programs and 2018 Plan ...................................................... 78
Residential Sector ...................................................................................................... 78
Commercial and Industrial Sectors .......................................................................... 79
8 COMPARISON WITH CURRENT PROGRAMS ...................................................... 80
Residential Comparison with 2016 CPA ................................................................................ 80
Nonresidential Comparison with 2016 CPA .......................................................................... 81

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 128 of 829
LIST OF FIGURES
Figure 1-1 Avista’s Service Territory (courtesy Avista) ................................................................... 2
Figure 2-1 LoadMAP Analysis Framework ....................................................................................... 7
Figure 2-2 Approach for ECM Assessment ................................................................................... 12
Figure 3-1 Sector-Level Natural Gas Use in Base Year 2015, Washington (annual therms, percent)
....................................................................................................................................... 25
Figure 3-2 Sector-Level Natural Gas Use in Base Year 2015, Idaho (annual therms, percent)26
Figure 3-3 Residential Natural Gas Use by Segment, Washington, 2015 ................................... 27
Figure 3-4 Residential Natural Gas Use by End Use, Washington, 2015..................................... 28
Figure 3-5 Residential Energy Intensity by End Use and Segment, Washington, 2015 (Annual
Therms/HH) .................................................................................................................... 28
Figure 3-6 Residential Natural Gas Use by Segment, Idaho, 2015 ............................................. 30
Figure 3-7 Residential Natural Gas Use by End Use, Idaho, 2015 ............................................... 30
Figure 3-8 Residential Energy Intensity by End Use and Segment, Idaho, 2015 (Annual
Therms/HH) .................................................................................................................... 31
Figure 3-9 Commercial Natural Gas Use by Segment, Washington, 2015 ................................ 33
Figure 3-10 Commercial Sector Natural Gas Use by End Use, Washington, 2015 ...................... 33
Figure 3-11 Commercial Energy Usage Intensity by End Use and Segment, Washington, 2015
(Annual Therms/Sq. Ft) ................................................................................................. 34
Figure 3-12 Commercial Natural Gas Use by Segment, Idaho, 2015 .......................................... 36
Figure 3-13 Commercial Sector Natural Gas Use by End Use, Idaho, 2015 ................................ 36
Figure 3-14 Commercial Energy Usage Intensity by End Use and Segment, Idaho, 2015 (Annual
Therms/Sq. Ft) ................................................................................................................ 37
Figure 3-15 Industrial Natural Gas Use by End Use, Washington, 2015 ........................................ 38
Figure 3-16 Industrial Natural Gas Use by End Use, Idaho, 2015 .................................................. 40
Figure 4-1 Baseline Projection Summary by Sector, Washington (dekatherms) ....................... 42
Figure 4-2 Baseline Projection Summary by Sector, Idaho (dekatherms) ................................. 43
Figure 4-3 Residential Baseline Projection by End Use, Washington (dekatherms) .................. 44
Figure 4-4 Residential Baseline Projection by End Use, Idaho (dekatherms) ............................ 45
Figure 4-5 Commercial Baseline Projection by End Use, Washington (dekatherms) ............... 46
Figure 4-6 Commercial Baseline Projection by End Use, Idaho (dekatherms) ......................... 47
Figure 4-7 Industrial Baseline Projection by End Use, Washington (dekatherms) ..................... 48
Figure 4-8 Industrial Baseline Projection by End Use, Idaho (dekatherms) ............................... 49
Figure 5-1 Summary of Energy Efficiency Potential as % of Baseline Projection, Washington
(dekatherms) ................................................................................................................. 52
Figure 5-2 Baseline Projection and Energy Efficiency Forecasts, Washington (dekatherms) . 52
Figure 5-3 Cumulative UCT Achievable Economic Potential by Sector, Washington (% of Total)
....................................................................................................................................... 53
Figure 5-4 Summary of Energy Efficiency Potential as % of Baseline Projection, Idaho
(dekatherms) ................................................................................................................. 55
Figure 5-5 Summary of Energy Efficiency Potential as % of Baseline Projection, Idaho
(dekatherms) ................................................................................................................. 55
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 129 of 829
Figure 5-6 Cumulative UCT Achievable Economic Potential by Sector, Idaho (% of Total) ... 56
Figure 6-1 Residential Energy Conservation by Case, Washington (dekatherms) ................... 57
Figure 6-2 Residential UCT Achievable Economic Potential – Cumulative Savings by End Use,
Washington (dekatherms, % of total) ......................................................................... 58
Figure 6-3 Residential Energy Conservation by Case, Idaho (dekatherms) ............................. 60
Figure 6-4 Residential UCT Achievable Economic Potential – Cumulative Savings by End Use,
Idaho (dekatherms, % of total) ................................................................................... 61
Figure 6-5 Commercial Energy Conservation by Case, Washington (dekatherms) ................ 63
Figure 6-6 Commercial UCT Achievable Economic Potential – Cumulative Savings by End Use,
Washington (dekatherms, % of total) ......................................................................... 64
Figure 6-7 Commercial Energy Conservation by Case, Idaho (dekatherms) ........................... 66
Figure 6-8 Commercial UCT Achievable Economic Potential – Cumulative Savings by End Use,
Idaho (dekatherms, % of total) ................................................................................... 67
Figure 6-9 Industrial Energy Conservation Potential, Washington (dekatherms) ..................... 69
Figure 6-10 Industrial UCT Achievable Economic Potential – Cumulative Savings by End Use,
Washington (dekatherms, % of total) ......................................................................... 70
Figure 6-11 Industrial Energy Conservation Potential, Idaho (dekatherms) ............................... 72
Figure 6-12 Industrial UCT Achievable Economic Potential – Cumulative Savings by End Use,
Idaho (dekatherms, % of total) ................................................................................... 73

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 130 of 829
LIST OF TABLES
Table ES-1 Washington Conservation Potential by Case, Selected Years (dekatherms) ........... i
Table ES-2 Idaho Conservation Potential by Case, Selected Years (dekatherms) ..................... ii
Table 1-1 Explanation of Abbreviations and Acronyms .............................................................. 4
Table 2-1 Overview of Avista Analysis Segmentation Scheme ................................................... 9
Table 2-2 Example Equipment Measures for Direct Fuel Furnace – Single-Family Home,
Washington ................................................................................................................... 13
Table 2-3 Example Non-Equipment Measures – Existing Single Family Home, Washington ... 14
Table 2-4 Number of Measures Evaluated .................................................................................. 14
Table 2-5 Data Applied for the Market Profiles .......................................................................... 20
Table 2-6 Data Applied for the Baseline Projection in LoadMAP ............................................. 21
Table 2-7 Residential Natural Gas Equipment Federal Standards ............................................ 22
Table 2-8 Commercial and Industrial Natural Gas Equipment Standards ............................... 22
Table 2-9 Data Inputs for the Measure Characteristics in LoadMAP ....................................... 23
Table 3-1 Avista Sector Control Totals, Washington, 2015 ......................................................... 25
Table 3-2 Avista Sector Control Totals, Idaho, 2015 ................................................................... 26
Table 3-3 Residential Sector Control Totals, Washington, 2015 ................................................ 27
Table 3-4 Average Market Profile for the Residential Sector, 2015 .......................................... 29
Table 3-5 Residential Sector Control Totals, Idaho, 2015 .......................................................... 29
Table 3-6 Average Market Profile for the Residential Sector, 2015 .......................................... 31
Table 3-7 Commercial Sector Control Totals, Washington, 2015 .............................................. 32
Table 3-8 Average Market Profile for the Commercial Sector, Washington, 2015 ................. 34
Table 3-9 Commercial Sector Control Totals, Idaho, 2015 ........................................................ 35
Table 3-10 Average Market Profile for the Commercial Sector, Idaho, 2015 ............................ 37
Table 3-11 Industrial Sector Control Totals, Washington, 2015 .................................................... 38
Table 3-12 Average Natural Gas Market Profile for the Industrial Sector, Washington, 2015 .. 39
Table 3-13 Industrial Sector Control Totals, Idaho, 2015 .............................................................. 39
Table 3-14 Average Natural Gas Market Profile for the Industrial Sector, Washington, 2015 .. 40
Table 4-1 Baseline Projection Summary by Sector, Washington, Selected Years (dekatherms)
....................................................................................................................................... 42
Table 4-2 Baseline Projection Summary by Sector, Idaho, Selected Years (dekatherms) ..... 43
Table 4-3 Residential Baseline Projection by End Use, Washington (dekatherms) .................. 44
Table 4-4 Residential Baseline Projection by End Use, Idaho (dekatherms) ............................ 45
Table 4-5 Commercial Baseline Projection by End Use, Washington (dekatherms) ............... 46
Table 4-6 Commercial Baseline Projection by End Use, Idaho (dekatherms) ......................... 47
Table 4-7 Industrial Baseline Projection by End Use, Washington (dekatherms) ..................... 48
Table 4-8 Industrial Baseline Projection by End Use, Idaho (dekatherms) ............................... 49
Table 5-1 Summary of Energy Efficiency Potential, Washington (dekatherms) ...................... 51
Table 5-2 Cumulative UCT Achievable Economic Potential by Sector, Washington, Selected
Years (dekatherms) ...................................................................................................... 53
Table 5-3 Summary of Energy Efficiency Potential, Idaho (dekatherms)................................. 54
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 131 of 829
Table 5-4 Cumulative UCT Achievable Economic Potential by Sector, Idaho, Selected Years
(dekatherms) ................................................................................................................. 56
Table 6-1 Residential Energy Conservation Potential Summary, Washington (dekatherms) . 57
Table 6-2 Residential Top Measures in 2018 and 2019, UCT Achievable Economic Potential,
Washington (dekatherms) ........................................................................................... 59
Table 6-3 Residential Energy Conservation Potential Summary, Idaho (dekatherms) ........... 60
Table 6-4 Residential Top Measures in 2018 and 2019, UCT Achievable Economic Potential,
Idaho (dekatherms) ..................................................................................................... 62
Table 6-5 Commercial Energy Conservation Potential Summary, Washington ....................... 63
Table 6-6 Commercial Top Measures in 2018 and 2019, UCT Achievable Economic Potential,
Washington (dekatherms) ........................................................................................... 65
Table 6-7 Commercial Energy Conservation Potential Summary, Idaho ................................. 66
Table 6-8 Commercial Top Measures in 2018 and 2019, UCT Achievable Economic Potential,
Idaho (dekatherms) ..................................................................................................... 68
Table 6-9 Industrial Energy Conservation Potential Summary, Washington (dekatherms) .... 69
Table 6-10 Industrial Top Measures in 2018 and 2019, UCT Achievable Economic Potential,
Washington (dekatherms) ........................................................................................... 71
Table 6-11 Industrial Energy Conservation Potential Summary, Idaho (dekatherms)............... 72
Table 6-12 Industrial Top Measures in 2018 and 2019, UCT Achievable Economic Potential, Idaho
(dekatherms) ................................................................................................................. 74
Table 7-1 Comparison of Avista’s Washington Residential Programs with 2018 UCT Achievable
Economic Potential (dekatherms) .............................................................................. 76
Table 7-2 Comparison of Avista’s Washington Nonresidential Accomplishments with 2018 UCT
Achievable Economic Potential (dekatherms) ......................................................... 77
Table 7-3 Comparison of Avista’s Idaho Residential Programs with 2018 UCT Achievable
Economic Potential (dekatherms) .............................................................................. 78
Table 7-4 Comparison of Avista’s Idaho Nonresidential Accomplishments with 2018 UCT
Achievable Economic Potential (dekatherms) ......................................................... 79
Table 8-1 Comparison of Avista’s Residential UCT Achievable Economic Potential between the
2016 and 2018 CPAs (dekatherms) ............................................................................. 80
Table 8-2 Comparison of Avista’s Nonresidential UCT Achievable Economic Potential between
the 2016 and 2018 CPAs (dekatherms) ...................................................................... 81

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 132 of 829
1
INTRODUCTION
This report documents the results of the Avista Utilities 2018-2038 Conservation Potential Assessment
(CPA) as well as the steps followed in its completion. Throughout this study, AEG worked with Avista to
understand the baseline characteristics of their service territory, including a detailed understanding of
energy consumption in the territory, the assumptions and methodologies used in Avista’s official load
forecast, and recent programmatic accomplishments. Adapting methodologies consistent with the
Northwest Power and Conservation Council’s (Council’s) Seventh Conservation and Electric Power Plan1
for natural gas studies, AEG then developed an independent estimate of achievable, cost-effective EE
potential within Avista’s service territory between 2018 and 2038.
Goals of the Conservation Potential Assessment
The first primary objective of this study was to develop independent and credible estimates of EE potential
achievably available within Avista’s service territory using accepted regional inputs and methodologies.
This included estimating technical, achievable technical, then achievable economic potential, using the
Council’s ramp rates as the starting point for all achievability assumptions, leveraging Northwest Energy
Efficiency Alliance’s (NEEA’s) market research initiatives, and utilizing assumptions consistent with Seventh
Plan supply curves and RTF measure workbooks when appropriate for use in natural gas planning studies.
Additionally, the CPA is intended to support the design of programs to be implemented by Avista during
the upcoming years. One output of the LoadMAP model is a comprehensive summary of measures. This
summary documents input assumptions and sources on a per-unit value, program applicability and
achievability (ramp rates), and potential results (units, incremental potential, and cumulative potential) as
well as cost-effectiveness at the UCT and TRC levels. This summary was developed in collaboration with
Avista and refined throughout the project.
Finally, this study was developed to provide EE inputs into Avista’s Integrated Resource Planning (IRP)
process. To this end, AEG developed detailed achievable economic EE inputs by measure for input into
Avista’s SENDOUT planning model under the utility cost test (UCT). These inputs are highly customizable
and provide potential estimates at the state level by measure and end use. We present a map of Avista’s
service territory in Figure 1-1.
1 “Seventh Northwest Conservation and Electric Power Plan.” Northwest Power & Conservation Council, February 10, 2015.
http://www.nwcouncil.org/energy/powerplan/7/plan/
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 133 of 829
Figure 1-1 Avista’s Service Territory (courtesy Avista)

Summary of Report Contents
The document is divided into seven additional chapters, summarizing the approach, assumptions, and
results of the EE potential analysis. We describe each section below:
Volume 1, Final Report:
 Analysis Approach and Data Development. Detailed description of AEG’s approach to conducting
Avista’s 2018-2038 Natural Gas CPA and documentation of primary and secondary sources used.
 Market Characterization and Market Profiles. Characterization of Avista’s service territory in the base
year of the study, 2015, including total consumption, number of customers and market units, and
energy intensity. This also includes a breakdown of the energy consumption for residential,
commercial, and eligible industrial customers by end use and technology.
 Baseline Projection. Projection of baseline energy consumption under a naturally occurring efficiency
case, described at the end-use level. The LoadMAP models were first aligned with actual sales and
Avista’s official, weather-normalized econometric forecast and then varied to include the impacts of
future federal standards, ongoing impacts of energy codes, such as the 2015 Washington State Energy
Code on new construction, and future technology purchasing decisions.
 Overall Energy Efficiency Potential. Summary of EE potential for Avista’s Washington and Idaho service
territories for selected years between 2018 and 2038.
 Sector-Level Energy Efficiency Potential. Summary of EE potential for each market sector within Avista’s
service territory, including residential, commercial, and eligible industrial customers for both
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 134 of 829
Washington and Idaho. This section includes a more detailed breakdown of potential by measure type,
vintage, market segment, end use, and state.
 Comparison with Current Programs Detailed comparison of potential with Avista’s 2016 CPA and
current Avista programs, including new opportunities for potential.
 Comparison with 2016 CPA Detailed comparison of potential with Avista’s 2016 CPA, conducted by
AEG.
Volume 2, Appendices:
 Market Profiles. Detailed market profiles for each market segment. Includes equipment saturation,
unit energy consumption or energy usage index, energy intensity, and total consumption.
 Customer Adoption Factors. Documentation of the ramp rates used in this analysis. These were
adapted from the Seventh Plan electrical power conservation supply curve workbooks for use in the
estimation of achievable natural gas potential.
 Measure List. Contained in a separate spreadsheet accompanying delivery of this report. List of
measures, along with example baseline definitions and efficiency options by market sector analyzed.
 Detailed Measure Assumptions. Contained in a separate spreadsheet accompanying delivery of this
report. This dataset provides input assumptions, measure characteristics, cost-effectiveness results,
and potential estimates for each measure permutation analyzed within the study.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 135 of 829
Abbreviations and Acronyms
Throughout the report we use several abbreviations and acronyms. Table 1-1 shows the abbreviation or
acronym, along with an explanation.
Table 1-1 Explanation of Abbreviations and Acronyms
Acronym Explanation
AEO Annual Energy Outlook forecast developed by EIA
B/C Ratio Benefit to Cost Ratio
BEST AEG’s Building Energy Simulation Tool
BPA Bonneville Power Administration
C&I Commercial and Industrial
CBSA NEEA’s 2014 Commercial Building Stock Assessment
Council Northwest Power and Conservation Council (NWPCC)
DHW Domestic Hot Water
DSM Demand Side Management
EE Energy Efficiency
EIA Energy Information Administration
EUL Estimated Useful Life
EUI Energy Usage Intensity
HVAC Heating Ventilation and Air Conditioning
IFSA NEEA’s 2014 Industrial Facilities Site Assessment
IRP Integrated Resource Plan
LoadMAP AEG’s Load Management Analysis and Planning™ tool
NEEA Northwest Energy Efficiency Alliance
O&M Operations and Maintenance
RBSA NEEA’s 2012 Residential Building Stock Assessment
RTF Regional Technical Forum
RVT Resource Value Test
TRC Total Resource Cost test
UCT Utility Cost Test
UEC Unit Energy Consumption
UES Unit Energy Savings
WSEC 2015 Washington State Energy Code

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 136 of 829
2
ANALYSIS APPROACH AND DATA DEVELOPMENT
This section describes the analysis approach taken for the study and the data sources used to develop the
potential estimates.
Overview of Analysis Approach
To perform the potential analysis, AEG used a bottom-up approach following the major steps listed below.
We describe these analysis steps in more detail throughout the remainder of this chapter.
1. Performed a market characterization to describe sector-level natural gas use for the residential,
commercial, and industrial sectors for the base year, 2015. This included extensive use of Avista data
and other secondary data sources from NEEA and the Energy Information Administration (EIA).
2. Developed a baseline projection of energy consumption by sector, segment, end use, and
technology for 2016 through 2038.
3. Defined and characterized several hundred EE measures to be applied to all sectors, segments, and
end uses.
4. Estimated technical, achievable technical, and achievable economic energy savings at the measure
level for 2018-2038. Achievable economic potential was assessed using both the UCT and TRC
screens.
Comparison with Northwest Power & Conservation Council Methodology
It is important to note the Council’s methodology was developed for, and used, in electric CPAs. Natural
gas impacts are typically assessed when they overlap with electricity measures (e.g. gas water heating
impacts in an electrically heated “Built Green Washington” home). The Council’s ramp rates were also
developed with electric utility DSM programs in mind. Electricity is the primary focus of the regionwide
potential assessed in the Council’s Plans. Although Avista is a dual-fuel utility, this study focuses on natural
gas measures and programs, which exhibit noticeable differences from electric programs, notably
regarding avoided costs. To account for this, AEG adapted Council methodologies in some cases, rather
than using them directly from the source. This is especially relevant in the development of ramp rates
when achievability was determined to not be applicable to a specific natural gas measure or program. We
discuss this in Section 7 of this report.
A primary objective of the study was to estimate natural gas potential consistent with the Northwest Power
& Conservation Council’s (NWPCC) analytical methodologies and procedures for electric utilities. While
developing Avista’s 2018-2038 CPA, the AEG team relied on an approach vetted and adapted through the
successful completion of CPAs under the Council’s Fifth, Sixth, and now Seventh Power Plans. Among
other aspects, this approach involves using consistent:
 Data sources: Avista surveys, regional surveys, market research, and assumptions
 Measures and assumptions: Avista TRM, Seventh Plan supply curves and RTF work products
 Potential factors: Seventh Plan ramp rates
 Levels of potential: technical, achievable technical, and achievable economic
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 137 of 829
 Cost-effectiveness approaches: assessed potential under the UCT as well as Council’s TRC method,
including non-energy impacts (and non-gas energy impacts) which may be quantified and monetized
as well as O&M impacts within the TRC
 Conservation credits: applied a 10% conservation credit to avoided energy costs for energy benefits
was applied to the TRC calculation
LoadMAP Model
For this analysis, AEG used its Load Management Analysis and Planning tool (LoadMAP™) version 5.0 to
develop both the baseline projection and the estimates of potential. AEG developed LoadMAP in 2007
and has enhanced it over time, using it for the EPRI National Potential Study and numerous utility-specific
forecasting and potential studies since. Built in Excel, the LoadMAP framework (see Figure 2-1) is both
accessible and transparent and has the following key features.
 Embodies the basic principles of rigorous end-use models (such as EPRI’s Residential End-Use Energy
Planning System (REEPS) and Commercial End-Use Planning System (COMMEND)) but in a more
simplified, accessible form.
 Includes stock-accounting algorithms that treat older, less efficient appliance/equipment stock
separately from newer, more efficient equipment. Equipment is replaced according to the measure life
and appliance vintage distributions defined by the user.
 Balances the competing needs of simplicity and robustness by incorporating important modeling
details related to equipment saturations, efficiencies, vintage, and the like, where market data are
available, and treats end uses separately to account for varying importance and availability of data
resources.
 Isolates new construction from existing equipment and buildings and treats purchase decisions for
new construction and existing buildings separately. This is especially relevant in the state of
Washington where the 2015 WSEC substantially enhances the efficiency of the new construction
market.
 Uses a simple logic for appliance and equipment decisions. Other models available for this purpose
embody complex customer choice algorithms or diffusion assumptions, and the model parameter s
tend to be difficult to estimate or observe and sometimes produce anomalous results that require
calibration or even overriding. The LoadMAP approach allows the user to drive the appliance and
equipment choices year by year directly in the model. This flexible approach allows users to import
the results from diffusion models or to input individual assumptions. The framework also facilitates
sensitivity analysis.
 Includes appliance and equipment models customized by end use. For example, the logic for water
heating is distinct from furnaces and fireplaces.
 Can accommodate various levels of segmentation. Analysis can be performed at the sector level (e.g.,
total residential) or for customized segments within sectors (e.g., housing type, state, or income level).
 Natively outputs model results in a detailed line-by-line summary file, allowing for review of input
assumptions, cost-effectiveness results, and potential estimates at a granular level. Also allows for the
development of IRP supply curves, both at the achievable technical and achievable economic potential
levels.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 138 of 829
Consistent with the segmentation scheme and the market profiles we describe below, the LoadMAP model
provides projections of baseline energy use by sector, segment, end use, and technology for existing and
new buildings. It also provides forecasts of total energy use and energy-efficiency savings associated with
the various types of potential. 2
Figure 2-1 LoadMAP Analysis Framework

Definitions of Potential
Before we delve into the details of the analysis approach, it is important to define what we mean when
discussing energy efficiency (EE) potential. In this study, the savings estimates are developed for three
types of potential: technical potential, economic potential, and achievable potential. These are developed
at the measure level, and results are provided as savings impacts over the 21-year forecasting horizon.
The various levels are described below.
 Technical Potential is defined as the theoretical upper limit of EE potential. It assumes customers
adopt all feasible measures regardless of their cost. At the time of existing equipment failure,
customers replace their equipment with the most efficient option available. In new construction,
customers and developers also choose the most efficient equipment option.
Technical potential also assumes the adoption of every other available measure, where technically
feasible. For example, it includes installation of high-efficiency windows in all new construction
opportunities and furnace maintenance in all existing buildings with installed furnaces. These retrofit
measures are phased in over a number of years to align with the stock turnover of related equipment
units, rather than modeled as immediately available all at once.
2 The model computes energy forecasts for each type of potential for each end use as an intermediate calculation. Annual-energy savings
are calculated as the difference between the value in the baseline projection and the value in the potential forecast (e.g., the technical potential forecast).
Market Profiles
Base-Year Energy
Consumption

Analysis
Projection Results
Customer
segmentation
Market size
Equipment saturation
Technology shares
Vintage distribution
Unit energy
consumption
New construction
profile
By technology, end
use, segment, vintage,
sector, and state
Economic Data
Customer growth
Energy prices
Elasticities & HDD65s
Technology Data
Efficiency options
Codes and standards
List of measures
Saturations
Ramp rates
Avoided cost
Cost-effectiveness
Baseline Projection
Energy-efficiency
Projections
Technical
Achievable Technical
Achievable Economic
(UCT and TRC)
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 139 of 829
 Achievable Technical Potential refines technical potential by applying customer participation
rates that account for market barriers, customer awareness and attitudes, program maturity, and other
factors that affect market penetration of conservation measures. The customer adoption rates used
in this study were the ramp rates developed for the Northwest Power & Conservation Council’s
Seventh Plan based on the electric-utility model, tailored for use in natural gas EE programs.
 UCT Achievable Economic Potential further refines achievable technical potential by applying
an economic cost-effectiveness screen. In this analysis, primary cost-effectiveness is measured by the
utility cost test (UCT), which assesses cost-effectiveness from the utility’s perspective. This test
compares lifetime energy benefits to the costs of delivering the measure through a utility program,
excluding monetized non-energy impacts. These costs are the incentive, as a percent of incremental
cost of the given efficiency measure, relative to the relevant baseline course of action (e.g. federal
standard for lost opportunity and no action for retrofits), plus any administrative costs that are
incurred by the program to deliver and implement the measure. If the benefits outweigh the costs
(that is, if the UCT ratio is greater than 1.0), a given measure is included in the economic potential.
 TRC Achievable Economic Potential is similar to UCT achievable economic potential in that it
refines achievable technical potential through cost-effectiveness analysis. The total resource cost (TRC)
test assesses cost-effectiveness from a combined utility and participant perspective. As such, this test
includes full measure costs but also includes non-energy impacts realized by the customer if
quantifiable and monetized. In addition to non-energy impacts, we assessed the impacts of non-gas
savings following Council methodology. This includes a calibration credit for space heating equipment
consumption to account for secondary heating equipment present in an average home as well as
other electric end-use impacts such as cooling and interior lighting as applicable on a measure-by-
measure basis. As a secondary screen, we include TRC results for comparative purposes.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 140 of 829
Market Characterization
Now that we have described the modeling tool and provided the definitions of the potential cases, the
first step in the actual analysis approach is market characterization. To estimate the savings potential from
energy-efficient measures, it is necessary to understand how much energy is used today and what
equipment is currently in service. This characterization begins with a segmentation of Avista’s natural gas
footprint to quantify energy use by sector, segment, end-use application, and the current set of
technologies in use. For this we rely primarily on information from Avista, augmenting with secondary
sources as necessary.
Segmentation for Modeling Purposes
This assessment first defined the market segments (states, building types, end uses, and other dimensions)
that are relevant in Avista’s service territory. The segmentation scheme for this project is presented in
Table 2-1.
Table 2-1 Overview of Avista Analysis Segmentation Scheme
Dimension Segmentation Variable Description
0 State Washington and Idaho
1 Sector Residential, Commercial, Industrial
2 Segment
Residential: Single Family, Multifamily, Mobile Home, Low Income
Commercial: Office, Restaurant, Retail, Grocery, School, College,
Health, Lodging, Warehouse, Miscellaneous
Industrial
3 Vintage Existing and new construction
4 End uses Heating, secondary heating, water heating, food preparation, process,
and miscellaneous (as appropriate by sector)
5 Appliances/end uses and
technologies
Technologies such as furnaces, water heaters, and process heating by
application, etc.
6 Equipment efficiency levels
for new purchases
Baseline and higher-efficiency options as appropriate for each
technology
With the segmentation scheme defined, we then performed a high-level market characterization of natural
gas sales in the base year, 2015. This is the same year that the 2016 CPA began in. We started in this year
for consistency but aligned the forecast (and equipment purchases) in subsequent years with weather-
actual sales. This data was based on detailed baseline studies conducted by Avista as well as regional data
available. This information provided control totals at a sector level for calibrating the LoadMAP model to
known data for the base-year.
Market Profiles
The next step was to develop market profiles for each sector, customer segment, end use, and technology.
A market profile includes the following elements:
 Market size is a representation of the number of customers in the segment. For the residential sector,
the unit we use is number of households. In the commercial sector, it is floor space measured in square
feet. For the industrial sector, it is number of employees.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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 Saturations indicate the share of the market that is served by a particular end-use technology. Three
types of saturation definitions are commonly used:
o The conditioned space approach accounts for the fraction of each building that is conditioned by
the end use. This applies to cooling and heating end uses.
o The whole-building approach measures shares of space in a building with an end use regardless
of the portion of each building that is served by the end use. Examples are commercial
refrigeration and food service, and domestic water heating and appliances.
o The 100% saturation approach applies to end uses that are generally present in every building or
home and are simply set to 100% in the base year.
 UEC (Unit Energy Consumption) or EUI (Energy Usage Index) define consumption for a
given technology. UEC represents the amount of energy a given piece of equipment is expected to
use in one year. EUI is a UEC indexed to a non-building market unit, such as per square foot or per
employee)
o These are indices that refer to a measure of average annual energy use per market unit (home,
floor space, or employee in the residential, commercial, and industrial sector, respectively) that
are served by an end-use technology. UECs and EUIs embody an average level of service and
average equipment efficiency for the market segment.
 Annual energy intensity for the residential sector represents the average energy use for the
technology across all homes in 2015. It is computed as the product of the saturation and the UEC and
is defined as therms/household for natural gas. For the commercial and industrial sectors, intensity,
computed as the product of the saturation and the EUI, represents the average use for the technology
across all floor space or all employees in the base year.
 Annual usage is the annual energy used by each end-use technology in the segment. It is the
product of the market size and intensity and is quantified in therms or dekatherms.
The market characterization results and the market profiles are presented in Section 3 and Appendix A.
Baseline Projection
The next step was to develop the baseline projection of annual natural gas use for 2016 through 2038 by
customer segment and end use in the absence of new utility energy efficiency programs.
We first aligned with Avista’s official forecast. AEG incorporated assumptions and data utilized in the
official utility forecast. Avista’s heating degree days (base 65°F) were incorporated into the LoadMAP
model to align the baseline projection with the official utility forecast. We calibrated to actual sales when
available.
The end-use projection includes impacts of future federal standards that were effective as of December
2017, which drive energy consumption down through the study period.
Naturally occurring energy conservation, that is, energy conservation that is realized within the service
area independent of utility-sponsored programs, is incorporated into the baseline projection consistent
with the US Energy Information Administration’s Annual Energy Outlook for the Pacific region. Results of
the primary market research were used to calibrate these assumptions to ensure the secondary sources
were relevant to Avista customers. For example, some customers will purchase and install energy
conservation measures that are available in the market without a utility incentive.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 142 of 829
As such, the baseline projection is the foundation for the analysis of savings in future conservation cases
and scenarios as well as the metric against which potential savings are measured.
Inputs to the baseline projection include:
 Current economic growth forecasts (i.e., customer growth, changes in weather (Heating Degree Day,
base-65°F (HDD65) normalization))
 Trends in fuel shares and equipment saturations
 Existing and approved changes to building codes and equipment standards
We present the baseline projection results for the system as a whole, and for each sector in Section 4.
Energy Efficiency Measure Development
This section describes the framework used to assess the savings, costs, and other attributes of energy
efficiency measures. These characteristics form the basis for measure-level cost-effectiveness analyses as
well as for determining measure-level savings. For all measures, AEG assembled information to reflect
equipment performance, incremental costs, and equipment lifetimes. This information combined with
Avista’s avoided cost data informs the economic screens that determine economically feasible measures.
In this section, AEG would like to acknowledge the work of the Avista team in detailed measure
assumptions specific to the territory and region within the Avista TRM, which was provided at the outset
of this study.
Figure 2-2 outlines the framework for measure characterization analysis. First, the list of measures is
identified; each measure is then assigned an applicability for each market sector and segment and
characterized with appropriate savings, costs and other attributes; then the cost-effectiveness screening
is performed. Avista provided feedback during each step of the process to ensure measure assumptions
and results lined up with programmatic experience.
We compiled a robust list of conservation measures for each customer sector, drawing upon Avista’s TRM
and program experience, AEG’s own measure databases and building simulation models, and secondary
sources, primarily the Regional Technical Forum’s (RTF) UES measure workbooks and the Seventh Plan’s
electric power conservation supply curves. This universal list of measures covers all major types of end-
use equipment, as well as devices and actions to reduce energy consumption.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 143 of 829
Figure 2-2 Approach for ECM Assessment

The selected measures are categorized into two types according to the LoadMAP modeling taxonomy:
equipment measures and non-equipment measures.
 Equipment measures are efficient energy-consuming pieces of equipment that save energy by
providing the same service with a lower energy requirement than a standard unit. An example is an
ENERGY STAR® residential water heater (UEF 0.64) that replaces a standard efficiency water heater
(UEF 0.58). For equipment measures, many efficiency levels may be available for a given technology,
ranging from the baseline unit (often determined by a code or standard) up to the most efficient
product commercially available. These measures are applied on a stock-turnover basis, and in general,
are referred to as lost opportunity (LO) measures by the Council because once a purchase decision is
made, there will not be another opportunity to improve the efficiency of that equipment item until its
effective useful life (EUL) is reached once again.
 Non-equipment measures save energy by reducing the need for delivered energy, but do not
necessarily involve replacement or purchase of major end-use equipment (such as a furnace or water
heater). Measure installation is not tied to a piece of equipment reaching end of useful life, so these
are generally categorized as “retrofit” measures. An example would be low-flow showerheads that
modify a household’s hot water consumption. The existing showerheads can be achievably replaced
without waiting for the existing showerhead to malfunction, and saves energy used by the water
heating equipment. Non-equipment measures typically fall into one of the following categories:
o Building shell (windows, insulation, roofing material)
o Equipment controls (smart thermostats, water heater setback)
o Whole-building design (ENERGY STAR homes)
AEG universal
measure list
Measure
descriptions
Measure characterization
Economic screen
UCT and TRC
Energy savings Costs and NEIs
Lifetime Base saturation and
applicability
Client measure
data library
(RTF, 7th Plan, AEO, Statewide
TRMs, evaluation reports, etc.)
AEG measure
data library
(DEEM)
Building Simulations
Avoided costs, discount rate,
transport losses
Inputs Process
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 144 of 829
o Retrocommissioning and strategic energy management
We developed a preliminary list of efficient measures, which was distributed to Avista’s project team for
review. Once we assembled the list of measures, the AEG team assessed their energy-saving
characteristics. For each measure, we also characterized incremental cost, service life, non-energy impacts,
and other performance factors. Following the measure characterization, we performed an economic
screening of each measure, which serves as the basis for developing the economic and achievable
potential scenarios.
Representative Measure Data Inputs
To provide an example of measure data, Table 2-2 and Table 2-3 present examples of the detailed data
inputs behind both equipment and non-equipment measures, respectively, for the case of residential
direct-fuel furnaces in single-family homes in Washington. Table 2-2 displays the various efficiency levels
available as equipment measures, as well as the corresponding effective useful life, energy usage, and
cost estimates. The columns labeled “On Market” and “Off Market” reflect equipment availability due to
codes and standards or the entry of new products to the market.
Table 2-2 Example Equipment Measures for Direct Fuel Furnace – Single-Family Home,
Washington
Efficiency Level Useful Life
(years)
Equipment
Cost
Energy Usage
(therms/yr)
On
Market
Off
Market
AFUE 80% 20 $1,955 517 2015 2023
AFUE 90% 20 $2,058 465 2015 2023
AFUE 92% 20 $2,099 453 2015 n/a
AFUE 95% 20 $2,778 438 2015 n/a
AFUE 98% 20 $3,035 423 2015 n/a
Convert to NG Heat Pump 20 $6,739 345 2015 n/a
Table 2-3 lists some of the non-equipment measures applicable to a direct-fuel furnace in an existing
single-family home. All measures are evaluated for cost effectiveness based on the lifetime benefits
relative to the cost of the measure. The total savings, costs, and monetized non-energy impacts are
calculated for each year of the study and depend on the base year saturation of the measure, the
applicability of the measure, and the savings as a percentage of the relevant energy end uses. We model
two flavors of most shell insulations measures. The first is the installation of insulation where there is none
(or very little). This applies to a small subset of the population (roughly 6% of the population is eligible
for this measure per RBSA 2011) but has large savings impacts. This percentage is low due to the impacts
of current Avista programs, strict Washington building codes, and naturally occurring efficiency. The
second is an insulation upgrade measure where homes with existing insulation below the threshold but
not classified as no insulation, may be upgraded to higher R-values. This applies to a much larger
percentage of the market.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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Table 2-3 Example Non-Equipment Measures – Existing Single Family Home, Washington3
End Use Measure Saturation
in 20154 Applicability Lifetime
(yrs)
Measure
Installed Cost
Energy
Savings (%)
Heating Insulation - Ceiling
Installation 0% 6% 45 $1,280 31.3%
Heating Insulation – Ceiling Upgrade 20% 88% 45 $1,739 1.2%
Heating Ducting Repair and Sealing 15% 50% 20 $794 6.0%
Heating Windows - High Efficiency 89% 100% 45 $5,337 25.5%
Table 2-4 summarizes the number of measures evaluated for each segment within each sector.
Table 2-4 Number of Measures Evaluated
Sector Total Measures Measure Permutations
w/ 2 Vintages
Measure Permutations
w/ All Segments & States
Residential 44 88 704
Commercial 52 104 2,080
Industrial 32 64 128
Total Measures Evaluated 128 256 2,912
Calculation of Energy Conservation Potential
The approach we used for this study to calculate the energy conservation potential adheres to the
approaches and conventions outlined in the National Action Plan for Energy-Efficiency (NAPEE) Guide for
Conducting Potential Studies.5 This document represents credible and comprehensive industry best
practices for specifying energy conservation potential. Three types of potential were developed as part of
this effort: technical potential, achievable technical potential, and achievable economic potential (using
UCT and TRC). The calculation of technical potential is a straightforward algorithm which, as described
above, assumes that customers adopt all feasible measures regardless of their cost.
Stacking of Measures and Interactive Effects
An important factor when estimating potential is to consider interactions between measures when they
are applied within the same space. This is important to avoid double counting and could feasibly result in
savings at greater than 100% of equipment consumption if not properly accounted for.
This occurs at the population or system level, where multiple DSM actions must be stacked or layered on
top of each other in succession, rather than simply summed arithmetically. These interactions are
automatically handled within the LoadMAP models where measure impacts are stacked on top of each
other, modifying the baseline for each subsequent measure. We first compute the total savings of each
measure on a standalone basis, then also assign a stacking priority, based on levelized cost, to the
measures such that “integrated” or “stacked” savings will be calculated as a percent reduction to the
3 The applicability factors consider whether the measure is applicable to a particular building type and whether it is feasible to install the
measure. For instance, duct repair and sealing is not applicable to homes with zonal heating systems since there is no ductwork present
to repair.
4 Note that saturation levels reflected increase from their base year saturation as more measures are adopted.
5 National Action Plan for Energy Efficiency (2007). National Action Plan for Energy Efficiency Vision for 2025: Developing a Framework for Change. www.epa.gov/eeactionplan.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
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running total of baseline energy remaining in each end use after the previous measures have been applied.
This ensures that the available pie of baseline energy shrinks in proportion to the number of DSM
measures applied, as it would in reality. The loading order is based on the levelized cost of conserved
energy, such that the more economical measures that are more likely to be selected from a resource
planning perspective will be the first to be applied to the modeled population.
We also account for exclusivity of certain measure options when defining measure assumptions. For
instance, if an AFUE 95% furnace is installed in a single-family home, the model will not allow that same
home to install an AFUE 98% furnace, or any other furnace, until the newly installed AFUE 95% option has
reached its end of useful life. For non-equipment measures, which do not have a native applicability limit,
we define base saturations and applicabilities such that measures do not overlap. For example, we model
two flavors of ceiling insulation. The first assumes the installation of insulation where there previously was
none. The second upgrades pre-existing insulation if it falls under a certain threshold. We used regional
market research data to ensure exclusivity of these two options. NEEA’s 2014 RBSA contains information
on average R-values of insulation installed. The AEG team used this data to define the percent of homes
that could install one measure, but not the other.
Estimating Customer Adoption
Once the technical potential is established, estimates for the market adoption rates for each measure are
applied that specify the percentage of customers that will select the highest–efficiency economic option.
This phases potential in over a more realistic time frame that considers barriers such as imperfect
information, supplier constraints, technology availability, and individual customer preferences. The intent
of market adoption rates is to establish a path to full market maturity for each measure or technology
group and ensure resource planning does not overstep acquisition capabilities. We adapted the Northwest
Power and Conservation Council’s Seventh Plan ramp rates to develop these achievability factors for each
measure. Applying these ramp rates as factors leads directly to the achievable technical potential.
Screening Measures for Cost-Effectiveness
With achievable technical potential established, the final step is to apply an economic screen and arrive
at the subset of measures that are cost-effective and ultimately included in achievable economic potential.
LoadMAP performs an economic screen for each individual measure in each year of the planning horizon.
This study uses the UCT test as the primary cost-effectiveness metric, which compares the lifetime hourly
energy benefits of each applicable measure with the incentive and administrative costs incurred by the
utility. The lifetime benefits are calculated by multiplying the annual energy savings for each measure by
Avista’s avoided costs and discounting the dollar savings to the present value equivalent. Lifetime costs
represent incremental measure cost. The analysis uses each measure’s values for savings, costs, and
lifetimes that were developed as part of the measure characterization process described above.
The LoadMAP model performs this screening dynamically, considering changing savings and cost data
over time. Thus, some measures pass the economic screen for some, but not all, of the years in the
forecast.
It is important to note the following about the economic screen:
 The economic evaluation of every measure in the screen is conducted relative to a baseline
condition. For instance, in order to determine the therm savings potential of a measure,
consumption with the measure applied must be compared to the consumption of a baseline
condition.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 147 of 829
 The economic screening was conducted only for measures that are applicable to each building type
and vintage; thus, if a measure is deemed to be irrelevant to a building type and vintage, it is
excluded from the respective economic screen.
This constitutes the achievable economic potential and includes every program-ready opportunity for
conservation savings. Potential results are presented in Sections 4 and 5. Measure-level detail is available
as a separate appendix to this report.
Data Development
This section details the data sources used in this study, followed by a discussion of how these sources
were applied. In general, data were adapted to local conditions, for example, by using local sources for
measure data and local weather for building simulations.
Data Sources
The data sources are organized into the following categories:
 Avista-provided data
 AEG’s databases and analysis tools
 Other secondary data and reports
Avista Data
Our highest priority data sources for this study were those that were specific to Avista, including the
primary market research conducted specifically for this study. This data is specific to Avista’s service
territory and is an important consideration when customizing the model for Avista’s market. This is best
practice when developing CPA baselines when the data is available.
 Avista customer account database. Avista provided billing data for development of customer
counts and energy use for each sector. This included a very detailed database of customer building
classifications which was instrumental in the development of segmentation.
 Avista’s 2013 GenPOP Residential Survey. In 2013, Avista hired The Cadmus Group to conduct a
residential saturation survey, which included results from 1,051 customers. The results of this survey
helped segment the residential sector and establish fuel and technology shares for the base year. This
data was very useful in developing a detailed estimate of energy consumption within Avista’s service
territory.
 Load forecasts. Avista provided forecasts, by sector and state, of energy consumption, customer
counts, weather actuals for 2015 and 2017, as well as weather-normal HDD65s.
 Economic information. Avista provided a discount rate as well as avoided cost forecasts consistent
with those utilized in the IRP.
 Avista program data. Avista provided information about past and current programs, including
program descriptions, goals, and measure achievements to date.
 Avista TRM. Avista provided a documented list of energy conservation measures and assumptions
considered within current programs. We utilized this as a primary source of measure information,
supplemented by Northwest data, AEG data, and secondary data as described below.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 148 of 829
Northwest Regional Data
The study utilized a variety of local data and research, including research performed by the Northwest
Energy Efficiency Alliance (NEEA) and analyses conducted by the Council. Most important among these
are:
 Northwest Power and Conservation Council Seventh Plan and Regional Technical
Forum workbooks. To develop its Power Plan, the Council maintains workbooks with detailed
information about measures. This was used as a primary data source when Avista-specific program
data was not available, and the data was determined to be applicable to natural gas conservation
measures. The most recent data and workbooks available were used at the time of this study.
 Northwest Energy Efficiency Alliance, 2011 Residential Building Stock Assessment
Single-Family, Market Research Report, http://neea.org/docs/reports/residential-building-stock-
assessment-single-family-characteristics-and-energy-use.pdf?sfvrsn=8
 Northwest Energy Efficiency Alliance, 2011 Residential Building Stock Assessment:
Manufactured Home, Market Research Report, #E13-249, January 2013.
http://neea.org/docs/default-source/reports/residential-building-stock-assessment--manufactured-
homes-characteristics-and-energy-use.pdf?sfvrsn=8
 Northwest Energy Efficiency Alliance, 2011 Residential Building Stock Assessment:
Multifamily, Market Research Report, #13-263, September 2013. http://neea.org/docs/default-
source/reports/residential-building-stock-assessment--multi-family-characteristics-and-energy-
use.pdf?sfvrsn=4
 Northwest Energy Efficiency Alliance, 20 14 Commercial Building Stock Assessment ,
December 16, 2014, http://neea.org/docs/default-source/reports/2014-cbsa-final-report_05-dec-
2014.pdf?sfvrsn=12.
 Northwest Energy Efficiency Alliance, 2014 Industrial Facilities Site Assessment,
December 29, 2014, http://neea.org/resource-center/regional-data-resources/industrial-facilities-
site-assessment
Since Avista’s GenPOP survey contained detailed appliance saturations, the 2011 RBSA was used more for
benchmarking and comparative purposes, rather than as a primary source of data. The NEEA surveys were
used extensively to develop base saturation and applicability assumptions for many of the non-equipment
measures within the study. It is worth noting that NEEA’s 2016 RBSA was released during the drafting of
this report, following conclusion of analysis. This survey incorporates new market trends and building
characteristics and is expected to be a useful source of measure baseline saturations when updating this
CPA.
AEG Data
AEG maintains several databases and modeling tools that we use for forecasting and potential studies.
Relevant data from these tools has been incorporated into the analysis and deliverables for this study.
 AEG Energy Market Profiles. For more than 10 years, AEG staff has maintained profiles of end-
use consumption for the residential, commercial, and industrial sectors. These profiles include market
size, fuel shares, unit consumption estimates, and annual energy use by fuel (natural gas and
electricity), customer segment and end use for 10 regions in the U.S. The Energy Information
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 149 of 829
Administration surveys (RECS, CBECS and MECS) as well as state-level statistics and local customer
research provide the foundation for these regional profiles.
 Building Energy Simulation Tool (BEST). AEG’s BEST is a derivative of the DOE 2.2 building
simulation model, used to estimate base-year UECs and EUIs, as well as measure savings for the HVAC-
related measures.
 AEG’s Database of Energy Conservation Measures (DEEM). AEG maintains an extensive
database of measure data for our studies. Our database draws upon reliable sources including the
California Database for Energy Efficient Resources (DEER), the EIA Technology Forecast Updates –
Residential and Commercial Building Technologies – Reference Case, RS Means cost data, and
Grainger Catalog Cost data.
 Recent studies. AEG has conducted more than 60 studies of EE potential in the last five years. We
checked our input assumptions and analysis results against the results from these other studies, both
within the region and across the country.
Other Secondary Data and Reports
Finally, a variety of secondary data sources and reports were used for this study. The main sources are
identified below.
 Annual Energy Outlook. The Annual Energy Outlook (AEO), conducted each year by the U.S.
Energy Information Administration (EIA), presents yearly projections and analysis of energy topics. For
this study, we used data from the 2015 and 2017 AEO.
 American Community Survey. The US Census American Community Survey is an ongoing survey
that provides data every year on household characteristics. http://www.census.gov/acs/www/
 Local Weather Data. Weather from NOAA’s National Climatic Data Center for Spokane in
Washington and Coure d’Alene in Idaho were used where applicable.
 EPRI End-Use Models (REEPS and COMMEND). These models provide the energy-use
elasticities we apply to prices, household income, home size, heating, and cooling.
 Database for Energy Efficient Resources (DEER). The California Energy Commission and
California Public Utilities Commission (CPUC) sponsor this database, which is designed to provide
well-documented estimates of energy and peak demand savings values, measure costs, and effective
useful life (EUL) for the state of California. We used the DEER database to cross check the measure
savings we developed using BEST and DEEM.
 Other relevant resources: These include reports from the Consortium for Energy Efficiency, the
EPA, and the American Council for an Energy-Efficient Economy. This also includes technical reference
manuals (TRMs) from other states. When using data from outside the region, especially weather-
sensitive data, AEG adapted assumptions for use within Avista’s territory.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 150 of 829
Application of Data to the Analysis
We now discuss how the data sources described above were used for each step of the study.
Data Application for Market Characterization
To construct the high-level market characterization of natural gas consumption and market size units
(households for residential, floor space for commercial, and employees for industrial), we primarily used
Avista’s billing data as well as secondary data from AEG’s Energy Market Profiles database.
Data Application for Market Profiles
The specific data elements for the market profiles, together with the key data sources, are shown in Table
2-5. To develop the market profiles for each segment, we used the following approach:
1. Develop control totals for each segment. These include market size, segment-level annual natural gas
use, and annual intensity. Control totals were based on Avista’s actual sales and customer-level
information found in Avista’s customer billing database. We used the market profiles from the 2016
CPA as a starting point.
2. Develop existing appliance saturations and the energy characteristics of appliances, equipment, and
buildings using equipment flags within Avista’s billing data, NEEA’s 2011 RBSA, 2014 CBSA, and 2014
IFSA, DOE’s 2009 RECS, the 2015 and 2017 editions of the Annual Energy Outlook, AEG’s Energy Market
Profile (EMP) for the Pacific region, and the American Housing Survey.
3. Ensure calibration to Avista control totals for annual natural gas sales in each sector and segment.
4. Compare and cross-check with other recent AEG studies.
5. Work with Avista staff to verify the data aligns with their knowledge and experience.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 151 of 829
Table 2-5 Data Applied for the Market Profiles
Model Inputs Description Key Sources
Market size Base-year residential dwellings, commercial
floor space, and industrial employment
Avista 2015 actual sales
Avista customer account database
Annual intensity
Residential: Annual use per household
Commercial: Annual use per square foot
Industrial: Annual use per employee
Avista customer account database
AEG’s Energy Market Profiles
AEO 2015 – Pacific Region
Other recent studies
Appliance/equipment
saturations
Fraction of dwellings with an
appliance/technology
Percentage of C&I floor space/employment
with equipment/technology
Avista 2013 GenPOP Survey
2011 RBSA, 2014 CBSA and IFSA
2014 American Community Survey
AEG’s Energy Market Profiles
UEC/EUI for each end-use
technology
UEC: Annual natural gas use in homes and
buildings that have the technology
EUI: Annual natural gas use per square
foot/employee for a technology in floor space
that has the technology
HVAC uses: BEST simulations using
prototypes developed for Avista
Engineering analysis
AEG DEEM
AEO 2015 – Pacific Region
Recent AEG studies
Appliance/equipment age
distribution Age distribution for each technology 2011 RBSA, 2014 CBSA, and recent
AEG studies
Efficiency options for each
technology
List of available efficiency options and annual
energy use for each technology
Avista current program offerings
AEG DEEM
AEO 2015 through AEO 2017
CA DEER
Recent AEG studies

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 152 of 829
Data Application for Baseline Projection
Table 2-6 summarizes the LoadMAP model inputs required for the baseline projection. These inputs are
required for each segment within each sector, as well as for new construction and existing
dwellings/buildings.
Table 2-6 Data Applied for the Baseline Projection in LoadMAP
Model Inputs Description Key Sources
Customer growth forecasts Forecasts of new construction in
residential and C&I sectors Avista load forecast
Equipment purchase shares for
baseline projection
For each equipment/technology,
purchase shares for each efficiency
level; specified separately for existing
equipment replacement and new
construction
Shipment data from AEO and ENERGY
STAR
AEO 2017 regional forecast
assumptions6
Appliance/efficiency standards
analysis
Utilization model parameters Price elasticities, elasticities for other
variables (income, weather) EPRI’s REEPS and COMMEND models
In addition, assumptions were incorporated for known future equipment standards as of December 2017,
as shown in Table 2-7 and Table 2-8. The assumptions tables here extend through 2025, after which all
standards are assumed to hold steady.

6 We developed baseline purchase decisions using the Energy Information Agency’s Annual Energy Outlook report (2017), which utilizes
the National Energy Modeling System (NEMS) to produce a self-consistent supply and demand economic model. We calibrated equipment purchase options to match distributions/allocations of efficiency levels to manufacturer shipment data for recent years.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 153 of 829
Table 2-7 Residential Natural Gas Equipment Federal Standards7
End Use Technology 2015 2017 2018 2019 2020 2021 2022 2023 2024 2025
Space Heating
Furnace – Direct Fuel AFUE 80% AFUE 92%*
Boiler – Direct Fuel AFUE 82% AFUE 84%
Secondary Heating Fireplace N/A
Water Heating
Water Heater <= 55 gal. UEF 0.58
Water Heater > 55 gal. UEF 0.76
Appliances
Clothes Dryer CEF 3.30
Stove/Oven N/A
Miscellaneous
Pool Heater TE 0.82
Miscellaneous N/A
* This code was originally set to take effect in 2021 but exempts smaller systems. The comment period was also extended into 2017 and the
standard will not take effect until at least 5 years after that has concluded. As a result, we modeled this standard coming online officially in 2024.

Table 2-8 Commercial and Industrial Natural Gas Equipment Standards
End Use Technology 2015 2017 2018 2019 2020 2021 2022 2023 2024 2025
Cooling
Furnace AFUE 80% / TE 0.80
Boiler Average around AFUE 80% / TE 0.80 (varies by size)
Unit Heater Standard (intermittent ignition and power venting or automatic flue damper)
Water Heater Water Heating TE 0.80

7 The assumptions tables here extend through 2025, after which all standards are assumed to hold steady.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 154 of 829
Energy Conservation Measure Data Application
Table 2-9 details the energy-efficiency data inputs to the LoadMAP model. It describes each input and
identifies the key sources used in the Avista analysis.
Table 2-9 Data Inputs for the Measure Characteristics in LoadMAP
Model Inputs Description Key Sources
Energy Impacts
The annual reduction in consumption attributable to each
specific measure. Savings were developed as a
percentage of the energy end use that the measure
affects.
Avista TRM
NWPCC workbooks, RTF
AEG BEST
AEG DEEM
AEO 2017
CA DEER
Other secondary sources
Costs
Equipment Measures: Includes the full cost of purchasing
and installing the equipment on a per-household, per-
square-foot, or per employee basis for the residential,
commercial, and industrial sectors, respectively.
Non-Equipment Measures: Existing buildings – full
installed cost. New Construction - the costs may be either
the full cost of the measure, or as appropriate, it may be
the incremental cost of upgrading from a standard level
to a higher efficiency level.
Avista TRM
NWPCC workbooks, RTF
AEG DEEM
AEO 2017
CA DEER
RS Means
Other secondary sources
Measure Lifetimes
Estimates derived from the technical data and secondary
data sources that support the measure demand and
energy savings analysis.
Avista TRM
NWPCC workbooks, RTF
AEG DEEM
AEO 2017
CA DEER
Other secondary sources
Applicability
Estimate of the percentage of dwellings in the residential
sector, square feet in the commercial sector, or
employees in the industrial sector where the measure is
applicable and where it is technically feasible to
implement.
2011 RBSA, 2014 CBSA
2015 WSEC for limitations on new
construction
AEG DEEM
CA DEER
Other secondary sources
On Market and Off
Market Availability
Expressed as years for equipment measures to reflect
when the equipment technology is available or no longer
available in the market.
AEG appliance standards and
building codes analysis

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 155 of 829
Data Application for Cost-effectiveness Screening
To perform the cost-effectiveness screening, a number of economic assumptions were needed. All cost
and benefit values were analyzed as real dollars, converted from nominal provided by Avista. We applied
Avista’s long-term discount rate of 4.34% excluding inflation. LoadMAP is configured to vary this by market
sector (e.g. residential and commercial) if Avista develops alternative values in the future.
Estimates of Customer Adoption
To estimate the timing and rate of customer adoption in the potential forecasts, two sets of parameters
are needed:
 Technical diffusion curves for non-equipment measures. Equipment measures are installed
when existing units fail. Non-equipment measures do not have this natural periodicity, so rather than
installing all available non-equipment measures in the first year of the projection (instantaneous
potential), they are phased in according to adoption schedules that generally align with the diffusion
of similar equipment measures. For this analysis, we used the Council’s retrofit ramp rates, “Retro”,
applied before the 85% achievability adjustment.
 Customer adoption rates, also referred to as take rates or ramp rates, are applied to measures on
a year by year basis. These rates represent customer adoption of measures when delivered through a
best-practice portfolio of well-operated efficiency programs under a reasonable policy or regulatory
framework. Information channels are assumed to be established and efficient for marketing, educating
consumers, and coordinating with trade allies and delivery partners. The primary barrier to adoption
reflected in this case is customer preferences. Again, these are based on the ramp rates from the
Northwest Power and Conservation Council’s Seventh Plan.
The ramp rates referenced above were adapted for use for assessing natural gas measure potential. We
describe this process in Section 7. The customer adoption rates used in this study are available in Appendix
B.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 156 of 829
3
MARKET CHARACTERIZATION AND MARKET PROFILES
In this section, we describe how customers in the Avista service territory use natural gas in the base year
of the study, 2015. It begins with a high-level summary of energy use across all sectors and then delves
into each sector in more detail.
Overall Energy Use Summary
Total natural gas consumption for all sectors for Avista’s Washington territory in 2015 was 15,376,657
dekatherms. As shown in Figure 3-1 and Table 3-1, the residential sector accounts for the largest share of
annual energy use at 60%, followed by the commercial sector at 37%. The industrial sector accounts for
3% of usage.
Figure 3-1 Sector-Level Natural Gas Use in Base Year 2015, Washington (annual therms, percent)

Table 3-1 Avista Sector Control Totals, Washington, 2015
Sector Natural Gas
Use (dekatherms) % of Use
Residential 9,186,242 60%
Commercial 5,734,759 37%
Industrial 455,656 3%
Total 15,376,657 100%

Residential, 60%
Commercial, 37%
Industrial, 3%
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 157 of 829
Total natural gas consumption for all sectors for Avista’s Idaho territory in 2015 was 7,215,664 dekatherms.
As shown in Figure 3-2 and Table 3-2, the residential sector accounts for the largest share of annual energy
use at 60%, followed by the commercial sector at 34%. The industrial sector accounts for 6% of usage.
Figure 3-2 Sector-Level Natural Gas Use in Base Year 2015, Idaho (annual therms, percent)

Table 3-2 Avista Sector Control Totals, Idaho, 2015
Sector Natural Gas
Use (dekatherms) % of Use
Residential 4,303,387 60%
Commercial 2,456,621 34%
Industrial 455,656 6%
Total 7,215,664 100%

Residential, 60%
Commercial, 34%
Industrial, 6%
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 158 of 829
Residential Sector
Washington Characterization
The total number of households and gas sales for the service territory were obtained from Avista’s actual
sales for 2015. Details, including number of households and 2015 natural gas consumption for the
residential sector in Washington can be found in Table 3-3 below. In 2015, there were over 141,000
households in Avista’s Washington territory that used a total of nearly 9,186,242 dekatherms, resulting in
an average use per household of 650 therms per year. This is an important number for the calibration
process.
These values represent weather actuals for 2015 and were adjusted within LoadMAP to normal weather
using heating degree day, base 65°F, using data provided by Avista. 2015 was an exceptionally warm year,
which is reflected in lower than average consumption. When adjusting these values for normal weather in
2018, heating consumption increased significantly.
Table 3-3 Residential Sector Control Totals, Washington, 2015
Segment Households Natural Gas Use
(dekatherms)
Annual Use/Customer
(therms/HH)
Single Family 85,875 6,014,673 700
Multi-Family 7,909 348,896 441
Mobile Home 5,085 299,121 588
Low Income 42,372 2,523,553 596
Total 141,241 9,186,242 650
Figure 3-3 Residential Natural Gas Use by Segment, Washington, 2015

Figure 3-3 shows the distribution of annual natural gas consumption by end use for an average residential
household. Space heating comprises a majority of the load at 75% followed by water heating at 19%.
Miscellaneous loads make up a very small portion of the total load. This is expected for a natural gas
profile as there are very few miscellaneous technologies. One example are natural gas barbecues.
Single Family
66%
Multi-Family
4%
Mobile Home
3%
Low Income
27%
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 159 of 829
Figure 3-4 Residential Natural Gas Use by End Use, Washington, 2015

Avista’s GenPOP survey informed estimates of the saturation of key equipment types, which were used to
distribute usage at the technology and end use level.
Figure 3-4 presents average natural gas intensities by end use and housing type. Single family homes
consume substantially more energy in space heating. This is due to two factors. The first is that single
family homes are larger. The second is that more walls are exposed to the outside environment, compared
to multifamily dwellings with many shared walls. This increases heat transfer, resulting in greater heating
loads. Water heating consumption is higher in single family homes as well. This is due to a greater number
of occupants, which increases the demand for hot water.
Figure 3-5 Residential Energy Intensity by End Use and Segment, Washington, 2015 (Annual
Therms/HH)

Space Heating
75%
Secondary
Heating
3%
Water Heating
19%
Appliances
1%
Miscellaneous
2%
0
100
200
300
400
500
600
700
800
Single Family Multi-Family Mobile Home Low Income Average
Home
therms/
HH
Space Heating
Secondary Heating
Water Heating
Appliances
Miscellaneous
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 160 of 829
The market profile for an average home in the residential sector is presented in Table 3-4 below. An
important step in the profile development process is model calibration. All consumption within an average
home must sum up to the intensity extracted from billing data. This is necessary so estimates of
consumption for a piece of equipment do not exceed the actual usage in a home. Since consumption in
2015 was rather low, the household intensity increased in 2018 when normalizing weather, allowing for
increased consumption in space heating and secondary heating technologies.
Table 3-4 Average Market Profile for the Residential Sector, 2015
End Use Technology Saturation UEC
(therms)
Intensity
(therms/HH)
Usage
(dekatherms)
Space Heating Furnace - Direct Fuel 88.2% 539.7 475.7 6,719,439
Boiler - Direct Fuel 2.3% 634.0 14.3 202,114
Secondary Heating Fireplace 20.9% 102.2 21.4 302,195
Water Heating Water Heater <= 55 gal. 55.8% 211.9 118.3 1,671,454
Water Heater > 55 gal. 0.7% 244.1 1.8 25,481
Appliances Clothes Dryer 5.4% 28.4 1.5 21,782
Stove/Oven 8.5% 57.3 4.9 68,899
Miscellaneous Pool Heater 0.7% 217.7 1.6 22,042
Miscellaneous 100.0% 10.8 10.8 152,837
Total 650.4 9,186,242

Idaho Characterization
Details for the residential sector in Idaho can be found in Table 3-5 below. In 2015, there were over 70,000
households in Avista’s Washington territory that used a total of nearly 4,303,387 dekatherms, resulting in
an average use per household of 611 therms per year. This is an important number for the calibration
process.
Table 3-5 Residential Sector Control Totals, Idaho, 2015
Segment Households Natural Gas Use
(dekatherms)
Annual Use/Customer
(therms/HH)
Single Family 42,852 2,813,132 656
Multi-Family 3,454 142,782 413
Mobile Home 3,172 174,973 552
Low Income 21,003 1,172,501 558
Total 70,481 4,303,387 611
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 161 of 829
Figure 3-6 Residential Natural Gas Use by Segment, Idaho, 2015

Figure 3-7 shows the distribution of annual natural gas consumption by end use for an average residential
household. Space heating comprises a majority of the load at 76% followed by water heating at 18%.
Miscellaneous loads make up a very small portion of the total load, as expected.
Figure 3-7 Residential Natural Gas Use by End Use, Idaho, 2015

Avista’s 2013 GenPOP survey informed estimates of the saturation of key equipment types, which were
used to distribute usage at the technology and end use level.
Figure 3-8 presents average natural gas intensities by end use and housing type. Single family homes
consume substantially more energy in space heating. Water heating consumption is higher in single family
homes as well, due to a greater number of occupants, which increases the demand for hot water.
Single Family
66%
Multi-Family
4%
Mobile Home
3%
Low Income
27%
Space Heating
76%
Secondary
Heating
4%
Water Heating
18%
Appliances
1%
Miscellaneous
1%
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 162 of 829
Figure 3-8 Residential Energy Intensity by End Use and Segment, Idaho, 2015 (Annual Therms/HH)

The market profile for an average home in the residential sector is presented in Table 3-6 below. An
important step in the profile development process is model calibration. All consumption within an average
home must sum up to the intensity extracted from billing data. This is necessary so estimates of
consumption for a piece of equipment do not exceed the actual usage in a home. Since consumption in
2015 was rather low, the household intensity increased in 2018 when normalizing weather, allowing for
increased consumption in space heating and secondary heating technologies.
Table 3-6 Average Market Profile for the Residential Sector, 2015
End Use Technology Saturation UEC
(therms)
Intensity
(therms/HH)
Usage
(dekatherms)
Space Heating Furnace - Direct Fuel 84.2% 537.1 452.0 3,185,558
Boiler - Direct Fuel 2.0% 633.6 12.9 91,149
Secondary Heating Fireplace 21.5% 102.0 21.9 154,505
Water Heating Water Heater <= 55 gal. 53.6% 202.0 108.2 762,884
Water Heater > 55 gal. 0.7% 231.9 1.7 11,736
Appliances Clothes Dryer 5.3% 30.0 1.6 11,099
Stove/Oven 9.2% 60.1 5.5 39,043
Miscellaneous Pool Heater 0.3% 217.7 0.6 4,139
Miscellaneous 100.0% 6.1 6.1 43,274
Total 610.6 4,303,387

0
100
200
300
400
500
600
700
Single Family Multi-Family Mobile Home Low Income Average
Home
therms/
HH
Space Heating
Secondary Heating
Water Heating
Appliances
Miscellaneous
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 163 of 829
Commercial Sector
Washington Characterization
The total number of nonresidential accounts and natural gas sales for the Washington service territory
were obtained from Avista’s customer account database.
AEG first separated the Commercial accounts from Industrial by analyzing the SIC codes and rate codes
assigned in the company’s billing system. Prior to using the data, AEG inspected individual accounts to
confirm proper assignment. This was done on the top accounts within each segment, but also via spot
checks when reviewing the database. Energy use from accounts where the customer type could not be
identified were distributed proportionally to all C&I segments.
Once the billing data was analyzed, the final segment control totals were derived by distributing the total
2015 nonresidential load to the sectors and segments according to the proportions in the billing data.
Table 3-7 below shows the final allocation of energy to each segment in the commercial sector, as well as
the energy intensity on a square-foot basis. Intensities for each segment were derived from a combination
of the 2014 CBSA and equipment saturations extracted from Avista’s database. The CBSA intensities
corresponded to spaces with lower natural gas saturations than Avista’s database, so AEG increased
intensities proportionally based on the additional presence of natural gas-consuming equipment.
Table 3-7 Commercial Sector Control Totals, Washington, 2015
Segment Description
Intensity
(therms/Sq
Ft)
2015 Natural Gas
Use (dekatherms)
Office Traditional office-based businesses including finance,
insurance, law, government buildings, etc.
0.66 671,012
Restaurant Sit-down, fast food, coffee shop, food service, etc. 4.97 345,789
Retail Department stores, services, boutiques, strip malls etc. 0.92 796,535
Grocery Supermarkets, convenience stores, market, etc. 1.26 233,347
School Day care, pre-school, elementary, secondary schools 0.40 201,308
College College, university, trade schools, etc. 0.84 197,890
Health Health practitioner office, hospital, urgent care centers, etc. 1.12 436,875
Lodging Hotel, motel, bed and breakfast, etc. 0.94 272,792
Warehouse Large storage facility, refrigerated/unrefrigerated warehouse 0.75 431,752
Miscellaneous
Catchall for buildings not included in other segments,
includes churches, recreational facilities, public assembly,
correctional facilities, etc.
1.55 2,147,459
Total 1.04 5,734,759
Figure 3-9 shows each segments’ natural gas consumption as a percentage of the entire commercial sector
energy consumption. The three segments with the highest natural gas usage in 2015 are miscellaneous,
retail, and office, in descending order. As expected, the highest intensity segment is restaurant. This is
based on the high presence of food preparation equipment.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 164 of 829
Figure 3-9 Commercial Natural Gas Use by Segment, Washington, 2015

Figure 3-10 shows the distribution of natural gas consumption by end use for the entire commercial sector.
Space heating is the largest end use, followed closely by food preparation and water heating. The
miscellaneous end use is quite small, as expected.
Figure 3-10 Commercial Sector Natural Gas Use by End Use, Washington, 2015

Figure 3-11 presents average natural gas intensities by end use and segment.
Office
12%
Restaurant
6%
Retail
14%
Grocery
4%
School
3%
College
3%Health
8%
Lodging
5%
Warehouse
8%
Miscellaneous
37%
Space Heating
65%
Water Heating
21%
Food
Preparation
12%
Miscellaneous
2%
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 165 of 829
Figure 3-11 Commercial Energy Usage Intensity by End Use and Segment, Washington, 2015 (Annual
Therms/Sq. Ft)

The total market profile for an average building in the commercial sector is presented in Table 3-8 below.
Avista customer account data informed the market profile by providing information on saturation of key
equipment types. Secondary data was used to develop estimates of energy intensity and square footage
and to fill in saturations for any equipment types not included in the database.
Table 3-8 Average Market Profile for the Commercial Sector, Washington, 2015
End Use Technology Saturation
EUI
(therms/
Sq Ft)
Intensity
(therms/
Sq Ft)
Usage
(dekatherms)
Heating
Furnace 54.3% 0.53 0.29 1,573,937
Boiler 33.1% 1.00 0.33 1,828,292
Unit Heater 4.7% 1.05 0.05 269,875
Water Heating Water Heater 68.7% 0.33 0.22 1,240,105
Food Preparation
Oven 11.3% 0.08 0.01 49,632
Conveyor Oven 5.6% 0.14 0.01 42,462
Double Rack Oven 5.6% 0.21 0.01 64,508
Fryer 7.3% 0.35 0.03 139,571
Broiler 12.2% 0.21 0.03 140,173
Griddle 16.4% 0.14 0.02 128,889
Range 17.9% 0.13 0.02 133,059
Steamer 2.1% 0.12 0.00 13,790
Commercial Food Prep Other 0.2% 0.03 0.00 315
Miscellaneous Pool Heater 0.9% 0.01 0.00 288
Miscellaneous 100.0% 0.02 0.02 109,864
Total 1.04 5,734,759

- 0.50 1.00 1.50 2.00
Average Building
Miscellaneous
Warehouse
Lodging
Health
College
School
Grocery
Retail
Office
therms/Sq Ft
- 1.00 2.00 3.00 4.00 5.00 6.00
Restaurant
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 166 of 829
Idaho Characterization
The total number of nonresidential accounts and natural gas sales for the Idaho service territory were
obtained from Avista’s customer account database.
Table 3-9 below shows the final allocation of energy to each segment in the commercial sector, as well as
the energy intensity on a square-foot basis. Intensities for each segment were derived from a combination
of the 2014 CBSA and equipment saturations extracted from Avista’s database. The CBSA intensities
corresponded to spaces with lower natural gas saturations than Avista’s database, so AEG increased
intensities proportionally based on the additional presence of natural gas-consuming equipment.
Table 3-9 Commercial Sector Control Totals, Idaho, 2015
Segment Description
Intensity
(therms/Sq
Ft)
2015 Natural Gas
Use (dekatherms)
Office Traditional office-based businesses including finance,
insurance, law, government buildings, etc.
0.65 255,885
Restaurant Sit-down, fast food, coffee shop, food service, etc. 4.91 58,036
Retail Department stores, services, boutiques, strip malls etc. 0.91 445,571
Grocery Supermarkets, convenience stores, market, etc. 1.24 97,394
School Day care, pre-school, elementary, secondary schools 0.45 203,476
College College, university, trade schools, etc. 0.83 175,787
Health Health practitioner office, hospital, urgent care centers, etc. 1.10 162,097
Lodging Hotel, motel, bed and breakfast, etc. 0.92 113,194
Warehouse Large storage facility, refrigerated/unrefrigerated warehouse 0.74 189,375
Miscellaneous
Catchall for buildings not included in other segments,
includes churches, recreational facilities, public assembly,
correctional facilities, etc.
1.53 755,805
Total 0.93 2,456,621
Figure 3-12 shows each segments’ natural gas consumption as a percentage of the entire commercial
sector energy consumption. The four segments with the highest natural gas usage in 2015 are
miscellaneous, retail, office, and warehouse, in descending order. As expected, the highest intensity
segment is restaurant. This is based on the high presence of food preparation equipment.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 167 of 829
Figure 3-12 Commercial Natural Gas Use by Segment, Idaho, 2015

Figure 3-13 shows the distribution of natural gas consumption by end use for the entire commercial sector.
Space heating is the largest end use, followed closely by food preparation and water heating. The
miscellaneous end use is quite small, as expected.
Figure 3-13 Commercial Sector Natural Gas Use by End Use, Idaho, 2015

Figure 3-14 presents average natural gas intensities by end use and segment.
Office
10%
Restaurant
2%
Retail
18%
Grocery
4%
School
8%College
7%
Health
7%
Lodging
5%
Warehouse
8%
Miscellaneous
31%
Space Heating
66%
Water Heating
22%
Food
Preparation
10%
Miscellaneous
2%
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 168 of 829
Figure 3-14 Commercial Energy Usage Intensity by End Use and Segment, Idaho, 2015 (Annual
Therms/Sq. Ft)

The total market profile for an average building in the commercial sector is presented in Table 3-10 below.
Avista customer account data informed the market profile by providing information on saturation of key
equipment types. Secondary data was used to develop estimates of energy intensity and square footage
and to fill in saturations for any equipment types not included in the database.
Table 3-10 Average Market Profile for the Commercial Sector, Idaho, 2015
End Use Technology Saturation
EUI
(therms/
Sq Ft)
Intensity
(therms/
Sq Ft)
Usage
(dekatherms)
Heating
Furnace 51.2% 0.51 0.26 694,580
Boiler 36.0% 0.83 0.30 792,880
Unit Heater 4.9% 1.00 0.05 130,092
Water Heating Water Heater 69.3% 0.30 0.20 543,424
Food Preparation
Oven 12.3% 0.07 0.01 21,431
Conveyor Oven 6.1% 0.11 0.01 18,335
Double Rack Oven 6.1% 0.17 0.01 27,854
Fryer 7.8% 0.20 0.02 41,753
Broiler 13.9% 0.12 0.02 44,973
Griddle 16.4% 0.10 0.02 41,389
Range 18.4% 0.09 0.02 44,283
Steamer 2.9% 0.08 0.00 6,105
Commercial Food Prep Other 0.1% 0.03 0.00 95
Miscellaneous Pool Heater 0.8% 0.01 0.00 128
Miscellaneous 100.0% 0.02 0.02 49,298
Total 0.93 2,456,621

- 0.50 1.00 1.50 2.00
Average Building
Miscellaneous
Warehouse
Lodging
Health
College
School
Grocery
Retail
Office
therms/Sq Ft
- 1.00 2.00 3.00 4.00 5.00 6.00
Restaurant
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 169 of 829
Industrial Sector
Washington Characterization
The total sum of natural gas used in 2015 by Avista’s Washington industrial customers was 20,341
dekatherms. Like in the commercial sector, customer account data was used to allocate usage among
segments. Energy intensity was derived from AEG’s Energy Market Profiles database. Most industrial
measures are installed through custom programs, where the unit of measure is not as necessary to
estimate potential.
Table 3-11 Industrial Sector Control Totals, Washington, 2015
Segment Intensity (therms/sq ft) Natural Gas Usage
(dekatherms)
Washington Industrial 0.75 268,452
Figure 3-15 shows the distribution of annual natural gas consumption by end use for all industrial
customers. Two major sources were used to develop this consumption profile. The first was AEG’s analysis
of warehouse usage as part of the commercial sector. We begin with this prototype as a starting point to
represent non-process loads. We then added in process loads using our Energy Market Profiles database,
which summarizes usage by end use and process type. Accordingly, process is the largest overall end use
for the industrial sector, accounting for 87% of energy use. Heating is the second largest end use, and
miscellaneous, non-process industrial uses round out consumption.
Figure 3-15 Industrial Natural Gas Use by End Use, Washington, 2015

Table 3-12 shows the composite market profile for the industrial sector. Process cooling is very small and
represents niche technologies such as gas-driven absorption chillers.
Space Heating
6%
Process
87%
Miscellaneous
7%
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 170 of 829
Table 3-12 Average Natural Gas Market Profile for the Industrial Sector, Washington, 2015
End Use Technology Saturation
EUI
(therms/
sq ft)
Intensity
(therms/
Sq ft)
Usage
(dekatherms)
Heating
Furnace 65.3% 0.04 0.02 8,832
Boiler 3.2% 0.12 0.00 1,371
Unit Heater 23.1% 0.08 0.02 6,490
Process
Process Boiler 100.0% 0.37 0.37 131,596
Process Heating 100.0% 0.28 0.28 100,538
Process Cooling 100.0% 0.00 0.00 407
Other Process 100.0% 0.00 0.00 1,580
Miscellaneous Miscellaneous 100.0% 0.05 0.05 17,638
Total 0.75 268,452
Idaho Characterization
The total sum of natural gas used in 2015 by Avista’s Idaho industrial customers was 20,341 dekatherms.
Number of employees is calculated by dividing total usage by intensity. For the industrial sector, the unit
of measure chosen is employment.
Table 3-13 Industrial Sector Control Totals, Idaho, 2015
Segment Intensity (therms/sq ft) Natural Gas Usage
(dekatherms)
Idaho Industrial 0.72 187,203
Figure 3-16 shows the distribution of annual natural gas consumption by end use for all industrial
customers. Two major sources were used to develop this consumption profile. The first was AEG’s analysis
of warehouse usage as part of the commercial sector. We begin with this prototype as a starting point to
represent non-process loads. We then added in process loads using our Energy Market Profiles database,
which summarizes usage by end use and process type. Accordingly, process is the largest overall end use
for the industrial sector, accounting for 87% of energy use. Heating is the second largest end use, and
miscellaneous, non-process industrial uses round out consumption.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 171 of 829
Figure 3-16 Industrial Natural Gas Use by End Use, Idaho, 2015

Table 3-14 shows the composite market profile for the industrial sector. Process cooling is very small and
represents technologies such as gas-driven absorption chillers.
Table 3-14 Average Natural Gas Market Profile for the Industrial Sector, Washington, 2015
End Use Technology Saturation
EUI
(therms/
sq ft)
Intensity
(therms/
Sq ft)
Usage
(dekatherms)
Heating
Furnace 65.3% 0.04 0.02 6,159
Boiler 3.2% 0.12 0.00 956
Unit Heater 23.1% 0.08 0.02 4,526
Process
Process Boiler 100.0% 0.35 0.35 91,768
Process Heating 100.0% 0.27 0.27 70,109
Process Cooling 100.0% 0.00 0.00 284
Other Process 100.0% 0.00 0.00 1,102
Miscellaneous Miscellaneous 100.0% 0.05 0.05 12,299
Total 0.72 187,203

Space Heating
6%
Process
87%
Miscellaneous
7%
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 172 of 829
4
BASELINE PROJECTION
Prior to developing estimates of energy conservation potential, we developed a baseline end-use
projection to quantify what the consumption is likely to be in the future in absence of any energy
conservation programs. The savings from past programs are embedded in the forecast, but the baseline
projection assumes that those past programs cease to exist in the future. Thus, the potential analysis
captures all possible savings from future programs.
The baseline projection incorporates assumptions about:
 2015 energy consumption based on the market profiles
 Customer population growth
 Appliance/equipment standards and building codes already mandated
 Appliance/equipment purchase decisions
 Avista’s customer forecast
 Trends in fuel shares and appliance saturations and assumptions about miscellaneous natural gas
growth
Although it aligns closely, the baseline projection is not Avista’s official load forecast. Rather it was
developed as an integral component of our modeling construct to serve as the metric against which
energy conservation potentials are measured. This chapter presents the baseline projections we developed
for this study. Below, we present the baseline projections for each sector, which include projections of
annual use in dekatherms. We also present a summary across all sectors.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 173 of 829
Overall Baseline Projection
Washington Projection
Table 4-1 and Figure 4-1 provide a summary of the baseline projection for annual use by sector for the
Avista’s Washington service territory. The large spike between 2015 and 2017 is due to the adjustment
from 2015 actual weather to 2017 actual weather (which was a colder year).
Overall, the forecast shows modest growth in natural gas consumption, driven by the residential and
commercial sectors
Table 4-1 Baseline Projection Summary by Sector, Washington, Selected Years (dekatherms)
Sector 2018 2019 2022 2028 2038 % Change
('18-'38)
Avg.
Growth
Residential 10,773,426 10,971,347 11,416,777 11,959,820 12,706,478 17.9% 0.8%
Commercial 6,197,173 6,197,918 6,219,237 6,325,464 6,578,501 6.2% 0.3%
Industrial 251,300 248,912 242,536 232,346 213,968 -14.9% -0.8%
Total 17,221,900 17,418,177 17,878,550 18,517,630 19,498,948 13.2% 0.6%
Figure 4-1 Baseline Projection Summary by Sector, Washington (dekatherms)

-
5,000,000
10,000,000
15,000,000
20,000,000
25,000,000
2015 2018 2021 2024 2027 2030 2033 2036
Dth
Residential Commercial Industrial Avista Forecast
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 174 of 829
Idaho Projection
Table 4-2 and Figure 4-2 provide a summary of the baseline projection for annual use by sector for Avista’s
Idaho service territory. The large spike between 2015 and 2017 is due to the adjustment from 2015 actual
weather to 2017 actual weather (which was a colder year and very similar to normal weather).
Overall, the forecast shows modest growth in natural gas consumption, driven roughly equally by the
residential sector. We compare change and growth rates starting in 2018 since that is the first year with
weather-normal assumptions.
Table 4-2 Baseline Projection Summary by Sector, Idaho, Selected Years (dekatherms)
Sector 2018 2019 2022 2028 2038 % Change
('18-'38)
Avg.
Growth
Residential 5,266,179 5,379,047 5,674,999 6,039,699 6,534,309 24.1% 1.1%
Commercial 3,050,738 3,045,031 3,039,479 3,067,352 3,197,949 4.8% 0.2%
Industrial 240,261 243,071 244,254 244,959 242,820 1.1% 0.1%
Total 8,557,178 8,667,149 8,958,733 9,352,011 9,975,077 16.6% 0.8%
Figure 4-2 Baseline Projection Summary by Sector, Idaho (dekatherms)

-
2,000,000
4,000,000
6,000,000
8,000,000
10,000,000
12,000,000
2015 2018 2021 2024 2027 2030 2033 2036
Dth
Residential Commercial Industrial Avista Forecast
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 175 of 829
Residential Sector
Washington Projection
Table 4-3 and Figure 4-3 present the baseline projection for natural gas at the end-use level for the
residential sector, as a whole. Overall, residential use increases from 10,773,426 dekatherms in 2018 to
12,706,478 dekatherms in 2038, an increase of 17.9%. There are two high-level factors affecting growth.
The first is a moderate increase in number of households and customers. The second is a decrease in
equipment consumption due to future standards and naturally occurring efficiency improvements (notably
the AFUE upcoming 92% furnace standard). We model gas-fired fireplaces as secondary heating. These
consume energy and may heat a space but are rarely relied on to be a primary heating technology. As
such, they are estimated to be more aesthetic and less weather-dependent. This end use grows faster than
others since new homes are more likely to install a unit, increasing fireplace stock. Miscellaneous is a very
small end use in natural gas studies and includes technologies with low penetration, such as gas
barbeques.
Table 4-3 Residential Baseline Projection by End Use, Washington (dekatherms)
End Use 2018 2019 2022 2028 2038
%
Change
('18-'38)
Avg.
Growth
Space Heating 8,412,059 8,564,268 8,896,876 9,234,926 9,676,794 15.0% 0.7%
Secondary Heating 338,235 344,941 361,556 391,980 438,702 29.7% 1.3%
Water Heating 1,749,711 1,783,530 1,867,034 2,018,550 2,241,383 28.1% 1.2%
Appliances 92,925 94,541 98,400 105,246 115,574 24.4% 1.1%
Miscellaneous 180,496 184,066 192,912 209,119 234,024 29.7% 1.3%
Total 10,773,426 10,971,347 11,416,777 11,959,820 12,706,478 17.9% 0.8%
Figure 4-3 Residential Baseline Projection by End Use, Washington (dekatherms)

Heating
Miscellaneous
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 176 of 829
Idaho Projection
Table 4-4 and Figure 4-4 present the baseline projection for natural gas at the end-use level for the
residential sector, as a whole. Overall, residential use increases from 5,266,179 dekatherms in 2018 to
6,534,309 dekatherms in 2038, an increase of 24.1%.
Table 4-4 Residential Baseline Projection by End Use, Idaho (dekatherms)
End Use 2018 2019 2022 2028 2038 % Change
('18-'38)
Avg.
Growth
Space Heating 4,155,191 4,246,597 4,489,608 4,758,176 5,109,973 23.0% 1.0%
Secondary Heating 179,236 182,789 191,594 207,716 232,475 29.7% 1.3%
Water Heating 827,802 843,793 883,269 954,888 1,060,196 28.1% 1.2%
Appliances 53,227 54,141 56,314 60,149 65,893 23.8% 1.1%
Miscellaneous 50,723 51,727 54,214 58,771 65,772 29.7% 1.3%
Total 5,266,179 5,379,047 5,674,999 6,039,699 6,534,309 24.1% 1.1%
Figure 4-4 Residential Baseline Projection by End Use, Idaho (dekatherms)

-
1,000,000
2,000,000
3,000,000
4,000,000
5,000,000
6,000,000
7,000,000
8,000,000
2015 2017 2019 2021 2023 2025 2027 2029 2031 2033 2035 2037
Dth
Space Heating
Secondary
Heating
Water Heating
Appliances
Miscellaneous
Avista Forecast
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 177 of 829
Commercial Sector
Washington Projection
Annual natural gas use in the commercial sector grows 24.7% during the overall forecast horizon, starting
at 6,197,173 dekatherms in 2018, and increasing to 6,578,501 dekatherms in 2038. Table 4-5 and Figure 4-5
present the baseline projection at the end-use level for the commercial sector, as a whole. Similar to the
residential sector, market size is increasing and usage per square foot is decreasing slightly. The weather
normalization between 2015 and 2018 is also readily apparent in both AEG’s projection and Avista’s official
load forecast.
Table 4-5 Commercial Baseline Projection by End Use, Washington (dekatherms)
End Use 2018 2019 2022 2028 2038
%
Change
('18-'38)
Avg.
Growth
Heating 4,196,574 4,199,252 4,221,488 4,305,032 4,481,443 6.8% 0.3%
Water Heating 1,179,697 1,171,006 1,149,673 1,133,956 1,159,165 -1.7% -0.1%
Food Preparation 710,971 716,824 734,505 767,813 812,434 14.3% 0.7%
Miscellaneous 109,932 110,837 113,571 118,662 125,460 14.1% 0.7%
Total 6,197,173 6,197,918 6,219,237 6,325,464 6,578,501 6.2% 0.3%
Figure 4-5 Commercial Baseline Projection by End Use, Washington (dekatherms)

-
1,000,000
2,000,000
3,000,000
4,000,000
5,000,000
6,000,000
7,000,000
8,000,000
2015 2017 2019 2021 2023 2025 2027 2029 2031 2033 2035 2037
Dth
Space Heating
Water Heating
Food Preparation
Miscellaneous
Avista Forecast
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 178 of 829
Idaho Projection
Annual natural gas use in the commercial sector grows 24.7% during the overall forecast horizon, starting
at 3,050,738 dekatherms in 2018, and increasing to 3,197,949 dekatherms in 2038. Table 4-6 and Figure
4-6 present the baseline projection at the end-use level for the commercial sector, as a whole. Similar to
the residential sector, market size is increasing and usage per square foot is decreasing slightly. The
weather normalization between 2015 and 2018 is also readily apparent in both AEG’s projection and
Avista’s official load forecast.
Table 4-6 Commercial Baseline Projection by End Use, Idaho (dekatherms)
End Use 2018 2019 2022 2028 2038
%
Change
('18-'38)
Avg.
Growth
Heating 2,119,893 2,117,464 2,118,692 2,145,398 2,239,540 5.6% 0.3%
Water Heating 592,484 587,087 573,650 561,613 575,786 -2.8% -0.1%
Food Preparation 281,793 283,558 289,103 300,130 318,742 13.1% 0.6%
Miscellaneous 56,568 56,922 58,035 60,210 63,881 12.9% 0.6%
Total 3,050,738 3,045,031 3,039,479 3,067,352 3,197,949 4.8% 0.2%
Figure 4-6 Commercial Baseline Projection by End Use, Idaho (dekatherms)

-
500,000
1,000,000
1,500,000
2,000,000
2,500,000
3,000,000
3,500,000
4,000,000
2015 2017 2019 2021 2023 2025 2027 2029 2031 2033 2035 2037
Dth
Space Heating
Water Heating
Food Preparation
Miscellaneous
Avista Forecast
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 179 of 829
Industrial Sector
Washington Projection
Industrial sector usage increases throughout the planning horizon. Table 4-7 and Figure 4-7 present the
projection at the end-use level. Overall, industrial annual natural gas use decreases from 251,300
dekatherms in 2018 to 213,968 dekatherms in 2038. Growth in most end uses is consistent at around -1.0%
per year but impacts of naturally occurring efficiency lowers consumption in the space heating end use.
We applied a much smaller weather normalization factor for the industrial heating end use since
consumption is so heavily dominated by motors and process and a correlation to such small consumption
values is much lower.
Table 4-7 Industrial Baseline Projection by End Use, Washington (dekatherms)
End Use 2018 2019 2022 2028 2038 % Change
('18-'38)
Avg.
Growth
Heating 17,879 17,630 16,968 15,966 14,528 -18.7% -1.0%
Process 217,068 215,079 209,766 201,221 185,468 -14.6% -0.8%
Miscellaneous 16,353 16,203 15,803 15,159 13,972 -14.6% -0.8%
Total 251,300 248,912 242,536 232,346 213,968 -14.9% -0.8%
Figure 4-7 Industrial Baseline Projection by End Use, Washington (dekatherms)

-
50,000
100,000
150,000
200,000
250,000
300,000
350,000
2015 2017 2019 2021 2023 2025 2027 2029 2031 2033 2035 2037
Dth
Space Heating
Process
Miscellaneous
Avista Forecast
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 180 of 829
Idaho Projection
Industrial sector usage increases throughout the planning horizon. Table 4-8 and Figure 4-8 present the
projection at the end-use level. Overall, industrial annual natural gas use increases from 21,822 dekatherms
in 2018 to 28,137 dekatherms in 2038. We applied a much smaller weather normalization factor for the
industrial heating end use since consumption is so heavily dominated by motors and process and a
correlation to such small consumption values is much lower.
Table 4-8 Industrial Baseline Projection by End Use, Idaho (dekatherms)
End Use 2018 2019 2022 2028 2038 % Change
('18-'38)
Avg.
Growth
Heating 17,094 17,200 17,058 16,806 16,475 -3.6% -0.2%
Process 207,533 210,047 211,279 212,169 210,488 1.4% 0.1%
Miscellaneous 15,635 15,824 15,917 15,984 15,857 1.4% 0.1%
Total 240,261 243,071 244,254 244,959 242,820 1.1% 0.1%
Figure 4-8 Industrial Baseline Projection by End Use, Idaho (dekatherms)

-
50,000
100,000
150,000
200,000
250,000
300,000
2015 2017 2019 2021 2023 2025 2027 2029 2031 2033 2035 2037
Dth
Space Heating
Process
Miscellaneous
Avista Forecast
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 181 of 829
5
OVERALL ENERGY EFFICIENCY POTENTIAL
This chapter presents the measure-level energy conservation potential across all sectors for Avista’s
Washington and Idaho territories. This includes every possible measure that is considered in the measure
list, regardless of program implementation concerns. Year-by-year savings for annual energy usage are
available in the LoadMAP model and measure assumption summary, which were provided to Avista at the
conclusion of the study. Please note that all savings are provided at the customer site. This section includes
potential from the residential, commercial, and industrial analyses.
Overall Energy Efficiency Potential
Washington Potential
Table 5-1 and Figure 5-1 summarize the energy conservation savings in terms of annual energy use for all
measures for four levels of potential relative to the baseline projection. Figure 5-2 displays the energy
conservation forecasts. Savings are represented in cumulative terms, which reflect the effects of persistent
savings in prior years in addition to new savings. This allows for the reporting of annual savings impacts
as they actually impact each year of the forecast.
 Technical Potential reflects the adoption of all conservation measures regardless of cost-
effectiveness. In this potential case, efficient equipment makes up all lost opportunity installations and
all retrofit measures are installed, regardless of achievability. 2018 first-year savings are 217,202
dekatherms, or 1.3% of the baseline projection. Cumulative savings in 2028 are 3,251,362 dekatherms,
or 17.6% of the baseline. By 2038, cumulative savings reach 5,804,041 dekatherms, or 29.8% of the
baseline. Technical potential is useful as a theoretical construct, applying an upper bound to the
potential that may be realized in any one year. Other levels of potential are based off this level which
makes it an important component in the estimation of potential.
 Achievable Technical Potential refines technical potential by applying customer participation
rates that account for market barriers, customer awareness and attitudes, program maturity, and other
factors that affect market penetration of conservation measures. For the 2018-2038 CPA, ramp rates
from the Seventh Power Plan were customized for use in natural gas programs and applied. Since the
Seventh Plan does not assign ramp rates for the majority natural gas measures, we assigned these
based on similar electric technologies present in the Plan as a starting point. These ramp rates may
be found in Appendix B. 2018 first-year net savings are 86,389 dekatherms, or 0.5% of the baseline
projection. Cumulative net savings in 2028 are 2,405,890 dekatherms, or 13.0% of the baseline. By
2038 cumulative savings reach 4,901,043 dekatherms, or 25.1% of the baseline.
 UCT Achievable Economic Potential further refines achievable technical potential by applying
an economic cost-effectiveness screen. In this analysis, the cost-effectiveness is measured by the utility
cost test (UCT), which compares lifetime energy benefits to the total utility costs of delivering the
measure through a utility program, excluding monetized non-energy impacts. Avoided costs of energy
were provided by Avista. 2018 first-year savings are 61,279 dekatherms, or 0.4% of the baseline
projection. Cumulative savings in 2028 are 1,916,441 dekatherms, or 10.3% of the baseline. By 2038
cumulative savings reach 4,139,016 dekatherms, or 21.2% of the baseline.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 182 of 829
 TRC Achievable Economic Potential further refines achievable technical potential by applying an
economic cost-effectiveness screen. In this analysis, the cost-effectiveness is measured by the total
resource cost (TRC) test, which compares lifetime energy benefits to the total customer and utility
costs of delivering the measure through a utility program, including monetized non-energy impacts.
AEG also applied benefits for non-gas energy savings, such as electric HVAC savings for
weatherization and lighting savings for retrocommissioning. We also applied the Council’s calibration
credit to space heating savings to reflect the fact that additional fuels may be used as a supplemental
heat source within an average home and may be accounted for within the TRC. Avoided costs of
energy were provided by Avista. A 10% conservation credit was applied to these costs per the Council
methodologies. 2018 first-year savings are 33,893 dekatherms, or 0.2% of the baseline projection.
Cumulative net savings in 2028 are 1,297,679 dekatherms, or 7.0% of the baseline. By 2038 cumulative
savings reach 2,420,649 dekatherms, or 12.4% of the baseline. Potential under the TRC test is lower
than UCT due to the inclusion of full measure costs rather than the utility portion. For most measures,
these far outweigh the quantified and monetized non-energy impacts included in the TRC.
Table 5-1 Summary of Energy Efficiency Potential, Washington (dekatherms)
Scenario 2018 2019 2022 2028 2038
Baseline Projection (Dth) 17,221,900 17,418,177 17,878,550 18,517,630 19,498,948
Cumulative Savings (Dth)
UCT Achievable Economic Potential 61,279 133,576 500,422 1,916,441 4,139,016
TRC Achievable Economic Potential 33,893 73,100 276,379 1,297,679 2,420,649
Achievable Technical Potential 86,389 186,065 655,389 2,405,890 4,901,043
Technical Potential 217,202 434,037 1,189,331 3,251,362 5,804,041
Cumulative Savings (% of Baseline)
UCT Achievable Economic Potential 0.4% 0.8% 2.8% 10.3% 21.2%
TRC Achievable Economic Potential 0.2% 0.4% 1.5% 7.0% 12.4%
Achievable Technical Potential 0.5% 1.1% 3.7% 13.0% 25.1%
Technical Potential 1.3% 2.5% 6.7% 17.6% 29.8%

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 183 of 829
Figure 5-1 Summary of Energy Efficiency Potential as % of Baseline Projection, Washington
(dekatherms)

Figure 5-2 Baseline Projection and Energy Efficiency Forecasts, Washington (dekatherms)

Figure 5-3 shows the cumulative UCT achievable potential by sector for the full timeframe of the analysis
as percent of total. Table 5-2 summarizes UCT achievable potential by market sector for selected years.
While the residential and commercial sectors represent the lion’s share of the overall potential in the early
years, by the mid-2020s, the residential sector share grows to a significant majority of savings potential.
Since industrial consumption is such a low percentage of the baseline once ineligible customers have been
excluded, potential for this sector makes up a lower percentage of the total. While residential and
commercial potential ramps up, industrial potential is mainly retrofit in nature, and is much flatter. This is
because process equipment is highly custom and most potential comes from controls modifications or
process adjustments rather than high-efficiency equipment upgrades. Additionally, we model
retrocommissioning to phase in evenly over the next twenty years. This measure has a maintenance
0
1,000,000
2,000,000
3,000,000
4,000,000
5,000,000
6,000,000
7,000,000
2018 2019 2022 2028 2038
Dth
UCT Achievable Economic TRC Achievable Economic Achievable Technical Technical
-
5,000,000
10,000,000
15,000,000
20,000,000
25,000,000
2017 2019 2021 2023 2025 2027 2029 2031 2033 2035 2037
Dth
Baseline Forecast
Achievable Economic TRC Potential
Achievable Economic UCT Potential
Achievable Technical Potential
Technical Potential
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 184 of 829
component, and not all existing facilities may be old enough to require the tune-up immediately but will
be eligible at some point over the course of the study.
There is a notable downtick in residential savings around 2024. This is due to the impacts of the residential
forced-air furnace standard, which raises the baseline from AFUE 80% to AFUE 92%, which is a substantial
increase when the efficient option is an AFUE 95% unit.
Figure 5-3 Cumulative UCT Achievable Economic Potential by Sector, Washington (% of Total)

Table 5-2 Cumulative UCT Achievable Economic Potential by Sector, Washington, Selected Years
(dekatherms)
Sector 2018 2019 2022 2028 2038
Residential 39,979 88,051 345,801 1,362,078 3,107,847
Commercial 20,731 44,393 151,733 547,834 1,021,211
Industrial 569 1,132 2,887 6,528 9,957
Total 61,279 133,576 500,422 1,916,441 4,139,016

0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2018 2022 2026 2030 2034 2038
Share off
Total
Savings
Residential Commercial Industrial
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 185 of 829
Idaho Potential
Table 5-3 and Figure 5-4 summarize the energy conservation savings in terms of annual energy use for
all measures for four levels of potential relative to the baseline projection. Figure 5-5 displays the energy
conservation forecasts. Savings are represented in cumulative terms, which reflect the effects of persistent
savings in prior years in addition to new savings. This allows for the reporting of annual savings impacts
as they actually impact each year of the forecast.
 Technical Potential first-year savings in 2018 are 103,071 dekatherms, or 1.2% of the baseline
projection. Cumulative savings in 2028 are 1,660,809 dekatherms, or 17.8% of the baseline. By 2038,
cumulative savings reach 2,993,151 dekatherms, or 30.0% of the baseline.
 Achievable Technical Potential first-year net savings are 37,324 dekatherms, or 0.4% of the
baseline projection. Cumulative net savings in 2028 are 1,218,944 dekatherms, or 13.0% of the baseline.
By 2038 cumulative savings reach 2,514,049 dekatherms, or 25.2% of the baseline.
 UCT Achievable Economic Potential first-year savings are 26,340 dekatherms, or 0.3% of the
baseline projection. Cumulative savings in 2028 are 965,825 dekatherms, or 10.3% of the baseline. By
2038 cumulative savings reach 2,107,684 dekatherms, or 21.1% of the baseline.
 TRC Achievable Economic Potential first-year savings are 9,846 dekatherms, or 0.1% of the
baseline projection. Cumulative net savings in 2028 are 635,250 dekatherms, or 6.8% of the baseline.
By 2038 cumulative savings reach 1,204,809 dekatherms, or 12.1% of the baseline. Potential under the
TRC test is lower than UCT due to the inclusion of full measure costs rather than the utility portion.
For most measures, these far outweigh the quantified and monetized non-energy impacts included
in the TRC.
Table 5-3 Summary of Energy Efficiency Potential, Idaho (dekatherms)
Scenario 2018 2019 2022 2028 2038
Baseline Projection (Dth) 8,557,178 8,667,149 8,958,733 9,352,011 9,975,077
Cumulative Savings (Dth)
UCT Achievable Economic Potential 26,340 58,352 235,414 965,825 2,107,684
TRC Achievable Economic Potential 9,846 22,432 108,249 635,250 1,204,809
Achievable Technical Potential 37,324 81,526 310,222 1,218,944 2,514,049
Technical Potential 103,071 206,214 582,638 1,660,809 2,993,151
Cumulative Savings (% of Baseline)
UCT Achievable Economic Potential 0.3% 0.7% 2.6% 10.3% 21.1%
TRC Achievable Economic Potential 0.1% 0.3% 1.2% 6.8% 12.1%
Achievable Technical Potential 0.4% 0.9% 3.5% 13.0% 25.2%
Technical Potential 1.2% 2.4% 6.5% 17.8% 30.0%

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 186 of 829
Figure 5-4 Summary of Energy Efficiency Potential as % of Baseline Projection, Idaho (dekatherms)

Figure 5-5 Summary of Energy Efficiency Potential as % of Baseline Projection, Idaho (dekatherms)

Figure 5-6 shows the cumulative UCT achievable potential by sector for the full timeframe of the analysis
as percent of total. Table 5-4 summarizes UCT achievable potential by market sector for selected years.
.
0
500,000
1,000,000
1,500,000
2,000,000
2,500,000
3,000,000
3,500,000
2018 2019 2022 2028 2038
Dth
UCT Achievable Economic TRC Achievable Economic Achievable Technical Technical
-
2,000,000
4,000,000
6,000,000
8,000,000
10,000,000
12,000,000
2017 2019 2021 2023 2025 2027 2029 2031 2033 2035 2037
Dth
Baseline Forecast
Achievable Economic TRC Potential
Achievable Economic UCT Potential
Achievable Technical Potential
Technical Potential
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 187 of 829
Figure 5-6 Cumulative UCT Achievable Economic Potential by Sector, Idaho (% of Total)

Table 5-4 Cumulative UCT Achievable Economic Potential by Sector, Idaho, Selected Years
(dekatherms)
Sector 2018 2019 2022 2028 2038
Residential 18,354 41,176 174,333 720,226 1,615,844
Commercial 7,417 16,035 58,160 239,015 481,888
Industrial 569 1,140 2,922 6,584 9,952
Total 26,340 58,352 235,414 965,825 2,107,684

0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2018 2022 2026 2030 2034 2038
Share off
Total
Savings
Residential Commercial Industrial
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 188 of 829
6
SECTOR-LEVEL ENERGY EFFICIENCY POTENTIAL
The previous section provided a summary of potential for the Avista territory at the state level. In this
section, we provide details for each sector.
Residential Sector
Washington Potential
Table 6-1 and Figure 6-1 summarize the energy efficiency potential for the residential sector. In 2018, UCT
achievable economic potential is 39,979 dekatherms, or 0.4% of the baseline projection. By 2028,
cumulative savings are 1,362,078 dekatherms, or 11.4% of the baseline.
Table 6-1 Residential Energy Conservation Potential Summary, Washington (dekatherms)
Scenario 2018 2019 2022 2028 2038
Baseline Forecast (Dth) 10,773,426 10,971,347 11,416,777 11,959,820 12,706,478
Cumulative Savings (Dth)
UCT Achievable Economic Potential 39,979 88,051 345,801 1,362,078 3,107,847
TRC Achievable Economic Potential 14,920 32,308 139,361 824,953 1,573,939
Achievable Technical Potential 49,298 108,161 412,455 1,653,830 3,604,150
Technical Potential 137,252 272,444 753,898 2,170,218 4,226,558
Energy Savings (% of Baseline)
UCT Achievable Economic Potential 0.4% 0.8% 3.0% 11.4% 24.5%
TRC Achievable Economic Potential 0.1% 0.3% 1.2% 6.9% 12.4%
Achievable Technical Potential 0.5% 1.0% 3.6% 13.8% 28.4%
Technical Potential 1.3% 2.5% 6.6% 18.1% 33.3%
Figure 6-1 Residential Energy Conservation by Case, Washington (dekatherms)

0
500,000
1,000,000
1,500,000
2,000,000
2,500,000
3,000,000
3,500,000
4,000,000
4,500,000
2018 2019 2022 2028 2038
Dth
UCT Achievable Economic TRC Achievable Economic Achievable Technical Technical
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 189 of 829
Figure 6-2 presents forecasts of energy savings by end use as a percent of total annual savings and
cumulative savings. Space heating makes up a majority of potential but declines slightly in the early to
mid-2020s due to the future furnace standard.
Figure 6-2 Residential UCT Achievable Economic Potential – Cumulative Savings by End Use,
Washington (dekatherms, % of total)

-
500,000
1,000,000
1,500,000
2,000,000
2,500,000
3,000,000
3,500,000
2017 2019 2021 2023 2025 2027 2029 2031 2033 2035
Dth
Space Heating
Secondary Heating
Water Heating
Appliances
Miscellaneous
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2017 2019 2021 2023 2025 2027 2029 2031 2033 2035
Share of
Savings
Space Heating
Secondary Heating
Water Heating
Appliances
Miscellaneous
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 190 of 829
Table 6-2 identifies the top 20 residential measures by cumulative 2018 and 2019 savings. Furnaces,
windows, tankless water heaters, and learning thermostats are the top measures.
Table 6-2 Residential Top Measures in 2018 and 2019, UCT Achievable Economic Potential,
Washington (dekatherms)
Rank Measure / Technology
2018 Cumulative
Potential Savings
(dekatherms)
% of
Total
2019 Cumulative
Potential Savings
(dekatherms)
% of
Total
1 Furnace - Direct Fuel - AFUE 95% 19,091 48% 41,449 47%
2 Windows - High Efficiency - Double
Pane LowE CL22 9,426 24% 18,788 21%
3 Water Heater <= 55 gal. - Instantaneous
- ENERGY STAR (UEF 0.87) 4,193 10% 10,186 12%
4 Thermostat - Wi-Fi/Interactive -
Interactive/learning thermostat (ie,
NEST)
1,344 3% 3,094 4%
5 Insulation - Floor/Crawlspace - R-30 1,132 3% 2,818 3%
6 Insulation - Ceiling, Installation - R-38
(Retro only) 734 2% 1,672 2%
7 Boiler - Direct Fuel - AFUE 96% 619 2% 1,321 2%
8 Insulation - Wall Cavity, Installation - R-
11 572 1% 1,424 2%
9 Insulation - Ducting - duct thermal
losses reduced 50% 367 1% 914 1%
10 Water Heater - Low Flow Showerhead
(1.5 GPM) - 1.5 GPM showerhead 365 1% 921 1%
11 Water Heater - Faucet Aerators - 1.5
GPM faucet 349 1% 805 1%
12 Insulation - Ceiling, Upgrade - R-49 339 1% 772 1%
13 Insulation - Basement Sidewall - R-15 332 1% 827 1%
14 ENERGY STAR Homes - Built Green spec
(NC Only) 294 1% 982 1%
15 Water Heater - Low Flow Showerhead
(2.0 GPM) - 2.0 GPM showerhead 210 1% 529 1%
16 Water Heater - Pipe Insulation -
Insulated 5' of pipe between unit and
conditioned space
190 0% 438 0%
17 ENERGY STAR Clothes Washers -
ENERGY STAR unit 175 0% 530 1%
18 Water Heater - Thermostatic Shower
Restriction Valve - Restrictor installed,
shutting off water when it is warm
149 0% 343 0%
19 Water Heater > 55 gal. - Instantaneous -
ENERGY STAR (UEF 0.87) 63 0% 154 0%
20 Thermostat - Programmable -
Programmed thermostat 29 0% 68 0%
Subtotal 39,974 100% 88,037 100%
Total Savings in Year 39,979 100% 88,051 100%
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 191 of 829
Idaho Potential
Table 6-3 and Figure 6-3 summarize the energy efficiency potential for the residential sector. In 2018, UCT
achievable economic potential is 18,354 dekatherms, or 0.3% of the baseline projection. By 2028,
cumulative savings are 720,226 dekatherms, or 11.9% of the baseline.
Table 6-3 Residential Energy Conservation Potential Summary, Idaho (dekatherms)
Scenario 2018 2019 2022 2028 2038
Baseline Forecast (Dth) 5,266,179 5,379,047 5,674,999 6,039,699 6,534,309
Cumulative Savings (Dth)
UCT Achievable Economic Potential 18,354 41,176 174,333 720,226 1,615,844
TRC Achievable Economic Potential 3,744 9,243 62,156 458,445 833,329
Achievable Technical Potential 21,723 48,708 205,345 871,461 1,876,450
Technical Potential 65,563 130,317 376,364 1,132,377 2,199,415
Energy Savings (% of Baseline)
UCT Achievable Economic Potential 0.3% 0.8% 3.1% 11.9% 24.7%
TRC Achievable Economic Potential 0.1% 0.2% 1.1% 7.6% 12.8%
Achievable Technical Potential 0.4% 0.9% 3.6% 14.4% 28.7%
Technical Potential 1.2% 2.4% 6.6% 18.7% 33.7%

Figure 6-3 Residential Energy Conservation by Case, Idaho (dekatherms)

0
500,000
1,000,000
1,500,000
2,000,000
2,500,000
2018 2019 2022 2028 2038
Dth
UCT Achievable Economic TRC Achievable Economic Achievable Technical Technical
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 192 of 829
Figure 6-4 presents forecasts of energy savings by end use as a percent of total annual savings and
cumulative savings. Space heating makes up a majority of potential but declines slightly in the early to
mid-2020s due to the future furnace standard.
Figure 6-4 Residential UCT Achievable Economic Potential – Cumulative Savings by End Use, Idaho
(dekatherms, % of total)

Table 6-4 identifies the top 20 residential measures by cumulative 2018 and 2019 savings. Furnaces,
tankless water heaters, windows, and insulation are the top measures.

-
200,000
400,000
600,000
800,000
1,000,000
1,200,000
1,400,000
1,600,000
1,800,000
2017 2019 2021 2023 2025 2027 2029 2031 2033 2035
Dth
Space Heating
Secondary Heating
Water Heating
Appliances
Miscellaneous
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2017 2019 2021 2023 2025 2027 2029 2031 2033 2035
Share of
Savings
Space Heating
Secondary Heating
Water Heating
Appliances
Miscellaneous
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 193 of 829
Table 6-4 Residential Top Measures in 2018 and 2019, UCT Achievable Economic Potential, Idaho
(dekatherms)
Rank Measure / Technology
2018 Cumulative
Potential Savings
(dekatherms)
% of
Total
2019 Cumulative
Potential Savings
(dekatherms)
% of
Total
1 Furnace - Direct Fuel - AFUE 95% 11,816 64% 25,295 61%
2 Water Heater <= 55 gal. - Instantaneous
- ENERGY STAR (UEF 0.87) 1,983 11% 4,818 12%
3 Windows - High Efficiency - Double
Pane LowE CL22 820 4% 2,044 5%
4 Insulation - Floor/Crawlspace - R-30 772 4% 1,925 5%
5 Thermostat - Wi-Fi/Interactive -
Interactive/learning thermostat (ie,
NEST)
664 4% 1,529
4%
6 Insulation - Ceiling, Installation - R-38
(Retro only) 365 2% 833 2%
7 Boiler - Direct Fuel - AFUE 96% 307 2% 653 2%
8 Insulation - Wall Cavity, Installation - R-
11 285 2% 711 2%
9 Water Heater - Low Flow Showerhead
(1.5 GPM) - 1.5 GPM showerhead 182 1% 458 1%
10 Insulation - Ducting - duct thermal
losses reduced 50% 181 1% 450 1%
11 Water Heater - Faucet Aerators - 1.5
GPM faucet 174 1% 401 1%
12 Insulation - Ceiling, Upgrade - R-49 168 1% 383 1%
13 Insulation - Basement Sidewall - R-15 166 1% 415 1%
14 ENERGY STAR Homes - Built Green spec
(NC Only) 146 1% 486 1%
15 Water Heater - Low Flow Showerhead
(2.0 GPM) - 2.0 GPM showerhead 104 1% 263 1%
16 Water Heater - Pipe Insulation -
Insulated 5' of pipe between unit and
conditioned space
100 1% 230
1%
17 Water Heater - Thermostatic Shower
Restriction Valve - Restrictor installed,
shutting off water when it is warm
74 0% 171
0%
18 Water Heater > 55 gal. - Instantaneous -
ENERGY STAR (UEF 0.87) 30 0% 73 0%
19 Thermostat - Programmable -
Programmed thermostat 14 0% 33 0%
20 Insulation - Slab Foundation - R-11 (NC
Only) 2 0% 5 0%
Subtotal 18,354 100% 41,175 100%
Total Savings in Year 18,354 100% 41,176 100%

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 194 of 829
Commercial Sector
Washington Potential
Table 6-5 and Figure 6-5 summarize the energy conservation potential for the commercial sector. In 2018,
UCT achievable economic potential is 20,731 dekatherms, or 0.3% of the baseline projection. By 2028,
cumulative savings are 547,834 dekatherms, or 8.7% of the baseline.
Table 6-5 Commercial Energy Conservation Potential Summary, Washington
Scenario 2018 2019 2022 2028 2038
Baseline Forecast (dekatherms) 6,197,173 6,197,918 6,219,237 6,325,464 6,578,501
Cumulative Savings (dekatherms)
UCT Achievable Economic Potential 20,731 44,393 151,733 547,834 1,021,211
TRC Achievable Economic Potential 18,376 39,603 134,004 465,827 836,014
Achievable Technical Potential 36,328 76,386 239,042 743,027 1,283,162
Technical Potential 78,948 159,629 430,505 1,070,109 1,561,295
Energy Savings (% of Baseline)
UCT Achievable Economic Potential 0.3% 0.7% 2.4% 8.7% 15.5%
TRC Achievable Economic Potential 0.3% 0.6% 2.2% 7.4% 12.7%
Achievable Technical Potential 0.6% 1.2% 3.8% 11.7% 19.5%
Technical Potential 1.3% 2.6% 6.9% 16.9% 23.7%
Figure 6-5 Commercial Energy Conservation by Case, Washington (dekatherms)

0
200,000
400,000
600,000
800,000
1,000,000
1,200,000
1,400,000
1,600,000
1,800,000
2018 2019 2022 2028 2038
Thousand
Therms
UCT Achievable Economic TRC Achievable Economic Achievable Technical Technical
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 195 of 829
Figure 6-6 presents forecasts of energy savings by end use as a percent of total annual savings and
cumulative savings. Space heating makes up a majority of the potential early, but food preparation
equipment upgrades provide substantial savings opportunities in the later years.
Figure 6-6 Commercial UCT Achievable Economic Potential – Cumulative Savings by End Use,
Washington (dekatherms, % of total)

Table 6-6 identifies the top 20 commercial measures by cumulative savings in 2018 and 2019. Boilers are
the top measure, food preparation and custom HVAC measures. Retrocommissioning potential is present
in the top measures but is a smaller contributor due to revised savings assumptions. RCx in the commercial
sector is a restoration of HVAC systems to their original, or better, conditions.
-
200,000
400,000
600,000
800,000
1,000,000
1,200,000
2017 2019 2021 2023 2025 2027 2029 2031 2033 2035
Dth
Space Heating
Water Heating
Food Preparation
Miscellaneous
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2017 2019 2021 2023 2025 2027 2029 2031 2033 2035
Share of
Savings
Space Heating
Water Heating
Food Preparation
Miscellaneous
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 196 of 829
Table 6-6 Commercial Top Measures in 2018 and 2019, UCT Achievable Economic Potential,
Washington (dekatherms)
Rank Measure / Technology
2018 Cumulative
Potential Savings
(dekatherms)
% of
Total
2019 Cumulative
Potential Savings
(dekatherms)
% of
Total
1 Boiler - AFUE 97% 6,337 31% 13,775 31%
2 Fryer - ENERGY STAR 1,775 9% 3,653 8%
3
Gas Boiler - Insulate Steam
Lines/Condensate Tank - Lines and
condensate tank insulated
1,152 6% 2,262 5%
4 Gas Boiler - Hot Water Reset - Reset
control installed 1,123 5% 2,333 5%
5 HVAC - Demand Controlled Ventilation -
DCV enabled 1,033 5% 2,027 5%
6 Insulation - Roof/Ceiling - R-38 850 4% 2,079 5%
7 Water Heater - TE 0.94 838 4% 2,001 5%
8 Steam Trap Maintenance - Cleaning and
maintenance 820 4% 1,620 4%
9 Gas Boiler - Insulate Hot Water Lines -
Insulated water lines 770 4% 1,512 3%
10 Insulation - Wall Cavity - R-21 761 4% 1,862 4%
11 Retrocommissioning - HVAC - Optimized
HVAC flow and controls 661 3% 1,298 3%
12 Water Heater - Central Controls -
Central water boiler controls installed 573 3% 1,137 3%
13 Gas Boiler - High Turndown - Turndown
control installed 526 3% 1,091 2%
14
Strategic Energy Management - Energy
management system installed and
programmed
412 2% 820 2%
15 Double Rack Oven - FTSC Qualified
(>50% Cooking Efficiency) 405 2% 836 2%
16 Kitchen Hood - DCV/MUA - DCV/HUA
vent hood 329 2% 656 1%
17 Oven - ENERGY STAR (>42% Baking
Efficiency) 311 2% 669 2%
18
Building Automation System -
Automation system installed and
programmed
307 1% 765 2%
19 Gas Boiler - Stack Economizer -
Economizer installed 282 1% 593 1%
20 Water Heater - Faucet Aerator - 1.5
GPM faucet 219 1% 453 1%
Subtotal 19,485 94% 41,442 93%
Total Savings in Year 20,731 100% 44,393 100%

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 197 of 829
Idaho Potential
Table 6-7 and Figure 6-7 summarize the energy conservation potential for the commercial sector. In 2018,
UCT achievable economic potential is 7,417 dekatherms, or 0.2% of the baseline projection. By 2028,
cumulative savings are 239,015 dekatherms, or 7.8% of the baseline.
Table 6-7 Commercial Energy Conservation Potential Summary, Idaho
Scenario 2018 2019 2022 2028 2038
Baseline Forecast (dekatherms) 3,050,738 3,045,031 3,039,479 3,067,352 3,197,949
Cumulative Savings (dekatherms)
UCT Achievable Economic Potential 7,417 16,035 58,160 239,015 481,888
TRC Achievable Economic Potential 5,529 12,039 43,123 169,784 360,683
Achievable Technical Potential 14,871 31,349 101,064 338,527 623,867
Technical Potential 36,549 73,959 201,366 517,401 777,530
Energy Savings (% of Baseline)
UCT Achievable Economic Potential 0.2% 0.5% 1.9% 7.8% 15.1%
TRC Achievable Economic Potential 0.2% 0.4% 1.4% 5.5% 11.3%
Achievable Technical Potential 0.5% 1.0% 3.3% 11.0% 19.5%
Technical Potential 1.2% 2.4% 6.6% 16.9% 24.3%
Figure 6-7 Commercial Energy Conservation by Case, Idaho (dekatherms)

Figure 6-8 presents forecasts of energy savings by end use as a percent of total annual savings and
cumulative savings. Space heating makes up a majority of the potential early, but food preparation
equipment upgrades provide substantial savings opportunities in the later years.
0
100,000
200,000
300,000
400,000
500,000
600,000
700,000
800,000
900,000
2018 2019 2022 2028 2038
Thousand
Therms
UCT Achievable Economic TRC Achievable Economic Achievable Technical Technical
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 198 of 829
Figure 6-8 Commercial UCT Achievable Economic Potential – Cumulative Savings by End Use, Idaho
(dekatherms, % of total)

Table 6-8 identifies the top 20 commercial measures by cumulative savings in 2018 and 2019. Boilers are
the top measure, followed by custom HVAC measures and food preparation. Retrocommissioning
potential is present in the top measures but is a smaller contributor due to revised savings assumptions.
RCx in the commercial sector is a restoration of HVAC systems to their original, or better, conditions.
-
100,000
200,000
300,000
400,000
500,000
600,000
2017 2019 2021 2023 2025 2027 2029 2031 2033 2035
Dth
Space Heating
Water Heating
Food Preparation
Miscellaneous
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2017 2019 2021 2023 2025 2027 2029 2031 2033 2035
Share of
Savings
Space Heating
Water Heating
Food Preparation
Miscellaneous
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 199 of 829
Table 6-8 Commercial Top Measures in 2018 and 2019, UCT Achievable Economic Potential, Idaho
(dekatherms)
Rank Measure / Technology
2018 Cumulative
Potential Savings
(dekatherms)
% of
Total
2019 Cumulative
Potential Savings
(dekatherms)
% of
Total
1 Boiler - AFUE 97% 1,511 20% 3,456 22%
2
Gas Boiler - Insulate Steam
Lines/Condensate Tank - Lines and
condensate tank insulated
681 9% 1,339 8%
3 Fryer - ENERGY STAR 593 8% 1,220 8%
4 HVAC - Demand Controlled Ventilation -
DCV enabled 580 8% 1,139 7%
5 Insulation - Roof/Ceiling - R-38 478 6% 1,171 7%
6 Gas Boiler - Insulate Hot Water Lines -
Insulated water lines 456 6% 895 6%
7 Insulation - Wall Cavity - R-21 416 6% 1,019 6%
8 Steam Trap Maintenance - Cleaning and
maintenance 407 5% 805 5%
9 Retrocommissioning - HVAC - Optimized
HVAC flow and controls 266 4% 523 3%
10
Strategic Energy Management - Energy
management system installed and
programmed
265 4% 527 3%
11 Water Heater - TE 0.94 198 3% 505 3%
12 Double Rack Oven - FTSC Qualified
(>50% Cooking Efficiency) 196 3% 405 3%
13 Kitchen Hood - DCV/MUA - DCV/HUA
vent hood 193 3% 384 2%
14 Thermostat - Programmable -
Programmable thermostat installed 189 3% 370 2%
15
Building Automation System -
Automation system installed and
programmed
159 2% 396 2%
16 Oven - ENERGY STAR (>42% Baking
Efficiency) 149 2% 321 2%
17 Water Heater - Central Controls -
Central water boiler controls installed 91 1% 190 1%
18 Gas Boiler - Maintenance - General
cleaning and maintenance 76 1% 151 1%
19 Gas Boiler - Hot Water Reset - Reset
control installed 73 1% 163 1%
20 Gas Furnace - Maintenance - General
cleaning and maintenance 67 1% 132 1%
Subtotal 7,043 95% 15,111 94%
Total Savings in Year 7,417 100% 16,035 100%

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 200 of 829
Industrial Sector
Washington Potential
Table 6-9 and Figure 6-9 summarize the energy conservation potential for the core industrial sector. In
2018, UCT achievable economic potential is 569dekatherms, or 0.2% of the baseline projection. By 2028,
cumulative savings reach 6,528 dekatherms, or 2.8% of the baseline. Industrial potential is a lower
percentage of overall baseline compared to the residential and commercial sectors. While large, custom
process optimization and controls measures are present in potential, these are not applicable to all
processes which limits potential at the technical level. Additionally, since the largest customers were
excluded from this analysis due to their status as transport-only customers making them ineligible to
participate in energy efficiency programs for the utility, the remaining customers are smaller and tend to
have lower process end-use shares, further lowering industrial potential. As seen in the figure below,
industrial potential is substantially lower due to the smaller sector size and process uses.
Table 6-9 Industrial Energy Conservation Potential Summary, Washington (dekatherms)
Scenario 2018 2019 2022 2028 2038
Baseline Forecast (dekatherms) 251,300 248,912 247,616 232,346 213,968
Cumulative Savings (dekatherms)
UCT Achievable Economic Potential 569 1,132 1,709 6,528 9,957
TRC Achievable Economic Potential 597 1,188 1,785 6,899 10,696
Achievable Technical Potential 762 1,518 2,288 9,034 13,731
Technical Potential 1,002 1,964 2,942 11,035 16,187
Energy Savings (% of Baseline)
UCT Achievable Economic Potential 0.2% 0.5% 0.7% 2.8% 4.7%
TRC Achievable Economic Potential 0.2% 0.5% 0.7% 3.0% 5.0%
Achievable Technical Potential 0.3% 0.6% 0.9% 3.9% 6.4%
Technical Potential 0.4% 0.8% 1.2% 4.7% 7.6%
Figure 6-9 Industrial Energy Conservation Potential, Washington (dekatherms)

0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
18,000
2018 2019 2020 2028 2038
Dth
UCT Achievable Economic TRC Achievable Economic Achievable Technical Technical
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 201 of 829
Figure 6-10 presents forecasts of energy savings by end use as a percent of total annual savings and
cumulative savings.
Figure 6-10 Industrial UCT Achievable Economic Potential – Cumulative Savings by End Use,
Washington (dekatherms, % of total)

Table 6-10 identifies the top 20 industrial measures by cumulative 2018 and 2019 savings. Strategic energy
management and retrocommissioning are top measures in the industrial sector. Strategic energy
management of industrial process applications is the highest measure by total savings. For smaller
industrial customers, this measure typically involves a cohort of between five to ten customers who form
a working group facilitated by an energy management expert. One or more employees at each facility are
designated an energy conservation “champion” who work to integrate efficient energy-consuming
behavior into the company’s culture. Many of these measures are more custom in nature, such as strategic
energy management and retrocommissioning. These results in behavior-based and low-cost/no-cost
measures but result in larger custom projects. We estimate that this potential will be captured within these
measures/delivery mechanisms.
-
2,000
4,000
6,000
8,000
10,000
12,000
2017 2019 2021 2023 2025 2027 2029 2031 2033 2035
Dth
Space Heating
Process
Miscellaneous
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2017 2019 2021 2023 2025 2027 2029 2031 2033 2035
Share of
Savings
Space Heating
Process
Miscellaneous
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 202 of 829

Table 6-10 Industrial Top Measures in 2018 and 2019, UCT Achievable Economic Potential,
Washington (dekatherms)
Rank Measure / Technology
2018 Cumulative
Potential Savings
(dekatherms)
% of
Total
2019 Cumulative
Potential Savings
(dekatherms)
% of
Total
1
Strategic Energy Management - Energy
management system installed and
programmed
191 34% 380 34%
2 Retrocommissioning - Optimized
process design and controls 129 23% 255 23%
3 Gas Boiler - High Turndown - Turndown
control installed 82 14% 162 14%
4 Gas Boiler - Hot Water Reset - Reset
control installed 68 12% 142 12%
5 Steam Trap Maintenance - Cleaning and
maintenance 49 9% 97 9%
6 Gas Boiler - Maintenance - General
cleaning and maintenance 41 7% 76 7%
7
Gas Boiler - Burner Control
Optimization - Optimized burner
controls
4 1% 9 1%
8 Gas Furnace - Maintenance - General
cleaning and maintenance 3 1% 6 1%
9 Unit Heater - Infrared Radiant 2 0% 4 0%
10 Boiler - AFUE 97% 1 0% 3 0%
11 Furnace - AFUE 96% 0 0% 0 0%
12 Insulation - Roof/Ceiling - R-38 0 0% 0 0%
13 Insulation - Wall Cavity - R-21 0 0% 0 0%
14 Insulation - Ducting - 50% reduction in
thermal losses 0 0% 0 0%
15 HVAC - Duct Repair and Sealing - 30%
reduced duct leaking 0 0% 0 0%
16 Windows - High Efficiency - U-.22 or
better 0 0% 0 0%
17 HVAC - Demand Controlled Ventilation -
DCV enabled 0 0% 0 0%
18 Gas Boiler - Stack Economizer -
Economizer installed 0 0% 0 0%
Subtotal 569 100% 1,132 100%
Total Savings in Year 569 100% 1,132 100%

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 203 of 829
Idaho Potential
Table 6-11 and Figure 6-11 summarize the energy conservation potential for the core industrial sector. In
2018, UCT achievable economic potential is 569 dekatherms, or 0.2% of the baseline projection. By 2028,
cumulative savings reach 6,584 dekatherms, or 2.7% of the baseline. Industrial potential is a lower
percentage of overall baseline compared to the residential and commercial sectors. While large, custom
process optimization and controls measures are present in potential, these are not applicable to all
processes which limits potential at the technical level. Additionally, since the largest customers were
excluded from this analysis due to their status as transport-only customers making them ineligible to
participate in energy efficiency programs for the utility, the remaining customers are smaller and tend to
have lower process end-use shares, further lowering industrial potential. As seen in the figure below,
industrial potential is substantially lower due to the smaller sector size and process uses.
Table 6-11 Industrial Energy Conservation Potential Summary, Idaho (dekatherms)
Scenario 2018 2019 2022 2028 2038
Baseline Forecast (dekatherms) 240,261 243,071 244,930 244,959 242,820
Cumulative Savings (dekatherms)
UCT Achievable Economic Potential 569 1,140 1,718 6,584 9,952
TRC Achievable Economic Potential 573 1,150 1,738 7,021 10,797
Achievable Technical Potential 730 1,469 2,225 8,956 13,732
Technical Potential 959 1,939 2,921 11,030 16,205
Energy Savings (% of Baseline)
UCT Achievable Economic Potential 0.2% 0.5% 0.7% 2.7% 4.1%
TRC Achievable Economic Potential 0.2% 0.5% 0.7% 2.9% 4.4%
Achievable Technical Potential 0.3% 0.6% 0.9% 3.7% 5.7%
Technical Potential 0.4% 0.8% 1.2% 4.5% 6.7%
Figure 6-11 Industrial Energy Conservation Potential, Idaho (dekatherms)

Figure 6-12 presents forecasts of energy savings by end use as a percent of total annual savings and
cumulative savings.
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
18,000
2018 2019 2020 2028 2038
Dth
UCT Achievable Economic TRC Achievable Economic Achievable Technical Technical
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 204 of 829
Figure 6-12 Industrial UCT Achievable Economic Potential – Cumulative Savings by End Use, Idaho
(dekatherms, % of total)

Table 6-12 identifies the top 20 industrial measures by cumulative 2018 and 2019 savings. Strategic energy
management and retrocommissioning are top measures in the industrial sector. Strategic energy
management of industrial process applications is the highest measure by total savings. For smaller
industrial customers, this measure typically involves a cohort of between five to ten customers who form
a working group facilitated by an energy management expert. One or more employees at each facility are
designated an energy conservation “champion” who work to integrate efficient energy-consuming
behavior into the company’s culture. Many of these measures are more custom in nature, such as strategic
energy management and retrocommissioning. These results in behavior-based and low-cost/no-cost
measures but result in larger custom projects. We estimate that this potential will be captured within these
measures/delivery mechanisms.

-
2,000
4,000
6,000
8,000
10,000
12,000
2017 2019 2021 2023 2025 2027 2029 2031 2033 2035
Dth
Space Heating
Process
Miscellaneous
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2017 2019 2021 2023 2025 2027 2029 2031 2033 2035
Share of
Savings
Space Heating
Process
Miscellaneous
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 205 of 829
Table 6-12 Industrial Top Measures in 2018 and 2019, UCT Achievable Economic Potential, Idaho
(dekatherms)
Rank Measure / Technology
2018 Cumulative
Potential Savings
(dekatherms)
% of
Total
2019 Cumulative
Potential Savings
(dekatherms)
% of
Total
1
Strategic Energy Management - Energy
management system installed and
programmed
197 35% 397 35%
2 Retrocommissioning - Optimized
process design and controls 123 22% 244 21%
3 Gas Boiler - High Turndown - Turndown
control installed 78 14% 154 14%
4 Gas Boiler - Hot Water Reset - Reset
control installed 65 11% 135 12%
5 Steam Trap Maintenance - Cleaning and
maintenance 47 8% 94 8%
6 Gas Boiler - Maintenance - General
cleaning and maintenance 39 7% 72 6%
7 Retrocommissioning - Optimized HVAC
flow and controls 10 2% 20 2%
8
Gas Boiler - Burner Control
Optimization - Optimized burner
controls
4 1% 9 1%
9 Gas Furnace - Maintenance - General
cleaning and maintenance 3 1% 5 0%
10 Unit Heater - Infrared Radiant 2 0% 6 0%
11 Boiler - AFUE 97% 1 0% 3 0%
12 Furnace - AFUE 96% 0 0% 0 0%
13 Insulation - Roof/Ceiling - R-38 0 0% 0 0%
14 Insulation - Wall Cavity - R-21 0 0% 0 0%
15 Insulation - Ducting - 50% reduction in
thermal losses 0 0% 0 0%
16 HVAC - Duct Repair and Sealing - 30%
reduced duct leaking 0 0% 0 0%
17 Windows - High Efficiency - U-.22 or
better 0 0% 0 0%
18 HVAC - Demand Controlled Ventilation -
DCV enabled 0 0% 0 0%
Subtotal 569 100% 1,140 100%
Total Savings in Year 569 100% 1,140 100%

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 206 of 829
Incorporating the Total Resource Cost Test
In addition to the UCT, LoadMAP has been configured to evaluate potential using the TRC. This test focuses
on impacts for both the utility and customer, which is an alternative frame of reference from the UCT. The
TRC includes the full measure cost (incremental for lost opportunities, full cost for retrofits), which is
generally substantially higher than the incentive cost included within the UCT. The TRC does include one
additional value stream that the UCT does not, non-energy impacts. This test is fully incorporated into
LoadMAP and prepared for Avista to use in the event the Company feels a “fully balanced” TRC is
identified.
In accordance with Council methodology, these impacts must be quantified and monetized, meaning
impacts such as personal comfort, which are difficult to assign a value to, are not included. What this does
include are additional savings including water reductions due to low-flow measures or reduced detergent
requirements to wash clothes in a high-efficiency clothes washer. AEG has incorporated these impacts as
they are available in source documentation, such as RTF UES workbooks.
Some impacts are already included within Avista’s avoided costs. These include the 10% conservation
credit applied by the Council for infrastructure benefits of efficiency. The future prices of carbon are also
included. Per TRC methodology, as these impacts are already captured within the avoided costs provided
to AEG, we did not incorporate them a second time outside the costs.
Another set of impacts captured within Council methodology include the Simplified Energy Enthalpy
Model (SEEM) “calibration credits”. The Council calibrates this energy model using metered end-use
energy consumption to reflect actual conditions. While these are technically energy impacts, they are not
captured as a benefit to a natural-gas utility as they are instead an impact on the customer. The Council
then assumes the difference between the uncalibrated and calibrated models represents the impacts of
secondary heating by different fuels present in the home. In the Council’s case, these could be small gas
heaters or wood stoves present alongside an electric forced-air furnace. For Avista, AEG followed a similar
methodology, but instead applied the calibration percent impact to estimated gas-heating savings rather
than electric. To monetize these impacts, we incorporated the latest Mid C energy prices, including carbon
impacts, from the RTF’s website, adjusted for differences in efficiency between electric and natural gas
heating equipment (e.g. converted therm savings from an AFUE 80% baseline to kWh savings from an EF
0.97 resistance heater baseline). We applied these impacts to many non-equipment measures with space
heating impacts in all sectors as well as to residential space heating equipment, which was the primary
use for the Council.
Finally, AEG identified additional non-gas end uses which may be impacted by gas efficiency measures.
These include impacts from other end uses, such as cooling savings due to efficient shell measures or
lighting savings due to a comprehensive retrocommissioning or strategic energy management program.
Like the calibration credit above, these do not have a benefit to a natural-gas utility but do to the customer.
It is worth a note of caution when incorporating these impacts. Certain comprehensive building measures,
such as retrocommissioning and strategic energy management have very large electric impacts that may
be greater than the original estimated gas impacts. LED lighting is a very popular technology within
electric utility-programs and can have massive impacts. Commercial HVAC retrocommissioning (RCx)
includes both cooling and ventilation electric impacts, which could outweigh the gas space heating
impacts. To realize these cost-effective savings, Avista would need to offer a comprehensive RCx program
affecting both electric and natural gas end uses.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 207 of 829
7
COMPARISON WITH CURRENT PROGRAMS
One of the goals of this study is to inform targets for future programs, including the current calendar-
year, 2018. As such, AEG conducted an in-depth comparison of the CPA’s 2018 UCT Achievable Economic
Potential with Avista’s 2017 accomplishments and 2018 plan at the sector-level. This involved assigning
each measure within the CPA to an existing Avista program. C
Washington Comparison with 2017 Programs and 2018 Plan
Residential Sector
Table 7-1 summarizes Avista’s 2017 residential accomplishments, 2018 plan, and the 2018 UCT Achievable
Economic potential estimates from LoadMAP. The LoadMAP estimate of 39,979 dekatherms is lower than
Avista’s 2017 accomplishments at 62,156 dekatherms and lower than Avista’s 2018 plan at 50,402 therms.
Table 7-1 Comparison of Avista’s Washington Residential Programs with 2018 UCT Achievable
Economic Potential (dekatherms)
Program Group
2017
Accomplishments
(dekatherms)
2018 Plan
(dekatherms)
LoadMAP
2018 UCT
(dekatherms)
Furnace 40,003 28,600 19,091
Boiler 453 0 619
Water Heater 6,621 1,042 4,257
ENERGY STAR Homes 122 365 294
Smart Thermostat 4,884 2,340 1,344
Programmable Thermostat 0 55 0
Ceiling Insulation 540 280 1,072
Wall Insulation 218 240 904
Floor Insulation 66 266 1,135
Doors 40 63 0
Windows 8,911 15,940 9,426
Air Sealing 207 112 0
Duct Insulation 30 144 367
Duct Sealing 48 0 0
Showerheads 0 954 575
Miscellaneous 14 0 893
Program Total 62,156 50,402 39,979
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 208 of 829
The main reason that potential is lower is that the baseline assumed for forced-air furnaces is adjusted in
the following ways.
 The 2015 Washington State Energy Code (WSEC) prescribes very efficient building shell requirements,
which substantially reduces the consumption of a new home. Since every new home requires a lost
opportunity purchasing decision when constructed, they make up a large portion of the potential. The
lower unit energy savings in new homes due to lower heating requirements reduces the unit energy
savings (UES) from this measure.
 Another reason is the incorporation of a market baseline, which assumes not everyone purchases the
minimum federal standard in the absence of efficiency programs. This results in approximately 20%
of customers purchasing an AFUE 90% and 5% purchasing an AFUE 92% in the baseline, which reduces
the average unit energy consumption upon which savings for an AFUE 95% are based,
Additional descriptions for other measure differences are provided below:
 Potential for ENERGY STAR Homes has been reduced due to WSEC 2015. The efficient shell
requirements lower space heating savings from the prior estimate, which was made before this code
went into effect.
Commercial and Industrial Sectors
Table 7-2 summarizes Avista’s 2017 commercial and industrial accomplishments, 2018 plan, and the 2018
UCT Achievable Economic potential estimates from LoadMAP. The LoadMAP estimate of 21,300
dekatherms is very similar to Avista’s 2017 accomplishments at 22,405 dekatherms and 2018 plan at 20,251
dekatherms.
Table 7-2 Comparison of Avista’s Washington Nonresidential Accomplishments with 2018 UCT
Achievable Economic Potential (dekatherms)
Program Group
2017
Accomplishments
(dekatherms)
2018 Plan
(dekatherms)
LoadMAP
2018 UCT
(dekatherms)
HVAC 14,000 3,214 11,925
Weatherization 1,657 2,080 1,694
Appliances 380 0 838
Food Preparation 3,987 4,956 2,761
Custom 2,381 10,000 4,082
Program Total 22,405 20,251 21,300

The following are key drivers in commercial potential:
 The HVAC category includes both efficient equipment (e.g. boilers) as well as custom HVAC measures.
The 2018 Plan includes the latter in the “Custom” category, but 2017 accomplishments imply that these
are realized through the HVAC program group.
 Fryer and convection oven potential is substantial due to the high gas consumption of restaurants
and Avista’s current success with this program. This measure was heavily accelerated in LoadMAP.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 209 of 829
Idaho Comparison with 2017 Programs and 2018 Plan
Residential Sector
Table 7-3 summarizes Avista’s 2017 residential accomplishments, 2018 plan, and the 2018 UCT Achievable
Economic potential estimates from LoadMAP. The LoadMAP estimate of 18,354 dekatherms is very similar
to Avista’s 2017 accomplishments at 18,158 dekatherms and Avista’s 2018 plan at 17,311 therms.
Table 7-3 Comparison of Avista’s Idaho Residential Programs with 2018 UCT Achievable Economic
Potential (dekatherms)
Program Group
2017
Accomplishments
(dekatherms)
2018 Plan
(dekatherms)
LoadMAP
2018 UCT
(dekatherms)
Furnace 12,783 11,716 11,816
Boiler 134 0 307
Water Heater 1,775 2,077 2,014
ENERGY STAR Homes 41 41 146
Smart Thermostat 1,628 1,040 664
Programmable Thermostat 0 0 0
Ceiling Insulation 129 56 534
Wall Insulation 17 102 452
Floor Insulation 29 119 774
Doors 11 19 0
Windows 1,407 1,708 820
Air Sealing 87 48 0
Duct Insulation 56 153 181
Duct Sealing 59 0 0
Showerheads 0 233 286
Miscellaneous 2 0 362
Program Total 18,158 17,311 18,354
Potential for most measures is very similar to both accomplishments and the 2018 plan. In contrast to
Washington, Idaho’s energy code does not cannibalize a large portion of the HVAC-related savings,
resulting in a much steadier range of potential.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 210 of 829
Commercial and Industrial Sectors
Table 7-4 summarizes Avista’s 2017 commercial and industrial accomplishments, 2018 plan, and the 2018
UCT Achievable Economic potential estimates from LoadMAP. The LoadMAP estimate of 7,986 dekatherms
is substantially higher than Avista’s 2017 accomplishments at 3,987 dekatherms but similar to the 2018
plan at 7,336 dekatherms.
Table 7-4 Comparison of Avista’s Idaho Nonresidential Accomplishments with 2018 UCT
Achievable Economic Potential (dekatherms)
Program Group
2017
Accomplishments
(dekatherms)
2018 Plan
(dekatherms)
LoadMAP
2018 UCT
(dekatherms)
HVAC 1,390 805 3,769
Weatherization 874 940 941
Appliances 35 0 198
Food Preparation 1,359 1,490 1,045
Custom 0 4,100 2,033
Program Total 3,657 7,336 7,986

This is due to a “ramp up” period between 2017 and 2018 resulting from a recent-year restart of programs.
Similar to Washington, many custom HVAC measures were included within the HVAC category to reflect
actual accomplishments.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 211 of 829
8
COMPARISON WITH CURRENT PROGRAMS
One of the goals of this study is to inform targets for future programs, including the current calendar-
year, 2018. As such, AEG conducted an in-depth comparison of the CPA’s 2018 UCT Achievable Economic
Potential with Avista’s 2017 accomplishments and 2018 plan at the sector-level. This involved assigning
each measure within the CPA to an existing Avista program. C
Residential Comparison with 2016 CPA
Table 8-1 compares first-year residential potential between Avista’s 2016 and 2018 Natural Gas CPAs
conducted by AEG. In both cases, first-year potential is estimated to be higher.
Table 8-1 Comparison of Avista’s Residential UCT Achievable Economic Potential between the 2016
and 2018 CPAs (dekatherms)
Program Group Washington
2017 2018
Idaho
2017 2018
Furnace 9,524 19,091 3,209 11,816
Boiler 251 619 112 307
Water Heater 718 4,257 254 2,014
ENERGY STAR Homes 0 294 0 146
Smart Thermostat 445 1,344 213 664
Programmable Thermostat 0 0 0 0
Ceiling Insulation 1,218 1,072 577 534
Wall Insulation 0 904 0 452
Floor Insulation 0 1,135 0 774
Doors 0 0 0 0
Windows 8,491 9,426 4,044 820
Air Sealing 0 0 0 0
Duct Insulation 0 367 0 181
Duct Sealing 939 0 0 0
Showerheads 1,627 575 736 286
Miscellaneous 4,387 893 1,992 362
CPA Total 27,598 39,979 11,138 18,354
Increases in potential are due to a few factors:
 The update in ramp rates to Seventh Plan values. Some of these start as high as 40% achievability in
the first year.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 212 of 829
 Due to program accomplishments, particularly in HVAC. AEG accelerated key measures such as
furnace upgrades, to the faster ramp rates to align with program success.
 Measure savings, costs, and/or incentives have been updated for some measures, resulting in
additional cost-effective measures. New measures include ENERGY STAR homes as well as wall and
floor insulation.
Nonresidential Comparison with 2016 CPA
Table 8-2 compares first-year nonresidential potential between Avista’s 2016 and 2018 Natural Gas CPAs
conducted by AEG. In Washington, the potential is similar, while it is lower in Idaho.
Table 8-2 Comparison of Avista’s Nonresidential UCT Achievable Economic Potential between the
2016 and 2018 CPAs (dekatherms)
Program Group Washington
2017 2018
Idaho
2017 2018
HVAC 8,065 11,925 3,400 3,769
Weatherization 1,636 1,694 540 941
Appliances 953 838 453 198
Food Preparation 577 2,761 228 1,045
Custom 12,130 4,082 4,997 2,033
CPA Total 23,362 21,300 9,618 7,986
In addition to changes in ramp rates, differences in potential are due to a few factors:
 HVAC potential is similar to the previous study but accelerated slightly.
 Food preparation potential has been heavily accelerated.
 Potential has been lowered in the “Custom” category for both states due the revisions in the
commercial retrocommissioning savings assumptions. The Seventh Plan assumed a 15% heating
energy savings from commercial retrocommissioning programs. When AEG inspected this assumption
further, we discovered that the conversion from an assumption of 5% of building use was being
converted using a heating percentage of use of roughly 33%, much lower than AEG’s market
characterization analysis. By applying an Avista-specific conversion, AEG calculated a savings of closer
to 7% of heating use.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 213 of 829
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 214 of 829

Applied Energy Group, Inc.
500 Ygnacio Valley Road, Suite 250
Walnut Creek, CA 94596
P: 510.982.3525
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 215 of 829
APPENDIX 3.2: ENVIRONMENTAL EXTERNALITIES OVERVIEW
(OREGON JURISDICTION ONLY)
The methodology for determining avoided costs from reduced incremental natural gas usage considers
commodity and variable transportation costs only. These avoided cost streams do not include environmental
externality costs related to the gathering, transmission, distribution or end-use of natural gas.
Per traditional economic theory and industry practice, an environmental externality factor is typically added
to the avoided cost when there is an opportunity to displace traditional supply-side resources with an
alternative resource with no adverse environmental impact.
REGULATORY GUIDANCE
The Oregon Public Utility Commission (OPUC) issued Order 93-965 (UM-424) to address how utilities
should consider the impact of environmental externalities in planning for future energy resources. The
Order required analysis on the potential natural gas cost impacts from emitting carbon dioxide (CO2) and
nitric-oxide (NOx).
The OPUC’s Order No. 07-002 in Docket UM 1056 (Investigation Into Integrated Resource Planning)
established the following guideline for the treatment of environmental costs used by energy utilities that
evaluate demand-side and supply-side energy choices:
UM 1056, Guideline 8 - Environmental Costs
“Utilities should include, in their base-case analyses, the regulatory compliance costs they expect
for carbon dioxide (CO2), nitrogen oxides (NOx), sulfur oxides (SO2), and mercury (Hg) emissions.
Utilities should analyze the range of potential CO2 regulatory costs in Order No. 93-695, from $0
- $40 (1990$). In addition, utilities should perform sensitivity analysis on a range of reasonably
possible cost adders for nitrogen oxides (NOx), sulfur dioxide (SO2), and mercury (Hg), if
applicable.
In June 2008, the OPUC issued Order 08-338 (UM1302) which revised UM1056, Guideline 8. The revised
guideline requires the utility should construct a base case portfolio to reflect what it considers to be the
most likely regulatory compliance future for the various emissions. Additionally the guideline requires the
utility to develop several compliance scenarios ranging from the present CO2 regulatory level to the upper
reaches of credible proposals and each scenario should include a time profile of CO2 costs. The utility is
also required to include a “trigger point” analysis in which the utility must determine at what level of carbon
costs its selection of portfolio resources would be significantly different.
ANALYSIS
Unlike electric utilities, environmental cost issues rarely impact a natural gas utility's supply-side resource
options. This is because the only supply-side energy resource is natural gas. The utility cannot choose
between say "dirty" coal-fired generation and "clean" wind energy sources. The supply-side implication of
environmental externalities generally relates to combustion of fuel to move or compress natural gas.
Avista’s direct gas distribution system infrastructure relies solely on the upstream line pressure of the
interstate pipeline transportation network to distribute natural gas to its customers and thus does not directly
combust fuels that result in any CO2, NOx, SO2, or Hg emissions. Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 216 of 829
Upstream gas system infrastructure (pipelines, storage facilities, and gathering systems), however, do
produce CO2 emissions via compressors used to pressurize and move natural gas. Accessing CO2 emissions
data on these upstream activities to perform detailed meaningful analysis is challenging. In the 2009 Natural
Gas IRP there was significant momentum regarding GHG legislation and the movement towards the
creation of carbon cap and trade markets or tax structure. Additionally, the pricing level of the framework
has been greatly reduced. Whichever structure ultimately gets implemented, Avista believes the cost pass
through mechanisms for upstream gas system infrastructure will not make a difference in supply-side
resource selection although the amount of cost pass through could differ widely.
Table 3.2.1 summarizes a range of environmental cost adders we believe capture several compliance futures
including our expected scenario. The CO2 cost adders reflect outlooks we obtained from one of our
consultants, and following discussion and feedback from the TAC, have been incorporated into our
Expected, Low Growth/High Price, and Alternate Planning Standard portfolios.
The guidelines also call for a trigger point analysis that reflects a “turning point” at which an alternate
resource portfolio would be selected at different carbon cost adders levels. Because natural gas is the only
supply resource applicable to LDC’s any alternate resource portfolio selection would be a result of delivery
methods of natural gas to customers. Conceptually, there could be differing levels of cost adders applicable
to pipeline transported supply versus in service territory LNG storage gas. From a practical standpoint
however, the differences in these relative cost adders would be very minor and would not change supply-
side resource selection regardless of various carbon cost adder levels. We do acknowledge there is influence
to the avoided costs which would impact the cost effectiveness of demand-side measures in the DSM
business planning process.
CONSERVATON COST ADVANTAGE
For this IRP, we also incorporated a 10 percent environmental externality factor into our assessment of the
cost-effectiveness of existing demand-side management programs. Our assessment of prospective demand-
side management opportunities is based on an avoided cost stream that includes this 10 percent factor.
Environmental externalities were evaluated in the IRP by adding the cost per therm equivalent of the
externality cost values to supply-side resources as described in OPUC Order No. 93-965. Avista found that
the environmental cost adders had no impact on the company’s supply-side choices, although they did
impact the level of demand-side measures that could be cost-effective to acquire.
REGULATORY FILING
Avista will file revised cost-effectiveness limits (CELs) based upon the updated avoided costs available
from this IRP process within the prescribed regulatory timetable.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 217 of 829
TABLE 3.2.1: ENVIRONMENTAL EXTERNALITIES COST ADDER ANALYSIS (2015$)

2020 2025 2030 2035
$/short ton $ 2 $ 2 $ 2 $ 2
$/lb $ 0.00 $ 0.00 $ 0.00 $ 0.00
lbs/therm 0.008 0.008 0.008 0.008
NOx Adder
$/therm $ 0.00 $ 0.00 $ 0.00 $ 0.00
$/short ton $ 216 $ 216 $ 216 $ 216
$/lb $ 0.11 $ 0.11 $ 0.11 $ 0.11
lbs/therm $ 0.01 $ 0.01 $ 0.01 $ 0.01
NOx Adder
$/therm $ 0.00 $ 0.00 $ 0.00 $ 0.00
$/ton $ - $ 23.36 $ 32.72 $ 45.91
$/lb $ - $ 0.012 $ 0.016 $ 0.023
lbs/therm 11.64 11.64 11.64 11.64
CO2 Adder
$/therm $ - $ 0.14 $ 0.19 $ 0.27
2020 2025 2030 2035
$/short ton $ 2 $ 2 $ 2 $ 2
$/lb $ 0.00 $ 0.00 $ 0.00 $ 0.00
lbs/therm 0.008 0.008 0.008 0.008
NOx Adder
$/therm $ 0.00 $ 0.00 $ 0.00 $ 0.00
$/short ton $ 216 $ 216 $ 216 $ 216
$/lb $ 0.11 $ 0.11 $ 0.11 $ 0.11
lbs/therm $ 0.008 0.008 0.008 0.008
NOx Adder
$/therm $ 0.00 $ 0.00 $ 0.00 $ 0.00
$/ton $ 118.26 $ 120.17 $ 119.88 $ 120.01
$/lb $ 0.059 $ 0.060 $ 0.060 $ 0.060
lbs/therm 11.64 11.64 11.64 11.64
CO2 Adder
$/therm $ 0.69 $ 0.70 $ 0.70 $ 0.70
2020 2025 2030 2035
$/short ton $ 2 $ 2 $ 2 $ 2
$/lb $ 0.00 $ 0.00 $ 0.00 $ 0.00
lbs/therm 0.008 0.008 0.008 0.008
NOx Adder
$/therm $ 0.00 $ 0.00 $ 0.00 $ 0.00
$/short ton $ 216 $ 216 $ 216 $ 216
$/lb $ 0.11 $ 0.11 $ 0.11 $ 0.11
lbs/therm 0.008 0.008 0.008 0.008
NOx Adder
$/therm $ 0.00 $ 0.00 $ 0.00 $ 0.00
$/ton $ 11.54 $ 12.19 $ 12.62 $ 12.86
$/lb $ 0.006 $ 0.006 $ 0.006 $ 0.006
lbs/therm 11.64 11.64 11.64 11.64
CO2 Adder
$/therm $ 0.07 $ 0.07 $ 0.07 $ 0.07
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Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 218 of 829
APPENDIX 4.1: CURRENT TRANSPORTATION/STORAGE RATES AND ASSUMPTIONS

Reservation Commodity Fuel Rate
TransCanada NGTL System Firm Rates (2)
FT-D Demand Rate Alberta-B.C. Border $4.77CAD/GJ/month N/a N/a
TransCanada Foothills BC System Firm Rates (3)
FT A/BC to Kingsgate $2.32CAD/GJ/month N/a 1.70%
GTN FTS-1 Rates
Mileage Based - Representative Example
Kingsgate to Spokane $0.081391/Dth/day $0.001733/Dth/day 0.0042% per Dth/mile
Kingsgate to Malin $0.300201/Dth/day $0.009799/Dth/day 0.0042% per Dth/mile
Medford Lateral $0.247709/Dth/day $0.002291/Dth/day N/a
Spectra Energy/Westcoast System Firms Rates (4)
Postage Stamp Rates
Station 2 to Huntingdon/Sumas $477.81CAD/103m3/month N/a N/a
Williams NWP
Postage Stamp Rates
TF-1 $0.39294/Dth/day $0.00832/Dth/day 1.16%
TF-2 $0.39294/Dth/day $0.00832/Dth/day 1.16%
SGS-2F $0.01562/Dth/day $0.00057/Dth/day 0.17%
(1) Rates and Fuel reported are from current tariffed rates in the established currency and energy units of each pipeline
(2) Rate does not reflect current term-differentiation or Abandonment Surcharge
(3) Rate does not include Abandonment Surcharge
(4) Rate changes annually
Current Tariff Rates (1)
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 219 of 829
APPENDIX 6.1: MONTHLY PRICE DATA BY BASIN
EXPECTED PRICE

Scenario Index Gas Year Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct
Expected Case AECO 2017-2018 1.79$ 1.56$ 1.66$ 2.13$ 0.93$ 1.06$ 1.03$ 1.02$ 1.07$ 1.08$ 1.03$ 1.08$
Expected Case AECO 2018-2019 1.49$ 1.66$ 1.72$ 1.72$ 1.59$ 1.23$ 1.21$ 1.30$ 1.38$ 1.38$ 1.30$ 1.33$
Expected Case AECO 2019-2020 1.69$ 1.88$ 1.97$ 1.93$ 1.75$ 1.47$ 1.47$ 1.48$ 1.53$ 1.56$ 1.51$ 1.57$
Expected Case AECO 2020-2021 1.79$ 1.94$ 2.18$ 2.13$ 2.03$ 1.74$ 1.72$ 1.76$ 1.85$ 1.86$ 1.78$ 1.84$
Expected Case AECO 2021-2022 2.13$ 2.26$ 2.38$ 2.40$ 2.33$ 2.01$ 2.02$ 2.01$ 2.07$ 2.09$ 2.11$ 2.12$
Expected Case AECO 2022-2023 2.28$ 2.44$ 2.52$ 2.48$ 2.43$ 2.12$ 2.18$ 2.21$ 2.22$ 2.29$ 2.28$ 2.28$
Expected Case AECO 2023-2024 2.57$ 2.76$ 2.85$ 2.85$ 2.81$ 2.60$ 2.60$ 2.57$ 2.70$ 2.82$ 2.79$ 2.84$
Expected Case AECO 2024-2025 2.95$ 3.03$ 3.09$ 3.10$ 2.95$ 2.77$ 2.80$ 2.89$ 2.96$ 2.99$ 2.94$ 2.94$
Expected Case AECO 2025-2026 3.00$ 3.10$ 3.20$ 3.18$ 3.03$ 2.87$ 2.93$ 3.01$ 3.12$ 3.15$ 3.07$ 3.12$
Expected Case AECO 2026-2027 3.17$ 3.31$ 3.41$ 3.41$ 3.32$ 3.19$ 3.17$ 3.28$ 3.39$ 3.42$ 3.36$ 3.38$
Expected Case AECO 2027-2028 3.48$ 3.70$ 3.77$ 3.67$ 3.59$ 3.50$ 3.48$ 3.63$ 3.72$ 3.77$ 3.64$ 3.68$
Expected Case AECO 2028-2029 3.77$ 3.93$ 3.99$ 4.06$ 3.93$ 3.82$ 3.83$ 3.86$ 3.98$ 4.02$ 3.93$ 4.03$
Expected Case AECO 2029-2030 4.12$ 4.34$ 4.36$ 4.37$ 4.18$ 4.07$ 4.11$ 4.16$ 4.29$ 4.35$ 4.27$ 4.31$
Expected Case AECO 2030-2031 4.30$ 4.51$ 4.60$ 4.61$ 4.43$ 4.23$ 4.31$ 4.35$ 4.53$ 4.59$ 4.50$ 4.53$
Expected Case AECO 2031-2032 4.52$ 4.65$ 4.76$ 4.69$ 4.54$ 4.35$ 4.40$ 4.45$ 4.61$ 4.68$ 4.61$ 4.70$
Expected Case AECO 2032-2033 4.67$ 4.93$ 5.00$ 5.00$ 4.82$ 4.63$ 4.65$ 4.70$ 4.92$ 4.96$ 4.86$ 4.87$
Expected Case AECO 2033-2034 4.93$ 5.14$ 5.18$ 5.21$ 4.97$ 4.79$ 4.80$ 4.88$ 5.11$ 5.12$ 4.99$ 5.04$
Expected Case AECO 2034-2035 5.13$ 5.29$ 5.43$ 5.40$ 5.22$ 5.05$ 4.99$ 5.07$ 5.27$ 5.34$ 5.21$ 5.13$
Expected Case AECO 2035-2036 5.02$ 5.14$ 5.51$ 5.58$ 5.40$ 5.20$ 5.21$ 5.36$ 5.74$ 5.89$ 5.62$ 5.60$
Expected Case AECO 2036-2037 5.67$ 5.97$ 6.06$ 6.10$ 5.75$ 5.38$ 5.39$ 5.51$ 5.88$ 5.96$ 5.65$ 5.54$
Expected Case Malin 2017-2018 2.75$ 2.61$ 2.75$ 3.29$ 2.13$ 2.06$ 2.13$ 2.18$ 2.26$ 2.29$ 2.21$ 2.23$
Expected Case Malin 2018-2019 2.36$ 2.65$ 2.69$ 2.65$ 2.49$ 2.15$ 2.07$ 2.11$ 2.19$ 2.21$ 2.18$ 2.14$
Expected Case Malin 2019-2020 2.46$ 2.72$ 2.77$ 2.71$ 2.61$ 2.38$ 2.37$ 2.48$ 2.55$ 2.33$ 2.30$ 2.33$
Expected Case Malin 2020-2021 2.55$ 2.74$ 2.94$ 2.90$ 2.67$ 2.50$ 2.45$ 2.47$ 2.62$ 2.66$ 2.64$ 2.64$
Expected Case Malin 2021-2022 2.89$ 3.04$ 3.10$ 3.09$ 2.87$ 2.67$ 2.64$ 2.63$ 2.76$ 2.78$ 2.82$ 2.78$
Expected Case Malin 2022-2023 3.00$ 3.18$ 3.23$ 3.21$ 3.06$ 2.79$ 2.77$ 2.80$ 2.88$ 2.96$ 2.97$ 2.96$
Expected Case Malin 2023-2024 3.30$ 3.48$ 3.53$ 3.53$ 3.38$ 3.19$ 3.17$ 3.16$ 3.31$ 3.39$ 3.37$ 3.37$
Expected Case Malin 2024-2025 3.63$ 3.74$ 3.79$ 3.80$ 3.62$ 3.43$ 3.38$ 3.43$ 3.52$ 3.55$ 3.55$ 3.50$
Expected Case Malin 2025-2026 3.67$ 3.78$ 3.86$ 3.87$ 3.68$ 3.53$ 3.49$ 3.50$ 3.62$ 3.64$ 3.62$ 3.60$
Expected Case Malin 2026-2027 3.74$ 3.93$ 4.00$ 4.00$ 3.82$ 3.69$ 3.64$ 3.73$ 3.91$ 3.89$ 3.88$ 3.86$
Expected Case Malin 2027-2028 4.08$ 4.24$ 4.37$ 4.29$ 4.17$ 4.01$ 3.94$ 4.07$ 4.15$ 4.15$ 4.12$ 4.10$
Expected Case Malin 2028-2029 4.30$ 4.46$ 4.57$ 4.55$ 4.40$ 4.25$ 4.22$ 4.25$ 4.38$ 4.40$ 4.37$ 4.41$
Expected Case Malin 2029-2030 4.58$ 4.79$ 4.86$ 4.86$ 4.73$ 4.54$ 4.51$ 4.55$ 4.67$ 4.69$ 4.71$ 4.74$
Expected Case Malin 2030-2031 4.86$ 5.02$ 5.15$ 5.11$ 4.95$ 4.71$ 4.72$ 4.77$ 4.95$ 4.99$ 4.91$ 4.93$
Expected Case Malin 2031-2032 5.06$ 5.17$ 5.32$ 5.28$ 5.13$ 4.89$ 4.87$ 4.93$ 5.11$ 5.15$ 5.10$ 5.13$
Expected Case Malin 2032-2033 5.25$ 5.45$ 5.51$ 5.51$ 5.35$ 5.15$ 5.12$ 5.18$ 5.42$ 5.43$ 5.33$ 5.33$
Expected Case Malin 2033-2034 5.47$ 5.67$ 5.75$ 5.77$ 5.57$ 5.39$ 5.32$ 5.42$ 5.62$ 5.61$ 5.52$ 5.59$
Expected Case Malin 2034-2035 5.73$ 5.88$ 6.02$ 6.02$ 5.80$ 5.62$ 5.52$ 5.61$ 5.78$ 5.85$ 5.75$ 5.76$
Expected Case Malin 2035-2036 5.73$ 5.88$ 6.25$ 6.28$ 6.06$ 5.85$ 5.81$ 5.90$ 6.25$ 6.31$ 6.09$ 6.13$
Expected Case Malin 2036-2037 6.36$ 6.73$ 6.76$ 6.79$ 6.42$ 6.02$ 5.95$ 6.00$ 6.33$ 6.38$ 6.09$ 6.15$
Expected Case Rockies 2017-2018 2.70$ 2.50$ 3.07$ 3.23$ 2.05$ 1.99$ 2.04$ 2.09$ 2.15$ 2.18$ 2.10$ 2.13$
Expected Case Rockies 2018-2019 2.28$ 2.55$ 2.75$ 2.59$ 2.44$ 2.09$ 2.01$ 2.05$ 2.10$ 2.12$ 2.09$ 2.05$
Expected Case Rockies 2019-2020 2.37$ 2.62$ 2.83$ 2.65$ 2.55$ 2.32$ 2.31$ 2.42$ 2.46$ 2.24$ 2.21$ 2.24$
Expected Case Rockies 2020-2021 2.47$ 2.64$ 3.00$ 2.84$ 2.61$ 2.45$ 2.38$ 2.40$ 2.51$ 2.54$ 2.53$ 2.52$
Expected Case Rockies 2021-2022 2.77$ 2.92$ 2.98$ 2.98$ 2.81$ 2.61$ 2.57$ 2.57$ 2.64$ 2.67$ 2.70$ 2.66$
Expected Case Rockies 2022-2023 2.87$ 3.05$ 3.10$ 3.08$ 2.98$ 2.67$ 2.68$ 2.70$ 2.75$ 2.83$ 2.84$ 2.82$
Expected Case Rockies 2023-2024 3.16$ 3.34$ 3.38$ 3.38$ 3.30$ 3.09$ 3.06$ 3.06$ 3.18$ 3.24$ 3.23$ 3.22$
Expected Case Rockies 2024-2025 3.44$ 3.58$ 3.63$ 3.64$ 3.46$ 3.28$ 3.27$ 3.30$ 3.38$ 3.40$ 3.39$ 3.35$
Expected Case Rockies 2025-2026 3.47$ 3.62$ 3.71$ 3.71$ 3.53$ 3.38$ 3.35$ 3.37$ 3.47$ 3.49$ 3.47$ 3.45$
Expected Case Rockies 2026-2027 3.59$ 3.78$ 3.84$ 3.85$ 3.67$ 3.55$ 3.51$ 3.61$ 3.76$ 3.74$ 3.73$ 3.71$
Expected Case Rockies 2027-2028 3.92$ 4.08$ 4.20$ 4.12$ 4.01$ 3.86$ 3.85$ 3.98$ 4.00$ 4.00$ 3.97$ 3.94$
Expected Case Rockies 2028-2029 4.14$ 4.30$ 4.40$ 4.38$ 4.25$ 4.12$ 4.13$ 4.16$ 4.23$ 4.24$ 4.20$ 4.24$
Expected Case Rockies 2029-2030 4.40$ 4.60$ 4.67$ 4.67$ 4.58$ 4.41$ 4.41$ 4.43$ 4.52$ 4.52$ 4.53$ 4.56$
Expected Case Rockies 2030-2031 4.67$ 4.83$ 4.95$ 4.92$ 4.80$ 4.60$ 4.61$ 4.66$ 4.76$ 4.80$ 4.72$ 4.74$
Expected Case Rockies 2031-2032 4.86$ 4.97$ 5.11$ 5.07$ 4.96$ 4.78$ 4.75$ 4.81$ 4.96$ 4.97$ 4.91$ 4.93$
Expected Case Rockies 2032-2033 5.05$ 5.24$ 5.30$ 5.30$ 5.16$ 5.03$ 5.00$ 5.05$ 5.26$ 5.25$ 5.13$ 5.13$
Expected Case Rockies 2033-2034 5.26$ 5.45$ 5.53$ 5.55$ 5.38$ 5.26$ 5.19$ 5.29$ 5.45$ 5.42$ 5.31$ 5.38$
Expected Case Rockies 2034-2035 5.52$ 5.66$ 5.80$ 5.79$ 5.60$ 5.48$ 5.38$ 5.47$ 5.61$ 5.65$ 5.54$ 5.54$
Expected Case Rockies 2035-2036 5.50$ 5.65$ 6.02$ 6.05$ 5.86$ 5.71$ 5.66$ 5.75$ 6.07$ 6.10$ 5.87$ 5.90$
Expected Case Rockies 2036-2037 6.13$ 6.49$ 6.52$ 6.55$ 6.20$ 5.87$ 5.80$ 5.84$ 6.14$ 6.17$ 5.87$ 5.92$
Nominal$
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 220 of 829
APPENDIX 6.1: MONTHLY PRICE DATA BY BASIN
EXPECTED PRICE

Expected Case Stanfield 2017-2018 2.68$ 2.60$ 2.80$ 3.26$ 2.04$ 1.96$ 2.01$ 2.03$ 2.12$ 2.16$ 2.08$ 2.07$
Expected Case Stanfield 2018-2019 2.33$ 2.62$ 2.65$ 2.61$ 2.46$ 2.04$ 1.96$ 2.01$ 2.03$ 2.03$ 2.03$ 1.99$
Expected Case Stanfield 2019-2020 2.42$ 2.69$ 2.73$ 2.68$ 2.51$ 2.29$ 2.28$ 2.38$ 2.39$ 2.15$ 2.14$ 2.17$
Expected Case Stanfield 2020-2021 2.51$ 2.70$ 2.90$ 2.86$ 2.60$ 2.43$ 2.35$ 2.36$ 2.45$ 2.47$ 2.48$ 2.50$
Expected Case Stanfield 2021-2022 2.85$ 3.00$ 3.06$ 3.05$ 2.79$ 2.58$ 2.55$ 2.54$ 2.60$ 2.60$ 2.65$ 2.63$
Expected Case Stanfield 2022-2023 2.96$ 3.14$ 3.19$ 3.17$ 3.02$ 2.70$ 2.68$ 2.70$ 2.71$ 2.77$ 2.80$ 2.82$
Expected Case Stanfield 2023-2024 3.26$ 3.44$ 3.49$ 3.49$ 3.34$ 3.13$ 3.11$ 3.10$ 3.14$ 3.22$ 3.24$ 3.27$
Expected Case Stanfield 2024-2025 3.59$ 3.69$ 3.75$ 3.75$ 3.57$ 3.38$ 3.34$ 3.37$ 3.37$ 3.36$ 3.41$ 3.38$
Expected Case Stanfield 2025-2026 3.62$ 3.74$ 3.81$ 3.82$ 3.64$ 3.46$ 3.41$ 3.44$ 3.45$ 3.45$ 3.48$ 3.46$
Expected Case Stanfield 2026-2027 3.70$ 3.89$ 3.95$ 3.96$ 3.78$ 3.61$ 3.57$ 3.68$ 3.73$ 3.70$ 3.75$ 3.72$
Expected Case Stanfield 2027-2028 4.04$ 4.22$ 4.33$ 4.25$ 4.13$ 3.94$ 3.86$ 3.99$ 3.96$ 3.96$ 3.97$ 3.95$
Expected Case Stanfield 2028-2029 4.26$ 4.42$ 4.55$ 4.50$ 4.35$ 4.16$ 4.14$ 4.17$ 4.19$ 4.20$ 4.18$ 4.23$
Expected Case Stanfield 2029-2030 4.56$ 4.73$ 4.81$ 4.81$ 4.68$ 4.44$ 4.41$ 4.45$ 4.46$ 4.49$ 4.52$ 4.55$
Expected Case Stanfield 2030-2031 4.81$ 4.97$ 5.09$ 5.08$ 4.90$ 4.61$ 4.60$ 4.66$ 4.74$ 4.78$ 4.71$ 4.73$
Expected Case Stanfield 2031-2032 5.01$ 5.14$ 5.29$ 5.22$ 5.07$ 4.78$ 4.75$ 4.81$ 4.91$ 4.94$ 4.89$ 4.92$
Expected Case Stanfield 2032-2033 5.19$ 5.39$ 5.45$ 5.45$ 5.28$ 5.02$ 5.00$ 5.05$ 5.21$ 5.22$ 5.12$ 5.13$
Expected Case Stanfield 2033-2034 5.41$ 5.64$ 5.71$ 5.74$ 5.51$ 5.25$ 5.19$ 5.30$ 5.41$ 5.40$ 5.30$ 5.38$
Expected Case Stanfield 2034-2035 5.68$ 5.85$ 5.99$ 5.99$ 5.73$ 5.48$ 5.38$ 5.47$ 5.56$ 5.63$ 5.53$ 5.54$
Expected Case Stanfield 2035-2036 5.64$ 5.84$ 6.22$ 6.21$ 5.97$ 5.72$ 5.68$ 5.77$ 6.02$ 6.08$ 5.86$ 5.90$
Expected Case Stanfield 2036-2037 6.30$ 6.65$ 6.68$ 6.71$ 6.34$ 5.87$ 5.80$ 5.83$ 6.10$ 6.15$ 5.86$ 5.92$
Expected Case Sumas 2017-2018 2.69$ 2.78$ 2.72$ 3.20$ 1.98$ 1.80$ 1.75$ 1.80$ 1.98$ 2.01$ 2.01$ 2.10$
Expected Case Sumas 2018-2019 2.60$ 2.93$ 2.95$ 2.81$ 2.37$ 1.79$ 1.77$ 1.93$ 2.14$ 2.13$ 2.13$ 2.17$
Expected Case Sumas 2019-2020 2.54$ 3.08$ 3.10$ 2.88$ 2.36$ 1.94$ 1.92$ 1.91$ 2.05$ 2.08$ 2.07$ 2.19$
Expected Case Sumas 2020-2021 2.52$ 2.83$ 2.91$ 2.73$ 2.45$ 2.00$ 1.99$ 2.00$ 2.22$ 2.23$ 2.20$ 2.26$
Expected Case Sumas 2021-2022 2.68$ 3.07$ 3.11$ 3.00$ 2.74$ 2.19$ 2.19$ 2.16$ 2.34$ 2.36$ 2.42$ 2.46$
Expected Case Sumas 2022-2023 2.80$ 3.21$ 3.22$ 3.07$ 2.82$ 2.30$ 2.32$ 2.33$ 2.47$ 2.54$ 2.58$ 2.62$
Expected Case Sumas 2023-2024 3.09$ 3.51$ 3.57$ 3.44$ 3.21$ 2.82$ 2.80$ 2.76$ 3.02$ 3.15$ 3.15$ 3.19$
Expected Case Sumas 2024-2025 3.41$ 3.71$ 3.75$ 3.63$ 3.31$ 2.98$ 3.00$ 3.08$ 3.30$ 3.35$ 3.32$ 3.34$
Expected Case Sumas 2025-2026 3.48$ 3.79$ 3.85$ 3.70$ 3.40$ 3.09$ 3.14$ 3.24$ 3.50$ 3.52$ 3.46$ 3.51$
Expected Case Sumas 2026-2027 3.64$ 4.05$ 4.06$ 3.88$ 3.62$ 3.39$ 3.36$ 3.40$ 3.69$ 3.72$ 3.69$ 3.71$
Expected Case Sumas 2027-2028 3.95$ 4.43$ 4.46$ 4.22$ 3.94$ 3.68$ 3.66$ 3.78$ 4.00$ 4.06$ 3.96$ 4.01$
Expected Case Sumas 2028-2029 4.24$ 4.66$ 4.71$ 4.64$ 4.32$ 4.03$ 4.04$ 4.04$ 4.30$ 4.34$ 4.28$ 4.39$
Expected Case Sumas 2029-2030 4.61$ 5.10$ 5.09$ 4.98$ 4.60$ 4.32$ 4.34$ 4.38$ 4.64$ 4.70$ 4.66$ 4.71$
Expected Case Sumas 2030-2031 4.84$ 5.30$ 5.36$ 5.23$ 4.85$ 4.49$ 4.56$ 4.59$ 4.90$ 4.95$ 4.90$ 4.93$
Expected Case Sumas 2031-2032 5.08$ 5.46$ 5.52$ 5.31$ 4.97$ 4.60$ 4.64$ 4.68$ 4.97$ 5.04$ 5.00$ 5.10$
Expected Case Sumas 2032-2033 5.22$ 5.73$ 5.76$ 5.62$ 5.24$ 4.89$ 4.90$ 4.92$ 5.30$ 5.33$ 5.27$ 5.28$
Expected Case Sumas 2033-2034 5.47$ 5.94$ 5.94$ 5.82$ 5.38$ 5.03$ 5.04$ 5.10$ 5.46$ 5.48$ 5.37$ 5.42$
Expected Case Sumas 2034-2035 5.66$ 6.09$ 6.17$ 6.01$ 5.62$ 5.27$ 5.21$ 5.27$ 5.61$ 5.67$ 5.58$ 5.50$
Expected Case Sumas 2035-2036 5.58$ 5.93$ 6.25$ 6.18$ 5.79$ 5.43$ 5.43$ 5.57$ 6.08$ 6.22$ 5.99$ 5.97$
Expected Case Sumas 2036-2037 6.19$ 6.74$ 6.79$ 6.69$ 6.15$ 5.61$ 5.62$ 5.70$ 6.21$ 6.29$ 6.02$ 5.94$
Nominal$
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 221 of 829
APPENDIX 6.1: MONTHLY PRICE DATA BY BASIN
HIGH GROWTH LOW PRICE

Scenario Index Gas Year Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct
High Growth & Low Prices AECO 2017-2018 1.79$ 1.56$ 1.66$ 2.13$ 0.93$ 1.06$ 1.03$ 1.02$ 1.07$ 1.08$ 1.03$ 1.08$
High Growth & Low Prices AECO 2018-2019 1.32$ 1.48$ 1.54$ 1.55$ 1.42$ 1.07$ 1.05$ 1.14$ 1.22$ 1.22$ 1.13$ 1.17$
High Growth & Low Prices AECO 2019-2020 1.35$ 1.52$ 1.61$ 1.57$ 1.41$ 1.15$ 1.15$ 1.16$ 1.20$ 1.23$ 1.18$ 1.23$
High Growth & Low Prices AECO 2020-2021 1.26$ 1.39$ 1.61$ 1.56$ 1.48$ 1.23$ 1.22$ 1.25$ 1.32$ 1.33$ 1.25$ 1.30$
High Growth & Low Prices AECO 2021-2022 1.38$ 1.49$ 1.59$ 1.61$ 1.55$ 1.29$ 1.30$ 1.29$ 1.33$ 1.35$ 1.35$ 1.37$
High Growth & Low Prices AECO 2022-2023 1.31$ 1.43$ 1.49$ 1.46$ 1.42$ 1.18$ 1.23$ 1.25$ 1.26$ 1.30$ 1.29$ 1.29$
High Growth & Low Prices AECO 2023-2024 1.40$ 1.55$ 1.63$ 1.62$ 1.59$ 1.44$ 1.42$ 1.40$ 1.50$ 1.58$ 1.56$ 1.60$
High Growth & Low Prices AECO 2024-2025 1.57$ 1.63$ 1.67$ 1.67$ 1.55$ 1.43$ 1.45$ 1.51$ 1.57$ 1.59$ 1.55$ 1.56$
High Growth & Low Prices AECO 2025-2026 1.49$ 1.56$ 1.63$ 1.60$ 1.49$ 1.37$ 1.42$ 1.49$ 1.57$ 1.58$ 1.52$ 1.58$
High Growth & Low Prices AECO 2026-2027 1.50$ 1.59$ 1.65$ 1.65$ 1.59$ 1.50$ 1.48$ 1.53$ 1.62$ 1.63$ 1.58$ 1.62$ High Growth & Low Prices AECO 2027-2028 1.57$ 1.71$ 1.74$ 1.66$ 1.61$ 1.55$ 1.54$ 1.63$ 1.70$ 1.72$ 1.62$ 1.67$
High Growth & Low Prices AECO 2028-2029 1.68$ 1.77$ 1.81$ 1.86$ 1.77$ 1.69$ 1.68$ 1.69$ 1.77$ 1.78$ 1.71$ 1.80$
High Growth & Low Prices AECO 2029-2030 1.83$ 1.95$ 1.95$ 1.94$ 1.79$ 1.73$ 1.75$ 1.79$ 1.87$ 1.90$ 1.84$ 1.87$
High Growth & Low Prices AECO 2030-2031 1.81$ 1.94$ 1.98$ 1.98$ 1.87$ 1.73$ 1.78$ 1.79$ 1.90$ 1.93$ 1.88$ 1.90$
High Growth & Low Prices AECO 2031-2032 1.84$ 1.92$ 1.96$ 1.91$ 1.81$ 1.69$ 1.72$ 1.76$ 1.85$ 1.88$ 1.83$ 1.91$ High Growth & Low Prices AECO 2032-2033 1.83$ 1.96$ 2.00$ 1.99$ 1.87$ 1.77$ 1.75$ 1.78$ 1.91$ 1.92$ 1.86$ 1.87$
High Growth & Low Prices AECO 2033-2034 1.84$ 1.96$ 1.97$ 1.97$ 1.82$ 1.71$ 1.71$ 1.74$ 1.86$ 1.86$ 1.79$ 1.82$
High Growth & Low Prices AECO 2034-2035 1.84$ 1.92$ 1.98$ 1.94$ 1.86$ 1.75$ 1.69$ 1.72$ 1.83$ 1.84$ 1.78$ 1.73$
High Growth & Low Prices AECO 2035-2036 1.65$ 1.68$ 1.82$ 1.88$ 1.78$ 1.67$ 1.65$ 1.74$ 1.91$ 2.00$ 1.88$ 1.87$
High Growth & Low Prices AECO 2036-2037 1.81$ 1.90$ 1.95$ 1.98$ 1.81$ 1.64$ 1.63$ 1.69$ 1.89$ 1.93$ 1.78$ 1.71$
High Growth & Low Prices Malin 2017-2018 2.75$ 2.61$ 2.75$ 3.29$ 2.13$ 2.06$ 2.13$ 2.18$ 2.26$ 2.29$ 2.21$ 2.23$
High Growth & Low Prices Malin 2018-2019 2.19$ 2.47$ 2.51$ 2.47$ 2.32$ 1.99$ 1.92$ 1.95$ 2.02$ 2.05$ 2.01$ 1.97$
High Growth & Low Prices Malin 2019-2020 2.11$ 2.37$ 2.40$ 2.35$ 2.26$ 2.06$ 2.05$ 2.16$ 2.22$ 2.00$ 1.97$ 1.99$
High Growth & Low Prices Malin 2020-2021 2.02$ 2.19$ 2.37$ 2.34$ 2.12$ 1.99$ 1.94$ 1.96$ 2.10$ 2.13$ 2.11$ 2.10$ High Growth & Low Prices Malin 2021-2022 2.14$ 2.27$ 2.31$ 2.29$ 2.10$ 1.95$ 1.92$ 1.91$ 2.03$ 2.05$ 2.07$ 2.03$
High Growth & Low Prices Malin 2022-2023 2.03$ 2.17$ 2.20$ 2.19$ 2.05$ 1.85$ 1.82$ 1.84$ 1.92$ 1.97$ 1.98$ 1.96$
High Growth & Low Prices Malin 2023-2024 2.14$ 2.28$ 2.30$ 2.30$ 2.16$ 2.03$ 2.00$ 1.99$ 2.10$ 2.15$ 2.14$ 2.13$
High Growth & Low Prices Malin 2024-2025 2.25$ 2.33$ 2.36$ 2.37$ 2.22$ 2.08$ 2.03$ 2.05$ 2.13$ 2.15$ 2.15$ 2.12$
High Growth & Low Prices Malin 2025-2026 2.16$ 2.25$ 2.29$ 2.29$ 2.14$ 2.03$ 1.98$ 1.98$ 2.07$ 2.07$ 2.07$ 2.05$ High Growth & Low Prices Malin 2026-2027 2.08$ 2.21$ 2.24$ 2.24$ 2.09$ 2.00$ 1.95$ 1.99$ 2.14$ 2.10$ 2.11$ 2.10$
High Growth & Low Prices Malin 2027-2028 2.17$ 2.25$ 2.34$ 2.28$ 2.19$ 2.06$ 2.00$ 2.06$ 2.13$ 2.11$ 2.10$ 2.09$
High Growth & Low Prices Malin 2028-2029 2.21$ 2.30$ 2.39$ 2.34$ 2.23$ 2.12$ 2.07$ 2.09$ 2.18$ 2.17$ 2.16$ 2.18$
High Growth & Low Prices Malin 2029-2030 2.29$ 2.40$ 2.45$ 2.43$ 2.34$ 2.20$ 2.15$ 2.18$ 2.25$ 2.24$ 2.28$ 2.30$
High Growth & Low Prices Malin 2030-2031 2.37$ 2.45$ 2.53$ 2.49$ 2.39$ 2.22$ 2.19$ 2.21$ 2.32$ 2.33$ 2.29$ 2.31$ High Growth & Low Prices Malin 2031-2032 2.38$ 2.44$ 2.52$ 2.50$ 2.40$ 2.23$ 2.19$ 2.24$ 2.35$ 2.35$ 2.32$ 2.34$
High Growth & Low Prices Malin 2032-2033 2.40$ 2.48$ 2.52$ 2.50$ 2.40$ 2.29$ 2.22$ 2.26$ 2.40$ 2.39$ 2.32$ 2.33$
High Growth & Low Prices Malin 2033-2034 2.39$ 2.49$ 2.53$ 2.52$ 2.42$ 2.30$ 2.23$ 2.28$ 2.37$ 2.35$ 2.31$ 2.38$
High Growth & Low Prices Malin 2034-2035 2.44$ 2.51$ 2.57$ 2.56$ 2.43$ 2.31$ 2.21$ 2.25$ 2.33$ 2.35$ 2.32$ 2.36$
High Growth & Low Prices Malin 2035-2036 2.35$ 2.42$ 2.57$ 2.58$ 2.45$ 2.32$ 2.25$ 2.27$ 2.43$ 2.42$ 2.35$ 2.40$ High Growth & Low Prices Malin 2036-2037 2.51$ 2.66$ 2.66$ 2.67$ 2.48$ 2.28$ 2.19$ 2.19$ 2.34$ 2.35$ 2.23$ 2.31$
High Growth & Low Prices Rockies 2017-2018 2.70$ 2.50$ 3.07$ 3.23$ 2.05$ 1.99$ 2.04$ 2.09$ 2.15$ 2.18$ 2.10$ 2.13$
High Growth & Low Prices Rockies 2018-2019 2.11$ 2.37$ 2.57$ 2.41$ 2.26$ 1.93$ 1.85$ 1.89$ 1.94$ 1.96$ 1.92$ 1.88$
High Growth & Low Prices Rockies 2019-2020 2.03$ 2.26$ 2.47$ 2.30$ 2.20$ 2.00$ 1.99$ 2.10$ 2.13$ 1.91$ 1.88$ 1.90$ High Growth & Low Prices Rockies 2020-2021 1.94$ 2.09$ 2.43$ 2.28$ 2.06$ 1.94$ 1.88$ 1.89$ 1.98$ 2.01$ 2.00$ 1.99$
High Growth & Low Prices Rockies 2021-2022 2.02$ 2.15$ 2.19$ 2.19$ 2.03$ 1.89$ 1.85$ 1.85$ 1.91$ 1.93$ 1.95$ 1.91$
High Growth & Low Prices Rockies 2022-2023 1.91$ 2.05$ 2.08$ 2.06$ 1.97$ 1.73$ 1.73$ 1.74$ 1.79$ 1.84$ 1.85$ 1.83$
High Growth & Low Prices Rockies 2023-2024 2.00$ 2.13$ 2.16$ 2.16$ 2.08$ 1.92$ 1.89$ 1.89$ 1.97$ 2.00$ 2.00$ 1.98$
High Growth & Low Prices Rockies 2024-2025 2.07$ 2.18$ 2.21$ 2.21$ 2.07$ 1.94$ 1.92$ 1.93$ 1.99$ 2.00$ 2.00$ 1.96$
High Growth & Low Prices Rockies 2025-2026 1.97$ 2.08$ 2.14$ 2.13$ 1.99$ 1.89$ 1.84$ 1.84$ 1.92$ 1.92$ 1.92$ 1.90$
High Growth & Low Prices Rockies 2026-2027 1.92$ 2.05$ 2.09$ 2.08$ 1.94$ 1.86$ 1.82$ 1.87$ 1.99$ 1.95$ 1.96$ 1.94$
High Growth & Low Prices Rockies 2027-2028 2.01$ 2.09$ 2.17$ 2.11$ 2.03$ 1.91$ 1.91$ 1.97$ 1.98$ 1.95$ 1.94$ 1.93$
High Growth & Low Prices Rockies 2028-2029 2.05$ 2.14$ 2.22$ 2.17$ 2.08$ 1.99$ 1.98$ 2.00$ 2.02$ 2.00$ 1.99$ 2.01$
High Growth & Low Prices Rockies 2029-2030 2.11$ 2.22$ 2.27$ 2.24$ 2.19$ 2.07$ 2.06$ 2.06$ 2.10$ 2.06$ 2.10$ 2.12$
High Growth & Low Prices Rockies 2030-2031 2.19$ 2.26$ 2.34$ 2.30$ 2.24$ 2.11$ 2.08$ 2.10$ 2.13$ 2.14$ 2.10$ 2.12$
High Growth & Low Prices Rockies 2031-2032 2.18$ 2.24$ 2.32$ 2.30$ 2.23$ 2.12$ 2.07$ 2.12$ 2.20$ 2.17$ 2.13$ 2.14$
High Growth & Low Prices Rockies 2032-2033 2.20$ 2.27$ 2.30$ 2.29$ 2.22$ 2.17$ 2.10$ 2.14$ 2.24$ 2.21$ 2.12$ 2.13$
High Growth & Low Prices Rockies 2033-2034 2.18$ 2.27$ 2.31$ 2.31$ 2.23$ 2.18$ 2.10$ 2.14$ 2.21$ 2.16$ 2.11$ 2.17$
High Growth & Low Prices Rockies 2034-2035 2.23$ 2.28$ 2.35$ 2.33$ 2.23$ 2.18$ 2.08$ 2.11$ 2.16$ 2.15$ 2.11$ 2.14$
High Growth & Low Prices Rockies 2035-2036 2.13$ 2.19$ 2.34$ 2.35$ 2.24$ 2.18$ 2.10$ 2.12$ 2.24$ 2.21$ 2.13$ 2.17$
High Growth & Low Prices Rockies 2036-2037 2.27$ 2.42$ 2.41$ 2.42$ 2.26$ 2.14$ 2.04$ 2.03$ 2.15$ 2.14$ 2.00$ 2.08$
Nominal$
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 222 of 829
APPENDIX 6.1: MONTHLY PRICE DATA BY BASIN
HIGH GROWTH LOW PRICE

High Growth & Low Prices Stanfield 2017-2018 2.68$ 2.60$ 2.80$ 3.26$ 2.04$ 1.96$ 2.01$ 2.03$ 2.12$ 2.16$ 2.08$ 2.07$
High Growth & Low Prices Stanfield 2018-2019 2.16$ 2.45$ 2.47$ 2.44$ 2.29$ 1.88$ 1.80$ 1.85$ 1.87$ 1.87$ 1.87$ 1.82$
High Growth & Low Prices Stanfield 2019-2020 2.08$ 2.33$ 2.37$ 2.32$ 2.17$ 1.97$ 1.95$ 2.06$ 2.06$ 1.82$ 1.81$ 1.84$
High Growth & Low Prices Stanfield 2020-2021 1.98$ 2.16$ 2.33$ 2.30$ 2.05$ 1.92$ 1.85$ 1.85$ 1.93$ 1.94$ 1.94$ 1.96$
High Growth & Low Prices Stanfield 2021-2022 2.10$ 2.23$ 2.27$ 2.25$ 2.01$ 1.86$ 1.83$ 1.82$ 1.86$ 1.86$ 1.90$ 1.88$
High Growth & Low Prices Stanfield 2022-2023 1.99$ 2.13$ 2.16$ 2.14$ 2.01$ 1.77$ 1.73$ 1.75$ 1.75$ 1.79$ 1.80$ 1.83$
High Growth & Low Prices Stanfield 2023-2024 2.10$ 2.23$ 2.26$ 2.26$ 2.12$ 1.96$ 1.94$ 1.92$ 1.93$ 1.98$ 2.01$ 2.03$
High Growth & Low Prices Stanfield 2024-2025 2.21$ 2.29$ 2.32$ 2.32$ 2.17$ 2.03$ 1.98$ 2.00$ 1.98$ 1.96$ 2.02$ 1.99$
High Growth & Low Prices Stanfield 2025-2026 2.12$ 2.20$ 2.24$ 2.24$ 2.10$ 1.96$ 1.91$ 1.91$ 1.90$ 1.88$ 1.93$ 1.92$
High Growth & Low Prices Stanfield 2026-2027 2.04$ 2.16$ 2.20$ 2.19$ 2.05$ 1.93$ 1.89$ 1.93$ 1.96$ 1.90$ 1.97$ 1.96$
High Growth & Low Prices Stanfield 2027-2028 2.13$ 2.22$ 2.30$ 2.24$ 2.15$ 1.99$ 1.92$ 1.99$ 1.94$ 1.91$ 1.94$ 1.94$
High Growth & Low Prices Stanfield 2028-2029 2.17$ 2.26$ 2.36$ 2.30$ 2.18$ 2.02$ 1.99$ 2.00$ 1.98$ 1.97$ 1.97$ 2.01$
High Growth & Low Prices Stanfield 2029-2030 2.27$ 2.35$ 2.40$ 2.38$ 2.29$ 2.10$ 2.05$ 2.07$ 2.05$ 2.04$ 2.09$ 2.11$ High Growth & Low Prices Stanfield 2030-2031 2.32$ 2.40$ 2.48$ 2.46$ 2.34$ 2.11$ 2.07$ 2.10$ 2.12$ 2.13$ 2.09$ 2.11$
High Growth & Low Prices Stanfield 2031-2032 2.33$ 2.41$ 2.50$ 2.45$ 2.34$ 2.12$ 2.07$ 2.12$ 2.15$ 2.14$ 2.11$ 2.13$
High Growth & Low Prices Stanfield 2032-2033 2.35$ 2.42$ 2.45$ 2.44$ 2.34$ 2.16$ 2.10$ 2.14$ 2.19$ 2.18$ 2.11$ 2.12$
High Growth & Low Prices Stanfield 2033-2034 2.33$ 2.46$ 2.50$ 2.49$ 2.36$ 2.17$ 2.09$ 2.16$ 2.16$ 2.13$ 2.10$ 2.17$
High Growth & Low Prices Stanfield 2034-2035 2.39$ 2.48$ 2.54$ 2.53$ 2.36$ 2.18$ 2.08$ 2.11$ 2.11$ 2.13$ 2.10$ 2.14$ High Growth & Low Prices Stanfield 2035-2036 2.27$ 2.38$ 2.53$ 2.51$ 2.35$ 2.19$ 2.12$ 2.14$ 2.20$ 2.19$ 2.12$ 2.17$
High Growth & Low Prices Stanfield 2036-2037 2.45$ 2.58$ 2.57$ 2.58$ 2.40$ 2.14$ 2.04$ 2.02$ 2.11$ 2.12$ 2.00$ 2.08$
High Growth & Low Prices Sumas 2017-2018 2.69$ 2.78$ 2.72$ 3.20$ 1.98$ 1.80$ 1.75$ 1.80$ 1.98$ 2.01$ 2.01$ 2.10$
High Growth & Low Prices Sumas 2018-2019 2.44$ 2.76$ 2.77$ 2.63$ 2.20$ 1.63$ 1.61$ 1.77$ 1.98$ 1.97$ 1.97$ 2.01$ High Growth & Low Prices Sumas 2019-2020 2.20$ 2.73$ 2.74$ 2.52$ 2.01$ 1.62$ 1.60$ 1.59$ 1.73$ 1.74$ 1.74$ 1.85$
High Growth & Low Prices Sumas 2020-2021 1.99$ 2.28$ 2.34$ 2.16$ 1.90$ 1.49$ 1.48$ 1.49$ 1.69$ 1.70$ 1.67$ 1.72$
High Growth & Low Prices Sumas 2021-2022 1.93$ 2.30$ 2.32$ 2.21$ 1.97$ 1.47$ 1.47$ 1.44$ 1.61$ 1.62$ 1.67$ 1.71$
High Growth & Low Prices Sumas 2022-2023 1.83$ 2.20$ 2.19$ 2.05$ 1.81$ 1.37$ 1.37$ 1.37$ 1.51$ 1.55$ 1.59$ 1.63$
High Growth & Low Prices Sumas 2023-2024 1.92$ 2.30$ 2.35$ 2.21$ 1.99$ 1.65$ 1.63$ 1.58$ 1.81$ 1.92$ 1.92$ 1.95$
High Growth & Low Prices Sumas 2024-2025 2.03$ 2.31$ 2.32$ 2.19$ 1.91$ 1.63$ 1.64$ 1.71$ 1.91$ 1.95$ 1.93$ 1.95$
High Growth & Low Prices Sumas 2025-2026 1.97$ 2.26$ 2.27$ 2.11$ 1.85$ 1.60$ 1.64$ 1.72$ 1.95$ 1.95$ 1.91$ 1.96$
High Growth & Low Prices Sumas 2026-2027 1.97$ 2.33$ 2.30$ 2.11$ 1.89$ 1.71$ 1.67$ 1.66$ 1.91$ 1.93$ 1.92$ 1.95$
High Growth & Low Prices Sumas 2027-2028 2.04$ 2.44$ 2.43$ 2.20$ 1.96$ 1.73$ 1.71$ 1.78$ 1.98$ 2.01$ 1.94$ 2.00$
High Growth & Low Prices Sumas 2028-2029 2.15$ 2.50$ 2.53$ 2.44$ 2.15$ 1.90$ 1.89$ 1.88$ 2.09$ 2.10$ 2.07$ 2.16$
High Growth & Low Prices Sumas 2029-2030 2.33$ 2.71$ 2.69$ 2.54$ 2.21$ 1.98$ 1.99$ 2.01$ 2.23$ 2.25$ 2.23$ 2.27$
High Growth & Low Prices Sumas 2030-2031 2.36$ 2.73$ 2.75$ 2.61$ 2.29$ 2.00$ 2.04$ 2.03$ 2.27$ 2.29$ 2.27$ 2.31$
High Growth & Low Prices Sumas 2031-2032 2.40$ 2.73$ 2.73$ 2.53$ 2.24$ 1.95$ 1.96$ 1.99$ 2.21$ 2.24$ 2.23$ 2.31$
High Growth & Low Prices Sumas 2032-2033 2.37$ 2.76$ 2.76$ 2.61$ 2.30$ 2.02$ 2.00$ 2.00$ 2.28$ 2.29$ 2.26$ 2.28$
High Growth & Low Prices Sumas 2033-2034 2.39$ 2.76$ 2.72$ 2.58$ 2.24$ 1.95$ 1.94$ 1.95$ 2.21$ 2.21$ 2.16$ 2.20$
High Growth & Low Prices Sumas 2034-2035 2.37$ 2.72$ 2.72$ 2.55$ 2.25$ 1.97$ 1.91$ 1.92$ 2.16$ 2.17$ 2.15$ 2.11$
High Growth & Low Prices Sumas 2035-2036 2.20$ 2.46$ 2.56$ 2.48$ 2.18$ 1.90$ 1.87$ 1.94$ 2.25$ 2.33$ 2.25$ 2.24$
High Growth & Low Prices Sumas 2036-2037 2.33$ 2.68$ 2.68$ 2.57$ 2.21$ 1.87$ 1.86$ 1.89$ 2.22$ 2.26$ 2.15$ 2.10$
High Growth & Low Price Kingsgate 2017-2018 2.59$ 2.43$ 3.39$ 3.25$ 2.04$ 1.90$ 1.91$ 1.86$ 1.97$ 2.08$ 2.08$ 2.09$
High Growth & Low Price Kingsgate 2018-2019 2.23$ 2.37$ 2.42$ 2.41$ 2.22$ 1.93$ 1.88$ 1.89$ 1.94$ 1.90$ 1.92$ 1.97$
High Growth & Low Price Kingsgate 2019-2020 2.15$ 2.27$ 2.28$ 2.24$ 1.98$ 1.85$ 1.80$ 1.80$ 1.85$ 1.82$ 1.83$ 1.84$
High Growth & Low Price Kingsgate 2020-2021 2.02$ 2.11$ 2.18$ 2.16$ 1.92$ 1.81$ 1.74$ 1.75$ 1.83$ 1.84$ 1.84$ 1.84$
High Growth & Low Price Kingsgate 2021-2022 1.99$ 2.09$ 2.12$ 2.11$ 1.88$ 1.76$ 1.72$ 1.71$ 1.76$ 1.75$ 1.77$ 1.76$
High Growth & Low Price Kingsgate 2022-2023 1.91$ 2.02$ 2.04$ 2.03$ 1.90$ 1.66$ 1.63$ 1.67$ 1.64$ 1.68$ 1.70$ 1.75$
High Growth & Low Price Kingsgate 2023-2024 1.98$ 2.09$ 2.11$ 2.11$ 1.99$ 1.85$ 1.83$ 1.85$ 1.86$ 1.91$ 1.93$ 1.92$
High Growth & Low Price Kingsgate 2024-2025 2.09$ 2.14$ 2.16$ 2.17$ 2.04$ 1.92$ 1.87$ 1.88$ 1.90$ 1.85$ 1.94$ 1.91$
High Growth & Low Price Kingsgate 2025-2026 2.00$ 2.05$ 2.08$ 2.09$ 1.96$ 1.89$ 1.83$ 1.84$ 1.82$ 1.77$ 1.81$ 1.80$
High Growth & Low Price Kingsgate 2026-2027 1.91$ 2.01$ 2.03$ 2.04$ 1.91$ 1.81$ 1.77$ 1.82$ 1.81$ 1.77$ 1.84$ 1.83$
High Growth & Low Price Kingsgate 2027-2028 2.01$ 2.07$ 2.13$ 2.08$ 2.00$ 1.84$ 1.76$ 1.87$ 1.78$ 1.77$ 1.81$ 1.81$
High Growth & Low Price Kingsgate 2028-2029 2.04$ 2.12$ 2.25$ 2.16$ 2.05$ 1.88$ 1.83$ 1.84$ 1.86$ 1.83$ 1.88$ 1.92$ High Growth & Low Price Kingsgate 2029-2030 2.14$ 2.21$ 2.26$ 2.24$ 2.20$ 1.95$ 1.89$ 1.90$ 1.88$ 1.94$ 1.95$ 2.02$
High Growth & Low Price Kingsgate 2030-2031 2.22$ 2.26$ 2.34$ 2.32$ 2.21$ 1.96$ 1.90$ 1.92$ 1.95$ 1.98$ 1.94$ 2.01$
High Growth & Low Price Kingsgate 2031-2032 2.19$ 2.27$ 2.35$ 2.30$ 2.21$ 1.96$ 1.95$ 1.94$ 1.98$ 1.99$ 1.97$ 1.99$
High Growth & Low Price Kingsgate 2032-2033 2.20$ 2.28$ 2.29$ 2.30$ 2.20$ 2.00$ 1.93$ 1.96$ 2.02$ 2.03$ 2.02$ 1.98$
High Growth & Low Price Kingsgate 2033-2034 2.19$ 2.31$ 2.30$ 2.35$ 2.22$ 2.01$ 1.92$ 1.98$ 1.99$ 1.98$ 2.00$ 2.02$ High Growth & Low Price Kingsgate 2034-2035 2.25$ 2.34$ 2.40$ 2.38$ 2.22$ 2.07$ 1.90$ 1.93$ 1.94$ 2.03$ 2.01$ 1.99$
High Growth & Low Price Kingsgate 2035-2036 2.12$ 2.21$ 2.35$ 2.36$ 2.21$ 2.02$ 1.94$ 1.95$ 2.08$ 2.08$ 2.02$ 2.01$
High Growth & Low Price Kingsgate 2036-2037 2.30$ 2.38$ 2.39$ 2.43$ 2.25$ 2.02$ 1.91$ 1.83$ 1.99$ 2.00$ 1.84$ 1.93$
Nominal$
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 223 of 829
APPENDIX 6.1: MONTHLY PRICE DATA BY BASIN
LOW GROWTH HIGH PRICE

Scenario Index Gas Year Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct
Low Growth_High Prices AECO 2017-2018 1.79$ 1.56$ 1.66$ 2.13$ 0.93$ 1.06$ 1.03$ 1.02$ 1.07$ 1.08$ 1.03$ 1.08$
Low Growth_High Prices AECO 2018-2019 1.66$ 1.83$ 1.90$ 1.90$ 1.76$ 1.38$ 1.37$ 1.46$ 1.54$ 1.55$ 1.46$ 1.50$ Low Growth_High Prices AECO 2019-2020 2.04$ 2.23$ 2.33$ 2.28$ 2.10$ 1.79$ 1.79$ 1.80$ 1.86$ 1.89$ 1.84$ 1.90$
Low Growth_High Prices AECO 2020-2021 2.32$ 2.48$ 2.75$ 2.69$ 2.58$ 2.25$ 2.23$ 2.27$ 2.37$ 2.40$ 2.32$ 2.38$
Low Growth_High Prices AECO 2021-2022 2.88$ 3.04$ 3.17$ 3.20$ 3.10$ 2.73$ 2.74$ 2.73$ 2.80$ 2.83$ 2.86$ 2.87$
Low Growth_High Prices AECO 2022-2023 3.24$ 3.45$ 3.55$ 3.51$ 3.45$ 3.06$ 3.13$ 3.16$ 3.18$ 3.28$ 3.27$ 3.28$
Low Growth_High Prices AECO 2023-2024 3.73$ 3.96$ 4.08$ 4.08$ 4.03$ 3.77$ 3.77$ 3.74$ 3.91$ 4.05$ 4.02$ 4.08$
Low Growth_High Prices AECO 2024-2025 4.32$ 4.44$ 4.52$ 4.54$ 4.35$ 4.12$ 4.16$ 4.26$ 4.35$ 4.39$ 4.33$ 4.33$
Low Growth_High Prices AECO 2025-2026 4.50$ 4.64$ 4.78$ 4.76$ 4.58$ 4.37$ 4.43$ 4.53$ 4.68$ 4.72$ 4.62$ 4.67$ Low Growth_High Prices AECO 2026-2027 4.84$ 5.04$ 5.17$ 5.18$ 5.04$ 4.88$ 4.85$ 5.02$ 5.16$ 5.21$ 5.14$ 5.15$
Low Growth_High Prices AECO 2027-2028 5.39$ 5.69$ 5.80$ 5.68$ 5.57$ 5.45$ 5.43$ 5.63$ 5.74$ 5.82$ 5.66$ 5.69$
Low Growth_High Prices AECO 2028-2029 5.86$ 6.09$ 6.17$ 6.27$ 6.10$ 5.95$ 5.98$ 6.02$ 6.19$ 6.26$ 6.14$ 6.25$
Low Growth_High Prices AECO 2029-2030 6.41$ 6.72$ 6.76$ 6.81$ 6.57$ 6.42$ 6.47$ 6.53$ 6.71$ 6.80$ 6.70$ 6.75$
Low Growth_High Prices AECO 2030-2031 6.78$ 7.08$ 7.21$ 7.23$ 6.98$ 6.72$ 6.83$ 6.91$ 7.16$ 7.24$ 7.12$ 7.15$
Low Growth_High Prices AECO 2031-2032 7.20$ 7.38$ 7.55$ 7.46$ 7.27$ 7.01$ 7.08$ 7.14$ 7.37$ 7.48$ 7.39$ 7.49$
Low Growth_High Prices AECO 2032-2033 7.52$ 7.89$ 7.99$ 8.00$ 7.76$ 7.50$ 7.55$ 7.61$ 7.94$ 8.00$ 7.87$ 7.87$ Low Growth_High Prices AECO 2033-2034 8.01$ 8.32$ 8.40$ 8.46$ 8.12$ 7.87$ 7.89$ 8.03$ 8.35$ 8.39$ 8.19$ 8.25$
Low Growth_High Prices AECO 2034-2035 8.42$ 8.67$ 8.88$ 8.86$ 8.59$ 8.35$ 8.30$ 8.43$ 8.72$ 8.85$ 8.64$ 8.52$
Low Growth_High Prices AECO 2035-2036 8.40$ 8.60$ 9.20$ 9.28$ 9.01$ 8.73$ 8.77$ 8.99$ 9.56$ 9.78$ 9.37$ 9.34$
Low Growth_High Prices AECO 2036-2037 9.53$ 10.04$ 10.16$ 10.23$ 9.69$ 9.12$ 9.15$ 9.32$ 9.86$ 9.99$ 9.52$ 9.38$
Low Growth_High Prices Malin 2017-2018 2.75$ 2.61$ 2.75$ 3.29$ 2.13$ 2.06$ 2.13$ 2.18$ 2.26$ 2.29$ 2.21$ 2.23$
Low Growth_High Prices Malin 2018-2019 2.53$ 2.82$ 2.86$ 2.82$ 2.66$ 2.31$ 2.23$ 2.27$ 2.35$ 2.38$ 2.34$ 2.30$ Low Growth_High Prices Malin 2019-2020 2.80$ 3.08$ 3.13$ 3.07$ 2.95$ 2.70$ 2.69$ 2.81$ 2.87$ 2.66$ 2.63$ 2.66$
Low Growth_High Prices Malin 2020-2021 3.08$ 3.29$ 3.51$ 3.47$ 3.22$ 3.01$ 2.95$ 2.98$ 3.15$ 3.19$ 3.18$ 3.18$
Low Growth_High Prices Malin 2021-2022 3.64$ 3.82$ 3.89$ 3.88$ 3.65$ 3.39$ 3.36$ 3.36$ 3.49$ 3.52$ 3.57$ 3.53$
Low Growth_High Prices Malin 2022-2023 3.97$ 4.19$ 4.26$ 4.23$ 4.07$ 3.72$ 3.72$ 3.76$ 3.84$ 3.95$ 3.96$ 3.95$
Low Growth_High Prices Malin 2023-2024 4.47$ 4.69$ 4.75$ 4.76$ 4.60$ 4.36$ 4.34$ 4.34$ 4.52$ 4.62$ 4.60$ 4.60$
Low Growth_High Prices Malin 2024-2025 5.00$ 5.15$ 5.22$ 5.23$ 5.01$ 4.77$ 4.74$ 4.80$ 4.91$ 4.95$ 4.94$ 4.89$
Low Growth_High Prices Malin 2025-2026 5.17$ 5.32$ 5.44$ 5.45$ 5.23$ 5.03$ 4.99$ 5.02$ 5.17$ 5.21$ 5.17$ 5.14$ Low Growth_High Prices Malin 2026-2027 5.41$ 5.65$ 5.75$ 5.77$ 5.55$ 5.38$ 5.32$ 5.48$ 5.69$ 5.68$ 5.66$ 5.63$
Low Growth_High Prices Malin 2027-2028 5.99$ 6.23$ 6.40$ 6.30$ 6.15$ 5.96$ 5.89$ 6.07$ 6.17$ 6.20$ 6.14$ 6.11$
Low Growth_High Prices Malin 2028-2029 6.39$ 6.62$ 6.75$ 6.75$ 6.57$ 6.38$ 6.37$ 6.42$ 6.59$ 6.64$ 6.58$ 6.63$
Low Growth_High Prices Malin 2029-2030 6.87$ 7.17$ 7.27$ 7.29$ 7.12$ 6.88$ 6.87$ 6.92$ 7.08$ 7.14$ 7.14$ 7.18$
Low Growth_High Prices Malin 2030-2031 7.34$ 7.59$ 7.76$ 7.73$ 7.51$ 7.21$ 7.25$ 7.33$ 7.57$ 7.64$ 7.54$ 7.55$
Low Growth_High Prices Malin 2031-2032 7.74$ 7.91$ 8.11$ 8.06$ 7.86$ 7.55$ 7.55$ 7.62$ 7.87$ 7.95$ 7.88$ 7.92$
Low Growth_High Prices Malin 2032-2033 8.09$ 8.41$ 8.51$ 8.51$ 8.29$ 8.01$ 8.02$ 8.09$ 8.44$ 8.47$ 8.33$ 8.33$ Low Growth_High Prices Malin 2033-2034 8.55$ 8.85$ 8.96$ 9.02$ 8.72$ 8.47$ 8.41$ 8.56$ 8.87$ 8.88$ 8.72$ 8.81$
Low Growth_High Prices Malin 2034-2035 9.02$ 9.25$ 9.47$ 9.48$ 9.16$ 8.92$ 8.82$ 8.96$ 9.23$ 9.35$ 9.18$ 9.15$
Low Growth_High Prices Malin 2035-2036 9.10$ 9.34$ 9.94$ 9.98$ 9.67$ 9.38$ 9.37$ 9.53$ 10.07$ 10.20$ 9.83$ 9.86$
Low Growth_High Prices Malin 2036-2037 10.22$ 10.80$ 10.87$ 10.92$ 10.35$ 9.76$ 9.72$ 9.81$ 10.32$ 10.41$ 9.96$ 9.98$
Low Growth_High Prices Rockies 2017-2018 2.70$ 2.50$ 3.07$ 3.23$ 2.05$ 1.99$ 2.04$ 2.09$ 2.15$ 2.18$ 2.10$ 2.13$
Low Growth_High Prices Rockies 2018-2019 2.45$ 2.72$ 2.93$ 2.77$ 2.61$ 2.25$ 2.16$ 2.21$ 2.26$ 2.29$ 2.25$ 2.21$ Low Growth_High Prices Rockies 2019-2020 2.72$ 2.98$ 3.19$ 3.01$ 2.90$ 2.64$ 2.63$ 2.74$ 2.79$ 2.57$ 2.54$ 2.57$
Low Growth_High Prices Rockies 2020-2021 2.99$ 3.18$ 3.57$ 3.41$ 3.16$ 2.96$ 2.89$ 2.91$ 3.03$ 3.08$ 3.06$ 3.06$
Low Growth_High Prices Rockies 2021-2022 3.52$ 3.70$ 3.77$ 3.78$ 3.58$ 3.33$ 3.29$ 3.29$ 3.38$ 3.40$ 3.45$ 3.41$
Low Growth_High Prices Rockies 2022-2023 3.84$ 4.06$ 4.13$ 4.10$ 3.99$ 3.60$ 3.63$ 3.66$ 3.71$ 3.82$ 3.83$ 3.81$
Low Growth_High Prices Rockies 2023-2024 4.32$ 4.54$ 4.61$ 4.61$ 4.52$ 4.26$ 4.24$ 4.24$ 4.39$ 4.48$ 4.46$ 4.46$
Low Growth_High Prices Rockies 2024-2025 4.82$ 4.99$ 5.06$ 5.08$ 4.86$ 4.63$ 4.63$ 4.68$ 4.77$ 4.80$ 4.79$ 4.74$
Low Growth_High Prices Rockies 2025-2026 4.98$ 5.16$ 5.28$ 5.30$ 5.07$ 4.88$ 4.86$ 4.89$ 5.03$ 5.06$ 5.02$ 5.00$ Low Growth_High Prices Rockies 2026-2027 5.26$ 5.50$ 5.60$ 5.61$ 5.40$ 5.24$ 5.20$ 5.35$ 5.54$ 5.53$ 5.51$ 5.47$
Low Growth_High Prices Rockies 2027-2028 5.83$ 6.07$ 6.23$ 6.14$ 5.99$ 5.81$ 5.80$ 5.98$ 6.02$ 6.04$ 5.99$ 5.95$
Low Growth_High Prices Rockies 2028-2029 6.23$ 6.46$ 6.58$ 6.59$ 6.41$ 6.26$ 6.29$ 6.33$ 6.44$ 6.47$ 6.41$ 6.46$
Low Growth_High Prices Rockies 2029-2030 6.69$ 6.98$ 7.08$ 7.11$ 6.97$ 6.75$ 6.77$ 6.81$ 6.93$ 6.97$ 6.97$ 7.00$
Low Growth_High Prices Rockies 2030-2031 7.16$ 7.40$ 7.57$ 7.54$ 7.36$ 7.10$ 7.14$ 7.22$ 7.39$ 7.45$ 7.35$ 7.36$
Low Growth_High Prices Rockies 2031-2032 7.54$ 7.70$ 7.91$ 7.85$ 7.69$ 7.43$ 7.43$ 7.50$ 7.71$ 7.77$ 7.68$ 7.72$
Low Growth_High Prices Rockies 2032-2033 7.89$ 8.20$ 8.29$ 8.30$ 8.11$ 7.89$ 7.89$ 7.97$ 8.27$ 8.29$ 8.13$ 8.13$ Low Growth_High Prices Rockies 2033-2034 8.35$ 8.63$ 8.74$ 8.80$ 8.53$ 8.34$ 8.28$ 8.43$ 8.70$ 8.68$ 8.51$ 8.60$
Low Growth_High Prices Rockies 2034-2035 8.81$ 9.03$ 9.25$ 9.25$ 8.96$ 8.79$ 8.68$ 8.82$ 9.05$ 9.15$ 8.97$ 8.94$
Low Growth_High Prices Rockies 2035-2036 8.88$ 9.11$ 9.71$ 9.75$ 9.47$ 9.24$ 9.22$ 9.38$ 9.89$ 9.99$ 9.61$ 9.64$
Low Growth_High Prices Rockies 2036-2037 9.99$ 10.56$ 10.63$ 10.67$ 10.14$ 9.61$ 9.56$ 9.66$ 10.13$ 10.20$ 9.73$ 9.75$
Nominal$
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 224 of 829
APPENDIX 6.1: MONTHLY PRICE DATA BY BASIN
LOW GROWTH HIGH PRICE

Low Growth_High Prices Stanfield 2017-2018 2.68$ 2.60$ 2.80$ 3.26$ 2.04$ 1.96$ 2.01$ 2.03$ 2.12$ 2.16$ 2.08$ 2.07$
Low Growth_High Prices Stanfield 2018-2019 2.50$ 2.80$ 2.83$ 2.79$ 2.63$ 2.19$ 2.12$ 2.17$ 2.20$ 2.20$ 2.19$ 2.15$
Low Growth_High Prices Stanfield 2019-2020 2.77$ 3.05$ 3.10$ 3.04$ 2.86$ 2.61$ 2.60$ 2.70$ 2.72$ 2.48$ 2.47$ 2.51$
Low Growth_High Prices Stanfield 2020-2021 3.04$ 3.25$ 3.47$ 3.43$ 3.15$ 2.94$ 2.86$ 2.87$ 2.98$ 3.00$ 3.01$ 3.03$
Low Growth_High Prices Stanfield 2021-2022 3.60$ 3.78$ 3.85$ 3.84$ 3.57$ 3.30$ 3.27$ 3.26$ 3.33$ 3.34$ 3.41$ 3.38$
Low Growth_High Prices Stanfield 2022-2023 3.93$ 4.15$ 4.22$ 4.19$ 4.03$ 3.64$ 3.63$ 3.66$ 3.67$ 3.76$ 3.79$ 3.81$
Low Growth_High Prices Stanfield 2023-2024 4.43$ 4.65$ 4.71$ 4.71$ 4.56$ 4.29$ 4.29$ 4.27$ 4.34$ 4.46$ 4.47$ 4.51$ Low Growth_High Prices Stanfield 2024-2025 4.96$ 5.10$ 5.18$ 5.19$ 4.97$ 4.73$ 4.69$ 4.75$ 4.76$ 4.76$ 4.80$ 4.76$
Low Growth_High Prices Stanfield 2025-2026 5.13$ 5.27$ 5.39$ 5.40$ 5.18$ 4.96$ 4.92$ 4.96$ 5.00$ 5.02$ 5.03$ 5.01$
Low Growth_High Prices Stanfield 2026-2027 5.37$ 5.61$ 5.71$ 5.72$ 5.51$ 5.30$ 5.26$ 5.42$ 5.51$ 5.49$ 5.52$ 5.49$
Low Growth_High Prices Stanfield 2027-2028 5.95$ 6.21$ 6.36$ 6.26$ 6.11$ 5.88$ 5.81$ 5.99$ 5.98$ 6.00$ 5.99$ 5.96$
Low Growth_High Prices Stanfield 2028-2029 6.35$ 6.58$ 6.73$ 6.71$ 6.52$ 6.29$ 6.29$ 6.33$ 6.39$ 6.44$ 6.39$ 6.46$
Low Growth_High Prices Stanfield 2029-2030 6.85$ 7.12$ 7.21$ 7.24$ 7.07$ 6.78$ 6.77$ 6.82$ 6.88$ 6.94$ 6.95$ 6.99$
Low Growth_High Prices Stanfield 2030-2031 7.29$ 7.54$ 7.70$ 7.70$ 7.46$ 7.10$ 7.13$ 7.22$ 7.37$ 7.44$ 7.33$ 7.35$ Low Growth_High Prices Stanfield 2031-2032 7.68$ 7.88$ 8.08$ 8.00$ 7.80$ 7.44$ 7.43$ 7.50$ 7.66$ 7.74$ 7.67$ 7.71$
Low Growth_High Prices Stanfield 2032-2033 8.04$ 8.35$ 8.45$ 8.46$ 8.23$ 7.88$ 7.89$ 7.97$ 8.23$ 8.26$ 8.12$ 8.13$
Low Growth_High Prices Stanfield 2033-2034 8.49$ 8.82$ 8.93$ 8.99$ 8.66$ 8.33$ 8.28$ 8.45$ 8.66$ 8.66$ 8.50$ 8.60$
Low Growth_High Prices Stanfield 2034-2035 8.97$ 9.22$ 9.44$ 9.45$ 9.09$ 8.78$ 8.68$ 8.82$ 9.01$ 9.13$ 8.96$ 8.93$
Low Growth_High Prices Stanfield 2035-2036 9.02$ 9.30$ 9.91$ 9.91$ 9.58$ 9.25$ 9.23$ 9.40$ 9.85$ 9.97$ 9.61$ 9.63$
Low Growth_High Prices Stanfield 2036-2037 10.16$ 10.72$ 10.79$ 10.84$ 10.28$ 9.61$ 9.56$ 9.64$ 10.09$ 10.18$ 9.73$ 9.75$
Low Growth_High Prices Sumas 2017-2018 2.69$ 2.78$ 2.72$ 3.20$ 1.98$ 1.80$ 1.75$ 1.80$ 1.98$ 2.01$ 2.01$ 2.10$ Low Growth_High Prices Sumas 2018-2019 2.77$ 3.11$ 3.13$ 2.98$ 2.54$ 1.95$ 1.93$ 2.09$ 2.31$ 2.29$ 2.30$ 2.33$
Low Growth_High Prices Sumas 2019-2020 2.89$ 3.44$ 3.47$ 3.24$ 2.70$ 2.26$ 2.24$ 2.24$ 2.38$ 2.41$ 2.40$ 2.52$
Low Growth_High Prices Sumas 2020-2021 3.04$ 3.38$ 3.48$ 3.29$ 3.00$ 2.51$ 2.50$ 2.52$ 2.74$ 2.76$ 2.73$ 2.80$
Low Growth_High Prices Sumas 2021-2022 3.43$ 3.85$ 3.91$ 3.80$ 3.52$ 2.91$ 2.92$ 2.89$ 3.08$ 3.10$ 3.17$ 3.21$
Low Growth_High Prices Sumas 2022-2023 3.77$ 4.22$ 4.25$ 4.09$ 3.84$ 3.24$ 3.27$ 3.29$ 3.43$ 3.53$ 3.57$ 3.61$
Low Growth_High Prices Sumas 2023-2024 4.25$ 4.72$ 4.80$ 4.67$ 4.43$ 3.98$ 3.98$ 3.93$ 4.22$ 4.39$ 4.39$ 4.43$
Low Growth_High Prices Sumas 2024-2025 4.79$ 5.12$ 5.17$ 5.06$ 4.70$ 4.33$ 4.35$ 4.46$ 4.69$ 4.76$ 4.72$ 4.72$ Low Growth_High Prices Sumas 2025-2026 4.98$ 5.33$ 5.42$ 5.28$ 4.94$ 4.59$ 4.65$ 4.76$ 5.05$ 5.08$ 5.01$ 5.05$
Low Growth_High Prices Sumas 2026-2027 5.31$ 5.78$ 5.81$ 5.64$ 5.34$ 5.08$ 5.05$ 5.14$ 5.46$ 5.51$ 5.47$ 5.48$
Low Growth_High Prices Sumas 2027-2028 5.86$ 6.42$ 6.49$ 6.23$ 5.92$ 5.63$ 5.60$ 5.78$ 6.02$ 6.10$ 5.99$ 6.02$
Low Growth_High Prices Sumas 2028-2029 6.33$ 6.82$ 6.89$ 6.85$ 6.49$ 6.17$ 6.19$ 6.21$ 6.51$ 6.58$ 6.49$ 6.62$
Low Growth_High Prices Sumas 2029-2030 6.90$ 7.48$ 7.50$ 7.41$ 6.99$ 6.66$ 6.70$ 6.75$ 7.06$ 7.16$ 7.09$ 7.15$
Low Growth_High Prices Sumas 2030-2031 7.32$ 7.87$ 7.97$ 7.85$ 7.41$ 6.98$ 7.09$ 7.15$ 7.53$ 7.60$ 7.52$ 7.55$
Low Growth_High Prices Sumas 2031-2032 7.76$ 8.19$ 8.32$ 8.08$ 7.70$ 7.26$ 7.32$ 7.37$ 7.73$ 7.84$ 7.78$ 7.89$ Low Growth_High Prices Sumas 2032-2033 8.06$ 8.69$ 8.75$ 8.62$ 8.19$ 7.75$ 7.79$ 7.84$ 8.31$ 8.37$ 8.27$ 8.29$ Low Growth_High Prices Sumas 2033-2034 8.55$ 9.12$ 9.15$ 9.07$ 8.53$ 8.11$ 8.13$ 8.24$ 8.70$ 8.74$ 8.57$ 8.64$
Low Growth_High Prices Sumas 2034-2035 8.95$ 9.46$ 9.62$ 9.47$ 8.98$ 8.58$ 8.51$ 8.62$ 9.05$ 9.18$ 9.01$ 8.90$
Low Growth_High Prices Sumas 2035-2036 8.95$ 9.39$ 9.94$ 9.88$ 9.41$ 8.96$ 8.99$ 9.20$ 9.90$ 10.11$ 9.73$ 9.71$
Low Growth_High Prices Sumas 2036-2037 10.04$ 10.81$ 10.90$ 10.82$ 10.08$ 9.35$ 9.38$ 9.52$ 10.19$ 10.32$ 9.88$ 9.77$
Nominal$
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 225 of 829
APPENDIX 6.2: WEIGHTED AVERAGE COST OF CAPITAL

From 2015 Rate Case Settlement
Cost of Capital Percent of
Total Capital Cost Component After Tax
L/T Debt 51.50% 5.20% 2.68% 1.74%

Common Equity 48.50% 9.50% 4.61% 4.61%

TOTAL 100.00%7.29% 6.35%
From 2017 Rate Case Settlement
Cost of Capital Percent of
Total Capital Cost Component
L/T Debt 50.00% 5.72% 2.86% 1.86%

Common Equity 50.00% 9.50% 4.75% 4.75%
TOTAL 100.00%7.61% 6.61%
From 2016 Rate Case Settlement
Cost of Capital Percent of
Total Capital Cost Component
L/T Debt 50.00% 5.30% 2.65% 1.72%
Common Equity 50.00% 9.40% 4.70% 4.70%
TOTAL 100.00%7.35% 6.42%
Gas Net Rate Base AMA Thru November 2017
WA 311,457$ 45%
ID 146,468$ 21%
OR 227,301$ 33%
685,226$
System Weighted Average Cost of Capital (Nominal)*6.45%
GDP price deflator 2.00%
Real After Tax WACC 4.36%
OREGON
WASHINGTON
IDAHO
Avista Corporation Captial Structure and Overall Rate of Return
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 226 of 829
APPENDIX 6.3: POTENTIAL SUPPLY SIDE RESOURCE OPTIONS

Additional Resource Size Availability Notes
Unsubscribed GTN Capacity Up to 50,000 Dth Now Currently available unsubscribed capacity from Kingsgate to
Spokane
Medford Lateral Exp 50,000 Dth / Day 2019 Additional compression to facilitate more gas to flow from
mainline GTN to Medford
WA ID OR
$48 / Dth $40 / Dth $46 / Dth
WA ID OR
$13 / Dth $13 / Dth $13 / Dth
WA ID OR
$11 / Dth $11 / Dth $12 / Dth
WA ID OR
$34 / Dth $39 / Dth $33 / Dth
WA ID OR
$19 / Dth $18 / Dth $19 / Dth
WA ID OR
$38 / Dth $39 / Dth $38 / Dth
Plymouth LNG
241,700 Dth
w/70,500 Dth deliverability 2018
Provides for peaking services and alleviates the need for costly pipeline expansions
Pair with excess pipeline MDDO’s to create firm transport
Hydrogen 166 Dth / Day 2020
Cost estimates obtained from a consultant; levelized cost
includes revenue requirements, expected carbon adder and
assumed retail power rate
Renewable Natural Gas –
Distributed Landfill 635 Dth / Day
NWP Rate
2020
Costs estimates obtained from a consultant for each specific
type of RNG; levelized costs include revenue requirements,
distribution costs, and projected carbon intensity adder/(savings)
2020Renewable Natural Gas – Dairy 635 Dth / Day
Renewable Natural Gas – Waste
Water 513 Dth / Day 2020
2020298 Dth / DayRenewable Natural Gas – Food Waste to (RNG)
Renewable Natural Gas –
Centralized Landfill 1,814 Dth / Day
Cost/Rates
GTN Rate
$35M capital + GTN Rate
2020
Future Supply Resources Size Cost/Rates Availability Notes
Co. Owned LNG
600,000 Dth w/
150,000 of
deliverability
$75 Million plus
$2 Million annual
O&M
2024
On site, in service territory
liquefaction and vaporization
facility
Various pipelines – Pacific
Connector, Cross-Cascades, etc.Varies Precedent
Agreement Rates 2022
Requires additional mainline
capacity on NWPL or GTN to
get to service territory
Large Scale LNG Varies Commodity less
Fuel 2024 Speculative, needs pipeline
transport
In Ground Storage Varies Varies Varies
Requires additional mainline
transport to get to service
territory
Satellite LNG Varies $13M capital cost
plus 665k O&M 2022
provides for peaking services
and alleviates the need for
costly pipeline expansions.
$3,000 per m3 with O&M
assumed at 5.4%.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 227 of 829
APPENDIX 6.4: EXPECTED CASE AVOIDED COST

Sc
e
n
a
r
i
o

G
a
s

Y
e
a
r

I
D

B
o
t
h

I
D

G
T
N

I
D

N
W
P

K
l
a
m

F
a
l
l
s

L
a

G
r
a
n
d
e

M
e
d
f
o
r
d

G
T
N

M
e
d
f
o
r
d

N
W
P

R
o
s
e
b
u
r
g

W
A

B
o
t
h

W
A

G
T
N

W
A

N
W
P

I
D

A
n
n
u
a
l

W
A

A
n
n
u
a
l

O
R

A
n
n
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a
l
Ex
p
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d

C
a
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2
0
1
7
-
2
0
1
8

1
.
4
1
$

1
.
3
1
$

2
.
6
6
$

1.4
2
$

2.
7
1
$

1.
4
2
$

1.4
2
$

1.
4
2
$

1
.
4
1
$

1
.
3
1
$

2
.
6
6
$

1.
7
9
$

1.
7
9
$

1.6
8
$

Ex
p
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C
a
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2
0
1
8
-
2
0
1
9

1
.
5
9
$

1
.
4
7
$

2
.
7
2
$

1.6
0
$

2.
7
5
$

1.
6
0
$

1.6
0
$

1.
6
0
$

1
.
7
7
$

1
.
6
5
$

2
.
9
0
$

1.
9
3
$

2.
1
0
$

1.8
3
$

Ex
p
e
c
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d

C
a
s
e

2
0
1
9
-
2
0
2
0

1
.
8
0
$

1
.
6
8
$

2
.
7
0
$

1.8
1
$

2.
7
3
$

1.
8
1
$

1.8
1
$

1.
8
1
$

2
.
3
3
$

2
.
2
1
$

3
.
2
3
$

2.
0
6
$

2.
5
9
$

1.9
9
$

Ex
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c
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d

C
a
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e

2
0
2
0
-
2
0
2
1

2
.
0
4
$

1
.
9
2
$

2
.
6
5
$

2.8
1
$

3.
4
7
$

2.
8
1
$

2.8
1
$

2.
8
1
$

2
.
6
6
$

2
.
5
4
$

3
.
2
6
$

2.
2
0
$

2.
8
2
$

2.9
5
$

Ex
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d

C
a
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e

2
0
2
1
-
2
0
2
2

2
.
2
8
$

2
.
2
0
$

2
.
6
9
$

3.3
0
$

3.
7
3
$

3.
3
0
$

3.3
0
$

3.
3
0
$

3
.
0
1
$

2
.
9
3
$

3
.
4
2
$

2.
3
9
$

3.
1
2
$

3.3
9
$

Ex
p
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d

C
a
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e

2
0
2
2
-
2
0
2
3

2
.
4
4
$

2
.
3
6
$

2
.
8
5
$

3.5
2
$

3.
9
5
$

3.
5
2
$

3.5
2
$

3.
5
2
$

3
.
2
7
$

3
.
1
9
$

3
.
6
8
$

2.
5
5
$

3.
3
8
$

3.6
1
$

Ex
p
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d

C
a
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e

2
0
2
3
-
2
0
2
4

2
.
8
9
$

2
.
7
8
$

3
.
3
7
$

4.0
4
$

4.
5
4
$

4.
0
4
$

4.0
4
$

4.
0
4
$

3
.
8
3
$

3
.
7
2
$

4
.
3
1
$

3.
0
2
$

3.
9
5
$

4.1
4
$

Ex
p
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c
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d

C
a
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2
0
2
4
-
2
0
2
5

3
.
1
2
$

3
.
0
1
$

3
.
6
8
$

4.3
5
$

4.
9
2
$

4.
3
5
$

4.3
5
$

4.
3
5
$

4
.
1
6
$

4
.
0
5
$

4
.
7
2
$

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2
7
$

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3
1
$

4.4
6
$

Ex
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d

C
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2
0
2
5
-
2
0
2
6

3
.
2
4
$

3
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1
3
$

3
.
7
8
$

4.5
6
$

5.
1
1
$

4.
5
6
$

4.5
6
$

4.
5
6
$

4
.
3
9
$

4
.
2
8
$

4
.
9
3
$

3.
3
8
$

4.
5
3
$

4.6
7
$

Ex
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d

C
a
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e

2
0
2
6
-
2
0
2
7

3
.
4
9
$

3
.
3
8
$

3
.
9
2
$

4.9
0
$

5.
3
3
$

4.
9
0
$

4.9
0
$

4.
9
0
$

4
.
7
5
$

4
.
6
4
$

5
.
1
7
$

3.
6
0
$

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8
5
$

4.9
9
$

Ex
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d

C
a
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2
0
2
7
-
2
0
2
8

3
.
8
2
$

3
.
7
1
$

4
.
2
6
$

5.3
2
$

5.
7
7
$

5.
3
2
$

5.3
2
$

5.
3
2
$

5
.
1
8
$

5
.
0
7
$

5
.
6
2
$

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9
3
$

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2
9
$

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1
$

Ex
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C
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2
0
2
8
-
2
0
2
9

4
.
1
1
$

4
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0
1
$

4
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4
9
$

5.7
4
$

6.
1
0
$

5.
7
4
$

5.7
4
$

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7
4
$

5
.
5
7
$

5
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4
7
$

5
.
9
5
$

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2
0
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6
7
$

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1
$

Ex
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2
0
2
9
-
2
0
3
0

4
.
4
2
$

4
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3
3
$

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7
9
$

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8
$

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5
2
$

6.
1
8
$

6.1
8
$

6.
1
8
$

5
.
9
9
$

5
.
9
0
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6
.
3
6
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5
1
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6.
0
9
$

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5
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Ex
p
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c
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C
a
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2
0
3
0
-
2
0
3
1

4
.
6
3
$

4
.
5
4
$

4
.
9
9
$

6.5
2
$

6.
8
4
$

6.
5
2
$

6.5
2
$

6.
5
2
$

6
.
2
2
$

6
.
1
3
$

6
.
5
8
$

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7
2
$

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3
1
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6.5
8
$

Ex
p
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c
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C
a
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2
0
3
1
-
2
0
3
2

4
.
7
7
$

4
.
6
7
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5
.
1
9
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6.7
8
$

7.
1
8
$

6.
7
8
$

6.7
8
$

6.
7
8
$

6
.
3
6
$

6
.
2
6
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6
.
7
8
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8
8
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4
7
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6
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Ex
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2
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3
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2
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3

5
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0
2
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4
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3
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4
4
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8
$

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5
6
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1
8
$

7.1
8
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1
8
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6
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6
1
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6
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5
2
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0
3
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1
3
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7
2
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6
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Ex
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2
0
3
3
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2
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3
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5
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2
1
$

5
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1
1
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5
.
6
7
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1
$

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9
4
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5
1
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1
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5
1
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6
.
8
0
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6
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7
0
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2
6
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3
3
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9
2
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0
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Ex
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2
0
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9
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3
2
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8
8
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8
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0
1
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9
0
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4
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5
4
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1
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2
0
3
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3
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5
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6
6
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5
5
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6
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1
4
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2
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7
1
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2
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2
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1
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7
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2
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3
6
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3
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5
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9
4
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6
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2
1
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8.7
6
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8.
9
7
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8.
7
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4
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7
4
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7
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5
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7
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4
4
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8
1
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0
0
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5
9
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8.7
9
$

Sc
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G
a
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Y
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a
r

I
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B
o
t
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I
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G
T
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I
D

N
W
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F
a
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L
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G
r
a
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M
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f
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f
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b
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6
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1
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1
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.
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1
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1
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1
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2
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6
7
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7
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7
6
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0
7
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0
7
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.
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2
.
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0
6
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0
6
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1
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8
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2
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2
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2
.
6
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2
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3
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3
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3
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2
4
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7
7
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0
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8
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0
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7
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3
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0
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3
0
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.
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1
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7
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1
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1
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8
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4
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2
0
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.
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.
8
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4
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9
8
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7
4
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4
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7
4
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3
7
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5
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6
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6
3
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3
8
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$

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7
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1
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3
1
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6
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4
6
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1
6
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6
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1
6
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3
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8
2
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0
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2
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3
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1
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5
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.
6
3
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4.5
8
$

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8
4
$

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5
8
$

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8
$

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5
8
$

4
.
2
6
$

4
.
0
0
$

4
.
5
8
$

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3
3
$

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2
8
$

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3
$

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a
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e

2
0
2
5
-
2
0
2
6

3
.
3
9
$

3
.
1
1
$

3
.
7
4
$

4.7
5
$

5.
0
2
$

4.
7
5
$

4.7
5
$

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7
5
$

4
.
4
5
$

4
.
1
7
$

4
.
8
0
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4
1
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4
7
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0
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2
0
2
6
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2
0
2
7

3
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5
8
$

3
.
3
1
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3
.
8
6
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4.9
8
$

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2
3
$

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9
8
$

4.9
8
$

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9
8
$

4
.
7
5
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4
.
4
7
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5
.
0
2
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3.
5
8
$

4.
7
5
$

5.0
3
$

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2
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0
2
8

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.
9
3
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3
.
6
6
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4
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2
0
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1
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6
5
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4
1
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1
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4
1
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5
.
2
0
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4
.
9
4
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5
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4
8
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9
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2
1
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p
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8
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1
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4
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9
8
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7
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9
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7
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5
7
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2
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1
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5
7
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3
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7
8
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4
4
$

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2
8
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2
8
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6
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0
4
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8
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2
7
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5
5
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0
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1
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a
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2
0
3
0
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2
0
3
1

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.
7
4
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4
.
4
9
$

4
.
9
7
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6.6
1
$

6.
7
7
$

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6
1
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1
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6
1
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6
.
3
3
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6
.
0
8
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6
.
5
7
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7
4
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3
3
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4
$

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0
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-
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0
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2

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9
3
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6
8
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1
4
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2
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0
7
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9
2
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2
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9
2
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5
2
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2
7
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7
3
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9
2
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5
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0
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3

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1
4
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8
9
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4
1
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8
$

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4
7
$

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2
8
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7.2
8
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7.
2
8
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6
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7
4
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9
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0
1
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1
5
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7
4
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2
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2
0
3
3
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0
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4

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.
3
8
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1
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6
2
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5
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8
2
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6
5
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5
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6
5
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9
7
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2
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3
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9
7
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9
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p
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2
0
3
4
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5
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5
6
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3
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8
4
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0
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1
7
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0
0
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0
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0
0
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7
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1
6
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9
1
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4
3
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5
7
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1
6
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3
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2
0
3
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.
4
7
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1
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6
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0
8
$

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1
$

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5
2
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2
1
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1
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2
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0
6
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7
7
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7
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6
7
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5
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1
7
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7
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2
0
3
6
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3
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1
9
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9
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4
3
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8.9
7
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1
4
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9
7
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7
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9
7
$

7
.
7
8
$

7
.
5
3
$

8
.
0
2
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6.
1
8
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7.
7
8
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9.0
0
$

1/

A
v
o
i
d
e
d

c
o
s
t
s

a
r
e

b
e
f
o
r
e

E
n
v
i
r
o
n
m
e
n
t
a
l

E
x
t
e
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n
a
l
i
t
i
e
s

a
d
d
e
r
.
An
n
u
a
l

A
v
o
i
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e
d

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o
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s

1
/
No
m
i
n
a
l
$
Wi
n
t
e
r

A
v
o
i
d
e
d

C
o
s
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s

1
/
No
m
i
n
a
l
$
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 228 of 829
APPENDIX 6.4: LOW GROWTH CASE AVOIDED COST

Sc
e
n
a
r
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o

G
a
s

Y
e
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r

I
D

B
o
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h

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T
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I
D

N
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a

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a
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e
d
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a
l

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7
-
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0
1
8

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.
4
1
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3
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.
7
9
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2
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8
3
$

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4
2
$

1.4
2
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4
2
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.
4
1
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1
.
3
1
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.
7
9
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8
4
$

1.8
4
$

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0
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Lo
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2
0
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0
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7
6
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6
4
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8
6
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6
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8
9
$

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7
6
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6
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7
6
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.
9
3
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8
2
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3
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0
4
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0
9
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7
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8
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2
0
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1
4
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9
7
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3
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9
9
$

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1
3
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3
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1
3
$

2
.
6
7
$

2
.
5
6
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3
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5
0
$

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3
8
$

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1
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1
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Lo
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H
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h

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r
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s

2
0
2
0
-
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0
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1

2
.
5
6
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2
.
4
7
$

3
.
1
5
$

3.3
5
$

3.
9
6
$

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3
5
$

3.3
5
$

3.
3
5
$

3
.
1
8
$

3
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0
9
$

3
.
7
7
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7
2
$

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4
$

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$

Lo
w

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2
0
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9
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4
1
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6
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4
4
$

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0
6
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6
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0
6
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3
.
7
5
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.
6
9
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4
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1
4
$

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1
3
$

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6
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4
$

Lo
w

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h

&

H
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2
0
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-
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0
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3

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4
2
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3
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3
6
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8
2
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3
$

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9
2
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5
3
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3
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5
3
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4
.
2
5
$

4
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1
9
$

4
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6
5
$

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5
3
$

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6
$

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1
$

Lo
w

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h

&

H
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r
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2
0
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2
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1
1
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0
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5
9
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$

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7
6
$

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2
8
$

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2
8
$

5
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0
5
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2
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8
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Lo
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2
0
2
4
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0
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4
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5
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4
3
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5
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0
8
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3
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7
8
$

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8
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7
8
$

5
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5
7
$

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4
7
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6
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1
3
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6
8
$

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2
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$

Lo
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2
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6
2
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1
4
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4
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1
4
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5
.
9
4
$

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4
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6
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4
5
$

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9
3
$

6.0
8
$

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4
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Lo
w

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H
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r
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2
0
2
6
-
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5
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0
4
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6
9
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6
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6
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4
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1
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3
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2
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7
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3
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3
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9
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6
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2
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9
8
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9
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7
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7
7
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1
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4
0
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6
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4
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Lo
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2
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9
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6
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9
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2
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5
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4
0
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1
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1
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2
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3
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1
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2
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Lo
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2
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0
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8
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6
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6
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2
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6
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Lo
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5
9
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1
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9
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2
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2
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7
9
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0
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7
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w

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r
i
c
e
s

2
0
3
5
-
2
0
3
6

9
.
3
3
$

9
.
2
6
$

9
.
8
2
$

12
.
0
6
$

12
.
3
8
$

12
.
0
6
$

12
.
0
6
$

12
.
0
6
$

1
0
.
9
3
$

1
0
.
8
5
$

1
1
.
4
1
$

9.
4
7
$

11
.
0
6
$

12
.
1
2
$

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
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e
s

2
0
3
6
-
2
0
3
7

9
.
8
7
$

9
.
8
5
$

1
0
.
1
5
$

12
.
7
9
$

12
.
9
3
$

12
.
7
8
$

12
.
7
8
$

12
.
7
8
$

1
1
.
4
6
$

1
1
.
4
4
$

1
1
.
7
4
$

9.
9
6
$

11
.
5
5
$

12
.
8
1
$

Sc
e
n
a
r
i
o

G
a
s

Y
e
a
r

I
D

B
o
t
h

I
D

G
T
N

I
D

N
W
P

K
l
a
m

F
a
l
l
s

L
a

G
r
a
n
d
e

M
e
d
f
o
r
d

G
T
N

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e
d
f
o
r
d

N
W
P

R
o
s
e
b
u
r
g

W
A

B
o
t
h

W
A

G
T
N

W
A

N
W
P

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D

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n
n
u
a
l

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A

A
n
n
u
a
l

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R

A
n
n
u
a
l
Lo
w

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r
o
w
t
h

&

H
i
g
h

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r
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e
s

2
0
1
7
-
2
0
1
8

1
.
9
9
$

1
.
7
1
$

2
.
7
2
$

2.1
2
$

2.
7
8
$

2.
1
2
$

2.1
2
$

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1
2
$

1
.
9
9
$

1
.
7
1
$

2
.
7
2
$

(2
.
1
4
)
$

(2
.
1
4
)
$

(2
.
2
6
)
$

Lo
w

G
r
o
w
t
h

&

H
i
g
h

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r
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s

2
0
1
8
-
2
0
1
9

2
.
0
8
$

1
.
7
8
$

2
.
8
2
$

2.1
8
$

2.
8
9
$

2.
1
8
$

2.1
8
$

2.
1
8
$

2
.
0
8
$

1
.
7
8
$

2
.
8
2
$

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.
2
3
)
$

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.
2
3
)
$

(2
.
3
2
)
$

Lo
w

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r
o
w
t
h

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H
i
g
h

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r
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e
s

2
0
1
9
-
2
0
2
0

2
.
4
5
$

2
.
1
8
$

2
.
9
2
$

2.5
3
$

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9
9
$

2.
5
3
$

2.5
3
$

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5
3
$

2
.
9
8
$

2
.
7
1
$

3
.
4
5
$

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.
5
2
)
$

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.
0
5
)
$

(2
.
6
2
)
$

Lo
w

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r
o
w
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h

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H
i
g
h

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r
i
c
e
s

2
0
2
0
-
2
0
2
1

2
.
7
2
$

2
.
4
5
$

3
.
0
9
$

2.7
7
$

3.
1
6
$

2.
7
7
$

2.7
7
$

2.
7
7
$

3
.
2
5
$

2
.
9
8
$

3
.
6
2
$

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.
7
5
)
$

(3
.
2
8
)
$

(2
.
8
5
)
$

Lo
w

G
r
o
w
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h

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H
i
g
h

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r
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s

2
0
2
1
-
2
0
2
2

3
.
1
9
$

3
.
0
2
$

3
.
3
7
$

4.2
0
$

4.
4
0
$

4.
2
0
$

4.2
0
$

4.
2
0
$

3
.
8
3
$

3
.
6
6
$

4
.
0
1
$

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.
1
9
)
$

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.
8
3
)
$

(4
.
2
4
)
$

Lo
w

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r
o
w
t
h

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H
i
g
h

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r
i
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e
s

2
0
2
2
-
2
0
2
3

3
.
5
8
$

3
.
4
1
$

3
.
7
8
$

4.6
6
$

4.
8
7
$

4.
6
6
$

4.6
6
$

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6
6
$

4
.
3
2
$

4
.
1
6
$

4
.
5
2
$

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.
5
9
)
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.
3
3
)
$

(4
.
7
0
)
$

Lo
w

G
r
o
w
t
h

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H
i
g
h

P
r
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e
s

2
0
2
3
-
2
0
2
4

4
.
1
7
$

3
.
9
2
$

4
.
5
3
$

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3
$

5.
6
6
$

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3
3
$

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3
$

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3
3
$

5
.
0
2
$

4
.
7
7
$

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3
8
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.
2
1
)
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.
0
6
)
$

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.
4
0
)
$

Lo
w

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h

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s

2
0
2
4
-
2
0
2
5

4
.
7
1
$

4
.
4
7
$

5
.
0
3
$

5.9
6
$

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2
4
$

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9
6
$

5.9
6
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9
6
$

5
.
6
7
$

5
.
4
2
$

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.
9
9
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.
7
4
)
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6
9
)
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.
0
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Lo
w

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0
2
5
-
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2
6

4
.
9
0
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.
6
6
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5
.
2
5
$

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5
$

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5
3
$

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2
5
$

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5
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2
5
$

5
.
9
6
$

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.
7
2
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.
3
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.
9
4
)
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.
0
0
)
$

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.
3
0
)
$

Lo
w

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r
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h

&

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r
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2
0
2
6
-
2
0
2
7

5
.
2
7
$

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.
0
3
$

5
.
5
6
$

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7
$

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9
2
$

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6
7
$

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7
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6
7
$

6
.
4
3
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2
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.
7
3
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2
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4
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)
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7
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)
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Lo
w

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h

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2
0
2
7
-
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0
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8

5
.
8
8
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.
6
5
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6
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2
0
$

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6
$

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6
4
$

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3
6
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6
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3
6
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.
1
5
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.
9
3
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.
4
7
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.
9
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.
1
8
)
$

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.
4
2
)
$

Lo
w

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h

&

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r
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s

2
0
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8
-
2
0
2
9

6
.
3
2
$

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1
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$

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.
6
0
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0
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1
4
$

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9
0
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9
0
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.
7
0
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4
8
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.
9
8
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3
4
)
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7
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)
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.
9
5
)
$

Lo
w

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h

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r
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2
0
2
9
-
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0
3
0

6
.
8
8
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.
6
9
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7
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1
2
$

8.5
8
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8.
7
5
$

8.
5
8
$

8.5
8
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8.
5
8
$

8
.
3
6
$

8
.
1
8
$

8
.
6
0
$

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.
9
0
)
$

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.
3
8
)
$

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.
6
1
)
$

Lo
w

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r
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w
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h

&

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h

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r
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s

2
0
3
0
-
2
0
3
1

7
.
2
4
$

7
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0
7
$

7
.
5
2
$

9.1
2
$

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3
0
$

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1
2
$

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2
$

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1
2
$

8
.
8
3
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8
.
6
6
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.
1
1
$

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2
8
)
$

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.
8
7
)
$

(9
.
1
5
)
$

Lo
w

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r
o
w
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h

&

H
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g
h

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r
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s

2
0
3
1
-
2
0
3
2

7
.
6
1
$

7
.
4
3
$

7
.
8
6
$

9.6
2
$

9.
7
7
$

9.
6
2
$

9.6
2
$

9.
6
2
$

9
.
2
1
$

9
.
0
3
$

9
.
4
5
$

(7
.
6
3
)
$

(9
.
2
3
)
$

(9
.
6
5
)
$

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
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s

2
0
3
2
-
2
0
3
3

8
.
0
2
$

7
.
8
6
$

8
.
3
3
$

10
.
1
4
$

10
.
3
4
$

10
.
1
4
$

10
.
1
4
$

10
.
1
4
$

9.
6
1
$

9
.
4
5
$

9
.
9
2
$

(8
.
0
7
)
$

(9
.
6
6
)
$

(1
0
.
1
8
)
$

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
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c
e
s

2
0
3
3
-
2
0
3
4

8
.
4
9
$

8
.
3
2
$

8
.
7
6
$

10
.
7
9
$

10
.
9
5
$

10
.
7
9
$

10
.
7
9
$

10
.
7
9
$

1
0
.
0
8
$

9.9
2
$

1
0
.
3
5
$

(8
.
5
2
)
$

(1
0
.
1
1
)
$

(1
0
.
8
2
)
$

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
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c
e
s

2
0
3
4
-
2
0
3
5

8
.
8
8
$

8
.
7
1
$

9
.
1
4
$

11
.
3
7
$

11
.
5
2
$

11
.
3
7
$

11
.
3
7
$

11
.
3
7
$

1
0
.
4
7
$

1
0
.
3
0
$

1
0
.
7
4
$

(8
.
9
1
)
$

(1
0
.
5
0
)
$

(1
1
.
4
0
)
$

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s

2
0
3
5
-
2
0
3
6

8
.
8
9
$

8
.
6
7
$

9
.
6
1
$

11
.
6
8
$

12
.
0
5
$

11
.
6
8
$

11
.
6
8
$

11
.
6
8
$

1
0
.
4
8
$

1
0
.
2
6
$

1
1
.
2
0
$

(9
.
0
6
)
$

(1
0
.
6
5
)
$

(1
1
.
7
5
)
$

Lo
w

G
r
o
w
t
h

&

H
i
g
h

P
r
i
c
e
s

2
0
3
6
-
2
0
3
7

1
0
.
0
5
$

9.
9
8
$

1
0
.
3
2
$

13
.
0
0
$

13
.
1
4
$

13
.
0
0
$

13
.
0
0
$

13
.
0
0
$

1
1
.
6
4
$

1
1
.
5
7
$

1
1
.
9
1
$

(1
0
.
1
2
)
$

(1
1
.
7
1
)
$

(1
3
.
0
2
)
$

1/
A
v
o
i
d
e
d

c
o
s
t
s

a
r
e

b
e
f
o
r
e

E
n
v
i
r
o
n
m
e
n
t
a
l

E
x
t
e
r
n
a
l
i
t
i
e
s

a
d
d
e
r
.
An
n
u
a
l

A
v
o
i
d
e
d

C
o
s
t
s

1
/
No
m
i
n
a
l
$
Win
t
e
r

A
v
o
i
d
e
d

C
o
s
t
s

1
/
No
m
i
n
a
l
$
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 229 of 829
APPENDIX 6.4: HIGH GROWTH CASE AVOIDED COST

Sc
e
n
a
r
i
o

G
a
s

Y
e
a
r

I
D

B
o
t
h

I
D

G
T
N

I
D

N
W
P

K
l
a
m

F
a
l
l
s

L
a

G
r
a
n
d
e

M
e
d
f
o
r
d

G
T
N

M
e
d
f
o
r
d

N
W
P

R
o
s
e
b
u
r
g

W
A

B
o
t
h

W
A

G
T
N

W
A

N
W
P

I
D

A
n
n
u
a
l

W
A

A
n
n
u
a
l

O
R

A
n
n
u
a
l
Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
1
7
-
2
0
1
8

1
.
4
2
$

1
.
3
1
$

2
.
6
7
$

1.4
4
$

2.7
2
$

1.4
4
$

1.4
4
$

1.4
4
$

1
.
4
2
$

1
.
3
1
$

2
.
6
7
$

1.8
0
$

1.
8
0
$

1.6
9
$

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
1
8
-
2
0
1
9

1
.
4
3
$

1
.
3
0
$

2
.
6
3
$

1.4
5
$

2.6
7
$

1.4
5
$

1.4
5
$

1.4
5
$

1
.
4
3
$

1
.
3
0
$

2
.
6
3
$

1.7
9
$

1.
7
9
$

1.7
0
$

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
1
9
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3
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2
.
2
3
$

1
.
9
3
$

2
.
4
3
$

2.2
8
$

2.4
7
$

2.2
8
$

2.2
8
$

2.2
8
$

2
.
2
3
$

1
.
9
3
$

2
.
4
3
$

2.2
0
$

2.
2
0
$

2.3
2
$

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
3
0
-
2
0
3
1

2
.
2
2
$

1
.
9
2
$

2
.
4
6
$

2.3
0
$

2.5
3
$

2.3
0
$

2.3
0
$

2.3
0
$

2
.
2
2
$

1
.
9
2
$

2
.
4
6
$

2.2
0
$

2.
2
0
$

2.3
5
$

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
3
1
-
2
0
3
2

2
.
2
5
$

1
.
9
2
$

2
.
4
7
$

2.3
1
$

2.5
2
$

2.3
1
$

2.3
1
$

2.3
1
$

2
.
2
5
$

1
.
9
2
$

2
.
4
7
$

2.2
1
$

2.
2
1
$

2.3
6
$

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
3
2
-
2
0
3
3

2
.
2
6
$

1
.
9
3
$

2
.
4
8
$

2.3
5
$

2.5
5
$

2.3
5
$

2.3
5
$

2.3
5
$

2
.
2
6
$

1
.
9
3
$

2
.
4
8
$

2.2
3
$

2.
2
3
$

2.3
9
$

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
3
3
-
2
0
3
4

2
.
2
7
$

1
.
9
4
$

2
.
5
0
$

2.3
6
$

2.5
5
$

2.3
6
$

2.3
6
$

2.3
6
$

2
.
2
7
$

1
.
9
4
$

2
.
5
0
$

2.2
4
$

2.
2
4
$

2.4
0
$

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
3
4
-
2
0
3
5

2
.
2
5
$

1
.
9
2
$

2
.
5
1
$

2.3
8
$

2.5
9
$

2.3
8
$

2.3
8
$

2.3
8
$

2
.
2
5
$

1
.
9
2
$

2
.
5
1
$

2.2
3
$

2.
2
3
$

2.4
2
$

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
3
5
-
2
0
3
6

2
.
0
6
$

1
.
7
0
$

2
.
5
2
$

2.3
2
$

2.6
2
$

2.3
2
$

2.3
2
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2.3
2
$

2
.
0
6
$

1
.
7
0
$

2
.
5
2
$

2.0
9
$

2.
0
9
$

2.3
8
$

Hig
h

G
r
o
w
t
h

&

L
o
w

P
r
i
c
e
s

2
0
3
6
-
2
0
3
7

2
.
2
3
$

1
.
9
0
$

2
.
4
8
$

2.3
7
$

2.7
3
$

20
.
4
1
$

20
.
4
1
$

20
.
4
1
$

2.
2
3
$

1
.
9
0
$

2
.
4
8
$

2.2
0
$

2.
2
0
$

13
.
2
7
$

1/
A
v
o
i
d
e
d

c
o
s
t
s

a
r
e

b
e
f
o
r
e

E
n
v
i
r
o
n
m
e
n
t
a
l

E
x
t
e
r
n
a
l
i
t
i
e
s

a
d
d
e
r
.
An
n
u
a
l

A
v
o
i
d
e
d

C
o
s
t
s

1
/
No
m
i
n
a
l
$
Wi
n
t
e
r

A
v
o
i
d
e
d

C
o
s
t
s

1
/
No
m
i
n
a
l
$
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 230 of 829
APPENDIX 6.4: AVERAGE CASE AVOIDED COST

Sc
e
n
a
r
i
o

G
a
s

Y
e
a
r

I
D

B
o
t
h

I
D

G
T
N

I
D

N
W
P

K
l
a
m

F
a
l
l
s

L
a

G
r
a
n
d
e

M
e
d
f
o
r
d

G
T
N

M
e
d
f
o
r
d

N
W
P

R
o
s
e
b
u
r
g

W
A

B
o
t
h

W
A

G
T
N

W
A

N
W
P

I
D

A
n
n
u
a
l

W
A

A
n
n
u
a
l

O
R

A
n
n
u
a
l
Av
e
r
a
g
e

C
a
s
e

2
0
1
7
-
2
0
1
8

1
.
4
0
$

1
.
3
1
$

2
.
6
3
$

1.
3
9
$

2.
6
4
$

1.
3
9
$

1.3
9
$

1.
3
9
$

1
.
4
0
$

1
.
3
1
$

2
.
6
3
$

1.7
8
$

1.7
8
$

1.
6
4
$

Av
e
r
a
g
e

C
a
s
e

2
0
1
8
-
2
0
1
9

1
.
5
7
$

1
.
4
7
$

2
.
6
8
$

1.
5
6
$

2.
7
0
$

1.
5
6
$

1.5
6
$

1.
5
6
$

1
.
7
5
$

1
.
6
5
$

2
.
8
6
$

1.9
1
$

2.0
9
$

1.
7
8
$

Av
e
r
a
g
e

C
a
s
e

2
0
1
9
-
2
0
2
0

1
.
7
8
$

1
.
6
8
$

2
.
6
9
$

1.
7
6
$

2.
7
0
$

1.
7
6
$

1.7
6
$

1.
7
6
$

2
.
3
1
$

2
.
2
1
$

3
.
2
2
$

2.0
5
$

2.5
8
$

1.
9
5
$

Av
e
r
a
g
e

C
a
s
e

2
0
2
0
-
2
0
2
1

2
.
0
3
$

1
.
9
2
$

2
.
6
5
$

2.
7
7
$

3.
4
5
$

2.
7
7
$

2.7
7
$

2.
7
7
$

2
.
6
4
$

2
.
5
4
$

3
.
2
7
$

2.2
0
$

2.8
2
$

2.
9
1
$

Av
e
r
a
g
e

C
a
s
e

2
0
2
1
-
2
0
2
2

2
.
2
8
$

2
.
2
0
$

2
.
6
9
$

3.
2
6
$

3.
7
0
$

3.
2
6
$

3.2
6
$

3.
2
6
$

3
.
0
0
$

2
.
9
3
$

3
.
4
1
$

2.3
9
$

3.1
1
$

3.
3
5
$

Av
e
r
a
g
e

C
a
s
e

2
0
2
2
-
2
0
2
3

2
.
4
2
$

2
.
3
6
$

2
.
8
2
$

3.
4
9
$

3.
9
0
$

3.
4
9
$

3.4
9
$

3.
4
9
$

3
.
2
5
$

3
.
1
9
$

3
.
6
5
$

2.5
3
$

3.3
6
$

3.
5
7
$

Av
e
r
a
g
e

C
a
s
e

2
0
2
3
-
2
0
2
4

2
.
8
8
$

2
.
7
8
$

3
.
3
7
$

4.
0
0
$

4.
5
2
$

4.
0
0
$

4.0
0
$

4.
0
0
$

3
.
8
2
$

3
.
7
2
$

4
.
3
1
$

3.0
1
$

3.9
5
$

4.
1
0
$

Av
e
r
a
g
e

C
a
s
e

2
0
2
4
-
2
0
2
5

3
.
1
1
$

3
.
0
1
$

3
.
6
5
$

4.
3
0
$

4.
8
8
$

4.
3
0
$

4.3
0
$

4.
3
0
$

4
.
1
5
$

4
.
0
5
$

4
.
6
9
$

3.2
6
$

4.3
0
$

4.
4
2
$

Av
e
r
a
g
e

C
a
s
e

2
0
2
5
-
2
0
2
6

3
.
2
3
$

3
.
1
3
$

3
.
7
6
$

4.
5
1
$

5.
0
7
$

4.
5
1
$

4.5
1
$

4.
5
1
$

4
.
3
8
$

4
.
2
8
$

4
.
9
1
$

3.3
7
$

4.5
2
$

4.
6
2
$

Av
e
r
a
g
e

C
a
s
e

2
0
2
6
-
2
0
2
7

3
.
4
8
$

3
.
3
8
$

3
.
9
1
$

4.
8
6
$

5.
3
2
$

4.
8
6
$

4.8
6
$

4.
8
6
$

4
.
7
4
$

4
.
6
4
$

5
.
1
7
$

3.5
9
$

4.8
5
$

4.
9
5
$

Av
e
r
a
g
e

C
a
s
e

2
0
2
7
-
2
0
2
8

3
.
8
1
$

3
.
7
1
$

4
.
2
4
$

5.
2
9
$

5.
7
5
$

5.
2
9
$

5.2
9
$

5.
2
9
$

5
.
1
7
$

5
.
0
7
$

5
.
6
0
$

3.9
2
$

5.2
8
$

5.
3
8
$

Av
e
r
a
g
e

C
a
s
e

2
0
2
8
-
2
0
2
9

4
.
1
0
$

4
.
0
1
$

4
.
4
7
$

5.
7
1
$

6.
0
8
$

5.
7
1
$

5.7
1
$

5.
7
1
$

5
.
5
7
$

5
.
4
7
$

5
.
9
4
$

4.1
9
$

5.6
6
$

5.
7
9
$

Av
e
r
a
g
e

C
a
s
e

2
0
2
9
-
2
0
3
0

4
.
4
0
$

4
.
3
3
$

4
.
7
7
$

6.
1
6
$

6.
4
9
$

6.
1
6
$

6.1
6
$

6.
1
6
$

5
.
9
8
$

5
.
9
0
$

6
.
3
4
$

4.5
0
$

6.0
7
$

6.
2
2
$

Av
e
r
a
g
e

C
a
s
e

2
0
3
0
-
2
0
3
1

4
.
6
2
$

4
.
5
4
$

4
.
9
7
$

6.
5
0
$

6.
8
2
$

6.
5
0
$

6.5
0
$

6.
5
0
$

6
.
2
1
$

6
.
1
3
$

6
.
5
7
$

4.7
1
$

6.3
0
$

6.
5
6
$

Av
e
r
a
g
e

C
a
s
e

2
0
3
1
-
2
0
3
2

4
.
7
7
$

4
.
6
7
$

5
.
1
8
$

6.
7
6
$

7.
1
6
$

6.
7
6
$

6.7
6
$

6.
7
6
$

6
.
3
6
$

6
.
2
6
$

6
.
7
8
$

4.8
7
$

6.4
6
$

6.
8
4
$

Av
e
r
a
g
e

C
a
s
e

2
0
3
2
-
2
0
3
3

5
.
0
1
$

4
.
9
3
$

5
.
4
2
$

7.
1
6
$

7.
5
3
$

7.
1
6
$

7.1
6
$

7.
1
6
$

6
.
6
0
$

6
.
5
2
$

7
.
0
2
$

5.1
2
$

6.7
1
$

7.
2
3
$

Av
e
r
a
g
e

C
a
s
e

2
0
3
3
-
2
0
3
4

5
.
2
1
$

5
.
1
1
$

5
.
6
7
$

7.
5
0
$

7.
9
3
$

7.
5
0
$

7.5
0
$

7.
5
0
$

6
.
8
0
$

6
.
7
0
$

7
.
2
6
$

5.3
3
$

6.9
2
$

7.
5
8
$

Av
e
r
a
g
e

C
a
s
e

2
0
3
4
-
2
0
3
5

5
.
4
0
$

5
.
3
1
$

5
.
8
6
$

7.
8
7
$

8.
2
8
$

7.
8
7
$

7.8
7
$

7.
8
7
$

7
.
0
0
$

6
.
9
0
$

7
.
4
5
$

5.5
2
$

7.1
2
$

7.
9
5
$

Av
e
r
a
g
e

C
a
s
e

2
0
3
5
-
2
0
3
6

5
.
6
5
$

5
.
5
5
$

6
.
1
2
$

8.
3
1
$

8.
6
9
$

8.
3
1
$

8.3
1
$

8.
3
1
$

7
.
2
4
$

7
.
1
4
$

7
.
7
1
$

5.7
7
$

7.3
6
$

8.
3
9
$

Av
e
r
a
g
e

C
a
s
e

2
0
3
6
-
2
0
3
7

5
.
8
9
$

5
.
8
5
$

6
.
1
5
$

8.
7
4
$

8.
9
4
$

8.
7
3
$

8.7
3
$

8.
7
3
$

7
.
4
8
$

7
.
4
4
$

7
.
7
4
$

5.9
6
$

7.5
5
$

8.
7
7
$

Sc
e
n
a
r
i
o

G
a
s

Y
e
a
r

I
D

B
o
t
h

I
D

G
T
N

I
D

N
W
P

K
l
a
m

F
a
l
l
s

L
a

G
r
a
n
d
e

M
e
d
f
o
r
d

G
T
N

M
e
d
f
o
r
d

N
W
P

R
o
s
e
b
u
r
g

W
A

B
o
t
h

W
A

G
T
N

W
A

N
W
P

I
D

A
n
n
u
a
l

W
A

A
n
n
u
a
l

O
R

A
n
n
u
a
l
Av
e
r
a
g
e

C
a
s
e

2
0
1
7
-
2
0
1
8

1
.
9
7
$

1
.
7
1
$

2
.
5
4
$

1.
9
3
$

2.
5
4
$

1.
9
3
$

1.9
3
$

1.
9
3
$

1
.
9
7
$

1
.
7
1
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1/

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$
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 231 of 829
APPENDIX 6.4: COLD DAY 20 YR WEATHER STANDARD AVOIDED COST

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$

7
.
6
7
$

5.
5
7
$

7.
1
7
$

8.2
6
$

Co
l
d

D
a
y

2
0
y
r

W
e
a
t
h
e
r

S
t
d

2
0
3
6
-
2
0
3
7

6
.
1
9
$

5
.
9
4
$

6
.
4
3
$

8.9
5
$

9.
1
4
$

8.9
5
$

8.9
5
$

8.
9
5
$

7
.
7
8
$

7
.
5
3
$

8
.
0
2
$

6.
1
8
$

7.
7
8
$

8.9
8
$

1/
A
v
o
i
d
e
d

c
o
s
t
s

a
r
e

b
e
f
o
r
e

E
n
v
i
r
o
n
m
e
n
t
a
l

E
x
t
e
r
n
a
l
i
t
i
e
s

a
d
d
e
r
.
An
n
u
a
l

A
v
o
i
d
e
d

C
o
s
t
s

1
/
No
m
i
n
a
l
$
Wi
n
t
e
r

A
v
o
i
d
e
d

C
o
s
t
s

1
/
No
m
i
n
a
l
$
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 232 of 829
APPENDIX 6.4: 80% BELOW 1990 EMISSIONS AVOIDED COST

Sc
e
n
a
r
i
o

G
a
s

Y
e
a
r

I
D

B
o
t
h

I
D

G
T
N

I
D

N
W
P

K
l
a
m

F
a
l
l
s

L
a

G
r
a
n
d
e

M
e
d
f
o
r
d

G
T
N

M
e
d
f
o
r
d

N
W
P

R
o
s
e
b
u
r
g

W
A

B
o
t
h

W
A

G
T
N

W
A

N
W
P

I
D

A
n
n
u
a
l

W
A

A
n
n
u
a
l

O
R

A
n
n
u
a
l
80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
1
7
-
2
0
1
8

1
.
4
0
$

1
.
3
1
$

2
.
6
3
$

1.3
9
$

2.
6
6
$

1.3
9
$

1.3
9
$

1.
3
9
$

1
.
4
0
$

1
.
3
1
$

2
.
6
3
$

1.
7
8
$

1.
7
8
$

1.6
5
$

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
1
8
-
2
0
1
9

1
.
4
0
$

1
.
3
0
$

2
.
5
5
$

1.3
7
$

2.
5
7
$

1.3
7
$

1.3
7
$

1.
3
7
$

1
.
5
8
$

1
.
4
8
$

2
.
7
3
$

1.
7
5
$

1.
9
3
$

1.6
1
$

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
1
9
-
2
0
2
0

1
.
4
4
$

1
.
3
4
$

2
.
3
3
$

1.4
0
$

2.
3
4
$

1.4
0
$

1.4
0
$

1.
4
0
$

1
.
9
7
$

1
.
8
7
$

2
.
8
6
$

1.
7
0
$

2.
2
3
$

1.5
9
$

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
2
0
-
2
0
2
1

1
.
4
7
$

1
.
3
8
$

2
.
0
7
$

2.2
2
$

2.
8
7
$

2.2
2
$

2.2
2
$

2.
2
2
$

2
.
0
9
$

2
.
0
0
$

2
.
6
9
$

1.
6
4
$

2.
2
6
$

2.3
5
$

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
2
1
-
2
0
2
2

1
.
5
1
$

1
.
4
4
$

1
.
9
1
$

2.4
9
$

2.
9
3
$

2.4
9
$

2.4
9
$

2.
4
9
$

2
.
2
3
$

2
.
1
6
$

2
.
6
3
$

1.
6
2
$

2.
3
4
$

2.5
7
$

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
2
2
-
2
0
2
3

1
.
4
2
$

1
.
3
5
$

1
.
8
4
$

2.4
7
$

2.
9
3
$

2.4
7
$

2.4
7
$

2.
4
7
$

2
.
2
5
$

2
.
1
8
$

2
.
6
7
$

1.
5
4
$

2.
3
7
$

2.5
6
$

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
2
3
-
2
0
2
4

1
.
5
8
$

1
.
5
6
$

1
.
9
3
$

2.7
5
$

3.
0
9
$

2.7
5
$

2.7
5
$

2.
7
5
$

2
.
5
2
$

2
.
4
9
$

2
.
8
7
$

1.
6
9
$

2.
6
3
$

2.8
2
$

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
2
4
-
2
0
2
5

1
.
6
2
$

1
.
5
9
$

1
.
9
8
$

2.8
6
$

3.
2
2
$

2.8
6
$

2.8
6
$

2.
8
6
$

2
.
6
6
$

2
.
6
4
$

3
.
0
2
$

1.
7
3
$

2.
7
7
$

2.9
3
$

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
2
5
-
2
0
2
6

1
.
5
8
$

1
.
5
6
$

1
.
9
9
$

2.9
1
$

3.
3
1
$

2.9
1
$

2.9
1
$

2.
9
1
$

2
.
7
3
$

2
.
7
1
$

3
.
1
4
$

1.
7
1
$

2.
8
6
$

2.9
9
$

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
2
6
-
2
0
2
7

1
.
6
3
$

1
.
6
1
$

2
.
0
0
$

3.0
5
$

3.
4
1
$

3.0
5
$

3.0
5
$

3.
0
5
$

2
.
8
8
$

2
.
8
7
$

3
.
2
6
$

1.
7
5
$

3.
0
0
$

3.1
2
$

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
2
7
-
2
0
2
8

1
.
6
9
$

1
.
6
8
$

2
.
0
4
$

3.2
2
$

3.
5
4
$

3.2
2
$

3.2
2
$

3.
2
2
$

3
.
0
5
$

3
.
0
4
$

3
.
4
0
$

1.
8
0
$

3.
1
6
$

3.2
8
$

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
2
8
-
2
0
2
9

1
.
7
9
$

1
.
7
9
$

2
.
1
3
$

3.4
3
$

3.
7
4
$

3.4
3
$

3.4
3
$

3.
4
3
$

3
.
2
6
$

3
.
2
5
$

3
.
6
0
$

1.
9
0
$

3.
3
7
$

3.5
0
$

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
2
9
-
2
0
3
0

1
.
8
9
$

1
.
8
9
$

2
.
2
5
$

3.6
5
$

3.
9
7
$

3.6
5
$

3.6
5
$

3.
6
5
$

3
.
4
7
$

3
.
4
6
$

3
.
8
2
$

2.
0
1
$

3.
5
8
$

3.7
1
$

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
3
0
-
2
0
3
1

1
.
9
2
$

1
.
9
1
$

2
.
3
2
$

3.8
0
$

4.
1
6
$

3.8
0
$

3.8
0
$

3.
8
0
$

3
.
5
2
$

3
.
5
1
$

3
.
9
1
$

2.
0
5
$

3.
6
5
$

3.8
7
$

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
3
1
-
2
0
3
2

1
.
8
9
$

1
.
8
8
$

2
.
3
1
$

3.8
9
$

4.
2
8
$

3.8
9
$

3.8
9
$

3.
8
9
$

3
.
4
8
$

3
.
4
7
$

3
.
9
0
$

2.
0
3
$

3.
6
2
$

3.9
7
$

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
3
2
-
2
0
3
3

1
.
9
2
$

1
.
9
1
$

2
.
3
0
$

4.0
6
$

4.
4
0
$

4.0
6
$

4.0
6
$

4.
0
6
$

3
.
5
2
$

3
.
5
0
$

3
.
8
9
$

2.
0
4
$

3.
6
4
$

4.1
3
$

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
3
3
-
2
0
3
4

1
.
8
8
$

1
.
8
7
$

2
.
2
7
$

4.1
7
$

4.
5
2
$

4.1
7
$

4.1
7
$

4.
1
7
$

3
.
4
8
$

3
.
4
6
$

3
.
8
6
$

2.
0
1
$

3.
6
0
$

4.2
4
$

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
3
4
-
2
0
3
5

1
.
8
7
$

1
.
8
6
$

2
.
2
0
$

4.3
1
$

4.
6
1
$

4.3
1
$

4.3
1
$

4.
3
1
$

3
.
4
6
$

3
.
4
5
$

3
.
7
9
$

1.
9
8
$

3.
5
7
$

4.3
7
$

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
3
5
-
2
0
3
6

1
.
8
4
$

1
.
8
3
$

2
.
1
7
$

4.4
3
$

4.
7
3
$

4.4
3
$

4.4
3
$

4.
4
3
$

3
.
4
3
$

3
.
4
2
$

3
.
7
6
$

1.
9
5
$

3.
5
4
$

4.4
9
$

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
3
6
-
2
0
3
7

1
.
8
5
$

1
.
8
5
$

2
.
0
0
$

4.6
0
$

4.
7
3
$

4.5
7
$

4.5
7
$

4.
5
7
$

3
.
4
4
$

3
.
4
4
$

3
.
6
0
$

1.
9
0
$

3.
4
9
$

4.6
0
$

Sc
e
n
a
r
i
o

G
a
s

Y
e
a
r

I
D

B
o
t
h

I
D

G
T
N

I
D

N
W
P

K
l
a
m

F
a
l
l
s

L
a

G
r
a
n
d
e

M
e
d
f
o
r
d

G
T
N

M
e
d
f
o
r
d

N
W
P

R
o
s
e
b
u
r
g

W
A

B
o
t
h

W
A

G
T
N

W
A

N
W
P

I
D

A
n
n
u
a
l

W
A

A
n
n
u
a
l

O
R

A
n
n
u
a
l
80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
1
7
-
2
0
1
8

1
.
9
8
$

1
.
7
1
$

2
.
5
4
$

2.0
3
$

2.
6
2
$

2.0
3
$

2.0
3
$

2.
0
3
$

1
.
9
8
$

1
.
7
1
$

2
.
5
4
$

2.
0
8
$

2.
0
8
$

2.1
4
$

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
1
8
-
2
0
1
9

1
.
7
1
$

1
.
4
3
$

2
.
6
4
$

1.6
5
$

2.
6
9
$

1.6
5
$

1.6
5
$

1.
6
5
$

1
.
7
1
$

1
.
4
3
$

2
.
6
4
$

1.
9
3
$

1.
9
3
$

1.8
6
$

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
1
9
-
2
0
2
0

1
.
7
3
$

1
.
4
6
$

2
.
5
0
$

1.6
3
$

2.
5
4
$

1.6
3
$

1.6
3
$

1.
6
3
$

2
.
2
6
$

1
.
9
9
$

3
.
0
3
$

1.
9
0
$

2.
4
3
$

1.8
1
$

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
2
0
-
2
0
2
1

1
.
6
1
$

1
.
3
5
$

2
.
1
9
$

1.5
0
$

2.
2
4
$

1.5
0
$

1.5
0
$

1.
5
0
$

2
.
1
4
$

1
.
8
9
$

2
.
7
2
$

1.
7
2
$

2.
2
5
$

1.6
5
$

80
%

B
e
l
o
w

1
9
9
0

E
m
i
s
s
i
o
n
s

2
0
2
1
-
2
0
2
2

1
.
6
9
$

1
.
4
6
$

1
.
9
8
$

2.5
2
$

3.
0
0
$

2.5
2
$

2.5
2
$

2.
5
2
$

2
.
3
2
$

2
.
1
0
$

2
.
6
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Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 233 of 829
APPENDIX 6.4: LOW GROWTH – HIGH PRICE MONTHLY DETAIL

Scenario Gas Year Month ID Both ID GTN ID NWP Klam Falls La Grande Medford GTN Medford NWP Roseburg WA Both WA GTN WA NWP ID Annual WA Annual OR Annual
Low Growth_High Prices 2017-2018 Nov (1.83)$ (1.83)$ (2.72)$ (1.95)$ (2.72)$ (1.95)$ (1.95)$ (1.95)$ (1.83)$ (1.83)$ (2.72)$ (2.12)$ (2.12)$ (2.10)$
Low Growth_High Prices 2017-2018 Dec (2.15)$ (1.59)$ (2.73)$ (2.29)$ (2.85)$ (2.29)$ (2.29)$ (2.29)$ (2.15)$ (1.59)$ (2.73)$ (2.16)$ (2.16)$ (2.40)$
Low Growth_High Prices 2017-2018 Jan (2.16)$ (1.69)$ (2.73)$ (1.90)$ (2.79)$ (1.90)$ (1.90)$ (1.90)$ (2.16)$ (1.69)$ (2.73)$ (2.20)$ (2.20)$ (2.08)$
Low Growth_High Prices 2017-2018 Feb (2.38)$ (2.17)$ (2.75)$ (2.27)$ (3.03)$ (2.27)$ (2.27)$ (2.27)$ (2.38)$ (2.17)$ (2.75)$ (2.43)$ (2.43)$ (2.42)$
Low Growth_High Prices 2017-2018 Mar (0.95)$ (0.95)$ (2.75)$ (0.98)$ (2.75)$ (0.98)$ (0.98)$ (0.98)$ (0.95)$ (0.95)$ (2.75)$ (1.55)$ (1.55)$ (1.33)$
Low Growth_High Prices 2017-2018 Apr (1.08)$ (1.08)$ (2.76)$ (1.11)$ (2.76)$ (1.11)$ (1.11)$ (1.11)$ (1.08)$ (1.08)$ (2.76)$ (1.64)$ (1.64)$ (1.44)$
Low Growth_High Prices 2017-2018 May (1.05)$ (1.05)$ (2.76)$ (1.08)$ (2.76)$ (1.08)$ (1.08)$ (1.08)$ (1.05)$ (1.05)$ (2.76)$ (1.62)$ (1.62)$ (1.41)$
Low Growth_High Prices 2017-2018 Jun (1.05)$ (1.05)$ (2.77)$ (1.07)$ (2.77)$ (1.07)$ (1.07)$ (1.07)$ (1.05)$ (1.05)$ (2.77)$ (1.62)$ (1.62)$ (1.41)$ Low Growth_High Prices 2017-2018 Jul (1.09)$ (1.09)$ (2.78)$ (1.12)$ (2.78)$ (1.12)$ (1.12)$ (1.12)$ (1.09)$ (1.09)$ (2.78)$ (1.65)$ (1.65)$ (1.45)$ Low Growth_High Prices 2017-2018 Aug (1.10)$ (1.10)$ (2.79)$ (1.13)$ (2.79)$ (1.13)$ (1.13)$ (1.13)$ (1.10)$ (1.10)$ (2.79)$ (1.66)$ (1.66)$ (1.46)$ Low Growth_High Prices 2017-2018 Sep (1.06)$ (1.06)$ (2.80)$ (1.08)$ (2.80)$ (1.08)$ (1.08)$ (1.08)$ (1.06)$ (1.06)$ (2.80)$ (1.64)$ (1.64)$ (1.43)$ Low Growth_High Prices 2017-2018 Oct (1.10)$ (1.10)$ (3.17)$ (1.12)$ (3.17)$ (1.12)$ (1.12)$ (1.12)$ (1.10)$ (1.10)$ (3.17)$ (1.79)$ (1.79)$ (1.53)$ Low Growth_High Prices 2018-2019 Nov (1.74)$ (1.69)$ (2.81)$ (1.84)$ (2.81)$ (1.84)$ (1.84)$ (1.84)$ (1.74)$ (1.69)$ (2.81)$ (2.08)$ (2.08)$ (2.03)$ Low Growth_High Prices 2018-2019 Dec (2.40)$ (1.87)$ (2.83)$ (2.50)$ (2.96)$ (2.50)$ (2.50)$ (2.50)$ (2.40)$ (1.87)$ (2.83)$ (2.37)$ (2.37)$ (2.59)$ Low Growth_High Prices 2018-2019 Jan (2.40)$ (1.93)$ (2.83)$ (2.11)$ (2.87)$ (2.11)$ (2.11)$ (2.11)$ (2.40)$ (1.93)$ (2.83)$ (2.39)$ (2.39)$ (2.26)$ Low Growth_High Prices 2018-2019 Feb (2.29)$ (1.94)$ (2.85)$ (2.08)$ (2.99)$ (2.08)$ (2.08)$ (2.08)$ (2.29)$ (1.94)$ (2.85)$ (2.36)$ (2.36)$ (2.26)$ Low Growth_High Prices 2018-2019 Mar (1.80)$ (1.80)$ (2.85)$ (1.84)$ (2.85)$ (1.84)$ (1.84)$ (1.84)$ (1.80)$ (1.80)$ (2.85)$ (2.15)$ (2.15)$ (2.04)$ Low Growth_High Prices 2018-2019 Apr (1.41)$ (1.41)$ (2.85)$ (1.45)$ (2.85)$ (1.45)$ (1.45)$ (1.45)$ (1.41)$ (1.41)$ (2.85)$ (1.89)$ (1.89)$ (1.73)$ Low Growth_High Prices 2018-2019 May (1.40)$ (1.40)$ (2.86)$ (1.43)$ (2.86)$ (1.43)$ (1.43)$ (1.43)$ (1.40)$ (1.40)$ (2.86)$ (1.89)$ (1.89)$ (1.72)$ Low Growth_High Prices 2018-2019 Jun (1.49)$ (1.49)$ (2.87)$ (1.52)$ (2.87)$ (1.52)$ (1.52)$ (1.52)$ (1.49)$ (1.49)$ (2.87)$ (1.95)$ (1.95)$ (1.79)$ Low Growth_High Prices 2018-2019 Jul (1.57)$ (1.57)$ (2.88)$ (1.61)$ (2.88)$ (1.61)$ (1.61)$ (1.61)$ (2.10)$ (2.10)$ (3.41)$ (2.01)$ (2.54)$ (1.86)$
Low Growth_High Prices 2018-2019 Aug (1.58)$ (1.58)$ (2.89)$ (1.61)$ (2.89)$ (1.61)$ (1.61)$ (1.61)$ (2.11)$ (2.11)$ (3.42)$ (2.01)$ (2.55)$ (1.87)$
Low Growth_High Prices 2018-2019 Sep (1.49)$ (1.49)$ (2.90)$ (1.53)$ (2.90)$ (1.53)$ (1.53)$ (1.53)$ (2.02)$ (2.02)$ (3.43)$ (1.96)$ (2.49)$ (1.80)$
Low Growth_High Prices 2018-2019 Oct (1.53)$ (1.53)$ (2.96)$ (1.56)$ (2.96)$ (1.56)$ (1.56)$ (1.56)$ (2.06)$ (2.06)$ (3.50)$ (2.01)$ (2.54)$ (1.84)$
Low Growth_High Prices 2019-2020 Nov (2.12)$ (2.08)$ (2.91)$ (2.20)$ (2.91)$ (2.20)$ (2.20)$ (2.20)$ (2.65)$ (2.61)$ (3.44)$ (2.37)$ (2.90)$ (2.34)$
Low Growth_High Prices 2019-2020 Dec (2.76)$ (2.28)$ (2.93)$ (2.84)$ (3.06)$ (2.84)$ (2.84)$ (2.84)$ (3.29)$ (2.81)$ (3.46)$ (2.66)$ (3.19)$ (2.89)$
Low Growth_High Prices 2019-2020 Jan (2.83)$ (2.38)$ (2.93)$ (2.52)$ (2.97)$ (2.52)$ (2.52)$ (2.52)$ (3.36)$ (2.91)$ (3.46)$ (2.71)$ (3.24)$ (2.61)$
Low Growth_High Prices 2019-2020 Feb (2.64)$ (2.33)$ (2.96)$ (2.43)$ (3.08)$ (2.43)$ (2.43)$ (2.43)$ (3.17)$ (2.86)$ (3.49)$ (2.64)$ (3.18)$ (2.56)$
Low Growth_High Prices 2019-2020 Mar (2.14)$ (2.14)$ (2.93)$ (2.19)$ (2.93)$ (2.19)$ (2.19)$ (2.19)$ (2.67)$ (2.67)$ (3.46)$ (2.40)$ (2.93)$ (2.34)$
Low Growth_High Prices 2019-2020 Apr (1.83)$ (1.83)$ (2.93)$ (1.87)$ (2.93)$ (1.87)$ (1.87)$ (1.87)$ (2.36)$ (2.36)$ (3.46)$ (2.20)$ (2.73)$ (2.08)$
Low Growth_High Prices 2019-2020 May (1.83)$ (1.83)$ (2.94)$ (1.87)$ (2.94)$ (1.87)$ (1.87)$ (1.87)$ (2.36)$ (2.36)$ (3.47)$ (2.20)$ (2.73)$ (2.09)$
Low Growth_High Prices 2019-2020 Jun (1.84)$ (1.84)$ (2.95)$ (1.88)$ (2.95)$ (1.88)$ (1.88)$ (1.88)$ (2.37)$ (2.37)$ (3.48)$ (2.21)$ (2.74)$ (2.09)$
Low Growth_High Prices 2019-2020 Jul (1.90)$ (1.90)$ (2.96)$ (1.94)$ (2.96)$ (1.94)$ (1.94)$ (1.94)$ (2.43)$ (2.43)$ (3.49)$ (2.25)$ (2.78)$ (2.14)$
Low Growth_High Prices 2019-2020 Aug (1.93)$ (1.93)$ (2.97)$ (1.97)$ (2.97)$ (1.97)$ (1.97)$ (1.97)$ (2.46)$ (2.46)$ (3.50)$ (2.27)$ (2.81)$ (2.17)$
Low Growth_High Prices 2019-2020 Sep (1.88)$ (1.88)$ (2.98)$ (1.92)$ (2.98)$ (1.92)$ (1.92)$ (1.92)$ (2.41)$ (2.41)$ (3.51)$ (2.24)$ (2.78)$ (2.13)$ Low Growth_High Prices 2019-2020 Oct (1.94)$ (1.94)$ (3.19)$ (1.98)$ (3.19)$ (1.98)$ (1.98)$ (1.98)$ (2.47)$ (2.47)$ (3.72)$ (2.36)$ (2.89)$ (2.22)$ Low Growth_High Prices 2020-2021 Nov (2.41)$ (2.37)$ (3.09)$ (2.48)$ (3.09)$ (2.48)$ (2.48)$ (2.48)$ (2.94)$ (2.90)$ (3.62)$ (2.62)$ (3.15)$ (2.60)$ Low Growth_High Prices 2020-2021 Dec (3.01)$ (2.53)$ (3.10)$ (3.05)$ (3.23)$ (3.05)$ (3.05)$ (3.05)$ (3.54)$ (3.06)$ (3.63)$ (2.88)$ (3.41)$ (3.09)$ Low Growth_High Prices 2020-2021 Jan (3.14)$ (2.81)$ (3.14)$ (3.81)$ (4.08)$ (3.81)$ (3.81)$ (3.81)$ (3.77)$ (3.44)$ (3.77)$ (3.03)$ (3.66)$ (3.87)$ Low Growth_High Prices 2020-2021 Feb (3.00)$ (2.75)$ (3.16)$ (3.75)$ (4.25)$ (3.75)$ (3.75)$ (3.75)$ (3.64)$ (3.38)$ (3.79)$ (2.97)$ (3.61)$ (3.85)$ Low Growth_High Prices 2020-2021 Mar (2.63)$ (2.63)$ (3.12)$ (3.63)$ (4.07)$ (3.63)$ (3.63)$ (3.63)$ (3.27)$ (3.27)$ (3.76)$ (2.79)$ (3.43)$ (3.72)$ Low Growth_High Prices 2020-2021 Apr (2.29)$ (2.29)$ (3.13)$ (3.29)$ (4.08)$ (3.29)$ (3.29)$ (3.29)$ (2.93)$ (2.93)$ (3.77)$ (2.57)$ (3.21)$ (3.45)$ Low Growth_High Prices 2020-2021 May (2.28)$ (2.28)$ (3.14)$ (3.27)$ (4.08)$ (3.27)$ (3.27)$ (3.27)$ (2.91)$ (2.91)$ (3.77)$ (2.56)$ (3.20)$ (3.43)$ Low Growth_High Prices 2020-2021 Jun (2.32)$ (2.32)$ (3.15)$ (3.31)$ (4.09)$ (3.31)$ (3.31)$ (3.31)$ (2.95)$ (2.95)$ (3.78)$ (2.59)$ (3.23)$ (3.47)$ Low Growth_High Prices 2020-2021 Jul (2.42)$ (2.42)$ (3.15)$ (3.42)$ (4.10)$ (3.42)$ (3.42)$ (3.42)$ (3.05)$ (3.05)$ (3.79)$ (2.66)$ (3.30)$ (3.55)$ Low Growth_High Prices 2020-2021 Aug (2.44)$ (2.44)$ (3.16)$ (3.44)$ (4.11)$ (3.44)$ (3.44)$ (3.44)$ (3.08)$ (3.08)$ (3.80)$ (2.68)$ (3.32)$ (3.58)$ Low Growth_High Prices 2020-2021 Sep (2.36)$ (2.36)$ (3.17)$ (3.36)$ (4.12)$ (3.36)$ (3.36)$ (3.36)$ (3.00)$ (3.00)$ (3.81)$ (2.63)$ (3.27)$ (3.51)$ Low Growth_High Prices 2020-2021 Oct (2.42)$ (2.42)$ (3.28)$ (3.42)$ (4.23)$ (3.42)$ (3.42)$ (3.42)$ (3.06)$ (3.06)$ (3.91)$ (2.71)$ (3.34)$ (3.58)$ Low Growth_High Prices 2021-2022 Nov (2.98)$ (2.94)$ (3.35)$ (3.98)$ (4.29)$ (3.98)$ (3.98)$ (3.98)$ (3.61)$ (3.57)$ (3.98)$ (3.09)$ (3.72)$ (4.04)$
Low Growth_High Prices 2021-2022 Dec (3.39)$ (3.10)$ (3.39)$ (4.42)$ (4.50)$ (4.42)$ (4.42)$ (4.42)$ (4.03)$ (3.73)$ (4.03)$ (3.29)$ (3.93)$ (4.43)$
Low Growth_High Prices 2021-2022 Jan (3.40)$ (3.23)$ (3.40)$ (4.31)$ (4.42)$ (4.31)$ (4.31)$ (4.31)$ (4.14)$ (3.98)$ (4.14)$ (3.35)$ (4.09)$ (4.33)$
Low Growth_High Prices 2021-2022 Feb (3.38)$ (3.26)$ (3.43)$ (4.34)$ (4.57)$ (4.34)$ (4.34)$ (4.34)$ (4.13)$ (4.00)$ (4.17)$ (3.36)$ (4.10)$ (4.39)$
Low Growth_High Prices 2021-2022 Mar (3.16)$ (3.16)$ (3.37)$ (4.24)$ (4.38)$ (4.24)$ (4.24)$ (4.24)$ (3.91)$ (3.91)$ (4.11)$ (3.23)$ (3.98)$ (4.27)$
Low Growth_High Prices 2021-2022 Apr (2.79)$ (2.79)$ (3.38)$ (3.86)$ (4.39)$ (3.86)$ (3.86)$ (3.86)$ (3.53)$ (3.53)$ (4.12)$ (2.98)$ (3.73)$ (3.96)$
Low Growth_High Prices 2021-2022 May (2.79)$ (2.79)$ (3.39)$ (3.87)$ (4.40)$ (3.87)$ (3.87)$ (3.87)$ (3.54)$ (3.54)$ (4.13)$ (2.99)$ (3.73)$ (3.97)$
Low Growth_High Prices 2021-2022 Jun (2.79)$ (2.79)$ (3.39)$ (3.86)$ (4.41)$ (3.86)$ (3.86)$ (3.86)$ (3.53)$ (3.53)$ (4.14)$ (2.99)$ (3.73)$ (3.97)$
Low Growth_High Prices 2021-2022 Jul (2.86)$ (2.86)$ (3.40)$ (3.93)$ (4.42)$ (3.93)$ (3.93)$ (3.93)$ (3.60)$ (3.60)$ (4.15)$ (3.04)$ (3.78)$ (4.03)$
Low Growth_High Prices 2021-2022 Aug (2.88)$ (2.88)$ (3.41)$ (3.96)$ (4.43)$ (3.96)$ (3.96)$ (3.96)$ (3.63)$ (3.63)$ (4.16)$ (3.06)$ (3.80)$ (4.05)$
Low Growth_High Prices 2021-2022 Sep (2.91)$ (2.91)$ (3.42)$ (3.99)$ (4.43)$ (3.99)$ (3.99)$ (3.99)$ (3.66)$ (3.66)$ (4.16)$ (3.08)$ (3.83)$ (4.08)$
Low Growth_High Prices 2021-2022 Oct (2.93)$ (2.93)$ (3.60)$ (4.00)$ (4.61)$ (4.00)$ (4.00)$ (4.00)$ (3.67)$ (3.67)$ (4.34)$ (3.15)$ (3.90)$ (4.13)$
Low Growth_High Prices 2022-2023 Nov (3.35)$ (3.31)$ (3.76)$ (4.43)$ (4.77)$ (4.43)$ (4.43)$ (4.43)$ (4.09)$ (4.05)$ (4.50)$ (3.47)$ (4.21)$ (4.50)$
Low Growth_High Prices 2022-2023 Dec (3.80)$ (3.51)$ (3.80)$ (4.88)$ (4.97)$ (4.88)$ (4.88)$ (4.88)$ (4.55)$ (4.26)$ (4.55)$ (3.71)$ (4.45)$ (4.90)$ Low Growth_High Prices 2022-2023 Jan (3.81)$ (3.62)$ (3.81)$ (4.77)$ (4.90)$ (4.77)$ (4.77)$ (4.77)$ (4.66)$ (4.47)$ (4.66)$ (3.75)$ (4.60)$ (4.80)$ Low Growth_High Prices 2022-2023 Feb (3.74)$ (3.57)$ (3.83)$ (4.73)$ (5.04)$ (4.73)$ (4.73)$ (4.73)$ (4.59)$ (4.42)$ (4.68)$ (3.72)$ (4.57)$ (4.79)$ Low Growth_High Prices 2022-2023 Mar (3.51)$ (3.51)$ (3.79)$ (4.67)$ (4.87)$ (4.67)$ (4.67)$ (4.67)$ (4.36)$ (4.36)$ (4.64)$ (3.60)$ (4.45)$ (4.71)$ Low Growth_High Prices 2022-2023 Apr (3.12)$ (3.12)$ (3.79)$ (4.26)$ (4.88)$ (4.26)$ (4.26)$ (4.26)$ (3.96)$ (3.96)$ (4.64)$ (3.34)$ (4.19)$ (4.39)$ Low Growth_High Prices 2022-2023 May (3.19)$ (3.19)$ (3.80)$ (4.34)$ (4.89)$ (4.34)$ (4.34)$ (4.34)$ (4.04)$ (4.04)$ (4.65)$ (3.39)$ (4.24)$ (4.45)$ Low Growth_High Prices 2022-2023 Jun (3.23)$ (3.23)$ (3.81)$ (4.38)$ (4.90)$ (4.38)$ (4.38)$ (4.38)$ (4.07)$ (4.07)$ (4.66)$ (3.42)$ (4.27)$ (4.48)$ Low Growth_High Prices 2022-2023 Jul (3.25)$ (3.25)$ (3.82)$ (4.40)$ (4.91)$ (4.40)$ (4.40)$ (4.40)$ (4.09)$ (4.09)$ (4.67)$ (3.44)$ (4.29)$ (4.50)$ Low Growth_High Prices 2022-2023 Aug (3.34)$ (3.34)$ (3.83)$ (4.49)$ (4.91)$ (4.49)$ (4.49)$ (4.49)$ (4.19)$ (4.19)$ (4.68)$ (3.50)$ (4.35)$ (4.58)$ Low Growth_High Prices 2022-2023 Sep (3.33)$ (3.33)$ (3.84)$ (4.49)$ (4.92)$ (4.49)$ (4.49)$ (4.49)$ (4.18)$ (4.18)$ (4.69)$ (3.50)$ (4.35)$ (4.57)$ Low Growth_High Prices 2022-2023 Oct (3.34)$ (3.34)$ (3.99)$ (4.49)$ (5.08)$ (4.49)$ (4.49)$ (4.49)$ (4.19)$ (4.19)$ (4.84)$ (3.56)$ (4.41)$ (4.61)$ Low Growth_High Prices 2023-2024 Nov (3.84)$ (3.80)$ (4.52)$ (5.03)$ (5.60)$ (5.03)$ (5.03)$ (5.03)$ (4.69)$ (4.65)$ (5.37)$ (4.06)$ (4.90)$ (5.14)$ Low Growth_High Prices 2023-2024 Dec (4.48)$ (4.04)$ (4.54)$ (5.62)$ (5.72)$ (5.62)$ (5.62)$ (5.62)$ (5.33)$ (4.89)$ (5.39)$ (4.35)$ (5.20)$ (5.64)$ Low Growth_High Prices 2023-2024 Jan (4.57)$ (4.16)$ (4.57)$ (5.40)$ (5.73)$ (5.40)$ (5.40)$ (5.40)$ (5.52)$ (5.11)$ (5.52)$ (4.43)$ (5.39)$ (5.47)$ Low Growth_High Prices 2023-2024 Feb (4.40)$ (4.16)$ (4.58)$ (5.40)$ (5.82)$ (5.40)$ (5.40)$ (5.40)$ (5.36)$ (5.11)$ (5.53)$ (4.38)$ (5.33)$ (5.48)$
Low Growth_High Prices 2023-2024 Mar (4.11)$ (4.11)$ (4.56)$ (5.35)$ (5.72)$ (5.35)$ (5.35)$ (5.35)$ (5.06)$ (5.06)$ (5.51)$ (4.26)$ (5.21)$ (5.42)$
Low Growth_High Prices 2023-2024 Apr (3.84)$ (3.84)$ (4.56)$ (5.08)$ (5.72)$ (5.08)$ (5.08)$ (5.08)$ (4.80)$ (4.80)$ (5.52)$ (4.08)$ (5.04)$ (5.21)$
Low Growth_High Prices 2023-2024 May (3.84)$ (3.84)$ (4.57)$ (5.08)$ (5.73)$ (5.08)$ (5.08)$ (5.08)$ (4.80)$ (4.80)$ (5.53)$ (4.09)$ (5.04)$ (5.21)$
Low Growth_High Prices 2023-2024 Jun (3.82)$ (3.82)$ (4.58)$ (5.05)$ (5.74)$ (5.05)$ (5.05)$ (5.05)$ (4.77)$ (4.77)$ (5.54)$ (4.07)$ (5.03)$ (5.19)$
Low Growth_High Prices 2023-2024 Jul (3.99)$ (3.99)$ (4.59)$ (5.22)$ (5.75)$ (5.22)$ (5.22)$ (5.22)$ (4.94)$ (4.94)$ (5.55)$ (4.19)$ (5.14)$ (5.33)$
Low Growth_High Prices 2023-2024 Aug (4.13)$ (4.13)$ (4.60)$ (5.37)$ (5.76)$ (5.37)$ (5.37)$ (5.37)$ (5.09)$ (5.09)$ (5.56)$ (4.29)$ (5.24)$ (5.45)$
Low Growth_High Prices 2023-2024 Sep (4.10)$ (4.10)$ (4.61)$ (5.34)$ (5.77)$ (5.34)$ (5.34)$ (5.34)$ (5.06)$ (5.06)$ (5.56)$ (4.27)$ (5.23)$ (5.43)$
Low Growth_High Prices 2023-2024 Oct (4.16)$ (4.16)$ (4.84)$ (5.40)$ (6.00)$ (5.40)$ (5.40)$ (5.40)$ (5.11)$ (5.11)$ (5.79)$ (4.38)$ (5.34)$ (5.52)$
Low Growth_High Prices 2024-2025 Nov (4.45)$ (4.41)$ (5.02)$ (5.71)$ (6.18)$ (5.71)$ (5.71)$ (5.71)$ (5.40)$ (5.36)$ (5.98)$ (4.63)$ (5.58)$ (5.80)$
Low Growth_High Prices 2024-2025 Dec (4.97)$ (4.53)$ (5.04)$ (6.20)$ (6.29)$ (6.20)$ (6.20)$ (6.20)$ (5.92)$ (5.48)$ (6.00)$ (4.85)$ (5.80)$ (6.22)$
Low Growth_High Prices 2024-2025 Jan (5.02)$ (4.61)$ (5.04)$ (5.94)$ (6.28)$ (5.94)$ (5.94)$ (5.94)$ (6.08)$ (5.67)$ (6.10)$ (4.89)$ (5.95)$ (6.01)$
Low Growth_High Prices 2024-2025 Feb (4.89)$ (4.62)$ (5.08)$ (5.96)$ (6.41)$ (5.96)$ (5.96)$ (5.96)$ (5.96)$ (5.69)$ (6.15)$ (4.87)$ (5.93)$ (6.05)$
Low Growth_High Prices 2024-2025 Mar (4.43)$ (4.43)$ (5.06)$ (5.76)$ (6.30)$ (5.76)$ (5.76)$ (5.76)$ (5.50)$ (5.50)$ (6.12)$ (4.64)$ (5.70)$ (5.87)$ Low Growth_High Prices 2024-2025 Apr (4.20)$ (4.20)$ (5.07)$ (5.52)$ (6.31)$ (5.52)$ (5.52)$ (5.52)$ (5.26)$ (5.26)$ (6.13)$ (4.49)$ (5.55)$ (5.68)$ Low Growth_High Prices 2024-2025 May (4.24)$ (4.24)$ (5.08)$ (5.57)$ (6.32)$ (5.57)$ (5.57)$ (5.57)$ (5.30)$ (5.30)$ (6.14)$ (4.52)$ (5.58)$ (5.72)$ Low Growth_High Prices 2024-2025 Jun (4.35)$ (4.35)$ (5.09)$ (5.67)$ (6.33)$ (5.67)$ (5.67)$ (5.67)$ (5.41)$ (5.41)$ (6.15)$ (4.59)$ (5.66)$ (5.80)$ Low Growth_High Prices 2024-2025 Jul (4.43)$ (4.43)$ (5.10)$ (5.76)$ (6.34)$ (5.76)$ (5.76)$ (5.76)$ (5.50)$ (5.50)$ (6.16)$ (4.66)$ (5.72)$ (5.88)$ Low Growth_High Prices 2024-2025 Aug (4.48)$ (4.48)$ (5.11)$ (5.81)$ (6.35)$ (5.81)$ (5.81)$ (5.81)$ (5.54)$ (5.54)$ (6.17)$ (4.69)$ (5.75)$ (5.91)$ Low Growth_High Prices 2024-2025 Sep (4.41)$ (4.41)$ (5.12)$ (5.74)$ (6.36)$ (5.74)$ (5.74)$ (5.74)$ (5.48)$ (5.48)$ (6.18)$ (4.65)$ (5.71)$ (5.86)$ Low Growth_High Prices 2024-2025 Oct (4.41)$ (4.41)$ (5.19)$ (5.74)$ (6.43)$ (5.74)$ (5.74)$ (5.74)$ (5.47)$ (5.47)$ (6.25)$ (4.67)$ (5.73)$ (5.88)$ Low Growth_High Prices 2025-2026 Nov (4.63)$ (4.59)$ (5.24)$ (5.98)$ (6.48)$ (5.98)$ (5.98)$ (5.98)$ (5.69)$ (5.65)$ (6.30)$ (4.82)$ (5.88)$ (6.08)$
Monthly Avoided Costs 1/
Nominal$
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 234 of 829
APPENDIX 6.4: LOW GROWTH – HIGH PRICE MONTHLY DETAIL

Scenario Gas Year Month ID Both ID GTN ID NWP Klam Falls La Grande Medford GTN Medford NWP Roseburg WA Both WA GTN WA NWP ID Annual WA Annual OR Annual
Low Growth_High Prices 2025-2026 Dec (5.17)$ (4.73)$ (5.26)$ (6.51)$ (6.57)$ (6.51)$ (6.51)$ (6.51)$ (6.23)$ (5.79)$ (6.32)$ (5.05)$ (6.11)$ (6.52)$
Low Growth_High Prices 2025-2026 Jan (5.27)$ (4.87)$ (5.27)$ (6.29)$ (6.60)$ (6.29)$ (6.29)$ (6.29)$ (6.44)$ (6.04)$ (6.44)$ (5.14)$ (6.30)$ (6.35)$
Low Growth_High Prices 2025-2026 Feb (5.12)$ (4.86)$ (5.30)$ (6.28)$ (6.71)$ (6.28)$ (6.28)$ (6.28)$ (6.29)$ (6.02)$ (6.47)$ (5.09)$ (6.26)$ (6.36)$
Low Growth_High Prices 2025-2026 Mar (4.67)$ (4.67)$ (5.28)$ (6.08)$ (6.60)$ (6.08)$ (6.08)$ (6.08)$ (5.83)$ (5.83)$ (6.45)$ (4.87)$ (6.04)$ (6.19)$
Low Growth_High Prices 2025-2026 Apr (4.46)$ (4.46)$ (5.29)$ (5.87)$ (6.61)$ (5.87)$ (5.87)$ (5.87)$ (5.62)$ (5.62)$ (6.45)$ (4.73)$ (5.90)$ (6.02)$
Low Growth_High Prices 2025-2026 May (4.52)$ (4.52)$ (5.30)$ (5.93)$ (6.62)$ (5.93)$ (5.93)$ (5.93)$ (5.69)$ (5.69)$ (6.46)$ (4.78)$ (5.95)$ (6.07)$
Low Growth_High Prices 2025-2026 Jun (4.62)$ (4.62)$ (5.31)$ (6.04)$ (6.63)$ (6.04)$ (6.04)$ (6.04)$ (5.79)$ (5.79)$ (6.47)$ (4.85)$ (6.02)$ (6.16)$
Low Growth_High Prices 2025-2026 Jul (4.77)$ (4.77)$ (5.32)$ (6.19)$ (6.64)$ (6.19)$ (6.19)$ (6.19)$ (5.93)$ (5.93)$ (6.48)$ (4.95)$ (6.12)$ (6.28)$ Low Growth_High Prices 2025-2026 Aug (4.81)$ (4.81)$ (5.33)$ (6.23)$ (6.65)$ (6.23)$ (6.23)$ (6.23)$ (5.98)$ (5.98)$ (6.49)$ (4.98)$ (6.15)$ (6.31)$ Low Growth_High Prices 2025-2026 Sep (4.71)$ (4.71)$ (5.33)$ (6.13)$ (6.66)$ (6.13)$ (6.13)$ (6.13)$ (5.88)$ (5.88)$ (6.50)$ (4.92)$ (6.09)$ (6.24)$ Low Growth_High Prices 2025-2026 Oct (4.76)$ (4.76)$ (5.39)$ (6.18)$ (6.72)$ (6.18)$ (6.18)$ (6.18)$ (5.93)$ (5.93)$ (6.56)$ (4.97)$ (6.14)$ (6.29)$ Low Growth_High Prices 2026-2027 Nov (4.97)$ (4.93)$ (5.55)$ (6.41)$ (6.88)$ (6.41)$ (6.41)$ (6.41)$ (6.14)$ (6.10)$ (6.72)$ (5.15)$ (6.32)$ (6.50)$ Low Growth_High Prices 2026-2027 Dec (5.55)$ (5.13)$ (5.57)$ (6.92)$ (6.96)$ (6.92)$ (6.92)$ (6.92)$ (6.72)$ (6.30)$ (6.74)$ (5.42)$ (6.59)$ (6.93)$ Low Growth_High Prices 2026-2027 Jan (5.63)$ (5.27)$ (5.63)$ (6.79)$ (7.05)$ (6.79)$ (6.79)$ (6.79)$ (6.90)$ (6.54)$ (6.90)$ (5.51)$ (6.78)$ (6.84)$ Low Growth_High Prices 2026-2027 Feb (5.43)$ (5.28)$ (5.61)$ (6.80)$ (7.10)$ (6.80)$ (6.80)$ (6.80)$ (6.70)$ (6.55)$ (6.89)$ (5.44)$ (6.71)$ (6.86)$ Low Growth_High Prices 2026-2027 Mar (5.14)$ (5.14)$ (5.59)$ (6.66)$ (7.01)$ (6.66)$ (6.66)$ (6.66)$ (6.42)$ (6.42)$ (6.87)$ (5.29)$ (6.57)$ (6.73)$ Low Growth_High Prices 2026-2027 Apr (4.98)$ (4.98)$ (5.60)$ (6.49)$ (7.02)$ (6.49)$ (6.49)$ (6.49)$ (6.25)$ (6.25)$ (6.87)$ (5.18)$ (6.46)$ (6.60)$ Low Growth_High Prices 2026-2027 May (4.95)$ (4.95)$ (5.61)$ (6.46)$ (7.03)$ (6.46)$ (6.46)$ (6.46)$ (6.22)$ (6.22)$ (6.88)$ (5.17)$ (6.44)$ (6.58)$ Low Growth_High Prices 2026-2027 Jun (5.11)$ (5.11)$ (5.62)$ (6.63)$ (7.04)$ (6.63)$ (6.63)$ (6.63)$ (6.39)$ (6.39)$ (6.89)$ (5.28)$ (6.56)$ (6.71)$ Low Growth_High Prices 2026-2027 Jul (5.26)$ (5.26)$ (5.63)$ (6.78)$ (7.05)$ (6.78)$ (6.78)$ (6.78)$ (6.54)$ (6.54)$ (6.90)$ (5.38)$ (6.66)$ (6.83)$ Low Growth_High Prices 2026-2027 Aug (5.32)$ (5.32)$ (5.64)$ (6.84)$ (7.06)$ (6.84)$ (6.84)$ (6.84)$ (6.59)$ (6.59)$ (6.91)$ (5.42)$ (6.70)$ (6.88)$
Low Growth_High Prices 2026-2027 Sep (5.24)$ (5.24)$ (5.65)$ (6.75)$ (7.07)$ (6.75)$ (6.75)$ (6.75)$ (6.51)$ (6.51)$ (6.92)$ (5.37)$ (6.65)$ (6.82)$
Low Growth_High Prices 2026-2027 Oct (5.25)$ (5.25)$ (5.87)$ (6.77)$ (7.28)$ (6.77)$ (6.77)$ (6.77)$ (6.52)$ (6.52)$ (7.14)$ (5.45)$ (6.73)$ (6.87)$
Low Growth_High Prices 2027-2028 Nov (5.53)$ (5.49)$ (6.19)$ (7.08)$ (7.61)$ (7.08)$ (7.08)$ (7.08)$ (6.81)$ (6.77)$ (7.46)$ (5.74)$ (7.01)$ (7.18)$
Low Growth_High Prices 2027-2028 Dec (6.21)$ (5.80)$ (6.21)$ (7.64)$ (7.67)$ (7.64)$ (7.64)$ (7.64)$ (7.48)$ (7.08)$ (7.49)$ (6.07)$ (7.35)$ (7.64)$
Low Growth_High Prices 2027-2028 Jan (6.27)$ (5.91)$ (6.27)$ (7.54)$ (7.79)$ (7.54)$ (7.54)$ (7.54)$ (7.65)$ (7.29)$ (7.65)$ (6.15)$ (7.53)$ (7.59)$
Low Growth_High Prices 2027-2028 Feb (5.97)$ (5.79)$ (6.25)$ (7.42)$ (7.81)$ (7.42)$ (7.42)$ (7.42)$ (7.35)$ (7.17)$ (7.63)$ (6.00)$ (7.38)$ (7.50)$
Low Growth_High Prices 2027-2028 Mar (5.68)$ (5.68)$ (6.23)$ (7.31)$ (7.74)$ (7.31)$ (7.31)$ (7.31)$ (7.06)$ (7.06)$ (7.61)$ (5.86)$ (7.24)$ (7.40)$
Low Growth_High Prices 2027-2028 Apr (5.55)$ (5.55)$ (6.24)$ (7.18)$ (7.75)$ (7.18)$ (7.18)$ (7.18)$ (6.93)$ (6.93)$ (7.62)$ (5.78)$ (7.16)$ (7.29)$
Low Growth_High Prices 2027-2028 May (5.54)$ (5.54)$ (6.25)$ (7.16)$ (7.76)$ (7.16)$ (7.16)$ (7.16)$ (6.92)$ (6.92)$ (7.63)$ (5.77)$ (7.15)$ (7.28)$
Low Growth_High Prices 2027-2028 Jun (5.74)$ (5.74)$ (6.26)$ (7.37)$ (7.77)$ (7.37)$ (7.37)$ (7.37)$ (7.12)$ (7.12)$ (7.64)$ (5.91)$ (7.29)$ (7.45)$
Low Growth_High Prices 2027-2028 Jul (5.85)$ (5.85)$ (6.27)$ (7.48)$ (7.78)$ (7.48)$ (7.48)$ (7.48)$ (7.23)$ (7.23)$ (7.65)$ (5.99)$ (7.37)$ (7.54)$
Low Growth_High Prices 2027-2028 Aug (5.93)$ (5.93)$ (6.28)$ (7.56)$ (7.79)$ (7.56)$ (7.56)$ (7.56)$ (7.31)$ (7.31)$ (7.66)$ (6.04)$ (7.42)$ (7.61)$
Low Growth_High Prices 2027-2028 Sep (5.77)$ (5.77)$ (6.29)$ (7.40)$ (7.80)$ (7.40)$ (7.40)$ (7.40)$ (7.15)$ (7.15)$ (7.67)$ (5.94)$ (7.32)$ (7.48)$
Low Growth_High Prices 2027-2028 Oct (5.80)$ (5.80)$ (6.30)$ (7.43)$ (7.82)$ (7.43)$ (7.43)$ (7.43)$ (7.18)$ (7.18)$ (7.68)$ (5.97)$ (7.35)$ (7.50)$ Low Growth_High Prices 2028-2029 Nov (6.02)$ (5.98)$ (6.59)$ (7.66)$ (8.11)$ (7.66)$ (7.66)$ (7.66)$ (7.40)$ (7.36)$ (7.97)$ (6.20)$ (7.58)$ (7.75)$ Low Growth_High Prices 2028-2029 Dec (6.61)$ (6.21)$ (6.62)$ (8.14)$ (8.17)$ (8.14)$ (8.14)$ (8.14)$ (7.99)$ (7.59)$ (8.00)$ (6.48)$ (7.86)$ (8.14)$ Low Growth_High Prices 2028-2029 Jan (6.66)$ (6.29)$ (6.66)$ (8.07)$ (8.28)$ (8.07)$ (8.07)$ (8.07)$ (8.14)$ (7.78)$ (8.14)$ (6.54)$ (8.02)$ (8.11)$ Low Growth_High Prices 2028-2029 Feb (6.51)$ (6.39)$ (6.65)$ (8.14)$ (8.31)$ (8.14)$ (8.14)$ (8.14)$ (7.99)$ (7.88)$ (8.14)$ (6.52)$ (8.00)$ (8.17)$ Low Growth_High Prices 2028-2029 Mar (6.22)$ (6.22)$ (6.63)$ (7.96)$ (8.25)$ (7.96)$ (7.96)$ (7.96)$ (7.71)$ (7.71)$ (8.12)$ (6.36)$ (7.84)$ (8.02)$ Low Growth_High Prices 2028-2029 Apr (6.07)$ (6.07)$ (6.64)$ (7.81)$ (8.26)$ (7.81)$ (7.81)$ (7.81)$ (7.55)$ (7.55)$ (8.13)$ (6.26)$ (7.75)$ (7.90)$ Low Growth_High Prices 2028-2029 May (6.10)$ (6.10)$ (6.65)$ (7.84)$ (8.27)$ (7.84)$ (7.84)$ (7.84)$ (7.59)$ (7.59)$ (8.14)$ (6.28)$ (7.77)$ (7.93)$ Low Growth_High Prices 2028-2029 Jun (6.14)$ (6.14)$ (6.66)$ (7.88)$ (8.28)$ (7.88)$ (7.88)$ (7.88)$ (7.63)$ (7.63)$ (8.15)$ (6.31)$ (7.80)$ (7.96)$ Low Growth_High Prices 2028-2029 Jul (6.31)$ (6.31)$ (6.67)$ (8.05)$ (8.29)$ (8.05)$ (8.05)$ (8.05)$ (7.79)$ (7.79)$ (8.16)$ (6.43)$ (7.91)$ (8.10)$ Low Growth_High Prices 2028-2029 Aug (6.38)$ (6.38)$ (6.68)$ (8.12)$ (8.30)$ (8.12)$ (8.12)$ (8.12)$ (7.86)$ (7.86)$ (8.17)$ (6.48)$ (7.96)$ (8.16)$ Low Growth_High Prices 2028-2029 Sep (6.26)$ (6.26)$ (6.69)$ (8.00)$ (8.31)$ (8.00)$ (8.00)$ (8.00)$ (7.74)$ (7.74)$ (8.18)$ (6.40)$ (7.89)$ (8.06)$ Low Growth_High Prices 2028-2029 Oct (6.37)$ (6.37)$ (6.76)$ (8.12)$ (8.38)$ (8.12)$ (8.12)$ (8.12)$ (7.86)$ (7.86)$ (8.24)$ (6.50)$ (7.99)$ (8.17)$ Low Growth_High Prices 2029-2030 Nov (6.57)$ (6.53)$ (7.06)$ (8.32)$ (8.68)$ (8.32)$ (8.32)$ (8.32)$ (8.06)$ (8.02)$ (8.55)$ (6.72)$ (8.21)$ (8.39)$ Low Growth_High Prices 2029-2030 Dec (7.17)$ (6.85)$ (7.17)$ (8.82)$ (8.82)$ (8.82)$ (8.82)$ (8.82)$ (8.66)$ (8.33)$ (8.66)$ (7.07)$ (8.55)$ (8.82)$
Low Growth_High Prices 2029-2030 Jan (7.18)$ (6.89)$ (7.18)$ (8.76)$ (8.92)$ (8.76)$ (8.76)$ (8.76)$ (8.78)$ (8.49)$ (8.78)$ (7.09)$ (8.68)$ (8.79)$
Low Growth_High Prices 2029-2030 Feb (7.04)$ (6.94)$ (7.15)$ (8.81)$ (8.93)$ (8.81)$ (8.81)$ (8.81)$ (8.63)$ (8.53)$ (8.75)$ (7.04)$ (8.64)$ (8.83)$
Low Growth_High Prices 2029-2030 Mar (6.70)$ (6.70)$ (7.14)$ (8.56)$ (8.87)$ (8.56)$ (8.56)$ (8.56)$ (8.29)$ (8.29)$ (8.73)$ (6.84)$ (8.44)$ (8.63)$
Low Growth_High Prices 2029-2030 Apr (6.54)$ (6.54)$ (7.14)$ (8.40)$ (8.88)$ (8.40)$ (8.40)$ (8.40)$ (8.13)$ (8.13)$ (8.74)$ (6.74)$ (8.33)$ (8.50)$
Low Growth_High Prices 2029-2030 May (6.59)$ (6.59)$ (7.15)$ (8.46)$ (8.89)$ (8.46)$ (8.46)$ (8.46)$ (8.18)$ (8.18)$ (8.75)$ (6.78)$ (8.37)$ (8.54)$
Low Growth_High Prices 2029-2030 Jun (6.66)$ (6.66)$ (7.17)$ (8.52)$ (8.90)$ (8.52)$ (8.52)$ (8.52)$ (8.25)$ (8.25)$ (8.76)$ (6.83)$ (8.42)$ (8.60)$
Low Growth_High Prices 2029-2030 Jul (6.84)$ (6.84)$ (7.18)$ (8.70)$ (8.91)$ (8.70)$ (8.70)$ (8.70)$ (8.43)$ (8.43)$ (8.77)$ (6.95)$ (8.54)$ (8.75)$
Low Growth_High Prices 2029-2030 Aug (6.93)$ (6.93)$ (7.19)$ (8.80)$ (8.92)$ (8.80)$ (8.80)$ (8.80)$ (8.52)$ (8.52)$ (8.78)$ (7.02)$ (8.61)$ (8.82)$
Low Growth_High Prices 2029-2030 Sep (6.83)$ (6.83)$ (7.20)$ (8.70)$ (8.93)$ (8.70)$ (8.70)$ (8.70)$ (8.42)$ (8.42)$ (8.79)$ (6.95)$ (8.55)$ (8.75)$
Low Growth_High Prices 2029-2030 Oct (6.88)$ (6.88)$ (7.34)$ (8.75)$ (9.08)$ (8.75)$ (8.75)$ (8.75)$ (8.47)$ (8.47)$ (8.94)$ (7.04)$ (8.63)$ (8.82)$
Low Growth_High Prices 2030-2031 Nov (6.92)$ (6.92)$ (7.48)$ (8.84)$ (9.23)$ (8.84)$ (8.84)$ (8.84)$ (8.51)$ (8.51)$ (9.07)$ (7.10)$ (8.69)$ (8.92)$
Low Growth_High Prices 2030-2031 Dec (7.56)$ (7.22)$ (7.56)$ (9.38)$ (9.37)$ (9.38)$ (9.38)$ (9.38)$ (9.15)$ (8.81)$ (9.15)$ (7.44)$ (9.04)$ (9.38)$
Low Growth_High Prices 2030-2031 Jan (7.57)$ (7.35)$ (7.57)$ (9.35)$ (9.43)$ (9.35)$ (9.35)$ (9.35)$ (9.16)$ (8.94)$ (9.16)$ (7.50)$ (9.09)$ (9.36)$ Low Growth_High Prices 2030-2031 Feb (7.46)$ (7.37)$ (7.54)$ (9.37)$ (9.44)$ (9.37)$ (9.37)$ (9.37)$ (9.05)$ (8.96)$ (9.13)$ (7.45)$ (9.05)$ (9.38)$ Low Growth_High Prices 2030-2031 Mar (7.12)$ (7.12)$ (7.52)$ (9.11)$ (9.38)$ (9.11)$ (9.11)$ (9.11)$ (8.71)$ (8.71)$ (9.11)$ (7.25)$ (8.84)$ (9.17)$ Low Growth_High Prices 2030-2031 Apr (6.85)$ (6.85)$ (7.53)$ (8.84)$ (9.39)$ (8.84)$ (8.84)$ (8.84)$ (8.44)$ (8.44)$ (9.12)$ (7.08)$ (8.67)$ (8.95)$ Low Growth_High Prices 2030-2031 May (6.96)$ (6.96)$ (7.54)$ (8.96)$ (9.39)$ (8.96)$ (8.96)$ (8.96)$ (8.56)$ (8.56)$ (9.13)$ (7.16)$ (8.75)$ (9.04)$ Low Growth_High Prices 2030-2031 Jun (7.05)$ (7.05)$ (7.55)$ (9.04)$ (9.41)$ (9.04)$ (9.04)$ (9.04)$ (8.64)$ (8.64)$ (9.14)$ (7.21)$ (8.81)$ (9.11)$ Low Growth_High Prices 2030-2031 Jul (7.30)$ (7.30)$ (7.56)$ (9.29)$ (9.42)$ (9.29)$ (9.29)$ (9.29)$ (8.89)$ (8.89)$ (9.15)$ (7.38)$ (8.97)$ (9.32)$ Low Growth_High Prices 2030-2031 Aug (7.38)$ (7.38)$ (7.57)$ (9.38)$ (9.43)$ (9.38)$ (9.38)$ (9.38)$ (8.97)$ (8.97)$ (9.16)$ (7.44)$ (9.04)$ (9.39)$ Low Growth_High Prices 2030-2031 Sep (7.26)$ (7.26)$ (7.58)$ (9.26)$ (9.44)$ (9.26)$ (9.26)$ (9.26)$ (8.85)$ (8.85)$ (9.17)$ (7.37)$ (8.96)$ (9.29)$ Low Growth_High Prices 2030-2031 Oct (7.28)$ (7.28)$ (7.67)$ (9.28)$ (9.52)$ (9.28)$ (9.28)$ (9.28)$ (8.88)$ (8.88)$ (9.26)$ (7.41)$ (9.00)$ (9.33)$ Low Growth_High Prices 2031-2032 Nov (7.34)$ (7.34)$ (7.83)$ (9.39)$ (9.70)$ (9.39)$ (9.39)$ (9.39)$ (8.93)$ (8.93)$ (9.42)$ (7.50)$ (9.09)$ (9.45)$ Low Growth_High Prices 2031-2032 Dec (7.88)$ (7.52)$ (7.88)$ (9.84)$ (9.84)$ (9.84)$ (9.84)$ (9.84)$ (9.47)$ (9.12)$ (9.47)$ (7.76)$ (9.35)$ (9.84)$ Low Growth_High Prices 2031-2032 Jan (7.91)$ (7.70)$ (7.91)$ (9.83)$ (9.90)$ (9.83)$ (9.83)$ (9.83)$ (9.50)$ (9.29)$ (9.50)$ (7.84)$ (9.43)$ (9.85)$ Low Growth_High Prices 2031-2032 Feb (7.73)$ (7.61)$ (7.89)$ (9.74)$ (9.93)$ (9.74)$ (9.74)$ (9.74)$ (9.33)$ (9.20)$ (9.48)$ (7.74)$ (9.34)$ (9.78)$ Low Growth_High Prices 2031-2032 Mar (7.41)$ (7.41)$ (7.87)$ (9.54)$ (9.86)$ (9.54)$ (9.54)$ (9.54)$ (9.00)$ (9.00)$ (9.46)$ (7.56)$ (9.16)$ (9.60)$
Low Growth_High Prices 2031-2032 Apr (7.14)$ (7.14)$ (7.88)$ (9.27)$ (9.87)$ (9.27)$ (9.27)$ (9.27)$ (8.74)$ (8.74)$ (9.47)$ (7.39)$ (8.98)$ (9.39)$
Low Growth_High Prices 2031-2032 May (7.21)$ (7.21)$ (7.89)$ (9.34)$ (9.88)$ (9.34)$ (9.34)$ (9.34)$ (8.80)$ (8.80)$ (9.48)$ (7.44)$ (9.03)$ (9.45)$
Low Growth_High Prices 2031-2032 Jun (7.28)$ (7.28)$ (7.90)$ (9.41)$ (9.89)$ (9.41)$ (9.41)$ (9.41)$ (8.87)$ (8.87)$ (9.49)$ (7.49)$ (9.08)$ (9.50)$
Low Growth_High Prices 2031-2032 Jul (7.51)$ (7.51)$ (7.91)$ (9.64)$ (9.90)$ (9.64)$ (9.64)$ (9.64)$ (9.10)$ (9.10)$ (9.51)$ (7.64)$ (9.24)$ (9.69)$
Low Growth_High Prices 2031-2032 Aug (7.62)$ (7.62)$ (7.92)$ (9.76)$ (9.91)$ (9.76)$ (9.76)$ (9.76)$ (9.21)$ (9.21)$ (9.52)$ (7.72)$ (9.31)$ (9.79)$
Low Growth_High Prices 2031-2032 Sep (7.53)$ (7.53)$ (7.93)$ (9.66)$ (9.92)$ (9.66)$ (9.66)$ (9.66)$ (9.12)$ (9.12)$ (9.53)$ (7.66)$ (9.26)$ (9.71)$
Low Growth_High Prices 2031-2032 Oct (7.63)$ (7.63)$ (8.06)$ (9.76)$ (10.05)$ (9.76)$ (9.76)$ (9.76)$ (9.22)$ (9.22)$ (9.65)$ (7.77)$ (9.37)$ (9.82)$
Low Growth_High Prices 2032-2033 Nov (7.66)$ (7.66)$ (8.28)$ (9.85)$ (10.28)$ (9.85)$ (9.85)$ (9.85)$ (9.26)$ (9.26)$ (9.87)$ (7.87)$ (9.46)$ (9.94)$
Low Growth_High Prices 2032-2033 Dec (8.37)$ (8.04)$ (8.37)$ (10.42)$ (10.40)$ (10.42)$ (10.42)$ (10.42)$ (9.96)$ (9.63)$ (9.96)$ (8.26)$ (9.85)$ (10.42)$
Low Growth_High Prices 2032-2033 Jan (8.37)$ (8.15)$ (8.37)$ (10.43)$ (10.50)$ (10.43)$ (10.43)$ (10.43)$ (9.96)$ (9.74)$ (9.96)$ (8.29)$ (9.89)$ (10.44)$
Low Growth_High Prices 2032-2033 Feb (8.25)$ (8.16)$ (8.35)$ (10.44)$ (10.51)$ (10.44)$ (10.44)$ (10.44)$ (9.85)$ (9.75)$ (9.94)$ (8.25)$ (9.84)$ (10.45)$
Low Growth_High Prices 2032-2033 Mar (7.91)$ (7.91)$ (8.33)$ (10.19)$ (10.45)$ (10.19)$ (10.19)$ (10.19)$ (9.51)$ (9.51)$ (9.92)$ (8.05)$ (9.64)$ (10.25)$
Low Growth_High Prices 2032-2033 Apr (7.64)$ (7.64)$ (8.34)$ (9.91)$ (10.46)$ (9.91)$ (9.91)$ (9.91)$ (9.23)$ (9.23)$ (9.93)$ (7.87)$ (9.46)$ (10.02)$ Low Growth_High Prices 2032-2033 May (7.69)$ (7.69)$ (8.35)$ (9.97)$ (10.48)$ (9.97)$ (9.97)$ (9.97)$ (9.28)$ (9.28)$ (9.94)$ (7.91)$ (9.50)$ (10.07)$ Low Growth_High Prices 2032-2033 Jun (7.76)$ (7.76)$ (8.36)$ (10.03)$ (10.49)$ (10.03)$ (10.03)$ (10.03)$ (9.35)$ (9.35)$ (9.95)$ (7.96)$ (9.55)$ (10.13)$ Low Growth_High Prices 2032-2033 Jul (8.09)$ (8.09)$ (8.37)$ (10.38)$ (10.50)$ (10.38)$ (10.38)$ (10.38)$ (9.69)$ (9.69)$ (9.96)$ (8.19)$ (9.78)$ (10.40)$ Low Growth_High Prices 2032-2033 Aug (8.16)$ (8.16)$ (8.38)$ (10.44)$ (10.51)$ (10.44)$ (10.44)$ (10.44)$ (9.75)$ (9.75)$ (9.97)$ (8.23)$ (9.82)$ (10.45)$ Low Growth_High Prices 2032-2033 Sep (8.02)$ (8.02)$ (8.39)$ (10.30)$ (10.52)$ (10.30)$ (10.30)$ (10.30)$ (9.61)$ (9.61)$ (9.98)$ (8.14)$ (9.73)$ (10.34)$ Low Growth_High Prices 2032-2033 Oct (8.02)$ (8.02)$ (8.49)$ (10.30)$ (10.62)$ (10.30)$ (10.30)$ (10.30)$ (9.61)$ (9.61)$ (10.09)$ (8.18)$ (9.77)$ (10.37)$ Low Growth_High Prices 2033-2034 Nov (8.16)$ (8.16)$ (8.72)$ (10.49)$ (10.85)$ (10.49)$ (10.49)$ (10.49)$ (9.75)$ (9.75)$ (10.31)$ (8.35)$ (9.94)$ (10.56)$ Low Growth_High Prices 2033-2034 Dec (8.80)$ (8.48)$ (8.80)$ (11.07)$ (11.04)$ (11.07)$ (11.07)$ (11.07)$ (10.39)$ (10.07)$ (10.39)$ (8.69)$ (10.29)$ (11.07)$
Monthly Avoided Costs 1/
Nominal$
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 235 of 829
APPENDIX 6.4: LOW GROWTH – HIGH PRICE MONTHLY DETAIL

Scenario Gas Year Month ID Both ID GTN ID NWP Klam Falls La Grande Medford GTN Medford NWP Roseburg WA Both WA GTN WA NWP ID Annual WA Annual OR Annual
Low Growth_High Prices 2033-2034 Jan (8.80)$ (8.56)$ (8.80)$ (11.00)$ (11.08)$ (11.00)$ (11.00)$ (11.00)$ (10.40)$ (10.15)$ (10.40)$ (8.72)$ (10.31)$ (11.02)$
Low Growth_High Prices 2033-2034 Feb (8.71)$ (8.62)$ (8.79)$ (11.06)$ (11.15)$ (11.06)$ (11.06)$ (11.06)$ (10.30)$ (10.21)$ (10.38)$ (8.71)$ (10.30)$ (11.08)$
Low Growth_High Prices 2033-2034 Mar (8.27)$ (8.27)$ (8.76)$ (10.71)$ (11.04)$ (10.71)$ (10.71)$ (10.71)$ (9.87)$ (9.87)$ (10.35)$ (8.44)$ (10.03)$ (10.77)$
Low Growth_High Prices 2033-2034 Apr (8.02)$ (8.02)$ (8.77)$ (10.45)$ (11.05)$ (10.45)$ (10.45)$ (10.45)$ (9.61)$ (9.61)$ (10.36)$ (8.27)$ (9.86)$ (10.57)$
Low Growth_High Prices 2033-2034 May (8.04)$ (8.04)$ (8.78)$ (10.47)$ (11.06)$ (10.47)$ (10.47)$ (10.47)$ (9.64)$ (9.64)$ (10.37)$ (8.29)$ (9.88)$ (10.59)$
Low Growth_High Prices 2033-2034 Jun (8.18)$ (8.18)$ (8.79)$ (10.61)$ (11.07)$ (10.61)$ (10.61)$ (10.61)$ (9.77)$ (9.77)$ (10.38)$ (8.38)$ (9.98)$ (10.70)$
Low Growth_High Prices 2033-2034 Jul (8.51)$ (8.51)$ (8.80)$ (10.95)$ (11.08)$ (10.95)$ (10.95)$ (10.95)$ (10.11)$ (10.11)$ (10.40)$ (8.61)$ (10.20)$ (10.98)$
Low Growth_High Prices 2033-2034 Aug (8.55)$ (8.55)$ (8.82)$ (10.99)$ (11.09)$ (10.99)$ (10.99)$ (10.99)$ (10.14)$ (10.14)$ (10.41)$ (8.64)$ (10.23)$ (11.01)$ Low Growth_High Prices 2033-2034 Sep (8.35)$ (8.35)$ (8.83)$ (10.78)$ (11.10)$ (10.78)$ (10.78)$ (10.78)$ (9.94)$ (9.94)$ (10.42)$ (8.51)$ (10.10)$ (10.85)$ Low Growth_High Prices 2033-2034 Oct (8.41)$ (8.41)$ (9.06)$ (10.85)$ (11.33)$ (10.85)$ (10.85)$ (10.85)$ (10.00)$ (10.00)$ (10.65)$ (8.63)$ (10.22)$ (10.95)$ Low Growth_High Prices 2034-2035 Nov (8.58)$ (8.58)$ (9.12)$ (11.08)$ (11.41)$ (11.08)$ (11.08)$ (11.08)$ (10.17)$ (10.17)$ (10.71)$ (8.76)$ (10.35)$ (11.15)$ Low Growth_High Prices 2034-2035 Dec (9.17)$ (8.83)$ (9.17)$ (11.65)$ (11.63)$ (11.65)$ (11.65)$ (11.65)$ (10.76)$ (10.42)$ (10.76)$ (9.06)$ (10.65)$ (11.65)$ Low Growth_High Prices 2034-2035 Jan (9.22)$ (9.05)$ (9.22)$ (11.66)$ (11.68)$ (11.66)$ (11.66)$ (11.66)$ (10.82)$ (10.64)$ (10.82)$ (9.17)$ (10.76)$ (11.66)$ Low Growth_High Prices 2034-2035 Feb (9.13)$ (9.04)$ (9.20)$ (11.64)$ (11.74)$ (11.64)$ (11.64)$ (11.64)$ (10.72)$ (10.63)$ (10.79)$ (9.12)$ (10.71)$ (11.66)$ Low Growth_High Prices 2034-2035 Mar (8.75)$ (8.75)$ (9.16)$ (11.35)$ (11.60)$ (11.35)$ (11.35)$ (11.35)$ (10.34)$ (10.34)$ (10.75)$ (8.89)$ (10.48)$ (11.40)$ Low Growth_High Prices 2034-2035 Apr (8.51)$ (8.51)$ (9.17)$ (11.11)$ (11.61)$ (11.11)$ (11.11)$ (11.11)$ (10.10)$ (10.10)$ (10.77)$ (8.73)$ (10.33)$ (11.21)$ Low Growth_High Prices 2034-2035 May (8.45)$ (8.45)$ (9.18)$ (11.05)$ (11.62)$ (11.05)$ (11.05)$ (11.05)$ (10.05)$ (10.05)$ (10.78)$ (8.70)$ (10.29)$ (11.17)$ Low Growth_High Prices 2034-2035 Jun (8.59)$ (8.59)$ (9.20)$ (11.19)$ (11.63)$ (11.19)$ (11.19)$ (11.19)$ (10.18)$ (10.18)$ (10.79)$ (8.79)$ (10.38)$ (11.28)$ Low Growth_High Prices 2034-2035 Jul (8.89)$ (8.89)$ (9.21)$ (11.50)$ (11.64)$ (11.50)$ (11.50)$ (11.50)$ (10.48)$ (10.48)$ (10.80)$ (9.00)$ (10.59)$ (11.53)$ Low Growth_High Prices 2034-2035 Aug (9.02)$ (9.02)$ (9.22)$ (11.62)$ (11.65)$ (11.62)$ (11.62)$ (11.62)$ (10.61)$ (10.61)$ (10.81)$ (9.08)$ (10.68)$ (11.63)$ Low Growth_High Prices 2034-2035 Sep (8.81)$ (8.81)$ (9.23)$ (11.41)$ (11.67)$ (11.41)$ (11.41)$ (11.41)$ (10.40)$ (10.40)$ (10.82)$ (8.95)$ (10.54)$ (11.46)$ Low Growth_High Prices 2034-2035 Oct (8.69)$ (8.69)$ (9.38)$ (11.29)$ (11.82)$ (11.29)$ (11.29)$ (11.29)$ (10.28)$ (10.28)$ (10.97)$ (8.92)$ (10.51)$ (11.40)$
Low Growth_High Prices 2035-2036 Nov (8.56)$ (8.56)$ (9.48)$ (11.23)$ (11.91)$ (11.23)$ (11.23)$ (11.23)$ (10.15)$ (10.15)$ (11.07)$ (8.86)$ (10.46)$ (11.37)$
Low Growth_High Prices 2035-2036 Dec (9.21)$ (8.77)$ (9.74)$ (12.11)$ (12.18)$ (12.11)$ (12.11)$ (12.11)$ (10.81)$ (10.36)$ (11.33)$ (9.24)$ (10.83)$ (12.13)$
Low Growth_High Prices 2035-2036 Jan (9.70)$ (9.37)$ (9.74)$ (12.13)$ (12.33)$ (12.13)$ (12.13)$ (12.13)$ (11.29)$ (10.96)$ (11.34)$ (9.60)$ (11.20)$ (12.17)$
Low Growth_High Prices 2035-2036 Feb (9.56)$ (9.46)$ (9.79)$ (12.22)$ (12.44)$ (12.22)$ (12.22)$ (12.22)$ (11.15)$ (11.05)$ (11.39)$ (9.60)$ (11.20)$ (12.26)$
Low Growth_High Prices 2035-2036 Mar (9.18)$ (9.18)$ (9.77)$ (11.94)$ (12.35)$ (11.94)$ (11.94)$ (11.94)$ (10.78)$ (10.78)$ (11.36)$ (9.38)$ (10.97)$ (12.02)$
Low Growth_High Prices 2035-2036 Apr (8.90)$ (8.90)$ (9.78)$ (11.65)$ (12.36)$ (11.65)$ (11.65)$ (11.65)$ (10.49)$ (10.49)$ (11.37)$ (9.19)$ (10.78)$ (11.79)$
Low Growth_High Prices 2035-2036 May (8.94)$ (8.94)$ (9.79)$ (11.69)$ (12.37)$ (11.69)$ (11.69)$ (11.69)$ (10.53)$ (10.53)$ (11.38)$ (9.22)$ (10.82)$ (11.83)$
Low Growth_High Prices 2035-2036 Jun (9.17)$ (9.17)$ (9.80)$ (11.92)$ (12.38)$ (11.92)$ (11.92)$ (11.92)$ (10.76)$ (10.76)$ (11.39)$ (9.38)$ (10.97)$ (12.02)$
Low Growth_High Prices 2035-2036 Jul (9.74)$ (9.74)$ (9.88)$ (12.51)$ (12.47)$ (12.47)$ (12.47)$ (12.47)$ (11.33)$ (11.33)$ (11.48)$ (9.79)$ (11.38)$ (12.47)$
Low Growth_High Prices 2035-2036 Aug (9.97)$ (9.97)$ (10.11)$ (12.74)$ (12.69)$ (12.69)$ (12.69)$ (12.69)$ (11.56)$ (11.56)$ (11.70)$ (10.02)$ (11.61)$ (12.70)$
Low Growth_High Prices 2035-2036 Sep (9.55)$ (9.55)$ (9.84)$ (12.31)$ (12.42)$ (12.31)$ (12.31)$ (12.31)$ (11.14)$ (11.14)$ (11.43)$ (9.64)$ (11.24)$ (12.33)$
Low Growth_High Prices 2035-2036 Oct (9.51)$ (9.51)$ (10.06)$ (12.28)$ (12.64)$ (12.28)$ (12.28)$ (12.28)$ (11.11)$ (11.11)$ (11.65)$ (9.70)$ (11.29)$ (12.35)$
Low Growth_High Prices 2036-2037 Nov (9.71)$ (9.71)$ (10.26)$ (12.55)$ (12.88)$ (12.55)$ (12.55)$ (12.55)$ (11.30)$ (11.30)$ (11.86)$ (9.90)$ (11.49)$ (12.61)$
Low Growth_High Prices 2036-2037 Dec (10.37)$ (10.23)$ (10.37)$ (13.43)$ (13.39)$ (13.43)$ (13.43)$ (13.43)$ (11.97)$ (11.83)$ (11.97)$ (10.33)$ (11.92)$ (13.42)$ Low Growth_High Prices 2036-2037 Jan (10.38)$ (10.36)$ (10.38)$ (13.29)$ (13.29)$ (13.29)$ (13.29)$ (13.29)$ (11.97)$ (11.95)$ (11.97)$ (10.37)$ (11.97)$ (13.29)$ Low Growth_High Prices 2036-2037 Feb (10.51)$ (10.43)$ (10.52)$ (13.36)$ (13.47)$ (13.36)$ (13.36)$ (13.36)$ (12.11)$ (12.02)$ (12.11)$ (10.49)$ (12.08)$ (13.38)$ Low Growth_High Prices 2036-2037 Mar (9.88)$ (9.88)$ (10.49)$ (12.80)$ (13.23)$ (12.80)$ (12.80)$ (12.80)$ (11.47)$ (11.47)$ (12.08)$ (10.08)$ (11.67)$ (12.88)$ Low Growth_High Prices 2036-2037 Apr (9.29)$ (9.29)$ (9.70)$ (12.21)$ (12.43)$ (12.21)$ (12.21)$ (12.21)$ (10.88)$ (10.88)$ (11.29)$ (9.43)$ (11.02)$ (12.25)$ Low Growth_High Prices 2036-2037 May (9.33)$ (9.33)$ (9.71)$ (12.24)$ (12.45)$ (12.24)$ (12.24)$ (12.24)$ (10.92)$ (10.92)$ (11.30)$ (9.46)$ (11.05)$ (12.28)$ Low Growth_High Prices 2036-2037 Jun (9.50)$ (9.50)$ (9.72)$ (12.42)$ (12.46)$ (12.42)$ (12.42)$ (12.42)$ (11.09)$ (11.09)$ (11.31)$ (9.57)$ (11.17)$ (12.42)$ Low Growth_High Prices 2036-2037 Jul (10.05)$ (10.05)$ (10.19)$ (12.98)$ (12.93)$ (12.93)$ (12.93)$ (12.93)$ (11.65)$ (11.65)$ (11.78)$ (10.10)$ (11.69)$ (12.94)$ Low Growth_High Prices 2036-2037 Aug (10.18)$ (10.18)$ (10.32)$ (13.11)$ (13.06)$ (13.06)$ (13.06)$ (13.06)$ (11.77)$ (11.77)$ (11.92)$ (10.23)$ (11.82)$ (13.07)$ Low Growth_High Prices 2036-2037 Sep (9.70)$ (9.70)$ (9.87)$ (12.62)$ (12.60)$ (12.60)$ (12.60)$ (12.60)$ (11.29)$ (11.29)$ (11.46)$ (9.75)$ (11.35)$ (12.61)$ Low Growth_High Prices 2036-2037 Oct (9.56)$ (9.56)$ (10.25)$ (12.48)$ (12.98)$ (12.48)$ (12.48)$ (12.48)$ (11.15)$ (11.15)$ (11.84)$ (9.79)$ (11.38)$ (12.58)$ 1/ Avoided costs are before Environmental Externalities adder.
Monthly Avoided Costs 1/
Nominal$
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 236 of 829
APPENDIX 6.4: EXPECTED MONTHLY DETAIL

Scenario Gas Year Month ID Both ID GTN ID NWP Klam Falls La Grande Medford GTN Medford NWP Roseburg WA Both WA GTN WA NWP ID Annual WA Annual OR AnnualExpected Case 2017-2018 Nov (1.87)$ (1.83)$ (2.57)$ (1.94)$ (2.57)$ (1.94)$ (1.94)$ (1.94)$ (1.87)$ (1.83)$ (2.57)$ (2.09)$ (2.09)$ (2.06)$
Expected Case 2017-2018 Dec (2.13)$ (1.59)$ (2.58)$ (2.25)$ (2.72)$ (2.25)$ (2.25)$ (2.25)$ (2.13)$ (1.59)$ (2.58)$ (2.10)$ (2.10)$ (2.35)$
Expected Case 2017-2018 Jan (2.16)$ (1.69)$ (2.58)$ (2.00)$ (2.77)$ (2.00)$ (2.00)$ (2.00)$ (2.16)$ (1.69)$ (2.58)$ (2.15)$ (2.15)$ (2.15)$ Expected Case 2017-2018 Feb (2.42)$ (2.17)$ (2.60)$ (2.27)$ (2.91)$ (2.27)$ (2.27)$ (2.27)$ (2.42)$ (2.17)$ (2.60)$ (2.40)$ (2.40)$ (2.40)$
Expected Case 2017-2018 Mar (0.95)$ (0.95)$ (2.60)$ (0.98)$ (2.60)$ (0.98)$ (0.98)$ (0.98)$ (0.95)$ (0.95)$ (2.60)$ (1.50)$ (1.50)$ (1.30)$
Expected Case 2017-2018 Apr (1.08)$ (1.08)$ (2.61)$ (1.11)$ (2.61)$ (1.11)$ (1.11)$ (1.11)$ (1.08)$ (1.08)$ (2.61)$ (1.59)$ (1.59)$ (1.41)$ Expected Case 2017-2018 May (1.05)$ (1.05)$ (2.61)$ (1.08)$ (2.61)$ (1.08)$ (1.08)$ (1.08)$ (1.05)$ (1.05)$ (2.61)$ (1.57)$ (1.57)$ (1.38)$ Expected Case 2017-2018 Jun (1.05)$ (1.05)$ (2.62)$ (1.07)$ (2.62)$ (1.07)$ (1.07)$ (1.07)$ (1.05)$ (1.05)$ (2.62)$ (1.57)$ (1.57)$ (1.38)$
Expected Case 2017-2018 Jul (1.09)$ (1.09)$ (2.63)$ (1.12)$ (2.63)$ (1.12)$ (1.12)$ (1.12)$ (1.09)$ (1.09)$ (2.63)$ (1.60)$ (1.60)$ (1.42)$
Expected Case 2017-2018 Aug (1.10)$ (1.10)$ (2.64)$ (1.13)$ (2.64)$ (1.13)$ (1.13)$ (1.13)$ (1.10)$ (1.10)$ (2.64)$ (1.61)$ (1.61)$ (1.43)$ Expected Case 2017-2018 Sep (1.06)$ (1.06)$ (2.65)$ (1.08)$ (2.65)$ (1.08)$ (1.08)$ (1.08)$ (1.06)$ (1.06)$ (2.65)$ (1.59)$ (1.59)$ (1.40)$
Expected Case 2017-2018 Oct (1.10)$ (1.10)$ (3.17)$ (1.12)$ (3.17)$ (1.12)$ (1.12)$ (1.12)$ (1.10)$ (1.10)$ (3.17)$ (1.79)$ (1.79)$ (1.53)$
Expected Case 2018-2019 Nov (1.57)$ (1.52)$ (2.66)$ (1.67)$ (2.66)$ (1.67)$ (1.67)$ (1.67)$ (1.57)$ (1.52)$ (2.66)$ (1.92)$ (1.92)$ (1.87)$ Expected Case 2018-2019 Dec (2.25)$ (1.69)$ (2.68)$ (2.45)$ (2.86)$ (2.45)$ (2.45)$ (2.45)$ (2.25)$ (1.69)$ (2.68)$ (2.21)$ (2.21)$ (2.53)$ Expected Case 2018-2019 Jan (2.22)$ (1.75)$ (2.68)$ (2.00)$ (2.79)$ (2.00)$ (2.00)$ (2.00)$ (2.22)$ (1.75)$ (2.68)$ (2.22)$ (2.22)$ (2.16)$
Expected Case 2018-2019 Feb (2.14)$ (1.76)$ (2.72)$ (1.90)$ (2.84)$ (1.90)$ (1.90)$ (1.90)$ (2.14)$ (1.76)$ (2.72)$ (2.21)$ (2.21)$ (2.08)$
Expected Case 2018-2019 Mar (1.62)$ (1.62)$ (2.70)$ (1.66)$ (2.70)$ (1.66)$ (1.66)$ (1.66)$ (1.62)$ (1.62)$ (2.70)$ (1.98)$ (1.98)$ (1.87)$ Expected Case 2018-2019 Apr (1.25)$ (1.25)$ (2.70)$ (1.28)$ (2.70)$ (1.28)$ (1.28)$ (1.28)$ (1.25)$ (1.25)$ (2.70)$ (1.74)$ (1.74)$ (1.57)$ Expected Case 2018-2019 May (1.24)$ (1.24)$ (2.71)$ (1.27)$ (2.71)$ (1.27)$ (1.27)$ (1.27)$ (1.24)$ (1.24)$ (2.71)$ (1.73)$ (1.73)$ (1.56)$
Expected Case 2018-2019 Jun (1.32)$ (1.32)$ (2.72)$ (1.35)$ (2.72)$ (1.35)$ (1.35)$ (1.35)$ (1.32)$ (1.32)$ (2.72)$ (1.79)$ (1.79)$ (1.63)$
Expected Case 2018-2019 Jul (1.41)$ (1.41)$ (2.73)$ (1.44)$ (2.73)$ (1.44)$ (1.44)$ (1.44)$ (1.94)$ (1.94)$ (3.26)$ (1.85)$ (2.38)$ (1.70)$ Expected Case 2018-2019 Aug (1.41)$ (1.41)$ (2.74)$ (1.44)$ (2.74)$ (1.44)$ (1.44)$ (1.44)$ (1.94)$ (1.94)$ (3.27)$ (1.85)$ (2.38)$ (1.70)$
Expected Case 2018-2019 Sep (1.32)$ (1.32)$ (2.75)$ (1.36)$ (2.75)$ (1.36)$ (1.36)$ (1.36)$ (1.86)$ (1.86)$ (3.28)$ (1.80)$ (2.33)$ (1.63)$
Expected Case 2018-2019 Oct (1.36)$ (1.36)$ (2.80)$ (1.39)$ (2.80)$ (1.39)$ (1.39)$ (1.39)$ (1.89)$ (1.89)$ (3.33)$ (1.84)$ (2.37)$ (1.67)$ Expected Case 2019-2020 Nov (1.77)$ (1.72)$ (2.76)$ (1.86)$ (2.76)$ (1.86)$ (1.86)$ (1.86)$ (2.30)$ (2.26)$ (3.29)$ (2.09)$ (2.62)$ (2.04)$ Expected Case 2019-2020 Dec (2.45)$ (1.91)$ (2.78)$ (2.71)$ (2.92)$ (2.71)$ (2.71)$ (2.71)$ (2.98)$ (2.44)$ (3.31)$ (2.38)$ (2.91)$ (2.75)$
Expected Case 2019-2020 Jan (2.47)$ (2.01)$ (2.78)$ (2.17)$ (2.87)$ (2.17)$ (2.17)$ (2.17)$ (3.00)$ (2.54)$ (3.31)$ (2.42)$ (2.95)$ (2.31)$
Expected Case 2019-2020 Feb (2.31)$ (1.96)$ (2.79)$ (2.07)$ (2.88)$ (2.07)$ (2.07)$ (2.07)$ (2.84)$ (2.49)$ (3.32)$ (2.35)$ (2.88)$ (2.23)$ Expected Case 2019-2020 Mar (1.79)$ (1.79)$ (2.79)$ (1.83)$ (2.79)$ (1.83)$ (1.83)$ (1.83)$ (2.32)$ (2.32)$ (3.32)$ (2.12)$ (2.65)$ (2.02)$
Expected Case 2019-2020 Apr (1.50)$ (1.50)$ (2.59)$ (1.54)$ (2.59)$ (1.54)$ (1.54)$ (1.54)$ (2.03)$ (2.03)$ (3.12)$ (1.86)$ (2.39)$ (1.75)$
Expected Case 2019-2020 May (1.50)$ (1.50)$ (2.60)$ (1.54)$ (2.60)$ (1.54)$ (1.54)$ (1.54)$ (2.03)$ (2.03)$ (3.13)$ (1.87)$ (2.40)$ (1.75)$ Expected Case 2019-2020 Jun (1.51)$ (1.51)$ (2.60)$ (1.54)$ (2.60)$ (1.54)$ (1.54)$ (1.54)$ (2.04)$ (2.04)$ (3.13)$ (1.87)$ (2.40)$ (1.76)$ Expected Case 2019-2020 Jul (1.56)$ (1.56)$ (2.61)$ (1.60)$ (2.61)$ (1.60)$ (1.60)$ (1.60)$ (2.09)$ (2.09)$ (3.14)$ (1.91)$ (2.44)$ (1.80)$
Expected Case 2019-2020 Aug (1.59)$ (1.59)$ (2.62)$ (1.63)$ (2.62)$ (1.63)$ (1.63)$ (1.63)$ (2.12)$ (2.12)$ (3.15)$ (1.93)$ (2.46)$ (1.83)$
Expected Case 2019-2020 Sep (1.54)$ (1.54)$ (2.63)$ (1.58)$ (2.63)$ (1.58)$ (1.58)$ (1.58)$ (2.07)$ (2.07)$ (3.16)$ (1.90)$ (2.44)$ (1.79)$ Expected Case 2019-2020 Oct (1.60)$ (1.60)$ (2.85)$ (1.64)$ (2.85)$ (1.64)$ (1.64)$ (1.64)$ (2.13)$ (2.13)$ (3.38)$ (2.02)$ (2.55)$ (1.88)$ Expected Case 2020-2021 Nov (1.87)$ (1.83)$ (2.65)$ (1.95)$ (2.65)$ (1.95)$ (1.95)$ (1.95)$ (2.40)$ (2.36)$ (3.18)$ (2.12)$ (2.65)$ (2.09)$
Expected Case 2020-2021 Dec (2.48)$ (1.98)$ (2.66)$ (2.65)$ (2.82)$ (2.65)$ (2.65)$ (2.65)$ (3.01)$ (2.51)$ (3.19)$ (2.37)$ (2.90)$ (2.68)$
Expected Case 2020-2021 Jan (2.68)$ (2.23)$ (2.68)$ (3.22)$ (3.74)$ (3.22)$ (3.22)$ (3.22)$ (3.32)$ (2.86)$ (3.32)$ (2.53)$ (3.17)$ (3.33)$ Expected Case 2020-2021 Feb (2.55)$ (2.17)$ (2.68)$ (3.17)$ (3.76)$ (3.17)$ (3.17)$ (3.17)$ (3.19)$ (2.81)$ (3.32)$ (2.47)$ (3.11)$ (3.29)$
Expected Case 2020-2021 Mar (2.07)$ (2.07)$ (2.63)$ (3.06)$ (3.58)$ (3.06)$ (3.06)$ (3.06)$ (2.70)$ (2.70)$ (3.27)$ (2.26)$ (2.89)$ (3.16)$
Expected Case 2020-2021 Apr (1.77)$ (1.77)$ (2.60)$ (2.76)$ (3.54)$ (2.76)$ (2.76)$ (2.76)$ (2.41)$ (2.41)$ (3.23)$ (2.05)$ (2.69)$ (2.92)$ Expected Case 2020-2021 May (1.76)$ (1.76)$ (2.61)$ (2.75)$ (3.55)$ (2.75)$ (2.75)$ (2.75)$ (2.40)$ (2.40)$ (3.24)$ (2.04)$ (2.68)$ (2.91)$ Expected Case 2020-2021 Jun (1.80)$ (1.80)$ (2.61)$ (2.78)$ (3.56)$ (2.78)$ (2.78)$ (2.78)$ (2.43)$ (2.43)$ (3.25)$ (2.07)$ (2.71)$ (2.94)$
Expected Case 2020-2021 Jul (1.88)$ (1.88)$ (2.62)$ (2.87)$ (3.57)$ (2.87)$ (2.87)$ (2.87)$ (2.52)$ (2.52)$ (3.26)$ (2.13)$ (2.77)$ (3.01)$
Expected Case 2020-2021 Aug (1.90)$ (1.90)$ (2.63)$ (2.89)$ (3.58)$ (2.89)$ (2.89)$ (2.89)$ (2.54)$ (2.54)$ (3.27)$ (2.15)$ (2.78)$ (3.03)$ Expected Case 2020-2021 Sep (1.82)$ (1.82)$ (2.64)$ (2.81)$ (3.59)$ (2.81)$ (2.81)$ (2.81)$ (2.46)$ (2.46)$ (3.28)$ (2.09)$ (2.73)$ (2.96)$ Expected Case 2020-2021 Oct (1.87)$ (1.87)$ (2.73)$ (2.86)$ (3.68)$ (2.86)$ (2.86)$ (2.86)$ (2.51)$ (2.51)$ (3.37)$ (2.16)$ (2.80)$ (3.03)$
Expected Case 2021-2022 Nov (2.22)$ (2.17)$ (2.68)$ (3.22)$ (3.63)$ (3.22)$ (3.22)$ (3.22)$ (2.85)$ (2.81)$ (3.31)$ (2.35)$ (2.99)$ (3.30)$ Expected Case 2021-2022 Dec (2.72)$ (2.31)$ (2.72)$ (3.79)$ (3.90)$ (3.79)$ (3.79)$ (3.79)$ (3.36)$ (2.95)$ (3.36)$ (2.58)$ (3.22)$ (3.81)$ Expected Case 2021-2022 Jan (2.73)$ (2.43)$ (2.73)$ (3.49)$ (3.83)$ (3.49)$ (3.49)$ (3.49)$ (3.47)$ (3.17)$ (3.47)$ (2.63)$ (3.37)$ (3.56)$
Expected Case 2021-2022 Feb (2.68)$ (2.45)$ (2.74)$ (3.52)$ (3.86)$ (3.52)$ (3.52)$ (3.52)$ (3.42)$ (3.20)$ (3.48)$ (2.62)$ (3.37)$ (3.59)$
Expected Case 2021-2022 Mar (2.37)$ (2.37)$ (2.69)$ (3.44)$ (3.70)$ (3.44)$ (3.44)$ (3.44)$ (3.12)$ (3.12)$ (3.43)$ (2.48)$ (3.22)$ (3.49)$ Expected Case 2021-2022 Apr (2.05)$ (2.05)$ (2.63)$ (3.11)$ (3.64)$ (3.11)$ (3.11)$ (3.11)$ (2.79)$ (2.79)$ (3.37)$ (2.24)$ (2.99)$ (3.22)$ Expected Case 2021-2022 May (2.06)$ (2.06)$ (2.64)$ (3.12)$ (3.65)$ (3.12)$ (3.12)$ (3.12)$ (2.80)$ (2.80)$ (3.38)$ (2.25)$ (2.99)$ (3.22)$
Expected Case 2021-2022 Jun (2.05)$ (2.05)$ (2.65)$ (3.11)$ (3.66)$ (3.11)$ (3.11)$ (3.11)$ (2.79)$ (2.79)$ (3.39)$ (2.25)$ (2.99)$ (3.22)$
Expected Case 2021-2022 Jul (2.11)$ (2.11)$ (2.66)$ (3.17)$ (3.67)$ (3.17)$ (3.17)$ (3.17)$ (2.85)$ (2.85)$ (3.40)$ (2.29)$ (3.03)$ (3.27)$ Expected Case 2021-2022 Aug (2.13)$ (2.13)$ (2.66)$ (3.19)$ (3.68)$ (3.19)$ (3.19)$ (3.19)$ (2.87)$ (2.87)$ (3.41)$ (2.31)$ (3.05)$ (3.29)$
Expected Case 2021-2022 Sep (2.15)$ (2.15)$ (2.67)$ (3.21)$ (3.69)$ (3.21)$ (3.21)$ (3.21)$ (2.89)$ (2.89)$ (3.42)$ (2.32)$ (3.07)$ (3.30)$
Expected Case 2021-2022 Oct (2.16)$ (2.16)$ (2.84)$ (3.23)$ (3.86)$ (3.23)$ (3.23)$ (3.23)$ (2.91)$ (2.91)$ (3.59)$ (2.39)$ (3.13)$ (3.35)$ Expected Case 2022-2023 Nov (2.37)$ (2.32)$ (2.84)$ (3.44)$ (3.86)$ (3.44)$ (3.44)$ (3.44)$ (3.11)$ (3.06)$ (3.58)$ (2.51)$ (3.25)$ (3.52)$ Expected Case 2022-2023 Dec (2.89)$ (2.49)$ (2.89)$ (4.04)$ (4.11)$ (4.04)$ (4.04)$ (4.04)$ (3.63)$ (3.23)$ (3.63)$ (2.75)$ (3.50)$ (4.05)$
Expected Case 2022-2023 Jan (2.89)$ (2.57)$ (2.89)$ (3.71)$ (4.06)$ (3.71)$ (3.71)$ (3.71)$ (3.74)$ (3.42)$ (3.74)$ (2.78)$ (3.63)$ (3.78)$
Expected Case 2022-2023 Feb (2.80)$ (2.53)$ (2.87)$ (3.67)$ (4.07)$ (3.67)$ (3.67)$ (3.67)$ (3.65)$ (3.38)$ (3.72)$ (2.74)$ (3.58)$ (3.75)$ Expected Case 2022-2023 Mar (2.48)$ (2.48)$ (2.79)$ (3.62)$ (3.87)$ (3.62)$ (3.62)$ (3.62)$ (3.33)$ (3.33)$ (3.64)$ (2.58)$ (3.43)$ (3.67)$ Expected Case 2022-2023 Apr (2.16)$ (2.16)$ (2.80)$ (3.29)$ (3.88)$ (3.29)$ (3.29)$ (3.29)$ (3.01)$ (3.01)$ (3.64)$ (2.37)$ (3.22)$ (3.41)$
Expected Case 2022-2023 May (2.22)$ (2.22)$ (2.80)$ (3.35)$ (3.89)$ (3.35)$ (3.35)$ (3.35)$ (3.07)$ (3.07)$ (3.65)$ (2.42)$ (3.26)$ (3.46)$
Expected Case 2022-2023 Jun (2.25)$ (2.25)$ (2.81)$ (3.38)$ (3.90)$ (3.38)$ (3.38)$ (3.38)$ (3.10)$ (3.10)$ (3.66)$ (2.44)$ (3.29)$ (3.49)$ Expected Case 2022-2023 Jul (2.27)$ (2.27)$ (2.82)$ (3.40)$ (3.91)$ (3.40)$ (3.40)$ (3.40)$ (3.12)$ (3.12)$ (3.67)$ (2.45)$ (3.30)$ (3.50)$
Expected Case 2022-2023 Aug (2.34)$ (2.34)$ (2.83)$ (3.47)$ (3.92)$ (3.47)$ (3.47)$ (3.47)$ (3.18)$ (3.18)$ (3.68)$ (2.50)$ (3.35)$ (3.56)$
Expected Case 2022-2023 Sep (2.32)$ (2.32)$ (2.84)$ (3.46)$ (3.93)$ (3.46)$ (3.46)$ (3.46)$ (3.17)$ (3.17)$ (3.69)$ (2.50)$ (3.34)$ (3.55)$ Expected Case 2022-2023 Oct (2.33)$ (2.33)$ (2.99)$ (3.46)$ (4.08)$ (3.46)$ (3.46)$ (3.46)$ (3.18)$ (3.18)$ (3.84)$ (2.55)$ (3.40)$ (3.59)$ Expected Case 2023-2024 Nov (2.66)$ (2.62)$ (3.30)$ (3.82)$ (4.38)$ (3.82)$ (3.82)$ (3.82)$ (3.51)$ (3.47)$ (4.15)$ (2.86)$ (3.71)$ (3.93)$
Expected Case 2023-2024 Dec (3.27)$ (2.81)$ (3.32)$ (4.49)$ (4.54)$ (4.49)$ (4.49)$ (4.49)$ (4.12)$ (3.66)$ (4.17)$ (3.13)$ (3.98)$ (4.50)$
Expected Case 2023-2024 Jan (3.35)$ (2.91)$ (3.35)$ (4.13)$ (4.57)$ (4.13)$ (4.13)$ (4.13)$ (4.31)$ (3.87)$ (4.31)$ (3.21)$ (4.16)$ (4.22)$ Expected Case 2023-2024 Feb (3.24)$ (2.91)$ (3.36)$ (4.13)$ (4.60)$ (4.13)$ (4.13)$ (4.13)$ (4.19)$ (3.86)$ (4.31)$ (3.17)$ (4.12)$ (4.22)$
Expected Case 2023-2024 Mar (2.87)$ (2.87)$ (3.34)$ (4.09)$ (4.50)$ (4.09)$ (4.09)$ (4.09)$ (3.82)$ (3.82)$ (4.29)$ (3.02)$ (3.98)$ (4.17)$
Expected Case 2023-2024 Apr (2.66)$ (2.66)$ (3.34)$ (3.87)$ (4.50)$ (3.87)$ (3.87)$ (3.87)$ (3.61)$ (3.61)$ (4.30)$ (2.89)$ (3.84)$ (4.00)$ Expected Case 2023-2024 May (2.65)$ (2.65)$ (3.35)$ (3.86)$ (4.51)$ (3.86)$ (3.86)$ (3.86)$ (3.60)$ (3.60)$ (4.31)$ (2.88)$ (3.84)$ (3.99)$ Expected Case 2023-2024 Jun (2.62)$ (2.62)$ (3.36)$ (3.84)$ (4.52)$ (3.84)$ (3.84)$ (3.84)$ (3.58)$ (3.58)$ (4.32)$ (2.87)$ (3.82)$ (3.97)$
Expected Case 2023-2024 Jul (2.76)$ (2.76)$ (3.37)$ (3.97)$ (4.53)$ (3.97)$ (3.97)$ (3.97)$ (3.71)$ (3.71)$ (4.33)$ (2.96)$ (3.92)$ (4.09)$
Expected Case 2023-2024 Aug (2.87)$ (2.87)$ (3.38)$ (4.09)$ (4.54)$ (4.09)$ (4.09)$ (4.09)$ (3.83)$ (3.83)$ (4.34)$ (3.04)$ (4.00)$ (4.18)$ Expected Case 2023-2024 Sep (2.85)$ (2.85)$ (3.39)$ (4.07)$ (4.55)$ (4.07)$ (4.07)$ (4.07)$ (3.80)$ (3.80)$ (4.35)$ (3.03)$ (3.98)$ (4.16)$ Expected Case 2023-2024 Oct (2.89)$ (2.89)$ (3.59)$ (4.11)$ (4.75)$ (4.11)$ (4.11)$ (4.11)$ (3.85)$ (3.85)$ (4.54)$ (3.13)$ (4.08)$ (4.24)$
Expected Case 2024-2025 Nov (3.05)$ (3.00)$ (3.62)$ (4.28)$ (4.77)$ (4.28)$ (4.28)$ (4.28)$ (4.00)$ (3.96)$ (4.57)$ (3.22)$ (4.18)$ (4.38)$
Expected Case 2024-2025 Dec (3.56)$ (3.09)$ (3.63)$ (4.86)$ (4.91)$ (4.86)$ (4.86)$ (4.86)$ (4.51)$ (4.05)$ (4.59)$ (3.43)$ (4.38)$ (4.87)$ Expected Case 2024-2025 Jan (3.59)$ (3.15)$ (3.63)$ (4.46)$ (4.93)$ (4.46)$ (4.46)$ (4.46)$ (4.65)$ (4.22)$ (4.70)$ (3.46)$ (4.52)$ (4.55)$
Expected Case 2024-2025 Feb (3.53)$ (3.16)$ (3.67)$ (4.47)$ (4.99)$ (4.47)$ (4.47)$ (4.47)$ (4.59)$ (4.22)$ (4.73)$ (3.45)$ (4.52)$ (4.57)$
Expected Case 2024-2025 Mar (3.01)$ (3.01)$ (3.65)$ (4.31)$ (4.89)$ (4.31)$ (4.31)$ (4.31)$ (4.07)$ (4.07)$ (4.71)$ (3.22)$ (4.29)$ (4.43)$ Expected Case 2024-2025 Apr (2.83)$ (2.83)$ (3.66)$ (4.13)$ (4.90)$ (4.13)$ (4.13)$ (4.13)$ (3.89)$ (3.89)$ (4.72)$ (3.11)$ (4.17)$ (4.28)$ Expected Case 2024-2025 May (2.86)$ (2.86)$ (3.67)$ (4.16)$ (4.91)$ (4.16)$ (4.16)$ (4.16)$ (3.92)$ (3.92)$ (4.73)$ (3.13)$ (4.19)$ (4.31)$
Expected Case 2024-2025 Jun (2.95)$ (2.95)$ (3.68)$ (4.25)$ (4.92)$ (4.25)$ (4.25)$ (4.25)$ (4.01)$ (4.01)$ (4.74)$ (3.19)$ (4.25)$ (4.38)$
Expected Case 2024-2025 Jul (3.02)$ (3.02)$ (3.69)$ (4.32)$ (4.93)$ (4.32)$ (4.32)$ (4.32)$ (4.08)$ (4.08)$ (4.75)$ (3.24)$ (4.30)$ (4.44)$ Expected Case 2024-2025 Aug (3.05)$ (3.05)$ (3.70)$ (4.35)$ (4.94)$ (4.35)$ (4.35)$ (4.35)$ (4.11)$ (4.11)$ (4.76)$ (3.27)$ (4.33)$ (4.47)$
Expected Case 2024-2025 Sep (3.00)$ (3.00)$ (3.71)$ (4.30)$ (4.95)$ (4.30)$ (4.30)$ (4.30)$ (4.06)$ (4.06)$ (4.77)$ (3.23)$ (4.29)$ (4.43)$
Expected Case 2024-2025 Oct (3.00)$ (3.00)$ (3.79)$ (4.30)$ (5.03)$ (4.30)$ (4.30)$ (4.30)$ (4.06)$ (4.06)$ (4.85)$ (3.26)$ (4.32)$ (4.45)$ Expected Case 2025-2026 Nov (3.14)$ (3.06)$ (3.73)$ (4.42)$ (4.97)$ (4.42)$ (4.42)$ (4.42)$ (4.21)$ (4.12)$ (4.79)$ (3.31)$ (4.37)$ (4.53)$
Monthly Avoided Costs 1/
Nominal$
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 237 of 829
APPENDIX 6.4: EXPECTED MONTHLY DETAIL

Scenario Gas Year Month ID Both ID GTN ID NWP Klam Falls La Grande Medford GTN Medford NWP Roseburg WA Both WA GTN WA NWP ID Annual WA Annual OR AnnualExpected Case 2025-2026 Dec (3.63)$ (3.16)$ (3.75)$ (5.07)$ (5.08)$ (5.07)$ (5.07)$ (5.07)$ (4.69)$ (4.22)$ (4.81)$ (3.51)$ (4.57)$ (5.07)$
Expected Case 2025-2026 Jan (3.70)$ (3.27)$ (3.75)$ (4.66)$ (5.12)$ (4.66)$ (4.66)$ (4.66)$ (4.87)$ (4.43)$ (4.92)$ (3.57)$ (4.74)$ (4.75)$
Expected Case 2025-2026 Feb (3.61)$ (3.24)$ (3.78)$ (4.64)$ (5.18)$ (4.64)$ (4.64)$ (4.64)$ (4.78)$ (4.41)$ (4.95)$ (3.55)$ (4.71)$ (4.75)$ Expected Case 2025-2026 Mar (3.09)$ (3.09)$ (3.77)$ (4.48)$ (5.09)$ (4.48)$ (4.48)$ (4.48)$ (4.26)$ (4.26)$ (4.93)$ (3.32)$ (4.48)$ (4.60)$
Expected Case 2025-2026 Apr (2.93)$ (2.93)$ (3.77)$ (4.32)$ (5.10)$ (4.32)$ (4.32)$ (4.32)$ (4.10)$ (4.10)$ (4.94)$ (3.21)$ (4.38)$ (4.47)$
Expected Case 2025-2026 May (2.98)$ (2.98)$ (3.78)$ (4.37)$ (5.11)$ (4.37)$ (4.37)$ (4.37)$ (4.15)$ (4.15)$ (4.95)$ (3.25)$ (4.42)$ (4.52)$ Expected Case 2025-2026 Jun (3.07)$ (3.07)$ (3.79)$ (4.46)$ (5.09)$ (4.46)$ (4.46)$ (4.46)$ (4.24)$ (4.24)$ (4.96)$ (3.31)$ (4.48)$ (4.59)$ Expected Case 2025-2026 Jul (3.18)$ (3.18)$ (3.80)$ (4.57)$ (5.13)$ (4.57)$ (4.57)$ (4.57)$ (4.35)$ (4.35)$ (4.97)$ (3.39)$ (4.56)$ (4.69)$
Expected Case 2025-2026 Aug (3.21)$ (3.21)$ (3.81)$ (4.60)$ (5.14)$ (4.60)$ (4.60)$ (4.60)$ (4.38)$ (4.38)$ (4.98)$ (3.41)$ (4.58)$ (4.71)$
Expected Case 2025-2026 Sep (3.13)$ (3.13)$ (3.82)$ (4.52)$ (5.15)$ (4.52)$ (4.52)$ (4.52)$ (4.30)$ (4.30)$ (4.99)$ (3.36)$ (4.53)$ (4.65)$ Expected Case 2025-2026 Oct (3.18)$ (3.18)$ (3.83)$ (4.57)$ (5.16)$ (4.57)$ (4.57)$ (4.57)$ (4.35)$ (4.35)$ (5.00)$ (3.40)$ (4.57)$ (4.69)$
Expected Case 2026-2027 Nov (3.32)$ (3.23)$ (3.85)$ (4.68)$ (5.17)$ (4.68)$ (4.68)$ (4.68)$ (4.49)$ (4.40)$ (5.01)$ (3.47)$ (4.63)$ (4.78)$
Expected Case 2026-2027 Dec (3.83)$ (3.38)$ (3.87)$ (5.27)$ (5.28)$ (5.27)$ (5.27)$ (5.27)$ (5.00)$ (4.55)$ (5.03)$ (3.69)$ (4.86)$ (5.27)$ Expected Case 2026-2027 Jan (3.91)$ (3.48)$ (3.91)$ (4.97)$ (5.37)$ (4.97)$ (4.97)$ (4.97)$ (5.18)$ (4.75)$ (5.18)$ (3.77)$ (5.04)$ (5.05)$ Expected Case 2026-2027 Feb (3.80)$ (3.48)$ (3.90)$ (4.97)$ (5.38)$ (4.97)$ (4.97)$ (4.97)$ (5.07)$ (4.75)$ (5.17)$ (3.73)$ (5.00)$ (5.05)$
Expected Case 2026-2027 Mar (3.38)$ (3.38)$ (3.88)$ (4.87)$ (5.30)$ (4.87)$ (4.87)$ (4.87)$ (4.65)$ (4.65)$ (5.16)$ (3.55)$ (4.82)$ (4.95)$
Expected Case 2026-2027 Apr (3.25)$ (3.25)$ (3.89)$ (4.74)$ (5.31)$ (4.74)$ (4.74)$ (4.74)$ (4.53)$ (4.53)$ (5.17)$ (3.47)$ (4.74)$ (4.85)$ Expected Case 2026-2027 May (3.23)$ (3.23)$ (3.90)$ (4.71)$ (5.32)$ (4.71)$ (4.71)$ (4.71)$ (4.50)$ (4.50)$ (5.18)$ (3.45)$ (4.73)$ (4.83)$ Expected Case 2026-2027 Jun (3.34)$ (3.34)$ (3.91)$ (4.83)$ (5.33)$ (4.83)$ (4.83)$ (4.83)$ (4.61)$ (4.61)$ (5.19)$ (3.53)$ (4.80)$ (4.93)$
Expected Case 2026-2027 Jul (3.46)$ (3.46)$ (3.92)$ (4.94)$ (5.34)$ (4.94)$ (4.94)$ (4.94)$ (4.73)$ (4.73)$ (5.20)$ (3.61)$ (4.88)$ (5.02)$
Expected Case 2026-2027 Aug (3.49)$ (3.49)$ (3.93)$ (4.98)$ (5.35)$ (4.98)$ (4.98)$ (4.98)$ (4.76)$ (4.76)$ (5.21)$ (3.64)$ (4.91)$ (5.05)$ Expected Case 2026-2027 Sep (3.43)$ (3.43)$ (3.94)$ (4.91)$ (5.36)$ (4.91)$ (4.91)$ (4.91)$ (4.70)$ (4.70)$ (5.22)$ (3.60)$ (4.87)$ (5.00)$
Expected Case 2026-2027 Oct (3.45)$ (3.45)$ (4.08)$ (4.94)$ (5.50)$ (4.94)$ (4.94)$ (4.94)$ (4.72)$ (4.72)$ (5.35)$ (3.66)$ (4.93)$ (5.05)$
Expected Case 2027-2028 Nov (3.64)$ (3.55)$ (4.19)$ (5.10)$ (5.61)$ (5.10)$ (5.10)$ (5.10)$ (4.91)$ (4.82)$ (5.47)$ (3.79)$ (5.07)$ (5.20)$ Expected Case 2027-2028 Dec (4.21)$ (3.78)$ (4.21)$ (5.71)$ (5.69)$ (5.71)$ (5.71)$ (5.71)$ (5.49)$ (5.05)$ (5.49)$ (4.07)$ (5.34)$ (5.70)$ Expected Case 2027-2028 Jan (4.27)$ (3.84)$ (4.27)$ (5.44)$ (5.88)$ (5.44)$ (5.44)$ (5.44)$ (5.65)$ (5.22)$ (5.65)$ (4.13)$ (5.51)$ (5.53)$
Expected Case 2027-2028 Feb (4.08)$ (3.74)$ (4.25)$ (5.34)$ (5.81)$ (5.34)$ (5.34)$ (5.34)$ (5.46)$ (5.12)$ (5.63)$ (4.02)$ (5.40)$ (5.43)$
Expected Case 2027-2028 Mar (3.66)$ (3.66)$ (4.23)$ (5.25)$ (5.75)$ (5.25)$ (5.25)$ (5.25)$ (5.04)$ (5.04)$ (5.61)$ (3.85)$ (5.23)$ (5.35)$ Expected Case 2027-2028 Apr (3.57)$ (3.57)$ (4.24)$ (5.16)$ (5.76)$ (5.16)$ (5.16)$ (5.16)$ (4.95)$ (4.95)$ (5.62)$ (3.79)$ (5.17)$ (5.28)$
Expected Case 2027-2028 May (3.55)$ (3.55)$ (4.25)$ (5.14)$ (5.77)$ (5.14)$ (5.14)$ (5.14)$ (4.93)$ (4.93)$ (5.63)$ (3.79)$ (5.17)$ (5.27)$
Expected Case 2027-2028 Jun (3.70)$ (3.70)$ (4.26)$ (5.29)$ (5.78)$ (5.29)$ (5.29)$ (5.29)$ (5.08)$ (5.08)$ (5.64)$ (3.89)$ (5.27)$ (5.39)$ Expected Case 2027-2028 Jul (3.79)$ (3.79)$ (4.27)$ (5.38)$ (5.79)$ (5.38)$ (5.38)$ (5.38)$ (5.17)$ (5.17)$ (5.65)$ (3.95)$ (5.33)$ (5.46)$ Expected Case 2027-2028 Aug (3.84)$ (3.84)$ (4.28)$ (5.44)$ (5.80)$ (5.44)$ (5.44)$ (5.44)$ (5.22)$ (5.22)$ (5.66)$ (3.99)$ (5.37)$ (5.51)$
Expected Case 2027-2028 Sep (3.71)$ (3.71)$ (4.29)$ (5.30)$ (5.81)$ (5.30)$ (5.30)$ (5.30)$ (5.09)$ (5.09)$ (5.67)$ (3.91)$ (5.29)$ (5.41)$
Expected Case 2027-2028 Oct (3.75)$ (3.75)$ (4.30)$ (5.34)$ (5.78)$ (5.34)$ (5.34)$ (5.34)$ (5.13)$ (5.13)$ (5.68)$ (3.93)$ (5.31)$ (5.43)$ Expected Case 2028-2029 Nov (3.93)$ (3.85)$ (4.42)$ (5.54)$ (5.94)$ (5.54)$ (5.54)$ (5.54)$ (5.31)$ (5.23)$ (5.80)$ (4.07)$ (5.45)$ (5.62)$ Expected Case 2028-2029 Dec (4.44)$ (4.01)$ (4.45)$ (6.03)$ (6.02)$ (6.03)$ (6.03)$ (6.03)$ (5.82)$ (5.39)$ (5.83)$ (4.30)$ (5.68)$ (6.03)$
Expected Case 2028-2029 Jan (4.49)$ (4.07)$ (4.49)$ (5.85)$ (6.20)$ (5.85)$ (5.85)$ (5.85)$ (5.98)$ (5.55)$ (5.98)$ (4.35)$ (5.84)$ (5.92)$
Expected Case 2028-2029 Feb (4.40)$ (4.14)$ (4.48)$ (5.85)$ (6.13)$ (5.85)$ (5.85)$ (5.85)$ (5.89)$ (5.63)$ (5.96)$ (4.34)$ (5.83)$ (5.91)$ Expected Case 2028-2029 Mar (4.01)$ (4.01)$ (4.47)$ (5.71)$ (6.09)$ (5.71)$ (5.71)$ (5.71)$ (5.50)$ (5.50)$ (5.95)$ (4.16)$ (5.65)$ (5.79)$
Expected Case 2028-2029 Apr (3.89)$ (3.89)$ (4.47)$ (5.59)$ (6.10)$ (5.59)$ (5.59)$ (5.59)$ (5.38)$ (5.38)$ (5.96)$ (4.09)$ (5.57)$ (5.70)$
Expected Case 2028-2029 May (3.91)$ (3.91)$ (4.48)$ (5.61)$ (6.11)$ (5.61)$ (5.61)$ (5.61)$ (5.39)$ (5.39)$ (5.97)$ (4.10)$ (5.58)$ (5.71)$ Expected Case 2028-2029 Jun (3.93)$ (3.93)$ (4.49)$ (5.63)$ (6.12)$ (5.63)$ (5.63)$ (5.63)$ (5.42)$ (5.42)$ (5.98)$ (4.12)$ (5.61)$ (5.73)$ Expected Case 2028-2029 Jul (4.06)$ (4.06)$ (4.50)$ (5.76)$ (6.13)$ (5.76)$ (5.76)$ (5.76)$ (5.54)$ (5.54)$ (5.99)$ (4.21)$ (5.69)$ (5.83)$
Expected Case 2028-2029 Aug (4.10)$ (4.10)$ (4.51)$ (5.80)$ (6.14)$ (5.80)$ (5.80)$ (5.80)$ (5.58)$ (5.58)$ (6.00)$ (4.24)$ (5.72)$ (5.87)$
Expected Case 2028-2029 Sep (4.00)$ (4.00)$ (4.52)$ (5.71)$ (6.15)$ (5.71)$ (5.71)$ (5.71)$ (5.49)$ (5.49)$ (6.01)$ (4.18)$ (5.66)$ (5.79)$ Expected Case 2028-2029 Oct (4.10)$ (4.10)$ (4.53)$ (5.81)$ (6.13)$ (5.81)$ (5.81)$ (5.81)$ (5.59)$ (5.59)$ (6.02)$ (4.25)$ (5.73)$ (5.87)$ Expected Case 2029-2030 Nov (4.28)$ (4.20)$ (4.75)$ (6.00)$ (6.37)$ (6.00)$ (6.00)$ (6.00)$ (5.77)$ (5.69)$ (6.23)$ (4.41)$ (5.90)$ (6.07)$
Expected Case 2029-2030 Dec (4.82)$ (4.42)$ (4.82)$ (6.55)$ (6.52)$ (6.55)$ (6.55)$ (6.55)$ (6.31)$ (5.91)$ (6.31)$ (4.69)$ (6.17)$ (6.55)$ Expected Case 2029-2030 Jan (4.83)$ (4.44)$ (4.83)$ (6.32)$ (6.62)$ (6.32)$ (6.32)$ (6.32)$ (6.42)$ (6.03)$ (6.42)$ (4.70)$ (6.29)$ (6.38)$ Expected Case 2029-2030 Feb (4.72)$ (4.46)$ (4.79)$ (6.29)$ (6.55)$ (6.29)$ (6.29)$ (6.29)$ (6.31)$ (6.05)$ (6.38)$ (4.66)$ (6.25)$ (6.34)$
Expected Case 2029-2030 Mar (4.26)$ (4.26)$ (4.78)$ (6.08)$ (6.52)$ (6.08)$ (6.08)$ (6.08)$ (5.85)$ (5.85)$ (6.37)$ (4.43)$ (6.03)$ (6.17)$
Expected Case 2029-2030 Apr (4.15)$ (4.15)$ (4.75)$ (5.97)$ (6.48)$ (5.97)$ (5.97)$ (5.97)$ (5.74)$ (5.74)$ (6.34)$ (4.35)$ (5.94)$ (6.07)$ Expected Case 2029-2030 May (4.19)$ (4.19)$ (4.76)$ (6.01)$ (6.49)$ (6.01)$ (6.01)$ (6.01)$ (5.78)$ (5.78)$ (6.35)$ (4.38)$ (5.97)$ (6.11)$ Expected Case 2029-2030 Jun (4.24)$ (4.24)$ (4.77)$ (6.06)$ (6.50)$ (6.06)$ (6.06)$ (6.06)$ (5.83)$ (5.83)$ (6.36)$ (4.42)$ (6.01)$ (6.15)$
Expected Case 2029-2030 Jul (4.37)$ (4.37)$ (4.78)$ (6.19)$ (6.51)$ (6.19)$ (6.19)$ (6.19)$ (5.96)$ (5.96)$ (6.37)$ (4.51)$ (6.10)$ (6.26)$
Expected Case 2029-2030 Aug (4.43)$ (4.43)$ (4.79)$ (6.26)$ (6.48)$ (6.26)$ (6.26)$ (6.26)$ (6.02)$ (6.02)$ (6.38)$ (4.55)$ (6.14)$ (6.30)$ Expected Case 2029-2030 Sep (4.35)$ (4.35)$ (4.80)$ (6.18)$ (6.53)$ (6.18)$ (6.18)$ (6.18)$ (5.94)$ (5.94)$ (6.39)$ (4.50)$ (6.09)$ (6.25)$
Expected Case 2029-2030 Oct (4.40)$ (4.40)$ (4.88)$ (6.22)$ (6.61)$ (6.22)$ (6.22)$ (6.22)$ (5.99)$ (5.99)$ (6.47)$ (4.56)$ (6.15)$ (6.30)$
Expected Case 2030-2031 Nov (4.47)$ (4.38)$ (4.94)$ (6.31)$ (6.69)$ (6.31)$ (6.31)$ (6.31)$ (6.06)$ (5.98)$ (6.53)$ (4.60)$ (6.19)$ (6.39)$ Expected Case 2030-2031 Dec (5.01)$ (4.60)$ (5.01)$ (6.89)$ (6.86)$ (6.89)$ (6.89)$ (6.89)$ (6.60)$ (6.19)$ (6.60)$ (4.87)$ (6.47)$ (6.88)$ Expected Case 2030-2031 Jan (5.02)$ (4.69)$ (5.02)$ (6.64)$ (6.96)$ (6.64)$ (6.64)$ (6.64)$ (6.61)$ (6.28)$ (6.61)$ (4.91)$ (6.50)$ (6.70)$
Expected Case 2030-2031 Feb (4.92)$ (4.70)$ (4.99)$ (6.65)$ (6.88)$ (6.65)$ (6.65)$ (6.65)$ (6.52)$ (6.29)$ (6.58)$ (4.87)$ (6.46)$ (6.69)$
Expected Case 2030-2031 Mar (4.51)$ (4.51)$ (4.96)$ (6.46)$ (6.82)$ (6.46)$ (6.46)$ (6.46)$ (6.10)$ (6.10)$ (6.56)$ (4.66)$ (6.25)$ (6.53)$ Expected Case 2030-2031 Apr (4.31)$ (4.31)$ (4.96)$ (6.25)$ (6.81)$ (6.25)$ (6.25)$ (6.25)$ (5.90)$ (5.90)$ (6.55)$ (4.52)$ (6.12)$ (6.37)$ Expected Case 2030-2031 May (4.39)$ (4.39)$ (4.97)$ (6.33)$ (6.83)$ (6.33)$ (6.33)$ (6.33)$ (5.98)$ (5.98)$ (6.56)$ (4.58)$ (6.17)$ (6.43)$
Expected Case 2030-2031 Jun (4.44)$ (4.44)$ (4.98)$ (6.38)$ (6.84)$ (6.38)$ (6.38)$ (6.38)$ (6.03)$ (6.03)$ (6.57)$ (4.62)$ (6.21)$ (6.47)$
Expected Case 2030-2031 Jul (4.62)$ (4.62)$ (4.99)$ (6.57)$ (6.85)$ (6.57)$ (6.57)$ (6.57)$ (6.21)$ (6.21)$ (6.58)$ (4.74)$ (6.33)$ (6.62)$ Expected Case 2030-2031 Aug (4.67)$ (4.67)$ (5.00)$ (6.63)$ (6.86)$ (6.63)$ (6.63)$ (6.63)$ (6.27)$ (6.27)$ (6.59)$ (4.78)$ (6.37)$ (6.67)$
Expected Case 2030-2031 Sep (4.59)$ (4.59)$ (5.01)$ (6.54)$ (6.87)$ (6.54)$ (6.54)$ (6.54)$ (6.18)$ (6.18)$ (6.60)$ (4.73)$ (6.32)$ (6.60)$
Expected Case 2030-2031 Oct (4.61)$ (4.61)$ (5.02)$ (6.56)$ (6.87)$ (6.56)$ (6.56)$ (6.56)$ (6.20)$ (6.20)$ (6.61)$ (4.75)$ (6.34)$ (6.62)$ Expected Case 2031-2032 Nov (4.69)$ (4.61)$ (5.12)$ (6.66)$ (6.99)$ (6.66)$ (6.66)$ (6.66)$ (6.28)$ (6.20)$ (6.72)$ (4.81)$ (6.40)$ (6.72)$ Expected Case 2031-2032 Dec (5.16)$ (4.74)$ (5.16)$ (7.18)$ (7.14)$ (7.18)$ (7.18)$ (7.18)$ (6.75)$ (6.33)$ (6.75)$ (5.02)$ (6.61)$ (7.17)$
Expected Case 2031-2032 Jan (5.21)$ (4.85)$ (5.21)$ (6.94)$ (7.27)$ (6.94)$ (6.94)$ (6.94)$ (6.80)$ (6.44)$ (6.80)$ (5.09)$ (6.68)$ (7.00)$
Expected Case 2031-2032 Feb (5.14)$ (4.78)$ (5.18)$ (6.86)$ (7.21)$ (6.86)$ (6.86)$ (6.86)$ (6.73)$ (6.37)$ (6.77)$ (5.03)$ (6.62)$ (6.93)$ Expected Case 2031-2032 Mar (4.63)$ (4.63)$ (5.17)$ (6.71)$ (7.15)$ (6.71)$ (6.71)$ (6.71)$ (6.22)$ (6.22)$ (6.76)$ (4.81)$ (6.40)$ (6.80)$
Expected Case 2031-2032 Apr (4.44)$ (4.44)$ (5.18)$ (6.51)$ (7.16)$ (6.51)$ (6.51)$ (6.51)$ (6.03)$ (6.03)$ (6.77)$ (4.68)$ (6.27)$ (6.64)$
Expected Case 2031-2032 May (4.48)$ (4.48)$ (5.19)$ (6.56)$ (7.17)$ (6.56)$ (6.56)$ (6.56)$ (6.07)$ (6.07)$ (6.78)$ (4.72)$ (6.31)$ (6.68)$ Expected Case 2031-2032 Jun (4.54)$ (4.54)$ (5.20)$ (6.62)$ (7.19)$ (6.62)$ (6.62)$ (6.62)$ (6.13)$ (6.13)$ (6.79)$ (4.76)$ (6.35)$ (6.73)$ Expected Case 2031-2032 Jul (4.70)$ (4.70)$ (5.21)$ (6.78)$ (7.20)$ (6.78)$ (6.78)$ (6.78)$ (6.29)$ (6.29)$ (6.80)$ (4.87)$ (6.46)$ (6.86)$
Expected Case 2031-2032 Aug (4.77)$ (4.77)$ (5.22)$ (6.85)$ (7.21)$ (6.85)$ (6.85)$ (6.85)$ (6.36)$ (6.36)$ (6.81)$ (4.92)$ (6.51)$ (6.92)$
Expected Case 2031-2032 Sep (4.70)$ (4.70)$ (5.23)$ (6.78)$ (7.22)$ (6.78)$ (6.78)$ (6.78)$ (6.29)$ (6.29)$ (6.82)$ (4.87)$ (6.47)$ (6.87)$ Expected Case 2031-2032 Oct (4.79)$ (4.79)$ (5.24)$ (6.87)$ (7.23)$ (6.87)$ (6.87)$ (6.87)$ (6.38)$ (6.38)$ (6.83)$ (4.94)$ (6.53)$ (6.94)$ Expected Case 2032-2033 Nov (4.84)$ (4.76)$ (5.39)$ (6.96)$ (7.39)$ (6.96)$ (6.96)$ (6.96)$ (6.44)$ (6.35)$ (6.98)$ (5.00)$ (6.59)$ (7.05)$
Expected Case 2032-2033 Dec (5.43)$ (5.02)$ (5.44)$ (7.59)$ (7.55)$ (7.59)$ (7.59)$ (7.59)$ (7.03)$ (6.61)$ (7.03)$ (5.30)$ (6.89)$ (7.58)$
Expected Case 2032-2033 Jan (5.48)$ (5.09)$ (5.48)$ (7.32)$ (7.65)$ (7.32)$ (7.32)$ (7.32)$ (7.07)$ (6.68)$ (7.07)$ (5.35)$ (6.94)$ (7.39)$ Expected Case 2032-2033 Feb (5.36)$ (5.09)$ (5.44)$ (7.32)$ (7.59)$ (7.32)$ (7.32)$ (7.32)$ (6.95)$ (6.69)$ (7.03)$ (5.30)$ (6.89)$ (7.38)$
Expected Case 2032-2033 Mar (4.91)$ (4.91)$ (5.43)$ (7.14)$ (7.56)$ (7.14)$ (7.14)$ (7.14)$ (6.50)$ (6.50)$ (7.02)$ (5.09)$ (6.68)$ (7.22)$
Expected Case 2032-2033 Apr (4.72)$ (4.72)$ (5.41)$ (6.94)$ (7.53)$ (6.94)$ (6.94)$ (6.94)$ (6.32)$ (6.32)$ (7.00)$ (4.95)$ (6.54)$ (7.06)$ Expected Case 2032-2033 May (4.74)$ (4.74)$ (5.42)$ (6.96)$ (7.55)$ (6.96)$ (6.96)$ (6.96)$ (6.33)$ (6.33)$ (7.01)$ (4.97)$ (6.56)$ (7.08)$ Expected Case 2032-2033 Jun (4.79)$ (4.79)$ (5.43)$ (7.01)$ (7.56)$ (7.01)$ (7.01)$ (7.01)$ (6.38)$ (6.38)$ (7.02)$ (5.00)$ (6.59)$ (7.12)$
Expected Case 2032-2033 Jul (5.02)$ (5.02)$ (5.44)$ (7.25)$ (7.57)$ (7.25)$ (7.25)$ (7.25)$ (6.61)$ (6.61)$ (7.03)$ (5.16)$ (6.75)$ (7.31)$
Expected Case 2032-2033 Aug (5.06)$ (5.06)$ (5.45)$ (7.28)$ (7.58)$ (7.28)$ (7.28)$ (7.28)$ (6.65)$ (6.65)$ (7.04)$ (5.19)$ (6.78)$ (7.34)$ Expected Case 2032-2033 Sep (4.96)$ (4.96)$ (5.46)$ (7.18)$ (7.59)$ (7.18)$ (7.18)$ (7.18)$ (6.55)$ (6.55)$ (7.05)$ (5.12)$ (6.72)$ (7.26)$
Expected Case 2032-2033 Oct (4.96)$ (4.96)$ (5.47)$ (7.19)$ (7.59)$ (7.19)$ (7.19)$ (7.19)$ (6.56)$ (6.56)$ (7.06)$ (5.13)$ (6.72)$ (7.27)$
Expected Case 2033-2034 Nov (5.10)$ (5.02)$ (5.59)$ (7.35)$ (7.73)$ (7.35)$ (7.35)$ (7.35)$ (6.69)$ (6.61)$ (7.18)$ (5.24)$ (6.83)$ (7.43)$ Expected Case 2033-2034 Dec (5.65)$ (5.24)$ (5.65)$ (7.95)$ (7.91)$ (7.95)$ (7.95)$ (7.95)$ (7.24)$ (6.83)$ (7.24)$ (5.51)$ (7.10)$ (7.94)$
Monthly Avoided Costs 1/
Nominal$
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 238 of 829
APPENDIX 6.4: EXPECTED MONTHLY DETAIL

Scenario Gas Year Month ID Both ID GTN ID NWP Klam Falls La Grande Medford GTN Medford NWP Roseburg WA Both WA GTN WA NWP ID Annual WA Annual OR AnnualExpected Case 2033-2034 Jan (5.68)$ (5.28)$ (5.68)$ (7.66)$ (8.02)$ (7.66)$ (7.66)$ (7.66)$ (7.28)$ (6.88)$ (7.28)$ (5.55)$ (7.14)$ (7.74)$
Expected Case 2033-2034 Feb (5.63)$ (5.31)$ (5.65)$ (7.70)$ (7.97)$ (7.70)$ (7.70)$ (7.70)$ (7.22)$ (6.91)$ (7.24)$ (5.53)$ (7.12)$ (7.75)$
Expected Case 2033-2034 Mar (5.07)$ (5.07)$ (5.64)$ (7.44)$ (7.91)$ (7.44)$ (7.44)$ (7.44)$ (6.66)$ (6.66)$ (7.23)$ (5.26)$ (6.85)$ (7.54)$ Expected Case 2033-2034 Apr (4.88)$ (4.88)$ (5.65)$ (7.25)$ (7.92)$ (7.25)$ (7.25)$ (7.25)$ (6.47)$ (6.47)$ (7.24)$ (5.14)$ (6.73)$ (7.39)$
Expected Case 2033-2034 May (4.89)$ (4.89)$ (5.66)$ (7.27)$ (7.93)$ (7.27)$ (7.27)$ (7.27)$ (6.48)$ (6.48)$ (7.25)$ (5.15)$ (6.74)$ (7.40)$
Expected Case 2033-2034 Jun (4.98)$ (4.98)$ (5.67)$ (7.35)$ (7.95)$ (7.35)$ (7.35)$ (7.35)$ (6.57)$ (6.57)$ (7.26)$ (5.21)$ (6.80)$ (7.47)$ Expected Case 2033-2034 Jul (5.20)$ (5.20)$ (5.68)$ (7.58)$ (7.96)$ (7.58)$ (7.58)$ (7.58)$ (6.80)$ (6.80)$ (7.27)$ (5.36)$ (6.95)$ (7.66)$ Expected Case 2033-2034 Aug (5.22)$ (5.22)$ (5.69)$ (7.60)$ (7.97)$ (7.60)$ (7.60)$ (7.60)$ (6.82)$ (6.82)$ (7.28)$ (5.38)$ (6.97)$ (7.68)$
Expected Case 2033-2034 Sep (5.09)$ (5.09)$ (5.70)$ (7.46)$ (7.98)$ (7.46)$ (7.46)$ (7.46)$ (6.68)$ (6.68)$ (7.29)$ (5.29)$ (6.88)$ (7.57)$
Expected Case 2033-2034 Oct (5.13)$ (5.13)$ (5.81)$ (7.51)$ (8.08)$ (7.51)$ (7.51)$ (7.51)$ (6.73)$ (6.73)$ (7.40)$ (5.36)$ (6.95)$ (7.63)$ Expected Case 2034-2035 Nov (5.31)$ (5.23)$ (5.82)$ (7.71)$ (8.11)$ (7.71)$ (7.71)$ (7.71)$ (6.90)$ (6.82)$ (7.42)$ (5.45)$ (7.05)$ (7.79)$ Expected Case 2034-2035 Dec (5.81)$ (5.40)$ (5.85)$ (8.27)$ (8.23)$ (8.27)$ (8.27)$ (8.27)$ (7.41)$ (6.99)$ (7.44)$ (5.69)$ (7.28)$ (8.26)$
Expected Case 2034-2035 Jan (5.92)$ (5.53)$ (5.92)$ (8.08)$ (8.43)$ (8.08)$ (8.08)$ (8.08)$ (7.51)$ (7.12)$ (7.51)$ (5.79)$ (7.38)$ (8.15)$ Expected Case 2034-2035 Feb (5.86)$ (5.51)$ (5.89)$ (8.05)$ (8.37)$ (8.05)$ (8.05)$ (8.05)$ (7.45)$ (7.10)$ (7.48)$ (5.75)$ (7.34)$ (8.12)$ Expected Case 2034-2035 Mar (5.32)$ (5.32)$ (5.87)$ (7.86)$ (8.31)$ (7.86)$ (7.86)$ (7.86)$ (6.92)$ (6.92)$ (7.46)$ (5.51)$ (7.10)$ (7.95)$
Expected Case 2034-2035 Apr (5.15)$ (5.15)$ (5.88)$ (7.68)$ (8.32)$ (7.68)$ (7.68)$ (7.68)$ (6.74)$ (6.74)$ (7.47)$ (5.39)$ (6.98)$ (7.81)$
Expected Case 2034-2035 May (5.09)$ (5.09)$ (5.89)$ (7.62)$ (8.28)$ (7.62)$ (7.62)$ (7.62)$ (6.68)$ (6.68)$ (7.48)$ (5.36)$ (6.95)$ (7.76)$ Expected Case 2034-2035 Jun (5.17)$ (5.17)$ (5.90)$ (7.71)$ (8.34)$ (7.71)$ (7.71)$ (7.71)$ (6.76)$ (6.76)$ (7.49)$ (5.42)$ (7.01)$ (7.84)$ Expected Case 2034-2035 Jul (5.38)$ (5.38)$ (5.91)$ (7.92)$ (8.35)$ (7.92)$ (7.92)$ (7.92)$ (6.97)$ (6.97)$ (7.51)$ (5.56)$ (7.15)$ (8.00)$
Expected Case 2034-2035 Aug (5.45)$ (5.45)$ (5.93)$ (7.99)$ (8.36)$ (7.99)$ (7.99)$ (7.99)$ (7.04)$ (7.04)$ (7.52)$ (5.61)$ (7.20)$ (8.06)$
Expected Case 2034-2035 Sep (5.31)$ (5.31)$ (5.94)$ (7.85)$ (8.37)$ (7.85)$ (7.85)$ (7.85)$ (6.90)$ (6.90)$ (7.53)$ (5.52)$ (7.11)$ (7.96)$ Expected Case 2034-2035 Oct (5.23)$ (5.23)$ (5.95)$ (7.77)$ (8.38)$ (7.77)$ (7.77)$ (7.77)$ (6.82)$ (6.82)$ (7.54)$ (5.47)$ (7.06)$ (7.89)$
Expected Case 2035-2036 Nov (5.20)$ (5.12)$ (6.06)$ (7.82)$ (8.50)$ (7.82)$ (7.82)$ (7.82)$ (6.79)$ (6.71)$ (7.65)$ (5.46)$ (7.05)$ (7.96)$
Expected Case 2035-2036 Dec (5.73)$ (5.24)$ (6.09)$ (8.59)$ (8.55)$ (8.59)$ (8.59)$ (8.59)$ (7.32)$ (6.83)$ (7.68)$ (5.69)$ (7.28)$ (8.58)$ Expected Case 2035-2036 Jan (6.01)$ (5.61)$ (6.10)$ (8.67)$ (8.79)$ (8.67)$ (8.67)$ (8.67)$ (7.60)$ (7.21)$ (7.69)$ (5.91)$ (7.50)$ (8.69)$ Expected Case 2035-2036 Feb (6.09)$ (5.69)$ (6.14)$ (8.38)$ (8.77)$ (8.38)$ (8.38)$ (8.38)$ (7.68)$ (7.28)$ (7.73)$ (5.97)$ (7.56)$ (8.46)$
Expected Case 2035-2036 Mar (5.50)$ (5.50)$ (6.11)$ (8.19)$ (8.69)$ (8.19)$ (8.19)$ (8.19)$ (7.09)$ (7.09)$ (7.70)$ (5.70)$ (7.30)$ (8.29)$
Expected Case 2035-2036 Apr (5.30)$ (5.30)$ (6.12)$ (7.99)$ (8.70)$ (7.99)$ (7.99)$ (7.99)$ (6.89)$ (6.89)$ (7.71)$ (5.57)$ (7.17)$ (8.13)$ Expected Case 2035-2036 May (5.31)$ (5.31)$ (6.13)$ (8.00)$ (8.71)$ (8.00)$ (8.00)$ (8.00)$ (6.90)$ (6.90)$ (7.72)$ (5.59)$ (7.18)$ (8.14)$ Expected Case 2035-2036 Jun (5.47)$ (5.47)$ (6.14)$ (8.16)$ (8.72)$ (8.16)$ (8.16)$ (8.16)$ (7.06)$ (7.06)$ (7.73)$ (5.69)$ (7.29)$ (8.27)$
Expected Case 2035-2036 Jul (5.85)$ (5.85)$ (6.15)$ (8.54)$ (8.74)$ (8.54)$ (8.54)$ (8.54)$ (7.44)$ (7.44)$ (7.75)$ (5.95)$ (7.54)$ (8.58)$
Expected Case 2035-2036 Aug (6.01)$ (6.01)$ (6.17)$ (8.70)$ (8.75)$ (8.70)$ (8.70)$ (8.70)$ (7.60)$ (7.60)$ (7.76)$ (6.06)$ (7.65)$ (8.71)$ Expected Case 2035-2036 Sep (5.73)$ (5.73)$ (6.18)$ (8.43)$ (8.76)$ (8.43)$ (8.43)$ (8.43)$ (7.32)$ (7.32)$ (7.77)$ (5.88)$ (7.47)$ (8.49)$
Expected Case 2035-2036 Oct (5.71)$ (5.71)$ (6.28)$ (8.40)$ (8.87)$ (8.40)$ (8.40)$ (8.40)$ (7.30)$ (7.30)$ (7.88)$ (5.90)$ (7.49)$ (8.49)$
Expected Case 2036-2037 Nov (5.90)$ (5.78)$ (6.38)$ (8.59)$ (8.98)$ (8.59)$ (8.59)$ (8.59)$ (7.49)$ (7.37)$ (7.97)$ (6.02)$ (7.61)$ (8.67)$ Expected Case 2036-2037 Dec (6.47)$ (6.09)$ (6.47)$ (9.32)$ (9.29)$ (9.32)$ (9.32)$ (9.32)$ (8.06)$ (7.68)$ (8.06)$ (6.34)$ (7.94)$ (9.32)$ Expected Case 2036-2037 Jan (6.48)$ (6.17)$ (6.48)$ (9.35)$ (9.45)$ (9.35)$ (9.35)$ (9.35)$ (8.08)$ (7.77)$ (8.08)$ (6.38)$ (7.97)$ (9.37)$
Expected Case 2036-2037 Feb (6.51)$ (6.22)$ (6.51)$ (9.08)$ (9.30)$ (9.08)$ (9.08)$ (9.08)$ (8.10)$ (7.81)$ (8.10)$ (6.41)$ (8.01)$ (9.12)$
Expected Case 2036-2037 Mar (5.86)$ (5.86)$ (6.54)$ (8.71)$ (9.28)$ (8.71)$ (8.71)$ (8.71)$ (7.45)$ (7.45)$ (8.13)$ (6.09)$ (7.68)$ (8.83)$ Expected Case 2036-2037 Apr (5.48)$ (5.48)$ (5.92)$ (8.33)$ (8.65)$ (8.33)$ (8.33)$ (8.33)$ (7.08)$ (7.08)$ (7.51)$ (5.63)$ (7.22)$ (8.39)$ Expected Case 2036-2037 May (5.49)$ (5.49)$ (5.92)$ (8.34)$ (8.66)$ (8.34)$ (8.34)$ (8.34)$ (7.09)$ (7.09)$ (7.52)$ (5.64)$ (7.23)$ (8.40)$
Expected Case 2036-2037 Jun (5.61)$ (5.61)$ (5.94)$ (8.46)$ (8.67)$ (8.46)$ (8.46)$ (8.46)$ (7.21)$ (7.21)$ (7.53)$ (5.72)$ (7.31)$ (8.50)$
Expected Case 2036-2037 Jul (5.99)$ (5.99)$ (6.04)$ (8.84)$ (8.77)$ (8.78)$ (8.78)$ (8.78)$ (7.58)$ (7.58)$ (7.63)$ (6.01)$ (7.60)$ (8.79)$ Expected Case 2036-2037 Aug (6.07)$ (6.07)$ (6.13)$ (8.93)$ (8.86)$ (8.86)$ (8.86)$ (8.86)$ (7.67)$ (7.67)$ (7.72)$ (6.09)$ (7.68)$ (8.88)$
Expected Case 2036-2037 Sep (5.76)$ (5.76)$ (5.87)$ (8.61)$ (8.61)$ (8.61)$ (8.61)$ (8.61)$ (7.35)$ (7.35)$ (7.46)$ (5.80)$ (7.39)$ (8.61)$
Expected Case 2036-2037 Oct (5.65)$ (5.65)$ (6.37)$ (8.50)$ (9.10)$ (8.50)$ (8.50)$ (8.50)$ (7.24)$ (7.24)$ (7.96)$ (5.89)$ (7.48)$ (8.62)$ 1/ Avoided costs are before Environmental Externalities adder.
Monthly Avoided Costs 1/
Nominal$
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 239 of 829
APPENDIX 6.4: HIGH GROWTH – LOW PRICE MONTHLY DETAIL

Scenario Gas Year Month ID Both ID GTN ID NWP Klam Falls La Grande Medford GTN Medford NWP Roseburg WA Both WA GTN WA NWP ID Annual WA Annual OR Annual
High Growth_Low Prices 2017-2018 Nov (1.87)$ (1.83)$ (2.62)$ (1.94)$ (2.62)$ (1.94)$ (1.94)$ (1.94)$ (1.87)$ (1.83)$ (2.62)$ (2.11)$ (2.11)$ (2.08)$
High Growth_Low Prices 2017-2018 Dec (2.14)$ (1.59)$ (2.63)$ (2.39)$ (2.76)$ (2.39)$ (2.39)$ (2.39)$ (2.14)$ (1.59)$ (2.63)$ (2.12)$ (2.12)$ (2.47)$
High Growth_Low Prices 2017-2018 Jan (2.16)$ (1.69)$ (2.62)$ (2.03)$ (2.81)$ (2.03)$ (2.03)$ (2.03)$ (2.16)$ (1.69)$ (2.62)$ (2.16)$ (2.16)$ (2.19)$ High Growth_Low Prices 2017-2018 Feb (2.50)$ (2.17)$ (2.69)$ (2.27)$ (2.94)$ (2.27)$ (2.27)$ (2.27)$ (2.50)$ (2.17)$ (2.69)$ (2.45)$ (2.45)$ (2.40)$ High Growth_Low Prices 2017-2018 Mar (0.95)$ (0.95)$ (2.62)$ (0.98)$ (2.62)$ (0.98)$ (0.98)$ (0.98)$ (0.95)$ (0.95)$ (2.62)$ (1.51)$ (1.51)$ (1.31)$ High Growth_Low Prices 2017-2018 Apr (1.08)$ (1.08)$ (2.62)$ (1.11)$ (2.62)$ (1.11)$ (1.11)$ (1.11)$ (1.08)$ (1.08)$ (2.62)$ (1.59)$ (1.59)$ (1.41)$ High Growth_Low Prices 2017-2018 May (1.05)$ (1.05)$ (2.62)$ (1.08)$ (2.62)$ (1.08)$ (1.08)$ (1.08)$ (1.05)$ (1.05)$ (2.62)$ (1.57)$ (1.57)$ (1.38)$ High Growth_Low Prices 2017-2018 Jun (1.05)$ (1.05)$ (2.62)$ (1.07)$ (2.62)$ (1.07)$ (1.07)$ (1.07)$ (1.05)$ (1.05)$ (2.62)$ (1.57)$ (1.57)$ (1.38)$ High Growth_Low Prices 2017-2018 Jul (1.09)$ (1.09)$ (2.62)$ (1.12)$ (2.62)$ (1.12)$ (1.12)$ (1.12)$ (1.09)$ (1.09)$ (2.62)$ (1.60)$ (1.60)$ (1.42)$ High Growth_Low Prices 2017-2018 Aug (1.10)$ (1.10)$ (2.62)$ (1.13)$ (2.62)$ (1.13)$ (1.13)$ (1.13)$ (1.10)$ (1.10)$ (2.62)$ (1.61)$ (1.61)$ (1.43)$ High Growth_Low Prices 2017-2018 Sep (1.06)$ (1.06)$ (2.62)$ (1.08)$ (2.62)$ (1.08)$ (1.08)$ (1.08)$ (1.06)$ (1.06)$ (2.62)$ (1.58)$ (1.58)$ (1.39)$ High Growth_Low Prices 2017-2018 Oct (1.10)$ (1.10)$ (3.17)$ (1.12)$ (3.17)$ (1.12)$ (1.12)$ (1.12)$ (1.10)$ (1.10)$ (3.17)$ (1.79)$ (1.79)$ (1.53)$ High Growth_Low Prices 2018-2019 Nov (1.40)$ (1.35)$ (2.63)$ (1.51)$ (2.63)$ (1.51)$ (1.51)$ (1.51)$ (1.40)$ (1.35)$ (2.63)$ (1.79)$ (1.79)$ (1.73)$ High Growth_Low Prices 2018-2019 Dec (2.09)$ (1.51)$ (2.63)$ (2.51)$ (2.78)$ (2.51)$ (2.51)$ (2.51)$ (2.09)$ (1.51)$ (2.63)$ (2.08)$ (2.08)$ (2.56)$ High Growth_Low Prices 2018-2019 Jan (2.04)$ (1.57)$ (2.63)$ (1.87)$ (2.86)$ (1.87)$ (1.87)$ (1.87)$ (2.04)$ (1.57)$ (2.63)$ (2.08)$ (2.08)$ (2.07)$ High Growth_Low Prices 2018-2019 Feb (2.06)$ (1.58)$ (2.66)$ (1.72)$ (2.75)$ (1.72)$ (1.72)$ (1.72)$ (2.06)$ (1.58)$ (2.66)$ (2.10)$ (2.10)$ (1.93)$ High Growth_Low Prices 2018-2019 Mar (1.45)$ (1.45)$ (2.63)$ (1.48)$ (2.63)$ (1.48)$ (1.48)$ (1.48)$ (1.45)$ (1.45)$ (2.63)$ (1.84)$ (1.84)$ (1.71)$ High Growth_Low Prices 2018-2019 Apr (1.09)$ (1.09)$ (2.63)$ (1.12)$ (2.63)$ (1.12)$ (1.12)$ (1.12)$ (1.09)$ (1.09)$ (2.63)$ (1.60)$ (1.60)$ (1.42)$ High Growth_Low Prices 2018-2019 May (1.08)$ (1.08)$ (2.63)$ (1.10)$ (2.63)$ (1.10)$ (1.10)$ (1.10)$ (1.08)$ (1.08)$ (2.63)$ (1.59)$ (1.59)$ (1.41)$ High Growth_Low Prices 2018-2019 Jun (1.16)$ (1.16)$ (2.63)$ (1.19)$ (2.63)$ (1.19)$ (1.19)$ (1.19)$ (1.16)$ (1.16)$ (2.63)$ (1.65)$ (1.65)$ (1.48)$ High Growth_Low Prices 2018-2019 Jul (1.24)$ (1.24)$ (2.63)$ (1.27)$ (2.63)$ (1.27)$ (1.27)$ (1.27)$ (1.24)$ (1.24)$ (2.63)$ (1.70)$ (1.70)$ (1.54)$ High Growth_Low Prices 2018-2019 Aug (1.24)$ (1.24)$ (2.63)$ (1.27)$ (2.63)$ (1.27)$ (1.27)$ (1.27)$ (1.24)$ (1.24)$ (2.63)$ (1.71)$ (1.71)$ (1.55)$ High Growth_Low Prices 2018-2019 Sep (1.16)$ (1.16)$ (2.63)$ (1.19)$ (2.63)$ (1.19)$ (1.19)$ (1.19)$ (1.16)$ (1.16)$ (2.63)$ (1.65)$ (1.65)$ (1.48)$ High Growth_Low Prices 2018-2019 Oct (1.19)$ (1.19)$ (2.63)$ (1.22)$ (2.63)$ (1.22)$ (1.22)$ (1.22)$ (1.19)$ (1.19)$ (2.63)$ (1.67)$ (1.67)$ (1.50)$ High Growth_Low Prices 2019-2020 Nov (1.42)$ (1.37)$ (2.63)$ (1.53)$ (2.63)$ (1.53)$ (1.53)$ (1.53)$ (1.42)$ (1.37)$ (2.63)$ (1.81)$ (1.81)$ (1.75)$ High Growth_Low Prices 2019-2020 Dec (2.12)$ (1.55)$ (2.64)$ (2.52)$ (2.73)$ (2.52)$ (2.52)$ (2.52)$ (2.12)$ (1.55)$ (2.64)$ (2.10)$ (2.10)$ (2.56)$ High Growth_Low Prices 2019-2020 Jan (2.11)$ (1.64)$ (2.63)$ (1.89)$ (2.80)$ (1.89)$ (1.89)$ (1.89)$ (2.11)$ (1.64)$ (2.63)$ (2.13)$ (2.13)$ (2.07)$ High Growth_Low Prices 2019-2020 Feb (2.08)$ (1.60)$ (2.63)$ (1.71)$ (2.66)$ (1.71)$ (1.71)$ (1.71)$ (2.08)$ (1.60)$ (2.63)$ (2.10)$ (2.10)$ (1.90)$
High Growth_Low Prices 2019-2020 Mar (1.43)$ (1.43)$ (2.58)$ (1.47)$ (2.58)$ (1.47)$ (1.47)$ (1.47)$ (1.43)$ (1.43)$ (2.58)$ (1.82)$ (1.82)$ (1.69)$
High Growth_Low Prices 2019-2020 Apr (1.18)$ (1.18)$ (2.28)$ (1.20)$ (2.28)$ (1.20)$ (1.20)$ (1.20)$ (1.18)$ (1.18)$ (2.28)$ (1.54)$ (1.54)$ (1.42)$
High Growth_Low Prices 2019-2020 May (1.18)$ (1.18)$ (2.28)$ (1.21)$ (2.28)$ (1.21)$ (1.21)$ (1.21)$ (1.18)$ (1.18)$ (2.28)$ (1.54)$ (1.54)$ (1.42)$
High Growth_Low Prices 2019-2020 Jun (1.18)$ (1.18)$ (2.28)$ (1.21)$ (2.28)$ (1.21)$ (1.21)$ (1.21)$ (1.18)$ (1.18)$ (2.28)$ (1.55)$ (1.55)$ (1.42)$
High Growth_Low Prices 2019-2020 Jul (1.23)$ (1.23)$ (2.28)$ (1.26)$ (2.28)$ (1.26)$ (1.26)$ (1.26)$ (1.23)$ (1.23)$ (2.28)$ (1.58)$ (1.58)$ (1.46)$
High Growth_Low Prices 2019-2020 Aug (1.25)$ (1.25)$ (2.28)$ (1.28)$ (2.28)$ (1.28)$ (1.28)$ (1.28)$ (1.25)$ (1.25)$ (2.28)$ (1.60)$ (1.60)$ (1.48)$
High Growth_Low Prices 2019-2020 Sep (1.21)$ (1.21)$ (2.28)$ (1.24)$ (2.28)$ (1.24)$ (1.24)$ (1.24)$ (1.21)$ (1.21)$ (2.28)$ (1.56)$ (1.56)$ (1.44)$
High Growth_Low Prices 2019-2020 Oct (1.26)$ (1.26)$ (2.51)$ (1.29)$ (2.51)$ (1.29)$ (1.29)$ (1.29)$ (1.26)$ (1.26)$ (2.51)$ (1.68)$ (1.68)$ (1.53)$
High Growth_Low Prices 2020-2021 Nov (1.34)$ (1.29)$ (2.28)$ (1.42)$ (2.28)$ (1.42)$ (1.42)$ (1.42)$ (1.34)$ (1.29)$ (2.28)$ (1.64)$ (1.64)$ (1.59)$
High Growth_Low Prices 2020-2021 Dec (1.96)$ (1.42)$ (2.29)$ (2.29)$ (2.41)$ (2.29)$ (2.29)$ (2.29)$ (1.96)$ (1.42)$ (2.29)$ (1.89)$ (1.89)$ (2.31)$
High Growth_Low Prices 2020-2021 Jan (2.11)$ (1.65)$ (2.28)$ (1.73)$ (2.64)$ (1.73)$ (1.73)$ (1.73)$ (2.11)$ (1.65)$ (2.28)$ (2.01)$ (2.01)$ (1.91)$
High Growth_Low Prices 2020-2021 Feb (2.10)$ (1.60)$ (2.30)$ (1.65)$ (2.40)$ (1.65)$ (1.65)$ (1.65)$ (2.10)$ (1.60)$ (2.30)$ (2.00)$ (2.00)$ (1.80)$
High Growth_Low Prices 2020-2021 Mar (1.51)$ (1.51)$ (2.27)$ (1.54)$ (2.27)$ (1.54)$ (1.54)$ (1.54)$ (1.51)$ (1.51)$ (2.27)$ (1.76)$ (1.76)$ (1.69)$
High Growth_Low Prices 2020-2021 Apr (1.26)$ (1.26)$ (2.08)$ (1.29)$ (2.08)$ (1.29)$ (1.29)$ (1.29)$ (1.26)$ (1.26)$ (2.08)$ (1.53)$ (1.53)$ (1.45)$
High Growth_Low Prices 2020-2021 May (1.24)$ (1.24)$ (2.09)$ (1.27)$ (2.09)$ (1.27)$ (1.27)$ (1.27)$ (1.24)$ (1.24)$ (2.09)$ (1.52)$ (1.52)$ (1.44)$
High Growth_Low Prices 2020-2021 Jun (1.28)$ (1.28)$ (2.09)$ (1.31)$ (2.09)$ (1.31)$ (1.31)$ (1.31)$ (1.28)$ (1.28)$ (2.09)$ (1.55)$ (1.55)$ (1.46)$
High Growth_Low Prices 2020-2021 Jul (1.35)$ (1.35)$ (2.09)$ (1.38)$ (2.09)$ (1.38)$ (1.38)$ (1.38)$ (1.35)$ (1.35)$ (2.09)$ (1.59)$ (1.59)$ (1.52)$
High Growth_Low Prices 2020-2021 Aug (1.36)$ (1.36)$ (2.09)$ (1.39)$ (2.09)$ (1.39)$ (1.39)$ (1.39)$ (1.36)$ (1.36)$ (2.09)$ (1.60)$ (1.60)$ (1.53)$
High Growth_Low Prices 2020-2021 Sep (1.28)$ (1.28)$ (2.09)$ (1.31)$ (2.09)$ (1.31)$ (1.31)$ (1.31)$ (1.28)$ (1.28)$ (2.09)$ (1.55)$ (1.55)$ (1.46)$
High Growth_Low Prices 2020-2021 Oct (1.32)$ (1.32)$ (2.19)$ (1.36)$ (2.19)$ (1.36)$ (1.36)$ (1.36)$ (1.32)$ (1.32)$ (2.19)$ (1.61)$ (1.61)$ (1.52)$
High Growth_Low Prices 2021-2022 Nov (1.50)$ (1.41)$ (2.09)$ (1.50)$ (2.09)$ (1.50)$ (1.50)$ (1.50)$ (1.50)$ (1.41)$ (2.09)$ (1.67)$ (1.67)$ (1.62)$
High Growth_Low Prices 2021-2022 Dec (2.01)$ (1.52)$ (2.10)$ (2.21)$ (2.38)$ (2.21)$ (2.21)$ (2.21)$ (2.01)$ (1.52)$ (2.10)$ (1.88)$ (1.88)$ (2.24)$ High Growth_Low Prices 2021-2022 Jan (2.09)$ (1.62)$ (2.09)$ (1.67)$ (2.35)$ (1.67)$ (1.67)$ (1.67)$ (2.09)$ (1.62)$ (2.09)$ (1.93)$ (1.93)$ (1.81)$ High Growth_Low Prices 2021-2022 Feb (2.07)$ (1.64)$ (2.10)$ (1.68)$ (2.20)$ (1.68)$ (1.68)$ (1.68)$ (2.07)$ (1.64)$ (2.10)$ (1.94)$ (1.94)$ (1.78)$ High Growth_Low Prices 2021-2022 Mar (1.58)$ (1.58)$ (2.06)$ (1.62)$ (2.06)$ (1.62)$ (1.62)$ (1.62)$ (1.58)$ (1.58)$ (2.06)$ (1.74)$ (1.74)$ (1.71)$ High Growth_Low Prices 2021-2022 Apr (1.32)$ (1.32)$ (1.91)$ (1.35)$ (1.91)$ (1.35)$ (1.35)$ (1.35)$ (1.32)$ (1.32)$ (1.91)$ (1.52)$ (1.52)$ (1.46)$ High Growth_Low Prices 2021-2022 May (1.32)$ (1.32)$ (1.92)$ (1.35)$ (1.92)$ (1.35)$ (1.35)$ (1.35)$ (1.32)$ (1.32)$ (1.92)$ (1.52)$ (1.52)$ (1.47)$ High Growth_Low Prices 2021-2022 Jun (1.31)$ (1.31)$ (1.92)$ (1.35)$ (1.92)$ (1.35)$ (1.35)$ (1.35)$ (1.31)$ (1.31)$ (1.92)$ (1.51)$ (1.51)$ (1.46)$ High Growth_Low Prices 2021-2022 Jul (1.36)$ (1.36)$ (1.92)$ (1.39)$ (1.92)$ (1.39)$ (1.39)$ (1.39)$ (1.36)$ (1.36)$ (1.92)$ (1.55)$ (1.55)$ (1.50)$ High Growth_Low Prices 2021-2022 Aug (1.38)$ (1.38)$ (1.92)$ (1.41)$ (1.92)$ (1.41)$ (1.41)$ (1.41)$ (1.38)$ (1.38)$ (1.92)$ (1.56)$ (1.56)$ (1.51)$ High Growth_Low Prices 2021-2022 Sep (1.38)$ (1.38)$ (1.92)$ (1.41)$ (1.92)$ (1.41)$ (1.41)$ (1.41)$ (1.38)$ (1.38)$ (1.92)$ (1.56)$ (1.56)$ (1.51)$ High Growth_Low Prices 2021-2022 Oct (1.40)$ (1.40)$ (2.08)$ (1.43)$ (2.08)$ (1.43)$ (1.43)$ (1.43)$ (1.40)$ (1.40)$ (2.08)$ (1.63)$ (1.63)$ (1.56)$ High Growth_Low Prices 2022-2023 Nov (1.48)$ (1.34)$ (1.92)$ (1.42)$ (1.92)$ (1.42)$ (1.42)$ (1.42)$ (1.48)$ (1.34)$ (1.92)$ (1.58)$ (1.58)$ (1.52)$ High Growth_Low Prices 2022-2023 Dec (1.93)$ (1.46)$ (1.94)$ (2.07)$ (2.36)$ (2.07)$ (2.07)$ (2.07)$ (1.93)$ (1.46)$ (1.94)$ (1.78)$ (1.78)$ (2.13)$ High Growth_Low Prices 2022-2023 Jan (1.95)$ (1.52)$ (1.95)$ (1.56)$ (2.29)$ (1.56)$ (1.56)$ (1.56)$ (1.95)$ (1.52)$ (1.95)$ (1.81)$ (1.81)$ (1.70)$ High Growth_Low Prices 2022-2023 Feb (1.91)$ (1.49)$ (1.93)$ (1.52)$ (2.04)$ (1.52)$ (1.52)$ (1.52)$ (1.91)$ (1.49)$ (1.93)$ (1.78)$ (1.78)$ (1.63)$ High Growth_Low Prices 2022-2023 Mar (1.45)$ (1.45)$ (1.88)$ (1.48)$ (1.88)$ (1.48)$ (1.48)$ (1.48)$ (1.45)$ (1.45)$ (1.88)$ (1.59)$ (1.59)$ (1.56)$ High Growth_Low Prices 2022-2023 Apr (1.21)$ (1.21)$ (1.83)$ (1.24)$ (1.83)$ (1.24)$ (1.24)$ (1.24)$ (1.21)$ (1.21)$ (1.83)$ (1.42)$ (1.42)$ (1.36)$ High Growth_Low Prices 2022-2023 May (1.25)$ (1.25)$ (1.83)$ (1.28)$ (1.83)$ (1.28)$ (1.28)$ (1.28)$ (1.25)$ (1.25)$ (1.83)$ (1.45)$ (1.45)$ (1.39)$ High Growth_Low Prices 2022-2023 Jun (1.27)$ (1.27)$ (1.83)$ (1.30)$ (1.83)$ (1.30)$ (1.30)$ (1.30)$ (1.27)$ (1.27)$ (1.83)$ (1.46)$ (1.46)$ (1.41)$ High Growth_Low Prices 2022-2023 Jul (1.29)$ (1.29)$ (1.83)$ (1.32)$ (1.83)$ (1.32)$ (1.32)$ (1.32)$ (1.29)$ (1.29)$ (1.83)$ (1.47)$ (1.47)$ (1.42)$ High Growth_Low Prices 2022-2023 Aug (1.33)$ (1.33)$ (1.83)$ (1.36)$ (1.83)$ (1.36)$ (1.36)$ (1.36)$ (1.33)$ (1.33)$ (1.83)$ (1.50)$ (1.50)$ (1.46)$ High Growth_Low Prices 2022-2023 Sep (1.31)$ (1.31)$ (1.83)$ (1.34)$ (1.83)$ (1.34)$ (1.34)$ (1.34)$ (1.31)$ (1.31)$ (1.83)$ (1.49)$ (1.49)$ (1.44)$ High Growth_Low Prices 2022-2023 Oct (1.32)$ (1.32)$ (1.99)$ (1.35)$ (1.99)$ (1.35)$ (1.35)$ (1.35)$ (1.32)$ (1.32)$ (1.99)$ (1.54)$ (1.54)$ (1.48)$ High Growth_Low Prices 2023-2024 Nov (1.57)$ (1.43)$ (2.15)$ (1.60)$ (2.15)$ (1.60)$ (1.60)$ (1.60)$ (1.57)$ (1.43)$ (2.15)$ (1.72)$ (1.72)$ (1.71)$ High Growth_Low Prices 2023-2024 Dec (2.07)$ (1.58)$ (2.16)$ (2.28)$ (2.48)$ (2.28)$ (2.28)$ (2.28)$ (2.07)$ (1.58)$ (2.16)$ (1.94)$ (1.94)$ (2.32)$ High Growth_Low Prices 2023-2024 Jan (2.13)$ (1.66)$ (2.16)$ (1.79)$ (2.41)$ (1.79)$ (1.79)$ (1.79)$ (2.13)$ (1.66)$ (2.16)$ (1.98)$ (1.98)$ (1.91)$
High Growth_Low Prices 2023-2024 Feb (2.14)$ (1.66)$ (2.17)$ (1.71)$ (2.25)$ (1.71)$ (1.71)$ (1.71)$ (2.14)$ (1.66)$ (2.17)$ (1.99)$ (1.99)$ (1.82)$
High Growth_Low Prices 2023-2024 Mar (1.63)$ (1.63)$ (2.15)$ (1.66)$ (2.15)$ (1.66)$ (1.66)$ (1.66)$ (1.63)$ (1.63)$ (2.15)$ (1.80)$ (1.80)$ (1.76)$
High Growth_Low Prices 2023-2024 Apr (1.47)$ (1.47)$ (2.15)$ (1.50)$ (2.15)$ (1.50)$ (1.50)$ (1.50)$ (1.47)$ (1.47)$ (2.15)$ (1.70)$ (1.70)$ (1.63)$
High Growth_Low Prices 2023-2024 May (1.45)$ (1.45)$ (2.15)$ (1.48)$ (2.15)$ (1.48)$ (1.48)$ (1.48)$ (1.45)$ (1.45)$ (2.15)$ (1.68)$ (1.68)$ (1.62)$
High Growth_Low Prices 2023-2024 Jun (1.42)$ (1.42)$ (2.15)$ (1.46)$ (2.15)$ (1.46)$ (1.46)$ (1.46)$ (1.42)$ (1.42)$ (2.15)$ (1.67)$ (1.67)$ (1.60)$
High Growth_Low Prices 2023-2024 Jul (1.53)$ (1.53)$ (2.15)$ (1.56)$ (2.15)$ (1.56)$ (1.56)$ (1.56)$ (1.53)$ (1.53)$ (2.15)$ (1.74)$ (1.74)$ (1.68)$
High Growth_Low Prices 2023-2024 Aug (1.61)$ (1.61)$ (2.15)$ (1.65)$ (2.15)$ (1.65)$ (1.65)$ (1.65)$ (1.61)$ (1.61)$ (2.15)$ (1.79)$ (1.79)$ (1.75)$
High Growth_Low Prices 2023-2024 Sep (1.59)$ (1.59)$ (2.15)$ (1.63)$ (2.15)$ (1.63)$ (1.63)$ (1.63)$ (1.59)$ (1.59)$ (2.15)$ (1.78)$ (1.78)$ (1.73)$
High Growth_Low Prices 2023-2024 Oct (1.63)$ (1.63)$ (2.34)$ (1.67)$ (2.34)$ (1.67)$ (1.67)$ (1.67)$ (1.63)$ (1.63)$ (2.34)$ (1.87)$ (1.87)$ (1.80)$
High Growth_Low Prices 2024-2025 Nov (1.74)$ (1.60)$ (2.28)$ (1.77)$ (2.28)$ (1.77)$ (1.77)$ (1.77)$ (1.74)$ (1.60)$ (2.28)$ (1.87)$ (1.87)$ (1.87)$
High Growth_Low Prices 2024-2025 Dec (2.16)$ (1.66)$ (2.29)$ (2.40)$ (2.61)$ (2.40)$ (2.40)$ (2.40)$ (2.16)$ (1.66)$ (2.29)$ (2.04)$ (2.04)$ (2.44)$
High Growth_Low Prices 2024-2025 Jan (2.17)$ (1.70)$ (2.29)$ (1.86)$ (2.64)$ (1.86)$ (1.86)$ (1.86)$ (2.17)$ (1.70)$ (2.29)$ (2.05)$ (2.05)$ (2.01)$
High Growth_Low Prices 2024-2025 Feb (2.21)$ (1.71)$ (2.31)$ (1.76)$ (2.37)$ (1.76)$ (1.76)$ (1.76)$ (2.21)$ (1.71)$ (2.31)$ (2.08)$ (2.08)$ (1.88)$
High Growth_Low Prices 2024-2025 Mar (1.59)$ (1.59)$ (2.28)$ (1.62)$ (2.28)$ (1.62)$ (1.62)$ (1.62)$ (1.59)$ (1.59)$ (2.28)$ (1.82)$ (1.82)$ (1.76)$
High Growth_Low Prices 2024-2025 Apr (1.45)$ (1.45)$ (2.28)$ (1.49)$ (2.28)$ (1.49)$ (1.49)$ (1.49)$ (1.45)$ (1.45)$ (2.28)$ (1.73)$ (1.73)$ (1.65)$
High Growth_Low Prices 2024-2025 May (1.48)$ (1.48)$ (2.29)$ (1.51)$ (2.29)$ (1.51)$ (1.51)$ (1.51)$ (1.48)$ (1.48)$ (2.29)$ (1.75)$ (1.75)$ (1.67)$
High Growth_Low Prices 2024-2025 Jun (1.54)$ (1.54)$ (2.29)$ (1.58)$ (2.29)$ (1.58)$ (1.58)$ (1.58)$ (1.54)$ (1.54)$ (2.29)$ (1.79)$ (1.79)$ (1.72)$
High Growth_Low Prices 2024-2025 Jul (1.60)$ (1.60)$ (2.29)$ (1.64)$ (2.29)$ (1.64)$ (1.64)$ (1.64)$ (1.60)$ (1.60)$ (2.29)$ (1.83)$ (1.83)$ (1.77)$
High Growth_Low Prices 2024-2025 Aug (1.62)$ (1.62)$ (2.29)$ (1.66)$ (2.29)$ (1.66)$ (1.66)$ (1.66)$ (1.62)$ (1.62)$ (2.29)$ (1.84)$ (1.84)$ (1.79)$
High Growth_Low Prices 2024-2025 Sep (1.58)$ (1.58)$ (2.29)$ (1.61)$ (2.29)$ (1.61)$ (1.61)$ (1.61)$ (1.58)$ (1.58)$ (2.29)$ (1.81)$ (1.81)$ (1.75)$
High Growth_Low Prices 2024-2025 Oct (1.59)$ (1.59)$ (2.39)$ (1.62)$ (2.39)$ (1.62)$ (1.62)$ (1.62)$ (1.59)$ (1.59)$ (2.39)$ (1.85)$ (1.85)$ (1.78)$
High Growth_Low Prices 2025-2026 Nov (1.66)$ (1.52)$ (2.29)$ (1.71)$ (2.29)$ (1.71)$ (1.71)$ (1.71)$ (1.66)$ (1.52)$ (2.29)$ (1.83)$ (1.83)$ (1.82)$
Monthly Avoided Costs 1/
Nominal$
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 240 of 829
APPENDIX 6.4: HIGH GROWTH – LOW PRICE MONTHLY DETAIL

Scenario Gas Year Month ID Both ID GTN ID NWP Klam Falls La Grande Medford GTN Medford NWP Roseburg WA Both WA GTN WA NWP ID Annual WA Annual OR Annual
High Growth_Low Prices 2025-2026 Dec (2.11)$ (1.60)$ (2.30)$ (2.39)$ (2.53)$ (2.39)$ (2.39)$ (2.39)$ (2.11)$ (1.60)$ (2.30)$ (2.00)$ (2.00)$ (2.41)$
High Growth_Low Prices 2025-2026 Jan (2.13)$ (1.66)$ (2.30)$ (1.84)$ (2.57)$ (1.84)$ (1.84)$ (1.84)$ (2.13)$ (1.66)$ (2.30)$ (2.03)$ (2.03)$ (1.98)$
High Growth_Low Prices 2025-2026 Feb (2.16)$ (1.64)$ (2.30)$ (1.70)$ (2.35)$ (1.70)$ (1.70)$ (1.70)$ (2.16)$ (1.64)$ (2.30)$ (2.03)$ (2.03)$ (1.83)$ High Growth_Low Prices 2025-2026 Mar (1.52)$ (1.52)$ (2.25)$ (1.56)$ (2.25)$ (1.56)$ (1.56)$ (1.56)$ (1.52)$ (1.52)$ (2.25)$ (1.76)$ (1.76)$ (1.70)$ High Growth_Low Prices 2025-2026 Apr (1.40)$ (1.40)$ (2.25)$ (1.44)$ (2.25)$ (1.44)$ (1.44)$ (1.44)$ (1.40)$ (1.40)$ (2.25)$ (1.68)$ (1.68)$ (1.60)$ High Growth_Low Prices 2025-2026 May (1.45)$ (1.45)$ (2.25)$ (1.48)$ (2.25)$ (1.48)$ (1.48)$ (1.48)$ (1.45)$ (1.45)$ (2.25)$ (1.71)$ (1.71)$ (1.63)$ High Growth_Low Prices 2025-2026 Jun (1.52)$ (1.52)$ (2.25)$ (1.56)$ (2.23)$ (1.56)$ (1.56)$ (1.56)$ (1.52)$ (1.52)$ (2.25)$ (1.76)$ (1.76)$ (1.69)$ High Growth_Low Prices 2025-2026 Jul (1.60)$ (1.60)$ (2.25)$ (1.64)$ (2.25)$ (1.64)$ (1.64)$ (1.64)$ (1.60)$ (1.60)$ (2.25)$ (1.82)$ (1.82)$ (1.76)$ High Growth_Low Prices 2025-2026 Aug (1.61)$ (1.61)$ (2.25)$ (1.65)$ (2.25)$ (1.65)$ (1.65)$ (1.65)$ (1.61)$ (1.61)$ (2.25)$ (1.83)$ (1.83)$ (1.77)$ High Growth_Low Prices 2025-2026 Sep (1.55)$ (1.55)$ (2.25)$ (1.59)$ (2.25)$ (1.59)$ (1.59)$ (1.59)$ (1.55)$ (1.55)$ (2.25)$ (1.79)$ (1.79)$ (1.72)$ High Growth_Low Prices 2025-2026 Oct (1.61)$ (1.61)$ (2.27)$ (1.65)$ (2.27)$ (1.65)$ (1.65)$ (1.65)$ (1.61)$ (1.61)$ (2.27)$ (1.83)$ (1.83)$ (1.77)$ High Growth_Low Prices 2026-2027 Nov (1.67)$ (1.53)$ (2.25)$ (1.71)$ (2.25)$ (1.71)$ (1.71)$ (1.71)$ (1.67)$ (1.53)$ (2.25)$ (1.82)$ (1.82)$ (1.82)$ High Growth_Low Prices 2026-2027 Dec (2.12)$ (1.62)$ (2.27)$ (2.34)$ (2.50)$ (2.34)$ (2.34)$ (2.34)$ (2.12)$ (1.62)$ (2.27)$ (2.00)$ (2.00)$ (2.37)$ High Growth_Low Prices 2026-2027 Jan (2.15)$ (1.69)$ (2.26)$ (2.26)$ (2.51)$ (2.26)$ (2.26)$ (2.26)$ (2.15)$ (1.69)$ (2.26)$ (2.04)$ (2.04)$ (2.31)$ High Growth_Low Prices 2026-2027 Feb (2.20)$ (1.68)$ (2.27)$ (1.74)$ (2.30)$ (1.74)$ (1.74)$ (1.74)$ (2.20)$ (1.68)$ (2.27)$ (2.05)$ (2.05)$ (1.85)$ High Growth_Low Prices 2026-2027 Mar (1.62)$ (1.62)$ (2.22)$ (1.66)$ (2.22)$ (1.66)$ (1.66)$ (1.66)$ (1.62)$ (1.62)$ (2.22)$ (1.82)$ (1.82)$ (1.77)$ High Growth_Low Prices 2026-2027 Apr (1.53)$ (1.53)$ (2.22)$ (1.57)$ (2.22)$ (1.57)$ (1.57)$ (1.57)$ (1.53)$ (1.53)$ (2.22)$ (1.76)$ (1.76)$ (1.70)$ High Growth_Low Prices 2026-2027 May (1.51)$ (1.51)$ (2.22)$ (1.54)$ (2.19)$ (1.54)$ (1.54)$ (1.54)$ (1.51)$ (1.51)$ (2.22)$ (1.75)$ (1.75)$ (1.67)$ High Growth_Low Prices 2026-2027 Jun (1.57)$ (1.57)$ (2.22)$ (1.60)$ (2.22)$ (1.60)$ (1.60)$ (1.60)$ (1.57)$ (1.57)$ (2.22)$ (1.78)$ (1.78)$ (1.73)$ High Growth_Low Prices 2026-2027 Jul (1.65)$ (1.65)$ (2.22)$ (1.69)$ (2.22)$ (1.69)$ (1.69)$ (1.69)$ (1.65)$ (1.65)$ (2.22)$ (1.84)$ (1.84)$ (1.79)$ High Growth_Low Prices 2026-2027 Aug (1.67)$ (1.67)$ (2.22)$ (1.70)$ (2.22)$ (1.70)$ (1.70)$ (1.70)$ (1.67)$ (1.67)$ (2.22)$ (1.85)$ (1.85)$ (1.81)$ High Growth_Low Prices 2026-2027 Sep (1.62)$ (1.62)$ (2.23)$ (1.65)$ (2.23)$ (1.65)$ (1.65)$ (1.65)$ (1.62)$ (1.62)$ (2.23)$ (1.82)$ (1.82)$ (1.77)$ High Growth_Low Prices 2026-2027 Oct (1.65)$ (1.65)$ (2.29)$ (1.69)$ (2.29)$ (1.69)$ (1.69)$ (1.69)$ (1.65)$ (1.65)$ (2.29)$ (1.87)$ (1.87)$ (1.81)$ High Growth_Low Prices 2027-2028 Nov (1.75)$ (1.60)$ (2.23)$ (1.76)$ (2.23)$ (1.76)$ (1.76)$ (1.76)$ (1.75)$ (1.60)$ (2.23)$ (1.86)$ (1.86)$ (1.85)$ High Growth_Low Prices 2027-2028 Dec (2.22)$ (1.75)$ (2.25)$ (2.31)$ (2.45)$ (2.31)$ (2.31)$ (2.31)$ (2.22)$ (1.75)$ (2.25)$ (2.07)$ (2.07)$ (2.34)$ High Growth_Low Prices 2027-2028 Jan (2.24)$ (1.78)$ (2.25)$ (2.23)$ (2.59)$ (2.23)$ (2.23)$ (2.23)$ (2.24)$ (1.78)$ (2.25)$ (2.09)$ (2.09)$ (2.30)$ High Growth_Low Prices 2027-2028 Feb (2.18)$ (1.70)$ (2.26)$ (1.77)$ (2.29)$ (1.77)$ (1.77)$ (1.77)$ (2.18)$ (1.70)$ (2.26)$ (2.05)$ (2.05)$ (1.87)$ High Growth_Low Prices 2027-2028 Mar (1.64)$ (1.64)$ (2.23)$ (1.68)$ (2.23)$ (1.68)$ (1.68)$ (1.68)$ (1.64)$ (1.64)$ (2.23)$ (1.84)$ (1.84)$ (1.79)$
High Growth_Low Prices 2027-2028 Apr (1.58)$ (1.58)$ (2.23)$ (1.62)$ (2.23)$ (1.62)$ (1.62)$ (1.62)$ (1.58)$ (1.58)$ (2.23)$ (1.80)$ (1.80)$ (1.74)$
High Growth_Low Prices 2027-2028 May (1.57)$ (1.57)$ (2.23)$ (1.61)$ (2.23)$ (1.61)$ (1.61)$ (1.61)$ (1.57)$ (1.57)$ (2.23)$ (1.79)$ (1.79)$ (1.73)$
High Growth_Low Prices 2027-2028 Jun (1.66)$ (1.66)$ (2.23)$ (1.70)$ (2.23)$ (1.70)$ (1.70)$ (1.70)$ (1.66)$ (1.66)$ (2.23)$ (1.85)$ (1.85)$ (1.81)$
High Growth_Low Prices 2027-2028 Jul (1.73)$ (1.73)$ (2.23)$ (1.77)$ (2.23)$ (1.77)$ (1.77)$ (1.77)$ (1.73)$ (1.73)$ (2.23)$ (1.90)$ (1.90)$ (1.86)$
High Growth_Low Prices 2027-2028 Aug (1.76)$ (1.76)$ (2.23)$ (1.80)$ (2.21)$ (1.80)$ (1.80)$ (1.80)$ (1.76)$ (1.76)$ (2.23)$ (1.92)$ (1.92)$ (1.88)$
High Growth_Low Prices 2027-2028 Sep (1.65)$ (1.65)$ (2.24)$ (1.69)$ (2.23)$ (1.69)$ (1.69)$ (1.69)$ (1.65)$ (1.65)$ (2.24)$ (1.85)$ (1.85)$ (1.80)$
High Growth_Low Prices 2027-2028 Oct (1.70)$ (1.70)$ (2.24)$ (1.74)$ (2.24)$ (1.74)$ (1.74)$ (1.74)$ (1.70)$ (1.70)$ (2.24)$ (1.88)$ (1.88)$ (1.84)$
High Growth_Low Prices 2028-2029 Nov (1.86)$ (1.72)$ (2.26)$ (1.91)$ (2.26)$ (1.91)$ (1.91)$ (1.91)$ (1.86)$ (1.72)$ (2.26)$ (1.95)$ (1.95)$ (1.98)$
High Growth_Low Prices 2028-2029 Dec (2.28)$ (1.81)$ (2.29)$ (2.35)$ (2.52)$ (2.35)$ (2.35)$ (2.35)$ (2.28)$ (1.81)$ (2.29)$ (2.12)$ (2.12)$ (2.39)$
High Growth_Low Prices 2028-2029 Jan (2.29)$ (1.85)$ (2.29)$ (2.26)$ (2.67)$ (2.26)$ (2.26)$ (2.26)$ (2.29)$ (1.85)$ (2.29)$ (2.14)$ (2.14)$ (2.34)$
High Growth_Low Prices 2028-2029 Feb (2.30)$ (1.92)$ (2.30)$ (1.99)$ (2.32)$ (1.99)$ (1.99)$ (1.99)$ (2.30)$ (1.92)$ (2.30)$ (2.17)$ (2.17)$ (2.05)$
High Growth_Low Prices 2028-2029 Mar (1.80)$ (1.80)$ (2.25)$ (1.84)$ (2.25)$ (1.84)$ (1.84)$ (1.84)$ (1.80)$ (1.80)$ (2.25)$ (1.95)$ (1.95)$ (1.92)$
High Growth_Low Prices 2028-2029 Apr (1.72)$ (1.72)$ (2.25)$ (1.76)$ (2.25)$ (1.76)$ (1.76)$ (1.76)$ (1.72)$ (1.72)$ (2.25)$ (1.90)$ (1.90)$ (1.86)$
High Growth_Low Prices 2028-2029 May (1.71)$ (1.71)$ (2.25)$ (1.75)$ (2.25)$ (1.75)$ (1.75)$ (1.75)$ (1.71)$ (1.71)$ (2.25)$ (1.89)$ (1.89)$ (1.85)$
High Growth_Low Prices 2028-2029 Jun (1.73)$ (1.73)$ (2.25)$ (1.76)$ (2.25)$ (1.76)$ (1.76)$ (1.76)$ (1.73)$ (1.73)$ (2.25)$ (1.90)$ (1.90)$ (1.86)$
High Growth_Low Prices 2028-2029 Jul (1.81)$ (1.81)$ (2.25)$ (1.85)$ (2.25)$ (1.85)$ (1.85)$ (1.85)$ (1.81)$ (1.81)$ (2.25)$ (1.96)$ (1.96)$ (1.93)$
High Growth_Low Prices 2028-2029 Aug (1.82)$ (1.82)$ (2.25)$ (1.86)$ (2.25)$ (1.86)$ (1.86)$ (1.86)$ (1.82)$ (1.82)$ (2.25)$ (1.96)$ (1.96)$ (1.94)$
High Growth_Low Prices 2028-2029 Sep (1.75)$ (1.75)$ (2.26)$ (1.79)$ (2.25)$ (1.79)$ (1.79)$ (1.79)$ (1.75)$ (1.75)$ (2.26)$ (1.92)$ (1.92)$ (1.88)$
High Growth_Low Prices 2028-2029 Oct (1.84)$ (1.84)$ (2.26)$ (1.88)$ (2.26)$ (1.88)$ (1.88)$ (1.88)$ (1.84)$ (1.84)$ (2.26)$ (1.98)$ (1.98)$ (1.95)$
High Growth_Low Prices 2029-2030 Nov (2.01)$ (1.87)$ (2.42)$ (2.06)$ (2.42)$ (2.06)$ (2.06)$ (2.06)$ (2.01)$ (1.87)$ (2.42)$ (2.10)$ (2.10)$ (2.13)$
High Growth_Low Prices 2029-2030 Dec (2.45)$ (1.99)$ (2.45)$ (2.49)$ (2.52)$ (2.49)$ (2.49)$ (2.49)$ (2.45)$ (1.99)$ (2.45)$ (2.30)$ (2.30)$ (2.49)$
High Growth_Low Prices 2029-2030 Jan (2.45)$ (1.99)$ (2.45)$ (2.42)$ (2.62)$ (2.42)$ (2.42)$ (2.42)$ (2.45)$ (1.99)$ (2.45)$ (2.30)$ (2.30)$ (2.46)$ High Growth_Low Prices 2029-2030 Feb (2.44)$ (2.00)$ (2.44)$ (2.08)$ (2.45)$ (2.08)$ (2.08)$ (2.08)$ (2.44)$ (2.00)$ (2.44)$ (2.29)$ (2.29)$ (2.16)$ High Growth_Low Prices 2029-2030 Mar (1.84)$ (1.83)$ (2.44)$ (1.87)$ (2.44)$ (1.87)$ (1.87)$ (1.87)$ (1.84)$ (1.83)$ (2.44)$ (2.03)$ (2.03)$ (1.98)$ High Growth_Low Prices 2029-2030 Apr (1.76)$ (1.76)$ (2.36)$ (1.80)$ (2.36)$ (1.80)$ (1.80)$ (1.80)$ (1.76)$ (1.76)$ (2.36)$ (1.96)$ (1.96)$ (1.91)$ High Growth_Low Prices 2029-2030 May (1.79)$ (1.79)$ (2.36)$ (1.83)$ (2.36)$ (1.83)$ (1.83)$ (1.83)$ (1.79)$ (1.79)$ (2.36)$ (1.98)$ (1.98)$ (1.94)$ High Growth_Low Prices 2029-2030 Jun (1.82)$ (1.82)$ (2.36)$ (1.87)$ (2.36)$ (1.87)$ (1.87)$ (1.87)$ (1.82)$ (1.82)$ (2.36)$ (2.00)$ (2.00)$ (1.96)$ High Growth_Low Prices 2029-2030 Jul (1.91)$ (1.91)$ (2.36)$ (1.95)$ (2.36)$ (1.95)$ (1.95)$ (1.95)$ (1.91)$ (1.91)$ (2.36)$ (2.06)$ (2.06)$ (2.03)$ High Growth_Low Prices 2029-2030 Aug (1.93)$ (1.93)$ (2.36)$ (1.98)$ (2.27)$ (1.98)$ (1.98)$ (1.98)$ (1.93)$ (1.93)$ (2.36)$ (2.08)$ (2.08)$ (2.04)$ High Growth_Low Prices 2029-2030 Sep (1.87)$ (1.87)$ (2.36)$ (1.91)$ (2.36)$ (1.91)$ (1.91)$ (1.91)$ (1.87)$ (1.87)$ (2.36)$ (2.04)$ (2.04)$ (2.00)$ High Growth_Low Prices 2029-2030 Oct (1.91)$ (1.91)$ (2.41)$ (1.95)$ (2.41)$ (1.95)$ (1.95)$ (1.95)$ (1.91)$ (1.91)$ (2.41)$ (2.08)$ (2.08)$ (2.04)$ High Growth_Low Prices 2030-2031 Nov (1.99)$ (1.85)$ (2.45)$ (2.06)$ (2.45)$ (2.06)$ (2.06)$ (2.06)$ (1.99)$ (1.85)$ (2.45)$ (2.10)$ (2.10)$ (2.14)$ High Growth_Low Prices 2030-2031 Dec (2.45)$ (1.98)$ (2.47)$ (2.53)$ (2.62)$ (2.53)$ (2.53)$ (2.53)$ (2.45)$ (1.98)$ (2.47)$ (2.30)$ (2.30)$ (2.55)$ High Growth_Low Prices 2030-2031 Jan (2.48)$ (2.02)$ (2.48)$ (2.45)$ (2.74)$ (2.45)$ (2.45)$ (2.45)$ (2.48)$ (2.02)$ (2.48)$ (2.33)$ (2.33)$ (2.51)$ High Growth_Low Prices 2030-2031 Feb (2.49)$ (2.06)$ (2.49)$ (2.14)$ (2.51)$ (2.14)$ (2.14)$ (2.14)$ (2.49)$ (2.06)$ (2.49)$ (2.35)$ (2.35)$ (2.21)$ High Growth_Low Prices 2030-2031 Mar (1.92)$ (1.91)$ (2.48)$ (1.95)$ (2.48)$ (1.95)$ (1.95)$ (1.95)$ (1.92)$ (1.91)$ (2.48)$ (2.10)$ (2.10)$ (2.05)$ High Growth_Low Prices 2030-2031 Apr (1.77)$ (1.77)$ (2.36)$ (1.81)$ (2.36)$ (1.81)$ (1.81)$ (1.81)$ (1.77)$ (1.77)$ (2.36)$ (1.97)$ (1.97)$ (1.92)$ High Growth_Low Prices 2030-2031 May (1.81)$ (1.81)$ (2.36)$ (1.85)$ (2.36)$ (1.85)$ (1.85)$ (1.85)$ (1.81)$ (1.81)$ (2.36)$ (2.00)$ (2.00)$ (1.96)$ High Growth_Low Prices 2030-2031 Jun (1.83)$ (1.83)$ (2.36)$ (1.87)$ (2.36)$ (1.87)$ (1.87)$ (1.87)$ (1.83)$ (1.83)$ (2.36)$ (2.01)$ (2.01)$ (1.97)$ High Growth_Low Prices 2030-2031 Jul (1.94)$ (1.94)$ (2.36)$ (1.98)$ (2.36)$ (1.98)$ (1.98)$ (1.98)$ (1.94)$ (1.94)$ (2.36)$ (2.08)$ (2.08)$ (2.06)$ High Growth_Low Prices 2030-2031 Aug (1.97)$ (1.97)$ (2.36)$ (2.01)$ (2.36)$ (2.01)$ (2.01)$ (2.01)$ (1.97)$ (1.97)$ (2.36)$ (2.10)$ (2.10)$ (2.08)$ High Growth_Low Prices 2030-2031 Sep (1.91)$ (1.91)$ (2.36)$ (1.96)$ (2.36)$ (1.96)$ (1.96)$ (1.96)$ (1.91)$ (1.91)$ (2.36)$ (2.06)$ (2.06)$ (2.04)$ High Growth_Low Prices 2030-2031 Oct (1.94)$ (1.94)$ (2.36)$ (1.99)$ (2.36)$ (1.99)$ (1.99)$ (1.99)$ (1.94)$ (1.94)$ (2.36)$ (2.08)$ (2.08)$ (2.06)$ High Growth_Low Prices 2031-2032 Nov (2.07)$ (1.88)$ (2.46)$ (2.08)$ (2.46)$ (2.08)$ (2.08)$ (2.08)$ (2.07)$ (1.88)$ (2.46)$ (2.13)$ (2.13)$ (2.16)$ High Growth_Low Prices 2031-2032 Dec (2.43)$ (1.95)$ (2.49)$ (2.54)$ (2.59)$ (2.54)$ (2.54)$ (2.54)$ (2.43)$ (1.95)$ (2.49)$ (2.29)$ (2.29)$ (2.55)$ High Growth_Low Prices 2031-2032 Jan (2.46)$ (2.00)$ (2.48)$ (2.46)$ (2.71)$ (2.46)$ (2.46)$ (2.46)$ (2.46)$ (2.00)$ (2.48)$ (2.32)$ (2.32)$ (2.51)$ High Growth_Low Prices 2031-2032 Feb (2.89)$ (1.98)$ (2.95)$ (2.08)$ (2.98)$ (2.08)$ (2.08)$ (2.08)$ (2.89)$ (1.98)$ (2.95)$ (2.61)$ (2.61)$ (2.26)$
High Growth_Low Prices 2031-2032 Mar (1.86)$ (1.85)$ (2.46)$ (1.89)$ (2.46)$ (1.89)$ (1.89)$ (1.89)$ (1.86)$ (1.85)$ (2.46)$ (2.06)$ (2.06)$ (2.00)$
High Growth_Low Prices 2031-2032 Apr (1.73)$ (1.73)$ (2.46)$ (1.77)$ (2.46)$ (1.77)$ (1.77)$ (1.77)$ (1.73)$ (1.73)$ (2.46)$ (1.97)$ (1.97)$ (1.91)$
High Growth_Low Prices 2031-2032 May (1.75)$ (1.75)$ (2.46)$ (1.79)$ (2.46)$ (1.79)$ (1.79)$ (1.79)$ (1.75)$ (1.75)$ (2.46)$ (1.99)$ (1.99)$ (1.92)$
High Growth_Low Prices 2031-2032 Jun (1.80)$ (1.80)$ (2.46)$ (1.84)$ (2.46)$ (1.84)$ (1.84)$ (1.84)$ (1.80)$ (1.80)$ (2.46)$ (2.02)$ (2.02)$ (1.96)$
High Growth_Low Prices 2031-2032 Jul (1.89)$ (1.89)$ (2.46)$ (1.93)$ (2.46)$ (1.93)$ (1.93)$ (1.93)$ (1.89)$ (1.89)$ (2.46)$ (2.08)$ (2.08)$ (2.04)$
High Growth_Low Prices 2031-2032 Aug (1.92)$ (1.92)$ (2.46)$ (1.96)$ (2.46)$ (1.96)$ (1.96)$ (1.96)$ (1.92)$ (1.92)$ (2.46)$ (2.10)$ (2.10)$ (2.06)$
High Growth_Low Prices 2031-2032 Sep (1.87)$ (1.87)$ (2.46)$ (1.91)$ (2.46)$ (1.91)$ (1.91)$ (1.91)$ (1.87)$ (1.87)$ (2.46)$ (2.07)$ (2.07)$ (2.02)$
High Growth_Low Prices 2031-2032 Oct (1.95)$ (1.95)$ (2.47)$ (1.99)$ (2.42)$ (1.99)$ (1.99)$ (1.99)$ (1.95)$ (1.95)$ (2.47)$ (2.12)$ (2.12)$ (2.08)$
High Growth_Low Prices 2032-2033 Nov (2.05)$ (1.86)$ (2.47)$ (2.13)$ (2.47)$ (2.13)$ (2.13)$ (2.13)$ (2.05)$ (1.86)$ (2.47)$ (2.13)$ (2.13)$ (2.20)$
High Growth_Low Prices 2032-2033 Dec (2.47)$ (2.00)$ (2.50)$ (2.55)$ (2.62)$ (2.55)$ (2.55)$ (2.55)$ (2.47)$ (2.00)$ (2.50)$ (2.32)$ (2.32)$ (2.57)$
High Growth_Low Prices 2032-2033 Jan (2.50)$ (2.04)$ (2.50)$ (2.47)$ (2.64)$ (2.47)$ (2.47)$ (2.47)$ (2.50)$ (2.04)$ (2.50)$ (2.35)$ (2.35)$ (2.50)$
High Growth_Low Prices 2032-2033 Feb (2.99)$ (2.06)$ (2.99)$ (2.15)$ (3.00)$ (2.15)$ (2.15)$ (2.15)$ (2.99)$ (2.06)$ (2.99)$ (2.68)$ (2.68)$ (2.32)$
High Growth_Low Prices 2032-2033 Mar (1.93)$ (1.91)$ (2.48)$ (1.95)$ (2.48)$ (1.95)$ (1.95)$ (1.95)$ (1.93)$ (1.91)$ (2.48)$ (2.10)$ (2.10)$ (2.06)$
High Growth_Low Prices 2032-2033 Apr (1.81)$ (1.81)$ (2.43)$ (1.85)$ (2.43)$ (1.85)$ (1.85)$ (1.85)$ (1.81)$ (1.81)$ (2.43)$ (2.01)$ (2.01)$ (1.96)$
High Growth_Low Prices 2032-2033 May (1.79)$ (1.79)$ (2.43)$ (1.83)$ (2.43)$ (1.83)$ (1.83)$ (1.83)$ (1.79)$ (1.79)$ (2.43)$ (2.00)$ (2.00)$ (1.95)$
High Growth_Low Prices 2032-2033 Jun (1.81)$ (1.81)$ (2.43)$ (1.86)$ (2.43)$ (1.86)$ (1.86)$ (1.86)$ (1.81)$ (1.81)$ (2.43)$ (2.02)$ (2.02)$ (1.97)$
High Growth_Low Prices 2032-2033 Jul (1.95)$ (1.95)$ (2.43)$ (1.99)$ (2.43)$ (1.99)$ (1.99)$ (1.99)$ (1.95)$ (1.95)$ (2.43)$ (2.11)$ (2.11)$ (2.08)$
High Growth_Low Prices 2032-2033 Aug (1.96)$ (1.96)$ (2.43)$ (2.00)$ (2.43)$ (2.00)$ (2.00)$ (2.00)$ (1.96)$ (1.96)$ (2.43)$ (2.12)$ (2.12)$ (2.09)$
High Growth_Low Prices 2032-2033 Sep (1.89)$ (1.89)$ (2.43)$ (1.94)$ (2.43)$ (1.94)$ (1.94)$ (1.94)$ (1.89)$ (1.89)$ (2.43)$ (2.07)$ (2.07)$ (2.04)$
High Growth_Low Prices 2032-2033 Oct (1.90)$ (1.90)$ (2.43)$ (1.95)$ (2.42)$ (1.95)$ (1.95)$ (1.95)$ (1.90)$ (1.90)$ (2.43)$ (2.08)$ (2.08)$ (2.04)$
High Growth_Low Prices 2033-2034 Nov (2.07)$ (1.88)$ (2.48)$ (2.15)$ (2.48)$ (2.15)$ (2.15)$ (2.15)$ (2.07)$ (1.88)$ (2.48)$ (2.14)$ (2.14)$ (2.22)$
High Growth_Low Prices 2033-2034 Dec (2.47)$ (2.00)$ (2.51)$ (2.57)$ (2.62)$ (2.57)$ (2.57)$ (2.57)$ (2.47)$ (2.00)$ (2.51)$ (2.33)$ (2.33)$ (2.58)$
Monthly Avoided Costs 1/
Nominal$
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 241 of 829

APPENDIX 6.4: HIGH GROWTH – LOW PRICE MONTHLY DETAIL

Scenario Gas Year Month ID Both ID GTN ID NWP Klam Falls La Grande Medford GTN Medford NWP Roseburg WA Both WA GTN WA NWP ID Annual WA Annual OR Annual
High Growth_Low Prices 2033-2034 Jan (2.47)$ (2.01)$ (2.52)$ (2.49)$ (2.69)$ (2.49)$ (2.49)$ (2.49)$ (2.47)$ (2.01)$ (2.52)$ (2.33)$ (2.33)$ (2.53)$
High Growth_Low Prices 2033-2034 Feb (3.00)$ (2.04)$ (3.01)$ (2.12)$ (3.05)$ (2.12)$ (2.12)$ (2.12)$ (3.00)$ (2.04)$ (3.01)$ (2.68)$ (2.68)$ (2.31)$
High Growth_Low Prices 2033-2034 Mar (1.87)$ (1.86)$ (2.49)$ (1.90)$ (2.49)$ (1.90)$ (1.90)$ (1.90)$ (1.87)$ (1.86)$ (2.49)$ (2.07)$ (2.07)$ (2.02)$
High Growth_Low Prices 2033-2034 Apr (1.74)$ (1.74)$ (2.49)$ (1.78)$ (2.49)$ (1.78)$ (1.78)$ (1.78)$ (1.74)$ (1.74)$ (2.49)$ (1.99)$ (1.99)$ (1.92)$
High Growth_Low Prices 2033-2034 May (1.74)$ (1.74)$ (2.49)$ (1.78)$ (2.49)$ (1.78)$ (1.78)$ (1.78)$ (1.74)$ (1.74)$ (2.49)$ (1.99)$ (1.99)$ (1.92)$
High Growth_Low Prices 2033-2034 Jun (1.77)$ (1.77)$ (2.49)$ (1.81)$ (2.49)$ (1.81)$ (1.81)$ (1.81)$ (1.77)$ (1.77)$ (2.49)$ (2.01)$ (2.01)$ (1.95)$
High Growth_Low Prices 2033-2034 Jul (1.89)$ (1.89)$ (2.49)$ (1.94)$ (2.49)$ (1.94)$ (1.94)$ (1.94)$ (1.89)$ (1.89)$ (2.49)$ (2.09)$ (2.09)$ (2.05)$
High Growth_Low Prices 2033-2034 Aug (1.90)$ (1.90)$ (2.49)$ (1.94)$ (2.49)$ (1.94)$ (1.94)$ (1.94)$ (1.90)$ (1.90)$ (2.49)$ (2.10)$ (2.10)$ (2.05)$
High Growth_Low Prices 2033-2034 Sep (1.82)$ (1.82)$ (2.49)$ (1.86)$ (2.46)$ (1.86)$ (1.86)$ (1.86)$ (1.82)$ (1.82)$ (2.49)$ (2.05)$ (2.05)$ (1.98)$
High Growth_Low Prices 2033-2034 Oct (1.86)$ (1.86)$ (2.55)$ (1.90)$ (2.55)$ (1.90)$ (1.90)$ (1.90)$ (1.86)$ (1.86)$ (2.55)$ (2.09)$ (2.09)$ (2.03)$
High Growth_Low Prices 2034-2035 Nov (2.06)$ (1.88)$ (2.50)$ (2.15)$ (2.50)$ (2.15)$ (2.15)$ (2.15)$ (2.06)$ (1.88)$ (2.50)$ (2.14)$ (2.14)$ (2.22)$
High Growth_Low Prices 2034-2035 Dec (2.44)$ (1.96)$ (2.53)$ (2.59)$ (2.68)$ (2.59)$ (2.59)$ (2.59)$ (2.44)$ (1.96)$ (2.53)$ (2.31)$ (2.31)$ (2.61)$
High Growth_Low Prices 2034-2035 Jan (2.48)$ (2.02)$ (2.53)$ (2.50)$ (2.76)$ (2.50)$ (2.50)$ (2.50)$ (2.48)$ (2.02)$ (2.53)$ (2.34)$ (2.34)$ (2.55)$
High Growth_Low Prices 2034-2035 Feb (3.00)$ (2.02)$ (3.04)$ (2.11)$ (3.09)$ (2.11)$ (2.11)$ (2.11)$ (3.00)$ (2.02)$ (3.04)$ (2.69)$ (2.69)$ (2.31)$
High Growth_Low Prices 2034-2035 Mar (1.94)$ (1.89)$ (2.49)$ (1.94)$ (2.49)$ (1.94)$ (1.94)$ (1.94)$ (1.94)$ (1.89)$ (2.49)$ (2.11)$ (2.11)$ (2.05)$
High Growth_Low Prices 2034-2035 Apr (1.78)$ (1.78)$ (2.49)$ (1.82)$ (2.49)$ (1.82)$ (1.82)$ (1.82)$ (1.78)$ (1.78)$ (2.49)$ (2.02)$ (2.02)$ (1.96)$
High Growth_Low Prices 2034-2035 May (1.72)$ (1.72)$ (2.49)$ (1.76)$ (2.49)$ (1.76)$ (1.76)$ (1.76)$ (1.72)$ (1.72)$ (2.49)$ (1.98)$ (1.98)$ (1.91)$
High Growth_Low Prices 2034-2035 Jun (1.75)$ (1.75)$ (2.49)$ (1.79)$ (2.49)$ (1.79)$ (1.79)$ (1.79)$ (1.75)$ (1.75)$ (2.49)$ (2.00)$ (2.00)$ (1.93)$
High Growth_Low Prices 2034-2035 Jul (1.86)$ (1.86)$ (2.49)$ (1.90)$ (2.49)$ (1.90)$ (1.90)$ (1.90)$ (1.86)$ (1.86)$ (2.49)$ (2.07)$ (2.07)$ (2.02)$
High Growth_Low Prices 2034-2035 Aug (1.88)$ (1.88)$ (2.49)$ (1.92)$ (2.49)$ (1.92)$ (1.92)$ (1.92)$ (1.88)$ (1.88)$ (2.49)$ (2.08)$ (2.08)$ (2.03)$
High Growth_Low Prices 2034-2035 Sep (1.82)$ (1.82)$ (2.49)$ (1.86)$ (2.48)$ (1.86)$ (1.86)$ (1.86)$ (1.82)$ (1.82)$ (2.49)$ (2.04)$ (2.04)$ (1.98)$ High Growth_Low Prices 2034-2035 Oct (1.77)$ (1.77)$ (2.51)$ (1.81)$ (2.51)$ (1.81)$ (1.81)$ (1.81)$ (1.77)$ (1.77)$ (2.51)$ (2.02)$ (2.02)$ (1.95)$ High Growth_Low Prices 2035-2036 Nov (1.87)$ (1.68)$ (2.50)$ (2.03)$ (2.50)$ (2.03)$ (2.03)$ (2.03)$ (1.87)$ (1.68)$ (2.50)$ (2.01)$ (2.01)$ (2.13)$ High Growth_Low Prices 2035-2036 Dec (2.24)$ (1.72)$ (2.53)$ (2.61)$ (2.74)$ (2.61)$ (2.61)$ (2.61)$ (2.24)$ (1.72)$ (2.53)$ (2.16)$ (2.16)$ (2.63)$ High Growth_Low Prices 2035-2036 Jan (2.32)$ (1.86)$ (2.53)$ (2.50)$ (2.89)$ (2.50)$ (2.50)$ (2.50)$ (2.32)$ (1.86)$ (2.53)$ (2.23)$ (2.23)$ (2.58)$ High Growth_Low Prices 2035-2036 Feb (2.95)$ (1.97)$ (3.04)$ (2.07)$ (3.12)$ (2.07)$ (2.07)$ (2.07)$ (2.95)$ (1.97)$ (3.04)$ (2.65)$ (2.65)$ (2.28)$ High Growth_Low Prices 2035-2036 Mar (1.86)$ (1.82)$ (2.48)$ (1.86)$ (2.48)$ (1.86)$ (1.86)$ (1.86)$ (1.86)$ (1.82)$ (2.48)$ (2.05)$ (2.05)$ (1.98)$ High Growth_Low Prices 2035-2036 Apr (1.70)$ (1.70)$ (2.45)$ (1.74)$ (2.45)$ (1.74)$ (1.74)$ (1.74)$ (1.70)$ (1.70)$ (2.45)$ (1.95)$ (1.95)$ (1.88)$ High Growth_Low Prices 2035-2036 May (1.69)$ (1.69)$ (2.45)$ (1.72)$ (2.45)$ (1.72)$ (1.72)$ (1.72)$ (1.69)$ (1.69)$ (2.45)$ (1.94)$ (1.94)$ (1.87)$ High Growth_Low Prices 2035-2036 Jun (1.77)$ (1.77)$ (2.46)$ (1.81)$ (2.45)$ (1.81)$ (1.81)$ (1.81)$ (1.77)$ (1.77)$ (2.46)$ (2.00)$ (2.00)$ (1.94)$ High Growth_Low Prices 2035-2036 Jul (1.95)$ (1.95)$ (2.46)$ (1.99)$ (2.46)$ (1.99)$ (1.99)$ (1.99)$ (1.95)$ (1.95)$ (2.46)$ (2.12)$ (2.12)$ (2.09)$ High Growth_Low Prices 2035-2036 Aug (2.04)$ (2.04)$ (2.46)$ (2.09)$ (2.46)$ (2.09)$ (2.09)$ (2.09)$ (2.04)$ (2.04)$ (2.46)$ (2.18)$ (2.18)$ (2.16)$ High Growth_Low Prices 2035-2036 Sep (1.92)$ (1.92)$ (2.46)$ (1.96)$ (2.40)$ (1.96)$ (1.96)$ (1.96)$ (1.92)$ (1.92)$ (2.46)$ (2.10)$ (2.10)$ (2.05)$ High Growth_Low Prices 2035-2036 Oct (1.90)$ (1.90)$ (2.51)$ (1.95)$ (2.51)$ (1.95)$ (1.95)$ (1.95)$ (1.90)$ (1.90)$ (2.51)$ (2.10)$ (2.10)$ (2.06)$ High Growth_Low Prices 2036-2037 Nov (2.04)$ (1.85)$ (2.46)$ (2.12)$ (2.46)$ (2.12)$ (2.12)$ (2.12)$ (2.04)$ (1.85)$ (2.46)$ (2.12)$ (2.12)$ (2.19)$ High Growth_Low Prices 2036-2037 Dec (2.42)$ (1.94)$ (2.50)$ (2.62)$ (2.98)$ (38.11)$ (38.11)$ (38.11)$ (2.42)$ (1.94)$ (2.50)$ (2.29)$ (2.29)$ (23.99)$ High Growth_Low Prices 2036-2037 Jan (2.45)$ (1.99)$ (2.49)$ (2.46)$ (2.91)$ (2.46)$ (2.46)$ (2.46)$ (2.45)$ (1.99)$ (2.49)$ (2.31)$ (2.31)$ (2.55)$ High Growth_Low Prices 2036-2037 Feb (3.00)$ (2.09)$ (3.00)$ (2.14)$ (3.09)$ (2.14)$ (2.14)$ (2.14)$ (3.00)$ (2.09)$ (3.00)$ (2.70)$ (2.70)$ (2.33)$ High Growth_Low Prices 2036-2037 Mar (1.89)$ (1.85)$ (2.55)$ (1.89)$ (2.55)$ (1.89)$ (1.89)$ (1.89)$ (1.89)$ (1.85)$ (2.55)$ (2.10)$ (2.10)$ (2.02)$ High Growth_Low Prices 2036-2037 Apr (1.67)$ (1.67)$ (2.14)$ (1.71)$ (2.14)$ (1.71)$ (1.71)$ (1.71)$ (1.67)$ (1.67)$ (2.14)$ (1.83)$ (1.83)$ (1.80)$ High Growth_Low Prices 2036-2037 May (1.66)$ (1.66)$ (1.97)$ (1.70)$ (1.97)$ (1.70)$ (1.70)$ (1.70)$ (1.66)$ (1.66)$ (1.97)$ (1.76)$ (1.76)$ (1.75)$ High Growth_Low Prices 2036-2037 Jun (1.73)$ (1.73)$ (1.97)$ (1.77)$ (1.97)$ (1.77)$ (1.77)$ (1.77)$ (1.73)$ (1.73)$ (1.97)$ (1.81)$ (1.81)$ (1.81)$ High Growth_Low Prices 2036-2037 Jul (1.93)$ (1.93)$ (1.97)$ (1.97)$ (1.97)$ (1.97)$ (1.97)$ (1.97)$ (1.93)$ (1.93)$ (1.97)$ (1.94)$ (1.94)$ (1.97)$ High Growth_Low Prices 2036-2037 Aug (1.97)$ (1.97)$ (1.97)$ (2.01)$ (1.98)$ (1.97)$ (1.97)$ (1.97)$ (1.97)$ (1.97)$ (1.97)$ (1.97)$ (1.97)$ (1.98)$ High Growth_Low Prices 2036-2037 Sep (1.82)$ (1.82)$ (1.86)$ (1.86)$ (1.86)$ (1.86)$ (1.86)$ (1.86)$ (1.82)$ (1.82)$ (1.86)$ (1.83)$ (1.83)$ (1.86)$
High Growth_Low Prices 2036-2037 Oct (1.74)$ (1.74)$ (2.49)$ (1.78)$ (2.49)$ (1.78)$ (1.78)$ (1.78)$ (1.74)$ (1.74)$ (2.49)$ (1.99)$ (1.99)$ (1.92)$
1/ Avoided costs are before Environmental Externalities adder.
Monthly Avoided Costs 1/Nominal$
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 242 of 829
APPENDIX 7.1: HIGH GROWTH CASES
SELECTED RESOURCES VS. PEAK DAY DEMAND
EXISTING PLUS EXPECTED AVAILABLE

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 243 of 829
APPENDIX 7.1: HIGH GROWTH CASES
SELECTED RESOURCES VS. PEAK DAY DEMAND
EXISTING PLUS EXPECTED AVAILABLE

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 244 of 829
APPENDIX 7.2: PEAK DAY DEMAND TABLE
HIGH GROWTH

Scenario Gas Year
LaGrande
Served
LaGrande
Unserved
LaGrande
Total
LaGrande % of Peak Day
Served
WA
Served
WA
Unserved WA Total
WA % of Peak Day
Served
ID
Served
ID
Unserved ID Total
ID % of
Peak Day
Served
High Growth_Low Prices 2017-2018 7.59 - 7.59 100%189.28 - 189.28 100%90.23 - 90.23 100%
High Growth_Low Prices 2018-2019 7.68 - 7.68 100%192.33 - 192.33 100%91.76 - 91.76 100%High Growth_Low Prices 2019-2020 7.77 - 7.77 100%195.29 - 195.29 100%93.31 - 93.31 100%
High Growth_Low Prices 2020-2021 7.86 - 7.86 100%198.09 - 198.09 100%94.87 - 94.87 100%High Growth_Low Prices 2021-2022 7.95 - 7.95 100%200.64 - 200.64 100%96.42 - 96.42 100%
High Growth_Low Prices 2022-2023 8.04 - 8.04 100%203.02 - 203.02 100%97.92 - 97.92 100%
High Growth_Low Prices 2023-2024 8.12 - 8.12 100%205.77 - 205.77 100%99.59 - 99.59 100%High Growth_Low Prices 2024-2025 8.19 - 8.19 100%207.58 - 207.58 100%100.71 - 100.71 100%
High Growth_Low Prices 2025-2026 8.27 - 8.27 100%209.64 - 209.64 100%101.96 - 101.96 100%High Growth_Low Prices 2026-2027 8.35 - 8.35 100%211.61 - 211.61 100%103.16 - 103.16 100%
High Growth_Low Prices 2027-2028 8.44 - 8.44 100%213.70 - 213.70 100%104.48 - 104.48 100%High Growth_Low Prices 2028-2029 8.53 - 8.53 100%215.35 - 215.35 100%105.61 - 105.61 100%
High Growth_Low Prices 2029-2030 8.62 - 8.62 100%217.17 - 217.17 100%106.87 - 106.87 100%High Growth_Low Prices 2030-2031 8.71 - 8.71 100%218.97 - 218.97 100%108.20 - 108.20 100%
High Growth_Low Prices 2031-2032 6.65 2.15 8.80 76%219.84 1.26 221.10 99%109.77 - 109.77 100%High Growth_Low Prices 2032-2033 6.65 2.23 8.88 75%222.62 - 222.62 100%107.22 3.87 111.09 97%
High Growth_Low Prices 2033-2034 6.65 2.30 8.95 74%217.46 7.01 224.47 97%112.65 - 112.65 100%High Growth_Low Prices 2034-2035 6.65 2.38 9.03 74%216.11 10.23 226.34 95%114.28 - 114.28 100%
High Growth_Low Prices 2035-2036 6.65 2.46 9.11 73%214.55 14.08 228.64 94%116.17 - 116.17 100%
High Growth_Low Prices 2036-2037 9.17 - 9.17 100%223.92 6.25 230.17 97%104.53 13.20 117.73 89%
Scenario Gas Year
Klamath
Falls
Served
Klamath
Falls
Unserved
Klamath
Falls Total
Klamath
Falls % of
Peak Day
Served

Medford/
Roseburg
Served

Medford/
Roseburg
Unserved

Medford/
Roseburg
Total

Medford/
Roseburg
% of Peak
Day
Served
High Growth_Low Prices 2017-2018 13.34 - 13.34 100%75.36 - 75.36 100%High Growth_Low Prices 2018-2019 13.52 - 13.52 100%76.47 - 76.47 100%
High Growth_Low Prices 2019-2020 13.71 - 13.71 100%77.55 - 77.55 100%
High Growth_Low Prices 2020-2021 13.90 - 13.90 100%78.64 - 78.64 100%High Growth_Low Prices 2021-2022 14.09 - 14.09 100%79.75 - 79.75 100%
High Growth_Low Prices 2022-2023 14.28 - 14.28 100%80.86 - 80.86 100%High Growth_Low Prices 2023-2024 14.47 - 14.47 100%81.91 - 81.91 100%
High Growth_Low Prices 2024-2025 14.65 - 14.65 100%82.79 - 82.79 100%High Growth_Low Prices 2025-2026 14.84 - 14.84 100%83.77 - 83.77 100%
High Growth_Low Prices 2026-2027 15.02 - 15.02 100%84.75 - 84.75 100%High Growth_Low Prices 2027-2028 15.20 - 15.20 100%85.72 - 85.72 100%
High Growth_Low Prices 2028-2029 15.37 - 15.37 100%86.66 - 86.66 100%High Growth_Low Prices 2029-2030 15.54 - 15.54 100%87.57 - 87.57 100%
High Growth_Low Prices 2030-2031 15.69 - 15.69 100%87.96 0.48 88.44 99%High Growth_Low Prices 2031-2032 15.85 - 15.85 100%87.97 1.30 89.27 99%
High Growth_Low Prices 2032-2033 16.01 - 16.01 100%87.96 2.10 90.07 98%
High Growth_Low Prices 2033-2034 16.17 - 16.17 100%87.97 2.89 90.85 97%High Growth_Low Prices 2034-2035 16.33 - 16.33 100%87.96 3.64 91.61 96%
High Growth_Low Prices 2035-2036 16.49 - 16.49 100%87.97 4.39 92.36 95%High Growth_Low Prices 2036-2037 16.65 - 16.65 100%87.96 5.14 93.10 94%
Peak Day Demand - Served and Unserved (MDth/d)
Before Resource Additions & Net of DSM Savings
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 245 of 829
APPENDIX 7.2: PEAK DAY DEMAND TABLE
LOW GROWTH

Scenario Gas Year
LaGrande
Served
LaGrande
Unserved

LaGrande
Total
LaGrande % of Peak
Day
Served
WA
Served
WA
Unserved WA Total
WA % of
Peak Day
Served
ID
Served
ID
Unserved ID Total
ID % of Peak
Day
Served
Low Growth_High Prices 2017-2018 7.47 - 7.47 100%186.53 - 186.53 100%88.59 - 88.59 100%
Low Growth_High Prices 2018-2019 7.44 - 7.44 100%188.06 - 188.06 100%89.11 - 89.11 100%Low Growth_High Prices 2019-2020 7.41 - 7.41 100%188.88 - 188.88 100%89.46 - 89.46 100%
Low Growth_High Prices 2020-2021 7.36 - 7.36 100%189.55 - 189.55 100%89.80 - 89.80 100%
Low Growth_High Prices 2021-2022 7.33 - 7.33 100%190.26 - 190.26 100%90.08 - 90.08 100%Low Growth_High Prices 2022-2023 7.32 - 7.32 100%190.74 - 190.74 100%90.30 - 90.30 100%Low Growth_High Prices 2023-2024 7.32 - 7.32 100%191.70 - 191.70 100%90.77 - 90.77 100%
Low Growth_High Prices 2024-2025 7.31 - 7.31 100%191.90 - 191.90 100%90.79 - 90.79 100%
Low Growth_High Prices 2025-2026 7.32 - 7.32 100%192.41 - 192.41 100%90.97 - 90.97 100%Low Growth_High Prices 2026-2027 7.32 - 7.32 100%192.85 - 192.85 100%91.12 - 91.12 100%
Low Growth_High Prices 2027-2028 7.32 - 7.32 100%193.42 - 193.42 100%91.36 - 91.36 100%
Low Growth_High Prices 2028-2029 7.31 - 7.31 100%193.37 - 193.37 100%91.30 - 91.30 100%Low Growth_High Prices 2029-2030 7.30 - 7.30 100%193.72 - 193.72 100%91.46 - 91.46 100%Low Growth_High Prices 2030-2031 7.30 - 7.30 100%194.08 - 194.08 100%91.67 - 91.67 100%
Low Growth_High Prices 2031-2032 7.31 - 7.31 100%194.79 - 194.79 100%92.07 - 92.07 100%
Low Growth_High Prices 2032-2033 7.30 - 7.30 100%194.91 - 194.91 100%92.20 - 92.20 100%Low Growth_High Prices 2033-2034 7.30 - 7.30 100%195.39 - 195.39 100%92.54 - 92.54 100%
Low Growth_High Prices 2034-2035 7.31 - 7.31 100%195.91 - 195.91 100%92.93 - 92.93 100%
Low Growth_High Prices 2035-2036 7.32 - 7.32 100%196.87 - 196.87 100%91.40 - 91.40 100%Low Growth_High Prices 2036-2037 7.32 - 7.32 100%197.07 - 197.07 100%90.70 - 90.70 100%
Scenario Gas Year
Klamath Falls
Served
Klamath Falls
Unserved
Klamath
Falls Total
Klamath
Falls % of Peak Day
Served

Medford/Roseburg
Served

Medford/Roseburg
Unserved

Medford/Roseburg
Total

Medford/
Roseburg
% of Peak Day
Served
Low Growth_High Prices 2017-2018 13.14 - 13.14 100%74.33 - 74.33 100%
Low Growth_High Prices 2018-2019 13.20 - 13.20 100%74.83 - 74.83 100%Low Growth_High Prices 2019-2020 13.25 - 13.25 100%75.18 - 75.18 100%
Low Growth_High Prices 2020-2021 13.30 - 13.30 100%75.55 - 75.55 100%
Low Growth_High Prices 2021-2022 13.29 - 13.29 100%75.63 - 75.63 100%Low Growth_High Prices 2022-2023 13.34 - 13.34 100%76.00 - 76.00 100%
Low Growth_High Prices 2023-2024 13.39 - 13.39 100%76.36 - 76.36 100%
Low Growth_High Prices 2024-2025 13.43 - 13.43 100%76.66 - 76.66 100%Low Growth_High Prices 2025-2026 13.49 - 13.49 100%77.05 - 77.05 100%Low Growth_High Prices 2026-2027 13.55 - 13.55 100%77.44 - 77.44 100%
Low Growth_High Prices 2027-2028 13.61 - 13.61 100%77.82 - 77.82 100%
Low Growth_High Prices 2028-2029 13.65 - 13.65 100%78.11 - 78.11 100%Low Growth_High Prices 2029-2030 13.70 - 13.70 100%78.45 - 78.45 100%
Low Growth_High Prices 2030-2031 13.75 - 13.75 100%78.77 - 78.77 100%
Low Growth_High Prices 2031-2032 13.81 - 13.81 100%79.07 - 79.07 100%Low Growth_High Prices 2032-2033 13.86 - 13.86 100%79.36 - 79.36 100%Low Growth_High Prices 2033-2034 13.92 - 13.92 100%79.63 - 79.63 100%
Low Growth_High Prices 2034-2035 13.97 - 13.97 100%79.89 - 79.89 100%
Low Growth_High Prices 2035-2036 14.03 - 14.03 100%80.15 - 80.15 100%Low Growth_High Prices 2036-2037 14.08 - 14.08 100%80.40 - 80.40 100%
Peak Day Demand - Served and Unserved (MDth/d)
Before Resource Additions & Net of DSM Savings
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 246 of 829
APPENDIX 7.2: PEAK DAY DEMAND TABLE
COLDEST IN 20 YEARS

Scenario Gas Year

LaGrande
Served

LaGrande
Unserved

LaGrande
Total
LaGrande
% of Peak
Day
Served
WA
Served
WA
Unserved WA Total
WA % of
Peak Day
Served
ID
Served
ID
Unserved
ID
Total
ID % of
Peak
Day
Served
Cold Day 20yr Weather Std 2017-2018 6.74 - 6.74 100%175.11 - 175.11 100%83.41 - 83.41 100%
Cold Day 20yr Weather Std 2018-2019 6.77 - 6.77 100%177.19 - 177.19 100%84.37 - 84.37 100%
Cold Day 20yr Weather Std 2019-2020 6.80 - 6.80 100%178.80 - 178.80 100%85.33 - 85.33 100%Cold Day 20yr Weather Std 2020-2021 6.82 - 6.82 100%180.21 - 180.21 100%86.27 - 86.27 100%Cold Day 20yr Weather Std 2021-2022 6.82 - 6.82 100%181.62 - 181.62 100%87.08 - 87.08 100%
Cold Day 20yr Weather Std 2022-2023 6.84 - 6.84 100%182.78 - 182.78 100%87.82 - 87.82 100%
Cold Day 20yr Weather Std 2023-2024 6.86 - 6.86 100%184.57 - 184.57 100%88.84 - 88.84 100%
Cold Day 20yr Weather Std 2024-2025 6.87 - 6.87 100%185.41 - 185.41 100%89.32 - 89.32 100%Cold Day 20yr Weather Std 2025-2026 6.90 - 6.90 100%186.51 - 186.51 100%89.93 - 89.93 100%
Cold Day 20yr Weather Std 2026-2027 6.92 - 6.92 100%187.53 - 187.53 100%90.51 - 90.51 100%
Cold Day 20yr Weather Std 2027-2028 6.94 - 6.94 100%188.68 - 188.68 100%91.19 - 91.19 100%
Cold Day 20yr Weather Std 2028-2029 6.96 - 6.96 100%189.39 - 189.39 100%91.67 - 91.67 100%Cold Day 20yr Weather Std 2029-2030 6.99 - 6.99 100%190.30 - 190.30 100%92.28 - 92.28 100%Cold Day 20yr Weather Std 2030-2031 7.01 - 7.01 100%191.20 - 191.20 100%92.93 - 92.93 100%
Cold Day 20yr Weather Std 2031-2032 7.03 - 7.03 100%192.45 - 192.45 100%93.80 - 93.80 100%
Cold Day 20yr Weather Std 2032-2033 7.05 - 7.05 100%193.10 - 193.10 100%94.41 - 94.41 100%Cold Day 20yr Weather Std 2033-2034 7.06 - 7.06 100%194.09 - 194.09 100%95.23 - 95.23 100%Cold Day 20yr Weather Std 2034-2035 7.08 - 7.08 100%195.12 - 195.12 100%96.11 - 96.11 100%
Cold Day 20yr Weather Std 2035-2036 7.11 - 7.11 100%196.57 - 196.57 100%97.24 - 97.24 100%
Cold Day 20yr Weather Std 2036-2037 7.11 - 7.11 100%197.27 - 197.27 100%98.01 - 98.01 100%
Scenario Gas Year
Klamath
Falls
Served
Klamath
Falls
Unserved
Klamath
Falls
Total
Klamath
Falls % of
Peak Day
Served

Medford/
Roseburg
Served

Medford/
Roseburg
Unserved

Medford/
Roseburg
Total

Medford/
Roseburg
% of Peak
Day
Served
Cold Day 20yr Weather Std 2017-2018 13.24 - 13.24 100%65.02 - 65.02 100%Cold Day 20yr Weather Std 2018-2019 13.36 - 13.36 100%65.71 - 65.71 100%
Cold Day 20yr Weather Std 2019-2020 13.49 - 13.49 100%66.38 - 66.38 100%
Cold Day 20yr Weather Std 2020-2021 13.62 - 13.62 100%67.06 - 67.06 100%
Cold Day 20yr Weather Std 2021-2022 13.67 - 13.67 100%67.37 - 67.37 100%Cold Day 20yr Weather Std 2022-2023 13.78 - 13.78 100%67.97 - 67.97 100%
Cold Day 20yr Weather Std 2023-2024 13.91 - 13.91 100%68.60 - 68.60 100%
Cold Day 20yr Weather Std 2024-2025 14.02 - 14.02 100%69.09 - 69.09 100%
Cold Day 20yr Weather Std 2025-2026 14.14 - 14.14 100%69.67 - 69.67 100%Cold Day 20yr Weather Std 2026-2027 14.26 - 14.26 100%70.24 - 70.24 100%Cold Day 20yr Weather Std 2027-2028 14.37 - 14.37 100%70.80 - 70.80 100%
Cold Day 20yr Weather Std 2028-2029 14.48 - 14.48 100%71.34 - 71.34 100%
Cold Day 20yr Weather Std 2029-2030 14.59 - 14.59 100%71.86 - 71.86 100%Cold Day 20yr Weather Std 2030-2031 14.69 - 14.69 100%72.35 - 72.35 100%Cold Day 20yr Weather Std 2031-2032 14.79 - 14.79 100%72.82 - 72.82 100%
Cold Day 20yr Weather Std 2032-2033 14.89 - 14.89 100%73.26 - 73.26 100%
Cold Day 20yr Weather Std 2033-2034 15.00 - 15.00 100%73.69 - 73.69 100%Cold Day 20yr Weather Std 2034-2035 15.10 - 15.10 100%74.10 - 74.10 100%Cold Day 20yr Weather Std 2035-2036 15.20 - 15.20 100%74.51 - 74.51 100%
Cold Day 20yr Weather Std 2036-2037 15.30 - 15.30 100%74.92 - 74.92 100%
Peak Day Demand - Served and Unserved (MDth/d)
Before Resource Additions & Net of DSM Savings
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 247 of 829
APPENDIX 7.2: PEAK DAY DEMAND TABLE
80% BELOW 1990 EMISSIONS

Scenario
Gas
Year

LaGrande
Served

LaGrande
Unserved

LaGrande
Total

LaGrande
% of Peak
Day
Served
WA
Served
WA
Unserved WA Total
WA % of
Peak Day
Served
ID
Served
ID
Unserved ID Total
ID % of
Peak Day
Served
80% Below 1990 Emissions 2017-2018 7.34 - 7.34 100%183.27 - 183.27 100%89.42 - 89.42 100%
80% Below 1990 Emissions 2018-2019 7.10 - 7.10 100%178.30 - 178.30 100%90.47 - 90.47 100%80% Below 1990 Emissions 2019-2020 6.85 - 6.85 100%172.54 - 172.54 100%91.51 - 91.51 100%
80% Below 1990 Emissions 2020-2021 6.65 - 6.65 100%168.02 - 168.02 100%92.53 - 92.53 100%80% Below 1990 Emissions 2021-2022 6.40 - 6.40 100%162.95 - 162.95 100%93.51 - 93.51 100%
80% Below 1990 Emissions 2022-2023 6.18 - 6.18 100%157.74 - 157.74 100%94.43 - 94.43 100%80% Below 1990 Emissions 2023-2024 5.94 - 5.94 100%152.30 - 152.30 100%95.53 - 95.53 100%
80% Below 1990 Emissions 2024-2025 5.74 - 5.74 100%147.29 - 147.29 100%96.11 - 96.11 100%
80% Below 1990 Emissions 2025-2026 5.53 - 5.53 100%141.86 - 141.86 100%96.80 - 96.80 100%80% Below 1990 Emissions 2026-2027 5.32 - 5.32 100%136.37 - 136.37 100%97.46 - 97.46 100%
80% Below 1990 Emissions 2027-2028 5.09 - 5.09 100%130.50 - 130.50 100%98.21 - 98.21 100%80% Below 1990 Emissions 2028-2029 4.90 - 4.90 100%125.34 - 125.34 100%98.78 - 98.78 100%
80% Below 1990 Emissions 2029-2030 4.70 - 4.70 100%119.86 - 119.86 100%99.46 - 99.46 100%80% Below 1990 Emissions 2030-2031 4.50 - 4.50 100%110.09 - 110.09 100%100.20 - 100.20 100%
80% Below 1990 Emissions 2031-2032 4.29 - 4.29 100%104.28 - 104.28 100%101.15 - 101.15 100%
80% Below 1990 Emissions 2032-2033 4.10 - 4.10 100%98.59 - 98.59 100%101.85 - 101.85 100%80% Below 1990 Emissions 2033-2034 3.90 - 3.90 100%92.99 - 92.99 100%102.76 - 102.76 100%
80% Below 1990 Emissions 2034-2035 3.71 - 3.71 100%87.49 - 87.49 100%103.72 - 103.72 100%80% Below 1990 Emissions 2035-2036 3.50 - 3.50 100%84.04 - 84.04 100%104.94 - 104.94 100%
80% Below 1990 Emissions 2036-2037 3.32 - 3.32 100%69.70 - 69.70 100%105.80 - 105.80 100%
Scenario
Gas
Year
Klamath
Falls
Served
Klamath
Falls
Unserved
Klamath
Falls
Total
Klamath
Falls % of
Peak Day
Served

Medford/
Roseburg
Served

Medford/
Roseburg
Unserved

Medford/
Roseburg
Total

Medford/
Roseburg
% of Peak
Day
Served
80% Below 1990 Emissions 2017-2018 12.91 - 12.91 100%72.99 - 72.99 100%
80% Below 1990 Emissions 2018-2019 12.56 - 12.56 100%71.11 - 71.11 100%80% Below 1990 Emissions 2019-2020 12.17 - 12.17 100%68.94 - 68.94 100%
80% Below 1990 Emissions 2020-2021 11.88 - 11.88 100%67.37 - 67.37 100%80% Below 1990 Emissions 2021-2022 11.48 - 11.48 100%65.15 - 65.15 100%
80% Below 1990 Emissions 2022-2023 11.14 - 11.14 100%63.29 - 63.29 100%
80% Below 1990 Emissions 2023-2024 10.76 - 10.76 100%61.15 - 61.15 100%80% Below 1990 Emissions 2024-2025 10.47 - 10.47 100%59.46 - 59.46 100%
80% Below 1990 Emissions 2025-2026 10.13 - 10.13 100%57.56 - 57.56 100%80% Below 1990 Emissions 2026-2027 9.80 - 9.80 100%55.66 - 55.66 100%
80% Below 1990 Emissions 2027-2028 9.42 - 9.42 100%53.51 - 53.51 100%80% Below 1990 Emissions 2028-2029 9.12 - 9.12 100%51.82 - 51.82 100%
80% Below 1990 Emissions 2029-2030 8.78 - 8.78 100%49.90 - 49.90 100%
80% Below 1990 Emissions 2030-2031 8.43 - 8.43 100%47.97 - 47.97 100%80% Below 1990 Emissions 2031-2032 8.06 - 8.06 100%45.82 - 45.82 100%
80% Below 1990 Emissions 2032-2033 7.75 - 7.75 100%44.08 - 44.08 100%80% Below 1990 Emissions 2033-2034 7.41 - 7.41 100%42.13 - 42.13 100%
80% Below 1990 Emissions 2034-2035 7.07 - 7.07 100%40.17 - 40.17 100%80% Below 1990 Emissions 2035-2036 6.70 - 6.70 100%38.04 - 38.04 100%
80% Below 1990 Emissions 2036-2037 6.39 - 6.39 100%36.26 - 36.26 100%
Peak Day Demand - Served and Unserved (MDth/d)
Before Resource Additions & Net of DSM Savings
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 248 of 829
APPENDIX 7.2: PEAK DAY DEMAND TABLE
AVERAGE CASE

Scenario Gas Year

LaGrande
Served

LaGrande
Unserved

LaGrande
Total

LaGrande
% of Peak
Day
Served
WA
Served
WA
Unserved WA Total
WA % of
Peak Day
Served
ID
Served
ID
Unserved ID Total
ID % of
Peak Day
Served
Average Case 2017-2018 3.43 - 3.43 100%79.08 - 79.08 100%38.27 - 38.27 100%
Average Case 2018-2019 3.44 - 3.44 100%79.90 - 79.90 100%38.65 - 38.65 100%
Average Case 2019-2020 3.45 - 3.45 100%80.49 - 80.49 100%39.02 - 39.02 100%Average Case 2020-2021 3.46 - 3.46 100%80.94 - 80.94 100%39.33 - 39.33 100%
Average Case 2021-2022 3.45 - 3.45 100%81.32 - 81.32 100%39.57 - 39.57 100%
Average Case 2022-2023 3.46 - 3.46 100%81.53 - 81.53 100%39.73 - 39.73 100%Average Case 2023-2024 3.47 - 3.47 100%82.23 - 82.23 100%40.15 - 40.15 100%
Average Case 2024-2025 3.46 - 3.46 100%82.16 - 82.16 100%40.13 - 40.13 100%
Average Case 2025-2026 3.47 - 3.47 100%82.20 - 82.20 100%40.16 - 40.16 100%
Average Case 2026-2027 3.47 - 3.47 100%82.18 - 82.18 100%40.17 - 40.17 100%Average Case 2027-2028 3.48 - 3.48 100%82.31 - 82.31 100%40.27 - 40.27 100%
Average Case 2028-2029 3.48 - 3.48 100%82.02 - 82.02 100%40.17 - 40.17 100%
Average Case 2029-2030 3.49 - 3.49 100%81.95 - 81.95 100%40.20 - 40.20 100%Average Case 2030-2031 3.49 - 3.49 100%81.90 - 81.90 100%40.26 - 40.26 100%
Average Case 2031-2032 3.50 - 3.50 100%82.21 - 82.21 100%40.53 - 40.53 100%
Average Case 2032-2033 3.49 - 3.49 100%81.95 - 81.95 100%40.52 - 40.52 100%
Average Case 2033-2034 3.50 - 3.50 100%82.05 - 82.05 100%40.72 - 40.72 100%Average Case 2034-2035 3.50 - 3.50 100%82.20 - 82.20 100%40.96 - 40.96 100%
Average Case 2035-2036 3.51 - 3.51 100%82.79 - 82.79 100%41.44 - 41.44 100%
Average Case 2036-2037 3.50 - 3.50 100%82.63 - 82.63 100%41.55 - 41.55 100%
Scenario Gas Year
Klamath
Falls
Served
Klamath
Falls
Unserved
Klamath
Falls
Total
Klamath
Falls % of
Peak Day
Served

Medford/
Roseburg
Served

Medford/
Roseburg
Unserved

Medford/
Roseburg
Total

Medford/
Roseburg
% of Peak
Day
Served
Average Case 2017-2018 6.90 - 6.90 100%34.80 - 34.80 100%
Average Case 2018-2019 6.96 - 6.96 100%35.13 - 35.13 100%Average Case 2019-2020 7.02 - 7.02 100%35.46 - 35.46 100%
Average Case 2020-2021 7.08 - 7.08 100%35.80 - 35.80 100%
Average Case 2021-2022 7.10 - 7.10 100%35.96 - 35.96 100%
Average Case 2022-2023 7.15 - 7.15 100%36.25 - 36.25 100%Average Case 2023-2024 7.21 - 7.21 100%36.55 - 36.55 100%
Average Case 2024-2025 7.26 - 7.26 100%36.79 - 36.79 100%
Average Case 2025-2026 7.31 - 7.31 100%37.06 - 37.06 100%Average Case 2026-2027 7.37 - 7.37 100%37.32 - 37.32 100%
Average Case 2027-2028 7.42 - 7.42 100%37.58 - 37.58 100%
Average Case 2028-2029 7.47 - 7.47 100%37.82 - 37.82 100%
Average Case 2029-2030 7.51 - 7.51 100%38.06 - 38.06 100%Average Case 2030-2031 7.55 - 7.55 100%38.27 - 38.27 100%
Average Case 2031-2032 7.59 - 7.59 100%38.47 - 38.47 100%
Average Case 2032-2033 7.64 - 7.64 100%38.66 - 38.66 100%Average Case 2033-2034 7.68 - 7.68 100%38.84 - 38.84 100%
Average Case 2034-2035 7.72 - 7.72 100%39.02 - 39.02 100%
Average Case 2035-2036 7.77 - 7.77 100%39.19 - 39.19 100%
Average Case 2036-2037 7.81 - 7.81 100%39.35 - 39.35 100%
Peak Day Demand - Served and Unserved (MDth/d)
Before Resource Additions & Net of DSM Savings
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 249 of 829
APPENDIX 7.2: ALTERNATE SUPPLY RESOURCES

Additional Resource Size Availability Notes
Unsubscribed GTN Capacity Up to 50,000 Dth Now Currently available unsubscribed capacity from Kingsgate to
Spokane
Medford Lateral Exp 50,000 Dth / Day 2019 Additional compression to facilitate more gas to flow from
mainline GTN to Medford
WA ID OR
$48 / Dth $40 / Dth $46 / Dth
WA ID OR
$13 / Dth $13 / Dth $13 / Dth
WA ID OR
$11 / Dth $11 / Dth $12 / Dth
WA ID OR
$34 / Dth $39 / Dth $33 / Dth
WA ID OR
$19 / Dth $18 / Dth $19 / Dth
WA ID OR
$38 / Dth $39 / Dth $38 / Dth
Plymouth LNG
241,700 Dth
w/70,500 Dth deliverability 2018
Provides for peaking services and alleviates the need for costly pipeline expansions
Pair with excess pipeline MDDO’s to create firm transport
Hydrogen 166 Dth / Day 2020
Cost estimates obtained from a consultant; levelized cost
includes revenue requirements, expected carbon adder and
assumed retail power rate
Renewable Natural Gas –
Distributed Landfill 635 Dth / Day
NWP Rate
2020
Costs estimates obtained from a consultant for each specific
type of RNG; levelized costs include revenue requirements,
distribution costs, and projected carbon intensity adder/(savings)
2020Renewable Natural Gas – Dairy 635 Dth / Day
Renewable Natural Gas – Waste
Water 513 Dth / Day 2020
2020298 Dth / DayRenewable Natural Gas – Food Waste to (RNG)
Renewable Natural Gas –
Centralized Landfill 1,814 Dth / Day
Cost/Rates
GTN Rate
$35M capital + GTN Rate
2020
Future Supply Resources Size Cost/Rates Availability Notes
Co. Owned LNG
600,000 Dth w/
150,000 of
deliverability
$75 Million plus
$2 Million annual
O&M
2024
On site, in service territory
liquefaction and vaporization
facility
Various pipelines – Pacific
Connector, Cross-Cascades, etc.Varies Precedent
Agreement Rates 2022
Requires additional mainline
capacity on NWPL or GTN to
get to service territory
Large Scale LNG Varies Commodity less
Fuel 2024 Speculative, needs pipeline
transport
In Ground Storage Varies Varies Varies
Requires additional mainline
transport to get to service
territory
Satellite LNG Varies $13M capital cost
plus 665k O&M 2022
provides for peaking services
and alleviates the need for
costly pipeline expansions.
$3,000 per m3 with O&M
assumed at 5.4%.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 250 of 829
APPENDIX 8.1: DISTRIBUTION SYSTEM MODELING

OVERVIEW
The primary goal of distribution system planning is to design for present needs and to plan for future
expansion in order to serve demand growth. This allows Avista to satisfy current demand-serving requirements, while taking steps toward meeting future needs. Distribution system planning identifies
potential problems and areas of the distribution system that require reinforcement. By knowing when and where pressure problems may occur, the necessary reinforcements can be incorporated into normal maintenance. Thus, more costly reactive and emergency solutions can be avoided.

COMPUTER MODELING
When designing new main extensions, computer modeling can help determine the optimum size facilities for present and future needs. Undersized facilities are costly to replace, and oversized facilities incur
unnecessary expenses to Avista and its customers. THEORY AND APPLICATION OF STUDY Natural gas network load studies have evolved in the last decade to become a highly technical and useful means of analyzing the operation of a distribution system. Using a pipeline fluid flow formula, a specified
parameter of each pipe element can be simultaneously solved. Through years of research, pipeline equations have been refined to the point where solutions obtained closely represent actual system
behavior.
Avista conducts network load studies using GL Noble Denton’s Synergi® 4.8.0 software. This computer-
based modeling tool runs on a Windows operating system and allows users to analyze and interpret
solutions graphically.
CREATING A MODEL To properly study the distribution system, all natural gas main information is entered (length, pipe
roughness and size) into the model. "Main" refers to all pipelines supplying services. Nodes are placed at all pipe intersections, beginnings and ends of mains, changes in pipe diameter/material, and to identify all large customers. A model element connects two nodes together.
Therefore, a "to node" and a "from node" will represent an element between those two nodes. Almost all of the elements in a model are pipes.

Regulators are treated like adjustable valves in which the downstream pressure is set to a known value. Although specific regulator types can be entered for realistic behavior, the expected flow passing through
the actual regulator is determined and the modeled regulator is forced to accommodate such flows.
FLUID MECHANICS OF THE MODEL Pipe flow equations are used to determine the relationships between flow, pressure drop, diameter and
pipe length. For all models, the Fundamental Flow equation (FM) is used due to its demonstrated
reliability.
Efficiency factors are used to account for the equivalent resistance of valves, fittings and angle changes
within the distribution system. Starting with a 95 percent factor, the efficiency can be changed to fine tune
the model to match field results.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 251 of 829
Pipe roughness, along with flow conditions, creates a friction factor for all pipes within a system. Thus,
each pipe may have a unique friction factor, minimizing computational errors associated with generalized
friction values.
LOAD DATA All studies are considered steady state; all natural gas entering the distribution system must equal the
natural gas exiting the distribution system at any given time.
Customer loads are obtained from Avista’s customer billing system and converted to an algebraic format
so loads can be generated for various conditions. Customer Management Module (CMM), an add-on application for Synergi, processes customer usage history and generates a base load (non-temperature dependent) and heat load (varying with temperature) for each customer.
In the event of a peak day or an extremely cold weather condition, it is assumed that all curtailable loads
are interrupted. Therefore, the models will be conducted with only core loads.
DETERMINING NATURAL GAS CUSTOMERS’ MAXIMUM HOURLY USAGE
DETERMINING DESIGN PEAK HOURLY LOAD
The design peak hourly load for a customer is estimated by adding the hourly base load and the hourly
heat load for a design temperature. This estimate reflects highest system hourly demands, as shown in Table 1:

This method differs from the approach that is used for IRP peak day load planning. The primary reason for this difference is due to the importance of responding to hourly peaking in the distribution system,
while IRP resource planning focuses on peak day requirements to the city gate.
APPLYING LOADS Having estimated the peak loads for all customers in a particular service area, the model can be loaded. The first step is to assign each load to the respective node or element.
GENERATING LOADS
Temperature-based and non-temperature-based loads are established for each node or element, thus loads
can be varied based on any temperature (HDD). Such a tool is necessary to evaluate the difference in flow
and pressure due to different weather conditions.

GEOGRAPHIC INFORMATION SYSTEM (GIS) Several years ago Avista converted the natural gas facility maps to GIS. While the GIS can provide a variety of map products, the true power lies in the analytical capabilities. A GIS consists of three
components: spatial operations, data association and map representation. A GIS allows analysts to conduct spatial operations (relating a feature or facility to another
geographically). A spatial operation is possible if a facility displayed on a map maintains a relationship to other facilities. Spatial relationships allow analysts to perform a multitude of queries, including:
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 252 of 829

number of customers assigned to particular pipes in Emergency Operating Procedure zones (geographical areas defined to aid in the safe isolation in the event of an emergency)
-pressure pipeline proximity criteria
The second component of the GIS is data association. This allows analysts to model relationships
between facilities displayed on a map to tabular information in a database. Databases store facility information, such as pipe size, pipe material, pressure rating, or related information (e.g., customer
databases, equipment databases and work management systems). Data association allows interactive
queries within a map-like environment.
Finally, the GIS provides a means to create maps of existing facilities in different scales, projections and
displays. In addition, the results of a comparative or spatial analysis can be presented pictorially. This allows users to present complex analyses rapidly and in an easy-to-understand method.

BUILDING SYNERGI® MODELS FROM A GIS
The GIS can provide additional benefits through the ease of creation and maintenance of load studies. Avista can create load studies from the GIS based on tabular data (attributes) installed during the mapping
process.
MAINTENANCE USING A GIS
The GIS helps maintain the existing distribution facility by allowing a design to be initiated on a GIS. Currently, design jobs for the company’s natural gas system are managed through Avista’s Maximo tool.
Once jobs are completed, the as-built information is automatically updated on GIS, eliminating the need
to convert physical maps to a GIS at a later date. Because the facility is updated, load studies can remain current by refreshing the analysis.
DEVELOPING A PRESENT CASE LOAD STUDY
In order for any model to have accuracy, a present case model has to be developed that reflects what the system was doing when downstream pressures and flows are known. To establish the present case,
pressure recording instruments located throughout the distribution system are used.
These field instruments record pressure and temperature throughout the winter season. Various locations
recording simultaneously are used to validate the model. Customer loads on Synergi® are generated to
correspond with actual temperatures recorded on the instruments. An accurate model’s downstream
pressures will match the corresponding field instrument’s pressures. Efficiency factors are adjusted to
further refine the model's pressures and better match the actual conditions.

Since telemetry at the gate stations record hourly flow, temperature and pressure, these values are used to
validate the model. All loads are representative of the average daily temperature and are defined as hourly
flows. If the load generating method is truly accurate, all natural gas entering the actual system (physical) equals total natural gas demand solved by the simulated system (model).
DEVELOPING A PEAK CASE LOAD STUDY
Using the calculated peak loads, a model can be analyzed to identify the behavior during a peak day. The efficiency factors established in the present case are used throughout subsequent models.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 253 of 829
ANALYZING RESULTS
After a model has been balanced, several features within the Synergi® model are used to interpret results. Color plots are generated to depict flow direction, pressure, and pipe diameter with specific break points.
Reinforcements can be identified by visual inspection. When user edits are completed and the model is re-balanced, pressure changes can be visually displayed, helping identify optimum reinforcements.
PLANNING CRITERIA In most instances, models resulting in node pressures below 15 psig indicate a likelihood of distribution
low pressure, and therefore necessitate reinforcements. For most Avista distribution systems, a minimum of 15 psig will ensure deliverability as natural gas exits the distribution mains and travels through service
pipelines to a customer’s meter. Some Avista distribution areas operate at lower pressures and are
assigned a minimum pressure of 5 psig for model results. Given a lower operating pressure, service pipelines in such areas are sized accordingly to maintain reliability.

DETERMINING MAXIMUM CAPACITY FOR A SYSTEM
Using a peak day model, loads can be prorated at intervals until area pressures drop to 15 psig. At that
point, the total amount of natural gas entering the system equals the maximum capacity before new construction is necessary. The difference between natural gas entering the system in this scenario and a
peak day model is the maximum additional capacity that can be added to the system. Since the approximate natural gas usage for the average customer is known, it can be determined how
many new customers can be added to the distribution system before necessitating system reinforcements. The above models and procedures are utilized with new construction proposals or pipe reinforcements to
determine the potential increase in capacity.
FIVE-YEAR FORECASTING
The intent of the load study forecasting is to predict the system’s behavior and reinforcements necessary
within the next five years. Various Avista personnel provide information to determine where and why
certain areas may experience growth.
By combining information from Avista’s demand forecast, IRP planning efforts, regional growth plans and area developments, proposals for pipeline reinforcements and expansions are evaluated with
Synergi®.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 254 of 829
Appendix 8.2

Oregon Public Utility Commission Order No. 16-109 (the Order) included the following
language:

Finally, as part of the IRP-vetting process and subsequent rate proceedings, we expect
that Avista conduct and present comprehensive analyses of its system upgrades. Such
analyses should provide: (1) a comprehensive cost-benefit analysis of whether and when
the investment should be built; (2) evaluation of a range of alternative build dates and
the impact on reliability and customer rates; (3) credible evidence on the likelihood of
disruptions based on historical experience; (4) evidence on the range of possible
reliability incidents; (5) evidence about projected loads and customers in the area; and
(6) adequate consideration of alternatives, including the use of interruptibility or
increased demand-side measures to improve reliability and system resiliency.

In order to address this portion of the Order, Avista has prepared this appendix, which
includes documentation addressing the six points above for each of the natural gas
distribution system enhancements included in the 2018 Natural Gas Integrated Resource
Plan (IRP) for Avista’s Oregon service territory. Each of these three enhancement projects
represents a significant, discrete project which is out of the ordinary course of business (that
is to say, different from ongoing capital investment to address Federal or State regulatory
requirements, relocation of pipe or facilities as requested by others, failed pipe or facilities,
etc., all of which occur routinely over time and which are discussed below).

The routine, ongoing capital investments can be loosely classified in the following categories
(which are not mutually exclusive):

 Safety – Ongoing safety related capital investment includes the repair or replacement
of obsolete or failed pipe and facilities. This category includes, but is not necessarily
limited to, investment to address deteriorated or isolated steel pipe, cathodic
protection, and the replacement of pipeline which has been built over, as well as the
remedy of shallow pipe or the repair or replacement of leaking pipe.
 System Maintenance – Ongoing capital investment related to system maintenance
includes replacement of facilities or pipe that has reached the end of their useful
lives, as well as other general investment required to maintain Avista’s ability to
reliably serve customers.
 Relocation Requested by Others – Ongoing capital investment related to relocation
requested by others falls primarily into two categories, relocation requested by other
parties which is required under the terms of our franchise agreements (such as
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 255 of 829
relocations required to accommodate road or highway construction or relocation),
or relocation requested by customers or others (in which case the customer would
be responsible for the cost of the immediate request, but in which case Avista may
perform additional work, such as the replacement of a steel service with
polyethylene to reduce future maintenance or cathodic protection requirements on
that pipe).
 Mandated System Investment – Ongoing capital investment in this category is driven
by Federal or State regulatory requirements, such as investment that results from
TIMP/DIMP programs, among other programs.
Avista’s Aldyl-A replacement program has been addressed in substantial detail in Oregon
Public Utility Commission Docket UG-246, Avista/500-501.

Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 256 of 829
1 1
2018 Avista Natural Gas IRP
Technical Advisory Committee Meeting
January 25, 2018
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 257 of 829
2 2
Agenda
•Introductions & Logistics
•Safety Moment
•Purpose of IRP and Avista’s IRP Process
•System Wide Peak Day
•Avista’s Demand Overview and 2016 IRP Revisited
•Economic Outlook and Customer Count Forecast
•Demand Forecast Methodology
•Dynamic Demand Forecasting
•Demand Side Management
•Questions/Wrap Up
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 258 of 829
3 3
Safety Moment
Make it Safe, Make it Personal, Make it Home
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 259 of 829
4 4
2018 IRP Timeline
•August 31, 2017 –Work Plan filed with WUTC
•January through May 2018 –Technical Advisory Committee
meetings. Meeting topics will include:
–TAC 1: Thursday, January 25, 2018: TAC meeting expectations, review of
2016 IRP acknowledgement letters, customer forecast, and demand-side
management (DSM) update.
–TAC 2: Thursday, February 22, 2018: Weather analysis, environmental
policies, market dynamics, price forecasts, cost of carbon.
–TAC 3: Thursday, March 29, 2018:Distribution, supply-side resources
overview, overview of the major interstate pipelines, RNG overview and future
potential resources.
–TAC 4: Thursday, May 10, 2018:DSM results, stochastic modeling and
supply-side options, final portfolio results, and 2020 Action Items.
•June 1, 2018 –Draft of IRP document to TAC
•June 29, 2018 –Comments on draft due back to Avista
•July 2018 –TAC final review meeting (if necessary)
•August 31, 2018 –File finalized IRP document
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 260 of 829
5 5
JANUARY FEBRUARY MARCH APRIL
S M T W T F S S M T W T F S S M T W T F S S M T W T F S
31 01 02 03 04 05 06 28 29 30 31 01 02 03 25 26 27 28 01 02 03 01 02 03 04 05 06 07
07 08 09 10 11 12 13 04 05 06 07 08 09 10 04 05 06 07 08 09 10 08 09 10 11 12 13 14
14 15 16 17 18 19 20 11 12 13 14 15 16 17 11 12 13 14 15 16 17 15 16 17 18 19 20 21
21 22 23 24 25 26 27 18 19 20 21 22 23 24 18 19 20 21 22 23 24 22 23 24 25 26 27 28
28 29 30 31 01 02 03 25 26 27 28 01 02 03 25 26 27 28 29 30 31 29 30 01 02 03 04 05
04 05 06 07 08 09 10 04 05 06 07 08 09 10 01 02 03 04 05 06 07 06 07 08 09 10 11 12
MAY JUNE JULY AUGUST
S M T W T F S S M T W T F S S M T W T F S S M T W T F S
29 30 01 02 03 04 05 27 28 29 30 31 01 02 01 02 03 04 05 06 07 29 30 31 01 02 03 04
06 07 08 09 10 11 12 03 04 05 06 07 08 09 08 09 10 11 12 13 14 05 06 07 08 09 10 11
13 14 15 16 17 18 19 10 11 12 13 14 15 16 15 16 17 18 19 20 21 12 13 14 15 16 17 18
20 21 22 23 24 25 26 17 18 19 20 21 22 23 22 23 24 25 26 27 28 19 20 21 22 23 24 25
27 28 29 30 31 01 02 24 25 26 27 28 29 30 29 30 31 01 02 03 04 26 27 28 29 30 31 01
03 04 05 06 07 08 09 01 02 03 04 05 06 07 05 06 07 08 09 10 11 02 03 04 05 06 07 08
IRP Filing Date in ID, OR, WA
Draft IRP sections due to Tom by COB
2018
ETO & AEG DSM Analysis
2018 Avista Scenario Analysis
TAC Meetings
Draft Sent out/due for TAC Members
TAC 5 - if
necessary
IRP Calendar
TAC 1 TAC 2 TAC 3
TAC 4
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 261 of 829
6 6
Purpose of Integrated Resource
Planning
•Comprehensive long-range resource planning tool
•Fully integrates forecasted demand requirements with
potential demand side and supply side resources
•Process determines the least cost, risk adjusted
means for meeting demand requirements for our firm
residential, commercial and industrial customers
•Responsive to Idaho, Oregon and Washington rules
and/or orders
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 262 of 829
7 7
Avista’s IRP Process
•Comprehensive analysis bringing demand forecasting and
existing and potential supply-side and demand-side
resources together into a 20-year, risk adjusted least-cost
plan
•Considers:
–Customer growth and usage
–Weather planning standard
–Demand-side management opportunities
–Existing and potential supply-side resource options
–Risk
–Public participation through Technical Advisory Committee meetings (TAC)
–Distribution upgrades
•2016 IRP filed in all three jurisdictions on
August 31, 2016 and acknowledged Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 263 of 829
8 8
The Natural Gas System
My House
Pipeline
Receipt
Point
Delivery Point/
Gate Station
Storage
Gathering
System
Local
Distribution
System
Producer
Supply
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 264 of 829
9 9
Avista’s Demand Overview and 2016 IRP Re-
Visited
Tom Pardee
Manager of Natural Gas Planning
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 265 of 829
1010
Avista’s Demand Overview
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 266 of 829
1111
–Population of service area 1.5 million
371,000 electric customers
348,000 natural gas customers
•Has one of the smallest carbon
footprints among America’s 100
largest investor-owned utilities
•Committed to environmental
stewardship and efficient use
of resources
Service Territory and Customer Overview
•Serves electric and natural gas customers in eastern Washington and northern Idaho,
and natural gas customers in southern and eastern Oregon
State Total Customers % of Total
Washington 163,000 47%
Oregon 102,000 29%
Idaho 83,000 24%
Total 348,000 100%Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 267 of 829
1212
2017 Customer Make Up and Demand Mix
Res
88.30%
Com
11.67%
Ind
0.03%
Oregon
Customer
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 268 of 829
1313
Seasonal Demand Profiles
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 269 of 829
1414
OR Daily Demand Profiles
-2,000
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
- 10 20 30 40 50 60 70 80 90 100
De
k
a
t
h
e
r
m
s
Roseburg
Daily Demand
*Data is from 2006-2017
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 270 of 829
1515
WA-ID Daily Demand Profiles
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 271 of 829
1616
System Wide Peak Day
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 272 of 829
1717
January 5, 2017
AREA_CODE Min Max Average HDD
Spokane -3 14 6 59
La Grande -9 9 0 65
Klamath Falls -19 8 -6 71
Medford 14 32 23 42
Roseburg 19 35 27 38
Area Coldest in 20 Year
HDD
Coldest on Record
HDD
WA-ID 76 82
Klamath Falls 72 72
La Grande 74 74
Medford 54 61
Roseburg 48 55
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 273 of 829
1818
System Wide Peak Day –1/5/2017
313,000 Dth
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 274 of 829
1919
System Wide Peak Day –1/5/2017 by
class
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 275 of 829
2020
Avista’s 2016 Natural Gas IRP Re-Visited
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 276 of 829
2121 Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 277 of 829
2222 Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 278 of 829
2323 Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 279 of 829
2424 Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 280 of 829
2525 Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 281 of 829
2626 Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 282 of 829
2727 Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 283 of 829
2828
Existing Resources vs. Peak Day Demand
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 284 of 829
2929
Existing Resources vs. Peak Day Demand
Expected Case –Medford/Roseburg
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 285 of 829
3030
Existing Resources vs. Peak Day Demand
Expected Case –Klamath Falls
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 286 of 829
3131
Existing Resources vs. Peak Day Demand
Expected Case –La Grande
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 287 of 829
3232
Our Biggest Risk Last IRP
“Flat Demand” Risk
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 288 of 829
3333
2016 IRP Final
Action Items
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 289 of 829
3434
IPUC
•Staff believes public participation could be further
enhanced through “bill stuffers, public flyers, local media,
individual invitations, and other methods.”
•Result: Avista utilized it’s Regional Business Managers
in addition to digital communications and newsletters in
all states in order to try and gain more public
participation. Previous IRP’s relied on website data and
word of mouth.
–eCommunity newsletter was sent out on January 15, 2018
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 290 of 829
3535
OPUC
•Staff Recommendation No. 1
–Staff recommends in Avista's 2018 IRP that Avista pursue an updated methodology, wherein
the low/high gas price curves continue to be based on low (high) historic prices in a Monte
Carlo setting, but are inflated to match the growth rate (yr/yr) of the expected price curve.
The resulting curves wouid be based on historic prices and also produce symmetric .risk
profiles throughout the time horizon.
•Staff Recommendation No. 2
–Staff recommends that Avista forecast its number of customers using at least two different
methods and to compare the accuracy of the different methods using actual data as a future
task in its next IRP.
–Result: Avista analyzed the data, but there was nothing material discovered the come up with
a meaningful forecast alternative.
•Staff Recommendation No. 3
–Avista's 2018 IRP will contain a dynamic DSM program structure in its analytics.
•In, prior IRPs, it was a deterministic method based on Expected Case assumptions, in
the 2018 IRP, each portion will have the ability to select conservation to meet unserved
customer demand, Avista will explore methods to enable a dynamic analytical process
for the evaluation of conservation potential within individual portfolios and will work with
Energy Trust of Oregon in the development of this process and in producing any final
results for its 2018 IRP for Oregon customers.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 291 of 829
3636
OPUC cont.
•Staff Recommendation No. 4
–Staff recommends that Avista provide Staff and stakeholders with updates
regarding its discussions and analysis regarding possible regional pipeline
projects that may move forward.
•Staff Recommendation No. 5
–Staff recommends that in its 2018 IRP process Avista work with Staff and
stakeholders to establish and complete stochastic analysis that considers a
range of alternative portfolios for comparison and consideration of both cost and
risk.
•Staff Recommendation No. 6
–Environmental Considerations
•1. Carbon Policy including federal and state regulations, specifically those
surrounding the Washington Clean Air Rule and federal Clean Power Plan;
•2. Weather analysis specific to Avista's service territories;
•3. Stochastic Modeling and supply resources; and
•4. Updated DSM methodology including the integration of ETO
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 292 of 829
3737
WUTC
•Include a section that discusses impacts of the Clean Air Rule (CAR).
–In its 2018 IRP expected case, Avista should model specific CAR impacts as well
as consider the costs and risk of additional environmental regulations, including a
possible carbon tax.
•Provide more detail on the company’s natural gas hedging strategy,
including information on upper and lower pricing points, transactions with
counterparties, and how diversification of the portfolio is achieved.
•Ensure that the entity performing the CPA evaluates and includes the
following information:
–All conservation measures excluded from the CPA, including those excluded
prior to technical potential determination
–The rationale for excluding any measure
–A description of Unit Energy Savings (UES) for each measure included in the
CPA, specifying how it was derived and the source of the data
–The rationale for any difference in economic and achievable potential savings,
including how the Company is working towards an achievable target of 85
percent of economic potential savings.
–A description of all efforts to create a fully-balanced cost effectiveness
metric within the planning horizon based on the TRC.Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 293 of 829
3838
WUTC cont.
•Discuss with the TAC:
–The results of Northwest Energy Efficiency Alliance (NEEA)
coordination, including non-energy benefits to include in the CPA.
–The appropriateness of listing and mapping all prospective distribution
system enhancement projects planned on the 20 year horizon, and
comparing actual projects completed to prospective projects listed in
previous IRP’s.
•Provide a rationale for any difference in economic and achievable
potential savings
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 294 of 829
3939
2017 –2018 Avista’s Action Plan
•The price of natural gas has dropped significantly since the 2014 IRP.This is primarily due to the
amount of economically extractable natural gas in shale formations,more efficient drilling
techniques,and warmer than normal weather.Wells have been drilled,but left uncompleted due
to the poor market economics.This is depressing natural gas prices and forcing many oil and
natural gas companies into bankruptcy.Due to historically low prices Avista will research market
opportunities including procuring a derivative based contract,10-year forward strip,and natural
gas reserves.
•Result:After exploring the opportunity of some type of reserves ownership,it was determined the
price as compared to risk of ownership was inappropriate to go forward with at this time.As an
ongoing aspect of managing the business,Avista will continue to look for opportunities to help
stabilize rates and/or reduce risk to our customers.
Monitor actual demand for accelerated growth to address resource deficiencies arising from exposure to “flat
demand”risk.This will include providing Commission Staff with IRP demand forecast-to-actual variance analysis
on customer growth and use-per-customer at least bi-annually.
Result:actual demand was closely tracked and shared with Commissions in semi-annual or quarterly meetings.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 295 of 829
4040
Ongoing Activities
•Continue to monitor supply resource trends including the availability
and price of natural gas to the region, LNG exports, methanol plants,
supply and market dynamics and pipeline and storage infrastructure
availability.
•Monitor availability of resource options and assess new resource
lead-time requirements relative to resource need to preserve
flexibility.
•Meet regularly with Commission Staff to provide information on
market activities and significant changes in assumptions and/or
status of Avista activities related to the IRP or natural gas
procurement practices.
•Appropriate management of existing resources including optimizing
underutilized resources to help reduce costs to customers.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 296 of 829
4141
Avista Natural Gas Forecasting
Grant D. Forsyth, Ph.D.
Chief Economist
[e-mail]
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 297 of 829
4242
Load Forecasts-Two Step Process
•First, forecast customers (C) by month by schedule (s) by
residential (r), commercial (c), industrial (i)—for example, Ct,y,s.r
•Forecast use per customer (U) by month by schedule by
class—for example, Ut,y,s.r
•Load forecast (L) is the product of the two:
Lt,y,s.r = Ct,y,s.r X Ut,y,s.r
For weather sensitive schedules a
20-yr MA defines normal weather.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 298 of 829
4343
The Basic Forecast Approach
Population Growth
Forecast
Residential Customer
Forecast ARIMA Model
Commercial Customer
ARIMA Forecast Model
Vary Population Growth
Assumptions
Firm Residential and
Commercial Firm Industrial
No Drivers
Forecast of no Significant
Growth
Vary “No Growth”
Assumption*
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 299 of 829
4444
System Industrial Customers, 2004-2017
No real change since January 2007
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 300 of 829
4545
Getting to Population as a Driver, 2018-2023 & 2024-2037
Average GDP Growth
Forecasts:
•IMF, FOMC,
Bloomberg, etc.
•Average forecasts
out 6-yrs.
Non-farm Employment
Growth Model:
•Model links year y, y-1, and
y-2 GDP growth to year y
regional employment
growth.
•Forecast out 6-yrs.
•Averaged with GI forecasts.
Regional Population Growth Models:
•Model links regional, U.S., and CA
year y-1 employment growth to year y
county population growth.
•Forecast out 6-yrs for Spokane, WA;
Kootenai, ID; and Jackson, OR.
•Averaged with IHS forecasts.
•Growth rates used to generate
population forecasts for customer
forecasts for residential schedules 101
and 410.
EMPGDP
2018-2023 For Spokane, WA; Kootenai,
ID, and Jackson, OR counties
OR Union, Klamath, and Douglas counties: IHS population growth forecasts for 2018-2037
Kootenai and Jackson: IHS population growth forecasts for 2024-2037
Spokane: OFM population growth forecasts for 2024-2037
Interpolation assumes: PN = P0erN
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 301 of 829
4646
The Relationship Between Classes
Customers Residential Commercial Industrial Load Residential Commercial Industrial
Residential 1.00 Residential 1.00
Commercial 0.80 1.00 Commercial 0.94 1.00
Industrial -0.38 -0.23 1.00 Industrial 0.21 0.24 1.00
Year-over-year Growth, Gas Correlations by Class, Jan. 2005-Jan 2016
Residential customer growth is approximately equal
to population growth in the long-run.
Commercial customer growth is highly correlated
with residential growth in the long-run.
Industrial’s correlation to residential is lower and
negative. Customer numbers stable or slightly
declining.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 302 of 829
4747
WA-ID Region Firm Customers: 2018 IRP and 2016 IRP
220,000
230,000
240,000
250,000
260,000
270,000
280,000
290,000
300,000
310,000
320,000
20
1
8
20
1
9
20
2
0
20
2
1
20
2
2
20
2
3
20
2
4
20
2
5
20
2
6
20
2
7
20
2
8
20
2
9
20
3
0
20
3
1
20
3
2
20
3
3
20
3
4
20
3
5
20
3
6
20
3
7
WA-ID Base 2016 WA-ID Base 2018
IRP Avg.Annual Growth
2018-2037
2016 1.1%
2018 1.3%
≈ +16,500
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 303 of 829
4848
95,000
100,000
105,000
110,000
115,000
120,000
125,000
130,000
20
1
8
20
1
9
20
2
0
20
2
1
20
2
2
20
2
3
20
2
4
20
2
5
20
2
6
20
2
7
20
2
8
20
2
9
20
3
0
20
3
1
20
3
2
20
3
3
20
3
4
20
3
5
20
3
6
20
3
7
OR Base 2016 OR Base 2018
OR Region Firm Customers: 2018 IRP and 2016 IRP
IRP Avg.Annual Growth
2018-2037
2016 1.1%
2018 0.9%
≈ -4,700
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 304 of 829
4949
Medford, OR Region Firm Customers: 2018 IRP and
2016 IRP
55,000
60,000
65,000
70,000
75,000
80,000
20
1
8
20
1
9
20
2
0
20
2
1
20
2
2
20
2
3
20
2
4
20
2
5
20
2
6
20
2
7
20
2
8
20
2
9
20
3
0
20
3
1
20
3
2
20
3
3
20
3
4
20
3
5
20
3
6
20
3
7
Medford Base 2016 Medford Base 2018
IRP Avg.Annual Growth
2018-2037
2016 1.2%
2018 1.0%
≈ -3,800
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 305 of 829
5050
Roseburg, OR Region Firm Customers: 2018 IRP and
2016 IRP
14,000
15,000
16,000
17,000
18,000
19,000
20,000
20
1
8
20
1
9
20
2
0
20
2
1
20
2
2
20
2
3
20
2
4
20
2
5
20
2
6
20
2
7
20
2
8
20
2
9
20
3
0
20
3
1
20
3
2
20
3
3
20
3
4
20
3
5
20
3
6
20
3
7
Roseburg Base 2016 Roseburg Base 2018
IRP Avg.Annual Growth
2018-2037
2016 0.9%
2018 1.0%
≈ -60
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 306 of 829
5151
Klamath, OR Region Firm Customers: 2018 IRP and
2016 IRP
IRP Avg.Annual Growth
2018-2037
2016 1.2%
2018 1.0%
≈ -790
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 307 of 829
5252
La Grande, OR Region Firm Customers: 2018 IRP and
2016 IRP
7,400
7,600
7,800
8,000
8,200
8,400
8,600
20
1
8
20
1
9
20
2
0
20
2
1
20
2
2
20
2
3
20
2
4
20
2
5
20
2
6
20
2
7
20
2
8
20
2
9
20
3
0
20
3
1
20
3
2
20
3
3
20
3
4
20
3
5
20
3
6
20
3
7
La Grande Base 2016 La Grande Base 2018
IRP Avg.Annual Growth
2018-2037
2016 0.5%
2018 0.5%
≈ -50
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 308 of 829
5353
System Firm Customers: 2018 IRP and 2016 IRP
320,000
340,000
360,000
380,000
400,000
420,000
440,000
20
1
8
20
1
9
20
2
0
20
2
1
20
2
2
20
2
3
20
2
4
20
2
5
20
2
6
20
2
7
20
2
8
20
2
9
20
3
0
20
3
1
20
3
2
20
3
3
20
3
4
20
3
5
20
3
6
20
3
7
WA-ID-OR Base 2016 WA-ID-OR Base 2018
IRP Avg.Annual Growth
2018-2037
2016 1.1%
2018 1.2%
≈ +11,900
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 309 of 829
5454
WA-ID Region Firm Customer Range, 2018-2037
Variable Low
Growth
Base
Growth
High
Growth
WA-ID Customers 0.9%1.3%1.6%
WA Population 0.5%0.8%1.1%
ID Population 1.1%1.6%2.1%
WA-ID Population 0.6%0.9%1.3%
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 310 of 829
5555
OR Region Firm Customer Range, 2018-2037
95,000
100,000
105,000
110,000
115,000
120,000
125,000
130,000
135,000
20
1
8
20
1
9
20
2
0
20
2
1
20
2
2
20
2
3
20
2
4
20
2
5
20
2
6
20
2
7
20
2
8
20
2
9
20
3
0
20
3
1
20
3
2
20
3
3
20
3
4
20
3
5
20
3
6
20
3
7
ORFIRMCUS Base ORFIRMCUS High ORFIRMCUS Low
Variable Low
Growth
Base
Growth
High
Growth
Customers 0.6%0.9%1.3%
Population 0.5%0.8%1.1%
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 311 of 829
5656
System Firm Customer Range, 2018-2037
Variable Low
Growth
Base
Growth
High
Growth
Customers 0.8%1.2%1.5%
Population 0.5%0.9%1.2%
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 312 of 829
5757
Summary of Growth Rates
System Base-Case High Low
Residential 1.2%1.6%0.9%
Commercial 0.7%1.0%0.3%
Industrial -0.3%2.2%-3.3%
Total 1.2%1.5%0.8%
WA Base-Case High Low
Residential 1.2%1.5%0.9%
Commercial 0.7%1.0%0.4%
Industrial -0.8%1.9%-3.1%
Total 1.2%1.5%0.8%
ID Base-Case High Low
Residential 1.5%2.0%1.0%
Commercial 0.6%1.1%0.1%
Industrial 0.1%1.7%-2.7%
Total 1.4%1.9%0.9%
OR Base-Case High Low
Residential 1.0%1.3%0.6%
Commercial 0.7%1.1%0.4%
Industrial 0.1%4.7%-7.8%
Total 0.9%1.3%0.6%
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 313 of 829
5858
Forecasting with Permits or Housing Starts
•Potential data sources have poor coverage in our service territory or series
are not long enough. This is especially a problem for non-MSA areas like
Roseburg, Klamath, and La Grande.
•IHS has annual and quarterly housing start data only for MSAs. IHS’s MSA
housing starts are estimates:
“We then use the permits-to-starts ratio for the national and regional level from the Census that is
released every year to derive the starts.Unfortunately, until recently, the census only has these
ratios at the national and regional level. As a consequence, we use this ratio for any county, metro
and state within the region to derive our starts from.”
•Prior use of IHS housing start forecasts resulted in significant over
forecasting of customers.
•NAHB also produces a housing start series, but their data only covers fairly
large MSAs.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 314 of 829
5959
Estimating the IMPACT of LEAP in WA: Residential
Customers
WA IRP Residential
Change by 2037
2018 IRP with LEAP Less 2016 IRP +11,300
2018 IRP w/o LEAP Less 2016 IRP +2,200
LEAP Contribution +9,100
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 315 of 829
6060
Estimating the IMPACT of LEAP in WA: Residential
Growth Rates
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 316 of 829
6161
Demand Forecast Methodology
Tom Pardee
Manager of Natural Gas Planning
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 317 of 829
6262
(CDD)
(HDD)
Temp
(℉)
Degree
Days
100 =35
90 =25
80 =15
70 =5
65 =0
60 =5
50 =15
40 =25
30 =35
20 =45
10 =55
0 =65
-10 =75
-20 =85
Temperature & Degree Days
Cooling
Degree Days
Heating
Degree Days
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 318 of 829
6363
Natural Gas Demand Forecasting
Financial
Planning and
Analysis
Resource
Accounting Gas Supply Rates Regulatory
Staff
Industry
Stakeholders
Average
Demand
Procurement
Planning
PGA Corporate
Budget
IRP
Peak Day
Planning
IRP
Scenario
Analysis
Other
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 319 of 829
6464
Weather
•NOAA 20 year actual average daily HDD’s (1998-
2017)
•Peak weather includes two winter storms (5 day
duration), one in December and one in February
•Planning Standard –coldest day on record
•Sensitivity around planning standard including
–Normal/Average
–Coldest in 20 years
–Monte Carlo simulation
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 320 of 829
6565
The Use per Customer Forecast cont.
•Historical data is used to determine initial base and heat
coefficients.
•Adjustments are made to incorporate DSM and price
elastic responses.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 321 of 829
6666
Residential –UPC and Weather
97% Correlated 65% Correlated
71% Correlated
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 322 of 829
6767
Residential –UPC and Weather
71% Correlated
83% Correlated
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 323 of 829
6868
Base Coefficients
July and August Average Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 324 of 829
6969
Demand Modeling Equation –a closer look
SENDOUT® requires inputs expressed in the below format to
compute daily demand in dekatherms. The base and weather
sensitive usage (degree-day usage) factors are developed
outside the model and capture a variety of demand usage
assumptions.
# of customers x Daily weather sensitive usage / customer
# of customers x Daily base usage / customer
Plus
Table 3.2 Basic Demand Formula
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 325 of 829
7070
1.Expected customer count forecast by each of the 5 areas
2.Use per customer coefficients –Flat all classes,5 year, 3 year or last year
average use per HDD per customer
3.Weather planning standard –coldest day on record
WA/ID 82; Medford 61; Roseburg 55; Klamath 72; La Grande 74
Developing a Reference Case
Customer
count
forecast
Use per
customer
coefficients
Weather Reference
Case Demand
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 326 of 829
7171
Dynamic Demand Methodology
Tom Pardee
Manager of Natural Gas Planning
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 327 of 829
7272
Dynamic Demand Methodology
Demand Influencing
–Conditions that DIRECTLY
affect core customer
volume consumed
Price Influencing
–PRICE SENSITIVE
conditions that, through price
elasticity, INDIRECTLY affect
core customer volume
consumed
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 328 of 829
7373
Demand
Customer Growth
•New Construction
•Conversion/Direct Use
•Economy
Customer Mix Shifts
•Res/Com/Ind
•Core vs. Transport
•Interruptible
Weather
•Normal
•Planning Standard
•Other
Technology
•Increased
efficiency/DSM
•New Uses
•Demand Response
3rd Party Demand
Trends
•Thermal Generation
•Non-Core Customer
•LNG Exports Supply Trends
•Conventional vs.
Unconventional
•Canadian Imports
•LNG
Pipeline Trends
•Regional Pipeline
Projects
•National Pipeline
Projects
•International Pipeline
Projects
Other
•Storage
•Climate Change
Legislation
•Energy Correlations
(i.e. oil and gas)
Demand Drivers
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 329 of 829
7474
Customer Growth and Mix –Demand
Influencing
•Key driver in demand growth
•Can change the timing and/or location of resource
needs
•Currently we model expected, high, and low growth
scenarios
•New construction vs. conversions
•Residential/Commercial/Industrial vs. Transportation
•New uses –CNG/NGV
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 330 of 829
7575
Weather Standard –Demand Influencing
•Has the potential to significantly change timing of
resource needs
•Significant qualitative considerations
–No infrastructure response time if standard
exceeded
–Significant safety and property damage risks
•Current Peak HDD Planning Standards
–WA/ID 82
–Medford 61
–Roseburg 55
–Klamath 72
–La Grande 74
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 331 of 829
7676
Technology –Demand Influencing
•Demand side management initiatives will reduce
demand HOWEVER, it is dependent upon customers
willingness/ability to participate.
•Development of new uses for natural gas
•CNG
•NGV
•LNG
•???NG
•Demand response (Smart Grid)
•New technologies in Demand Side Management
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 332 of 829
7777
Price Elasticity Factors Defined
•Price elasticity is usually expressed as a numerical factor
that defines the relationship of a consumer’s consumption
change in response to price change.
•Typically, the factor is a negative number as consumers
normally reduce their consumption in response to higher
prices or will increase their consumption in response to
lower prices.
•For example, a price elasticity factor of -0.13 means:
–A 10% price increase will prompt a 1.3% consumption
decrease
–A 10% price decrease will prompt a 1.3%
consumption increase Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 333 of 829
7878
Price Elasticity
•Establishes factors for use in other price influencing
scenarios
•Very complex relationship –we use historical data
however……
•Historical data has DSM, rate changes (PGA,
general rate, etc.), economic conditions,
technological changes, etc.
•History is not necessarily the best predictor of future
behavior
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 334 of 829
7979
Price Elasticity Assumptions
From 2018 IRP
Elasticity
Assumption
Real Price annual increase
within 30%
High Negative .20
Expected Negative .10
Low No response
Expected Elasticity is derived from Medford and
Roseburg and applied to all areas
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 335 of 829
8080
3rd Party Demand Trends –Price Influencing
•Gas fired generation
•Coal plant retirements driving gas for power
•CNG/NGV Transportation Fleets
•Export LNG
•Non-firm customer trends
•Mexico Exports
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 336 of 829
8181
Supply Trends –Price Influencing
•Shale is Everywhere
•LNG Export
•Associated gas from Oil –
25% of overall US
production
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 337 of 829
8282
Pipeline Trends –Price Influencing
•Regional Pipeline Proposals
•Sumas Express
•Pacific Connector –from Jordan
Cove LNG
•Trail West/N-Max (GTN to NWP –
Molalla area)
•National Pipeline Proposals
•International Pipeline Proposals
•T-South Looping
•NGTL Westpath Expansion
•Southern Crossing Expansion
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 338 of 829
8383
Other Supply Issues –Price Influencing
•Storage
•Climate Change and Carbon Legislation
•Energy Correlations
•Extraction cost
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 339 of 829
8484
Demand and
Supply Side
Sensitivities
Optimize
Resource
Portfolio
Stochastic
Cost/Risk Analysis
Prices and
Weather
Highest
Performing
Portfolios
selection
Preferred
Portfolio
selection
Core Cases Price Forecast
Sensitivities, Scenarios, Portfolios
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 340 of 829
8585
Sensitivities for 2018 IRP
Reference
Reference Plus
Peak Low Cust High Cust
No Conversion
to natural gas Alternate DSM Peak plus DSM Demand Desctruction Demand Destruction Alternate Historical Expected Low High Carbon
Case Case Growth Growth Growth Weather Std Case Case Reference Case Reference Plus Peak UPC Case Elasticity Prices Prices Legislation
Customer Growth Rate Reference Reference Plus Low Growth High Growth
Reference minus
LEAP Reference Reference Reference Reference Reference Reference Reference Reference Reference Reference
Use per Customer 3 Year Historical 3 Year Historical 3 Year
Historical
3 Year
Historical
3 Year Historical 3 Year
Historical
3 Year
Historical
3 Year Historical 3 Year Historical less
demand destruction
3 Year Historical less
demand destruction
5 Year Historical 3 Year
Historical
3 Year
Historical
3 Year
Historical
3 Year Historical
Weather
Planning Standard 20 Year Normal Coldest on Record
Coldest on
Record
Coldest on
Record Coldest on Record
Coldest in
20yrs Normal
Coldest on
Record Normal Coldest on Record Coldest on Record
Coldest on
Record
Coldest on
Record
Coldest on
Record Coldest on Record
Demand Side Management
Programs Included No No No No No No Expected Expected No No No No No No No
Prices
Price curve Expected Expected Expected Expected Expected Expected Expected Expected Expected Expected Expected Expected Low High High/Medium/Low
Price curve adder ($/Dth)None None None None None None None None None None None High/Medium/Low
Elasticity None None None None None None None None None None None Expected Expected Expected Expected
DEMAND INFLUENCING - DIRECT PRICE INFLUENCING - INDIRECT
INPUT ASSUMPTIONS
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 341 of 829
8686
2018 Natural Gas IRP
DSM -Energy Efficiency
Amber Gifford & Ryan Finesilver
First Technical Advisory Committee Meeting
January 25, 2018
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 342 of 829
8787
Demand Side Management (DSM)
The process of helping customers use energy more
efficiently.
The term DSM is used interchangeably with Energy
Efficiency and Conservation.
DSM Programs benefit the IRP by contributing to the
deferral of plant assets.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 343 of 829
8888
Team Roles
DSM Planning
& Analytics
Team
Applied Energy
Group (AEG)Gas Supply
Oregon DSM Programs
ACP CPA IRP
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 344 of 829
8989
Who DSM Serves
•Washington
•Idaho
•Oregon (ETO except
for Low-Income)
Three
Jurisdictions
•Residential
•Industrial/Commercial
•Low-Income
Residential
Multiple
Customer
Segments
•Aids in reducing
overall capacity
•Defers capital
investments
The
Company’s
Infrastructure
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 345 of 829
9090
DSM Funding –Natural Gas
$8.5 Million
Annual
Funding
(2017)
Tariff percentage of customer bill by state:
2.1%
3.7%
3%
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 346 of 829
9191
WA Gas Targets to Actual Savings
2014 2015 2016 2017 2018
Business Plan Target 637,042 602,010 567,653 620,310 719,451
IRP Target 1,310,000 1,287,000 737,000 489,110 612,830
Actual 615,418 919,892 548,756 889,776
0
200,000
400,000
600,000
800,000
1,000,000
1,200,000
1,400,000
Th
e
r
m

S
a
v
i
n
g
s
Business Plan Target IRP Target Actual
Figures exclude the negative impact to therm
savings due to fuel conversions.
2014 & 2015 target variance due to commodity
price decrease. Cost-effectiveness shift to UCT.
2015 large increase in actuals is due to multiple
large non-res projects coming to completion.
2017 Actuals are Unverified
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 347 of 829
9292
2014 2015 2016 2017 2018
Business Plan Target 0 0 232,737 219,272 252,712
IRP Target 456,000 228,000 114,000 197,640 246,440
Actual 0 0 189,295 245,747
0
50,000
100,000
150,000
200,000
250,000
300,000
350,000
400,000
450,000
500,000
Th
e
r
m

S
a
v
i
n
g
s
Business Plan Target IRP Target Actual
No Gas Programs in 2014 or 2015
2017 Actuals are Unverified
2018 Business Plan -DRAFT
*Figures exclude the negative impact to
therm savings due to fuel conversions.
No

G
a
s

P
r
o
g
r
a
m
s
No

G
a
s

P
r
o
g
r
a
m
s
ID Gas Targets to Actual Savings
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 348 of 829
9393
DSM Business Planning
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 349 of 829
9494
Conservation Potential Assessment
(CPA)
•Primary Objectives
–Meet legislative and regulatory requirements
–Support integrated resource planning
–Identify opportunities for savings; key measures in
target segments
•Key Deliverables
–20-year conservation potential
–Individual measures
–IRP target
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 350 of 829
9595
Conservation Potential Assessment
•Theoretical upper limit of conservation
•All efficiency measures are phased in regardless of cost
Technical
Potential
•Realistically achievable, accounting for adoption rates
and how quickly programs can be implemented
•Does not consider cost-effectiveness of measures
Achievable
Technical
Potential
•Includes economic screening of measures (cost
effectiveness)
•Informs our IRP Target
Achievable
Potential
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 351 of 829
9696
Business Planning Process
Business
Planning
Annual
Conservation
Plan
EM&V
Annual
Conservation
Report
Conservation
Potential
Assessment
Adaptive
Management
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 352 of 829
9797
Business Planning Process
CPA
•Sets overall
Savings Goal
•Identifies
Measures
Avista Programs
•Consult with
our existing
programs
•Add new
measures to
existing
programs
Update and
Evaluate
•Update
existing
savings
values
•Test for Cost-
Effectiveness
(UCT)
Feedback and
Modify
•DSM
Program
Managers
•Engineers
•Industry
Trends
•Other Parties
Energy Efficiency Advisory Group
Business Planning Process
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 353 of 829
9898
Incentive Setting
Decide Incentive Level
$3 per
Therm
70% of
CIC
UCT
Impact
Portfolio
Alignment
Cost-Effective Test
Utility Cost Test (UCT)Must have a UCT of 1.0
or Higher
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 354 of 829
9999
Significant Costs and Benefits
From Cost-effectiveness training (3/6/15) Powerpoint
http://www.cpuc.ca.gov/General.aspx?id=5267
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 355 of 829
100100
Questions?
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 356 of 829
101101
2018 IRP Timeline
•August 31, 2017 –Work Plan filed with WUTC
•January through May 2018 –Technical Advisory Committee
meetings. Meeting topics will include:
–TAC 1: Thursday, January 25, 2018: TAC meeting expectations, review of
2016 IRP acknowledgement letters, customer forecast, and demand-side
management (DSM) update.
–TAC 2: Thursday, February 22, 2018: Weather analysis, environmental
policies, market dynamics, price forecasts, cost of carbon.
–TAC 3: Thursday, March 29, 2018 :Distribution, supply-side resources
overview, overview of the major interstate pipelines, RNG overview and future
potential resources.
–TAC 4: Thursday, May 10, 2018:DSM results, stochastic modeling and
supply-side options, final portfolio results, and 2020 Action Items.
•June 1, 2018 –Draft of IRP document to TAC
•June 29, 2018 –Comments on draft due back to Avista
•July 2018 –TAC final review meeting (if necessary)
•August 31, 2018 –File finalized IRP document
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 357 of 829
1
2018 Avista Natural Gas IRP
Technical Advisory Committee Meeting
February 22, 2018
Spokane, WA
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 358 of 829
22
Agenda
2
Time Length Topic
9:30 AM 10 minutes Introductions & Logistics
9:40 AM 10 minutes Safety Moment
9:50 AM 30 minutes Weather Analysis
10:20 AM 60 minutes Market dynamics
11:20 AM 10 minutes break
11:30 AM 30 minutes Procurement Planning
12:00 PM 60 minutes Lunch
1:00 PM 30 minutes Emissions and Clean Air Rule
1:30 PM 30 minutes Carbon policies
2:00 PM 45 minutes Price forecasts and Carbon Adders
2:45 PM 15 minutes wrap-up
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 359 of 829
33
2018 IRP Timeline
•August 31, 2017 –Work Plan filed with WUTC
•January through May 2018 –Technical Advisory Committee
meetings. Meeting topics will include:
–TAC 1: Thursday, January 25, 2018: TAC meeting expectations, review of
2016 IRP acknowledgement letters, customer forecast, and demand-side
management (DSM) update.
–TAC 2: Thursday, February 22, 2018: Weather analysis, environmental
policies, market dynamics, price forecasts, cost of carbon.
–TAC 3: Thursday, March 29, 2018 :Distribution, supply-side resources
overview, overview of the major interstate pipelines, RNG overview and future
potential resources.
–TAC 4: Thursday, May 10, 2018:DSM results, stochastic modeling and
supply-side options, final portfolio results, and 2020 Action Items.
•June 1, 2018 –Draft of IRP document to TAC
•June 29, 2018 –Comments on draft due back to Avista
•July 2018 –TAC final review meeting (if necessary)
•August 31, 2018 –File finalized IRP document
3
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 360 of 829
44
Safety Moment
•Cold Weather Slips
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 361 of 829
5
Weather Analysis
Kaylene Schultz
5
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 362 of 829
6
Coldest on Record Dates
WA/ID –December 30, 1968
Medford –December 9, 1972
Roseburg –December 22, 1990
Klamath Falls –December 8, 2013
La Grande –December 23,1983
Area Coldest in 20 Year
HDD
Coldest on Record
HDD
WA-ID 76 82
Klamath Falls 72 72
La Grande 74 74
Medford 54 61
Roseburg 48 55
Planning Standard Assumptions
6
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 363 of 829
7 *1947 -2017
Spokane
7
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 364 of 829
8
Medford
*1928 -20178
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 365 of 829
9
La Grande
*1949 -20179
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 366 of 829
10
Klamath Falls
HDD's
Min 5,334
Max 7,548
Avg. 6,584
Stdev 426
2017 6,760
*1928 -201710
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 367 of 829
11
Roseburg
*1931 -201711
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 368 of 829
1212
Temperature Anomaly Distribution
Source: Hansen, J., R. Ruedy, M. Sato, and K. Lo (2010), Global surface temperature change, Rev. Geophys., 48, RG4004,
doi:10.1029/2010RG000345. This research has been updated and can be found at http://www.giss.nasa.gov/research/briefs/hansen_17/.
Temperature anomaly distribution:The frequency of occurrence (vertical axis)of local
temperature anomalies (relative to 1951-1980 mean)in units of local standard deviation
(horizontal axis).Area under each curve is unity.Image credit:NASA/GISS.
NASA Temperature Anomaly Distribution for Northern Hemisphere
Normal Distribution: Base Reference Period 1951-1980
12
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 369 of 829
1313
Spokane
13
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 370 of 829
1414
Medford
14
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 371 of 829
1515
La Grande
15
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 372 of 829
1616
Klamath Falls
16
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 373 of 829
1717
Roseburg
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 374 of 829
18
Market Dynamics
Tom Pardee
Manager of Natural Gas Planning
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 375 of 829
19
Assumptions about the size of U.S. resources and the
improvement in technology affect domestic oil and natural
gas prices—
0
50
100
150
200
250
2010 2030 2050
North Sea Brent oil price
2017 dollars per barrel
2017
history projections
0
1
2
3
4
5
6
7
8
9
10
2010 2030 2050
Henry Hub natural gas price
2017 dollars per million Btu
2017
history projections Low Oil and Gas
Resource and
Technology
High Oil Price
Reference
Low Oil Price
High Oil and Gas
Resource and
Technology
Source: EIA AEO 201819
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 376 of 829
20
$0.00
$1.00
$2.00
$3.00
$4.00
$5.00
$6.00
$7.00
$8.00
$9.00
$10.00
2005 2007 2009 2011 2013 2015 2017 2019 2021 2023 2025 2027 2029 2031 2033 2035 2037 2039
$
/

D
t
h
Henry Hub Forecast
(Nominal $)
Historic Consultant 1
Nominal Henry Hub
Consultant 2
Nominal Henry Hub
Forwards EIA 2018 AEO
Forecast
20
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 377 of 829
212121
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 378 of 829
2222
US Storage
22
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 379 of 829
232323
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 380 of 829
24
Industrial and electric power demand drives natural gas
consumption growth—
0
20
40
60
80
100
0
5
10
15
20
25
30
35
40
2000 2010 2020 2030 2040 2050
Natural gas consumption by sector
trillion cubic feet
electric power
industrial
transportation
commercial
residential
billion cubic feet per day2017
history projections
Source: EIA AEO 201824
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 381 of 829
25
The United States is a net natural gas exporter in the
Reference case because of near-term export growth and
continued import decline —
-14
-7
0
7
14
21
28
-5
0
5
10
2000 2010 2020 2030 2040 2050
Natural gas trade
trillion cubic feet
2017
history projections liquefied
natural gas
(LNG)
Mexico
(pipeline)
Canada
(pipeline)
Canada
(pipeline)
LNG
billion cubic feet per day
exports
imports
Source: EIA AEO 201825
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 382 of 829
2626
Exports
26
Reference Case: 23 Bcf per day by 2050
Driven by LNG and Mexico Exports
Source: EIA AEO 2018
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 383 of 829
2727
Mexico Exports
3.77 Bcf/d average
27
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 384 of 829
2828
US LNG Projects
28 https://www.ferc.gov/industries/gas/indus-act/lng/lng-existing.pdf
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 385 of 829
292929
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 386 of 829
30
What Drives the Natural Gas Market?
Natural Gas Spot Prices (Henry Hub)
Supply
–Type: Conventional vs. Non-conventional
–Location
–Cost
Demand
–Residential/Commercial/I
ndustrial
–Power Generation
–Natural Gas Vehicles
Legislation
–Environmental
Energy Correlations
–Oil vs. Gas
–Coal vs. Gas
–Natural Gas Liquids
Weather
Storage
30
$0.00
$2.00
$4.00
$6.00
$8.00
$10.00
$12.00
$14.00
$16.00
$18.00
$20.00
$/Dth Historic Henry Hub Cash Prices
Winter Weather Event
???
Hurricanes
Rita and
Katrina
Polar Vortex
East Coast
Winter
Weather
Event
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 387 of 829
31
Short Term Market Perspective
31
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 388 of 829
3232
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 389 of 829
3333
TransCanada System
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 390 of 829
34
•AECO –Empress
•Capacity through this corridor has been reduced over the years as
production has moved north and west, reducing pressure
•Newly contracted mainline firm contracts have used up
uncontracted capacity
•Storage owners (mainly between AECO and Empress) rely on IT
to inject/withdraw
•James River –ABC
•TransCanada has upgraded the capacity of the gathering system
north of James river.
•Capacity for JR-ABC remains limited to 2.3 bcf/d while GTN has
room for up to 2.9 bdf/d.
34
Sources of Congestion
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 391 of 829
35
•Demand:
•Incremental expansions in 2018, 2019 and 2020 will increase
James River –ABC capacity by roughly 700 mmcf/d to match
GTN takeaway capacity.
•Oil sands expansion expected to increase demand as several
new projects come on line in 2018.
•Talk of AECO –Empress expansion. Thus far no action.
•Supply:
•Sustained low prices have already led to a decrease in producer
CAPEX budgets for 2018 and 2019.
35
How will Alberta supply/demand rebalance?
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 392 of 829
36
Canadian Supply
Source: https://www.neb-one.gc.ca/nrg/ntgrtd/mrkt/snpsht/2018/02-02rssrrd-eng.html36
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 393 of 829
37
Natural Gas Rig Count
181 Active Rigs
37
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 394 of 829
38
Rig Type
Source: http://www.uncoverenergy.com/the-will-to-drill/38
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 395 of 829
39
US drilling
*Appalachia Production per rig increase
of almost 3500%per rig since Jan. 2007
7 Major drilling regions in US
Source: https://www.eia.gov/petroleum/drilling39
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 396 of 829
40
Rig efficiency and production
Source: https://www.eia.gov/petroleum/drilling40
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 397 of 829
41
*Almost 29 Bcf/d waiting to come online
Source: https://www.eia.gov/petroleum/drilling/xls/duc-data.xlsx
*Bcf per day estimate is from estimated production per well as of Dec ‘1741
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 398 of 829
42
Break (10 minutes)
42
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 399 of 829
43
Procurement Planning
Tom Pardee, Manager of Natural Gas Planning
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 400 of 829
4444
Procurement Plan Philosophy
•Mission
•To provide a diversified portfolio of reliable
supply and a level of price certainty in volatile
markets.
•We cannot accurately predict what natural gas prices will do, however we
can use experience, market intelligence, and fundamental market analysis to
structure and guide our procurement strategies.
•Our goal is to develop a plan that utilizes customer resources (storage and
transportation), layers in pricing over time for stability (time averaging),
allows discretion to take advantage of pricing opportunities should they arise,
and appropriately manages risk.
44
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 401 of 829
4545
Oversight and Control
Risk Management
Committee
•Comprised of Executive Officers
& Sr. Management
•Responsible for the Risk
Management Policy
•Provides oversight and guidance
on natural gas procurement
plan
Strategic
Oversight
Group
•Cross functional group
consisting of:
•Credit, Electric/Gas Supply,
Rates, Resource
Accounting, Risk
•Co-develops the
Procurement Plan
•Meets regularly
Natural Gas
Supply
•Monitors and manages the
Procurement Plan on a daily
basis
•Leads in the annual
Procurement Plan review
and modification
Commission
Update
•Semi-Annual Update
•New Procurement Plan is
communicated semi-
annually in the fall and
spring
•Intra-year changes
communicated to staff on an
ad-hoc basis
•
45
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 402 of 829
46
Review conducted with SOG includes:
•Mission statement and approach
•Current and future market dynamics
•Hedge type and percentage
•Resources available (i.e. storage and
transportation)
•Hedge windows (how many, how long)
•Long term hedging approach
•Storage utilization
•Analysis (volatility, past performance, scenarios,
etc.)
•Market opportunities
Comprehensive Review of Previous Plan
46
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 403 of 829
4747
A Thorough Evaluation of Risks
Risk
Assessment
Load
Volatility
•Seasonal
Swings
Price
•Cash vs.
Forward
Market
Liquidity
•Is there
enough?
Counterparty
•Who can we
transact with?
Foreign
Currency
•What’s our
exposure?
Legislation
•Does it impact
our plan?
47
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 404 of 829
4848
Procurement Plan Structure
•The procurement plan incorporates a portfolio approach
that is diversified in terms of:
–Components: The plan utilizes a mix of index, fixed price, and storage
transactions.
–Transaction Dates:Hedge windows are developed to distribute the
transactions throughout the plan.
–Supply Basins:Plan to primarily utilize AECO, execute at lowest price basis
at the time.
–Delivery Periods:Hedges are completed in annual and/or seasonal
timeframes. Long-term hedges may be executed.
•Transactions are executed pursuant to a plan and
process; however, the procurement plan allows Avista to
be flexible to market conditions and opportunistic when
appropriate.
48
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 405 of 829
4949
Avista’s Procurement Plan Composition
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 406 of 829
5050
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 407 of 829
5151
Procurement Plan
•Window mechanism with upper and lower bands
that will adjust to the price of the current month
of gas depending on the volatility and length of
the window.
•We hedge out up to 36 months from prompt
month
–Market is liquid during this timeframe on ICE
•Intercontinental Exchange
•46% of annual firm customer load hedged within
plan.
51
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 408 of 829
5252
Hedge window Example
# Days of open window
End of
Hedge Period
Forward Price
Price Ceiling (will adjust with volatility)
Price Floor (will adjust with volatility)
Starts from
previous
day index price
46% Hedges would run
through this mechanism
52
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 409 of 829
5353
Risk Responsive Hedging Tool
(in development)
•Incorporates monthly financial positions, along with
market volatility to determine VaR
•The RRHT is in addition to programmatic hedging
•Inputs: all utility purchase/sale transactions, estimated
customer load, storage injections and withdrawals
•Currently in testing/evaluation phase
•Anticipate reducing the amount hedged
programmatically
53
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 410 of 829
5454
Storage Optimization
•Utilize our Jackson Prairie facility to arbitrage spreads
between daily and future gas prices.
•Maintain a peak day capability in order to serve needed
demand from the facility during a peak event.
•Historic value of storage (Intrinsic)
–buy in the summer when prices are historically lower and storing this
gas until the winter when prices are historically higher
•We optimize storage by locking in spreads between any
month during the program horizon.
54
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 411 of 829
5555
Transportation
Optimization
AECO to MALIN
Demand $.45
Cost to transport .10
*AECO = $1.45
MALIN = $2.00
$.55 -$.10 = $.45
Lowered cost to
ratepayers by $.45
This is referred to as a
location spread.
Malin
AECO
*2/10/1655
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 412 of 829
56
Transport Optimization -GTN
56
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 413 of 829
57
Why do we optimize?
•Combine all optimization to create more value
•Optimization has the following effects on rates:
–WA/ID
For every $2.5M of optimization, rates
decrease by ~1%
–OR
For every $1M of optimization, rates
decrease by ~1%
57
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 414 of 829
58
Lunch –60 Minutes
58
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 415 of 829
59
Emissions
Tom Pardee
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 416 of 829
60
Avista and Carbon
Avista President Dennis Vermillion:
“We are fortunate that Washington, with its abundance of renewable hydropower
generation, is already among the cleanest states in the country, but that doesn’t
mean we can’t do more. Legislation that appropriately balances the interests of
our customers, the economy, and the environment can effectively get us there.
“Under the Governor’s proposed climate change legislation, electric and natural
gas utilities will have the ability to invest the carbon tax. Avista welcomes the
opportunity to work with the Governor and the Legislature on an approach that
supports our customer’s needs, creates technological advances, and considers
the economic impact, even beyond the state’s borders, with the goal to improve
our environment.”
60
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 417 of 829
61
BLM rule repeal
•Trump administration repealed a hydraulic fracturing regulations
covering oil and gas wells on federal and tribal lands.
•The repeal, which took effect Dec. 29, 2017
•required producers to obtain BLM approval of fracturing operations,
verify cementing, conduct pressure tests, and list non-proprietary
fracturing chemicals on FracFocus.
•The rule, finalized in 2015, never took effect, following a stay
imposed by the U.S. District Court for Wyoming, which ruled in 2016
that BLM lacked authority to adopt the regulation.
61
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 418 of 829
62
Natural Gas vs. Coal emissions
•IEA assumes a tonne of methane = 28 –36
tonnes of CO2 when considering its impact
over a 100-year timeframe
•For gas to have higher emissions than coal,
we calculate that more than 10-11% of the
produced gas would need to be lost along
the value chain assuming a 100 year Global
Warming Potential (GWP).
•This is equal to 35 bcfd
–Almost ¾ of the daily European demand or ½ US
demand.
Source: https://www.woodmac.com/news/opinion/do-fugitive-emissions-of-
methane-make-natural-gas-more-emissions-intensive-than-coal62
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 419 of 829
63
Natural Gas vs. Coal emissions cont.
•Losses are assumed to
be from direct leakage
into atmosphere in the
form of methane.
•If Shell had an
estimated10.5% loss of
it’s production it would
lose over $1 billion a
year in profits and $12.5
billion in corporate value.
Source: https://www.woodmac.com/news/opinion/do-fugitive-emissions-of-
methane-make-natural-gas-more-emissions-intensive-than-coal63
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 420 of 829
646464
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 421 of 829
65
Environmental Protection Agency (EPA)
On April 17, 2012, the U.S. Environmental Protection Agency (EPA) issued cost-
effective regulations to reduce harmful air pollution from the oil and natural gas
industry.
A key component of the final rules is expected to yield a nearly 95 percent reduction in
Volatile Organic Compounds emitted from more than 11,000 new hydraulically
fractured gas wells each year. This significant reduction would be accomplished
primarily through the use of a proven process –known as a “reduced emissions
completion” or “green completion” --to capture natural gas that currently escapes to
the air.
In a green completion, special equipment separates gas and liquid hydrocarbons from
the flowback that comes from the well as it is being prepared for production. The gas
and hydrocarbons can then be treated and used or sold, avoiding the waste of natural
resources that cannot be renewed.
65
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 422 of 829
6666
Natural Gas STAR Program
•EPA pollution prevention
•The Natural Gas STAR Program provides a framework
for partner companies with U.S. oil and gas operations to
implement methane reducing technologies and practices
and document their voluntary emission reduction
activities. By joining the Program, partners commit to:
–1) evaluate their methane emission reduction opportunities,
–2) implement methane reduction projects where feasible,
–3) annually report methane emission reduction actions to the
EPA.
•https://www.epa.gov/sites/production/files/2016
06/documents/partnerlist.pdf
66
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 423 of 829
6767
Natural Gas STAR Methane Challenge
Program –Avista
•Avista Utilities has agreed to pursue a Best Management Practice
(BMP) commitment in the NG Distribution-Excavation Damages
category.
•Avista plans for continuous improvement in reducing dig in damages
and has been pursuing a program for reducing such damages since
2007. This program has no scheduled end date and Avista is
committed to achieving the lowest possible dig in rates in our service
areas.
•Avista accumulates the number of dig-in damages that occur within
each natural gas operating district on a monthly basis.The number
of locate tickets generated in each of these districts are tallied also
by district and by month.A report is generated which then details
the number of dig-in damages per 1000 locate tickets for each
district.
67
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 424 of 829
6868
Avista Locates vs Dig In’s
68
82,666
70,599
75,113
69,547
80,629
92,190
99,635 103,574
108,897
609
528
619
552 517 494 514
474 509
0
20,000
40,000
60,000
80,000
100,000
120,000
0
100
200
300
400
500
600
700
800
900
1,000
2008 2009 2010 2011 2012 2013 2014 2015 2016
Nu
m
b
e
r

o
f

L
o
c
a
t
e
s
Nu
m
b
e
r

o
f

D
i
g

I
n
s
Year
Company Wide: Locates vs Dig In's
Locates Damages
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 425 of 829
696969
0.0 2.0 4.0 6.0 8.0 10.0
2008
2009
2010
2011
2012
2013
2014
2015
2016
7.4
7.5
8.2
7.9
6.4
5.36
5.16
4.58
4.67
Damages
Ye
a
r
Damages per 1000 locates
Avista Locates vs Dig In’s
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 426 of 829
70
Fracking
*For more information go to https://fracfocus.org/
•Fracking remains a potential risk
if more robust data shows higher
than known emissions or
environmental pollution is caused
by hydraulic fracking. This may
cause more policies to be put in
place making drilling less
economic or halt production all
together is some areas.
•*Most companies report the
chemicals used in the process of
hydraulically fractured wells.
Video:
http://www.youtube.com/watch?v=2
PBCTXHqZec&feature=share&list=
UUMdjBoSXSeV38gd3xCparmA
70
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 427 of 829
71
Clean Air Rule
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 428 of 829
7272
Terms
•"Emission reduction unit" or "ERU" is an accounting
unit representing the emission reduction of one metric
ton of CO2e.
•Renewable Energy Certificates (RECs) are tradable,
non-tangible energy commodities in the United States
that represent proof that 1 megawatt-hour (MWh) of
electricity was generated from an eligible renewable
energy resource (renewable electricity) and was fed into
the shared system of power lines which transport energy.
1 ERU = 2.25 RECs72
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 429 of 829
7373
Overview
•In 2015, Governor Inslee directed the Department of Ecology to
develop the Clean Air Rule (CAR) to cap and reduce carbon
emissions under Washington’s Clean Air Act authority.
•Includes entities with 100,000 metric tons of CO2e emissions
annually and lowers the threshold to 70,000 metric tons by 2035.
•Covers natural gas distributors and power plants, as well as other
facilities –baseline will be set by Ecology using five years of data
due on March 31, 2017. (2012-2016)
•The CAR went into effect on October 17, 2016.
•Annual emission reductions will equal:
–1.7% of baseline CO2e emissions
–5% over the three year compliance period
–Reductions are shown by banking emissions reduction units (ERUs) in the registry
73
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 430 of 829
7474
Overview cont.
•ERU must originate from reductions in Washington unless derived
from allowances and must be retired when used for compliance
•Generate ERUs by:
–Actual emissions reductions beyond annual compliance requirements
–Emission reduction projects, programs or activities
•ERU banking –10 Year Banking Provision
•Exchange ERUs through established registry
•Kaiser is excluded from Avista’s emissions baseline
74
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 431 of 829
7575
Activities and programs recognized as
generating ERU’s
•Transportation activities;
•Combined heat and power activities;
•Energy activities;
•Livestock and agricultural activities;
•Waste and wastewater activities;
•Industrial sector activities;
•Certain Energy Efficiency Site Evaluation Council
(EFSEC) recognized emission reductions; and
•Ecology approved emission reductions
75
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 432 of 829
7676
Percentage Limits on Use of Allowances
per compliance period
Compliance Period Upper Limit
2017-22 100%
2023-25 50%
2026-28 25%
2029-31 15%
2032-34 10%
2035 and beyond 5%
76
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 433 of 829
7777
CAR Allowances
-
50,000
100,000
150,000
200,000
250,000
300,000
350,000
400,000
450,000
500,000
MT
C
O
2
e
# of Needed ERUs Max Allowances
77
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 434 of 829
7878
Avista WA CAR goal
-
200,000
400,000
600,000
800,000
1,000,000
1,200,000
1,400,000
MT
C
O
2
e
# of Needed ERUs Avista WA CO2e…CAR Goal
78
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 435 of 829
7979
Potential Supply for CAR compliance
•RNG
•Solar
•Wind
•DSM
•Gas Customers, without a reduction in use,
would likely be required to purchase electric
generation resources in Washington State to
offset emissions.
79
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 436 of 829
80
2018 Natural Gas IRP
Carbon Policy Overview
John Lyons, Ph.D.
Second Technical Advisory Committee Meeting
February 22, 2018
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 437 of 829
8181
Carbon Laws and Regulations
•Big changes at the federal level with the Trump administration
•More activity at the state and local levels
•Three main areas for carbon emissions:
1.Regulatory mandates
2.Cap and trade programs
3.Carbon taxes
•Focus still on electric generation, but many states are
expanding to natural gas and other fuels
81
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 438 of 829
8282
Federal
•Current federal focus under a regulatory model through the
Clean Air Act (CAA)
•Clean Power Plan (CPP) –reduce greenhouse gas emissions
from covered existing power plants 32 percent below 2005
levels by 2030 under section 111(d) of the CAA.
–Regulates power generation, but would impact natural gas use.
–CPP stayed by US Supreme Court on February 9, 2016 and oral
arguments June 2, 2016 at DC Circuit Court of Appeals.
–April 4, 2017, EPA announced review to determine a new
proceeding to “suspend, revise or rescind the Clean Power
Plan.”
–10/16/17 –EPA proposed to repeal the CPP
–Public comment period reopened to April 26, 2018 and additional
listening sessions in February and March 2018
82
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 439 of 829
8383
Idaho
•No active or proposed greenhouse gas legislation
•Provided comments about the CPP and the federal
implementation plan
•Were working towards a state implementation plan by
September 2016, but work stopped with the Supreme
Court stay
•Will update after EPA makes a final decision on the CPP
83
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 440 of 829
8484
Oregon
•Last IRP, “Clean Electricity, Coal Transition” law set a 50%
renewable goal by 2040 and the elimination of coal power in
rates by 2030
•HB 4001 & SB 1507:both bills create a cap and trade system
for entities emitting over 25,000 metric tons carbon annually.
•In 2021, the Oregon Environmental Quality Commission
would set a statewide emissions on about 100 companies
who would need to reduce emissions or buy allowances.
•Revenue would be invested in clean energy or emissions
mitigation programs.
•Emissions under both bills would drop 20% below 1990 levels
by 2025, 45% by 2035, and 80% by 2050.
84
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 441 of 829
8585
Oregon
•HB 4001 moved from House Energy & Environment Committee and
referred to the Joint Committee on Ways & Means with no
scheduled action for the bill.
•SB 1507 was voted out of the Senate Environment & Natural
Resources Committee and referred to the Joint Committee on Ways
& Means with no currently scheduled action for the bill.
•The House bill mirrors California’s and the Senate bill tries to
complements the “Clean Electricity, Coal Transition” bill by giving
utilities free allowances for coal emissions.
•The biggest question from legislators has been the cost, which were
estimated between $400 and $700 million annually in a Senate
Committee on Environment and Natural Resources debate on
February 12, but a final cost hasn’t been issued yeat.
85
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 442 of 829
8686
Washington
•Clean Air Rule –invalidated 12/15/17
•SSB 6203: Current version is $12/metric ton from use of fossil fuels
and emissions from electric sector, increasing $1.80/year until
reaching $30/ton in 2030
–Originally $20 with 3.5% plus inflation, changed to $10 and $2 annual
increase
–Exempts many energy intensive, trade-exposed manufacturers
–Allows utilities a full tax credit for investing in projects and programs to
reduce emissions or mitigate costs to low-income customers. This
provision phases out for coal-fired generation.
–Possible ballot initiative if the measure fails
•SHB 2839 –allows alternative regulation by the UTC and requires
utilities to factor in a “carbon adder” starting at $40/ton in resource
and conservation planning if a carbon price is enacted. Failed to
meet the cutoff.
86
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 443 of 829
8787
Washington
•SB 6253 requires electric utilities to remove coal-fired generation
costs from rates by 2030, and reduce carbon emitting resources
until 100% renewable by 2045 or face a $100/ton cost for exceeding
emission targets. Failed to meet the chamber of origin cutoff.
•HB 2580, Rep. Morris Requires the WSU Extension Energy
Program and Department of Commerce to identify opportunities and
cost estimates for renewable natural gas and provide
recommendations by September 1, 2018. Failed to meet the
chamber of origin cutoff.
•HB 2402 for 50% RPS for investor-owned utilities by 2040,
consumer-owned utilities purchase non-emitting resources for future
needs, and sets minimum conservation 2% of electric load and 1.5%
for natural gas load. Failed to meet the chamber of origin cutoff.
•Elements of bills failing to meet the chamber of origin cutoff may still
be incorporated into other bills.
87
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 444 of 829
88
Price Forecasts and Carbon Adders
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 445 of 829
89
$0.00
$1.00
$2.00
$3.00
$4.00
$5.00
$6.00
$7.00
$8.00
$9.00
$10.00
2005 2007 2009 2011 2013 2015 2017 2019 2021 2023 2025 2027 2029 2031 2033 2035 2037 2039
$
/

D
t
h
Henry Hub Forecast
(Nominal $)
Historic Consultant 1
Nominal Henry Hub
Consultant 2
Nominal Henry Hub
Forwards EIA 2018 AEO
Forecast
89
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 446 of 829
9090
How prices affect IRP Planning?
•Major component of the total cost
•Change in price can trigger price elastic response
•THE major piece of avoided costs and therefore cost effectiveness
of DSM
•Can change resource selection based on basin differentials
•Storage utilization
90
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 447 of 829
91
IRP Natural Gas Price Forecast
Methodology
1.Two fundamental forecasts (Consultant #1 & Consultant #2)
2.Forward prices
3.Year 1 -forward price only
4.Year 2 -75% forward price / 25% average consultant forecasts
5.Year 3 -50% forward price / 50% average consultant forecasts
6.Year 4 –6 25% forward price / 75% average consultant forecasts
7.Year 7 -50% average consultant without CO2 / 50% average consultant with
CO2
91
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 448 of 829
92
$-
$1.00
$2.00
$3.00
$4.00
$5.00
$6.00
$7.00
$8.00
$-
$1.00
$2.00
$3.00
$4.00
$5.00
$6.00
$7.00
$8.00
$
p
e
r

D
t
h
Expected Price forecast methodology curves
Nominal $
Nymex (2/9/2018)Consultant 2 Consultant 192
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 449 of 829
93
Pricing starts at the expected price for the first year
Years 2-6 price deviates by 6% per year from the expected price to create the high and low
Years 7-11 price deviates by 3% per year from the expected price to create the high and low
Years 12 –20 the price deviates by 1.5% per year from the expected price
$-
$1.00
$2.00
$3.00
$4.00
$5.00
$6.00
$7.00
$8.00
$9.00
$10.00
$11.00
$12.00
$-
$1.00
$2.00
$3.00
$4.00
$5.00
$6.00
$7.00
$8.00
$9.00
$10.00
$11.00
$12.00
$
p
e
r

D
t
h
2018 Henry Hub Prices -Nominal
High HH Price…Low HH Price…HH Expected Price…
93
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 450 of 829
9494*nominal dollars94
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 451 of 829
9595
Carbon Price by Jurisdiction
*Idaho has no carbon price adder
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 452 of 829
9696
Carbon Tax Summary
•ID –None
•OR –Cap and Investment Program SB1070
–Avista’s price assumption are based on CA cap and
trade program
–Increases by 5% + inflation each year
•WA –Governor Inslee proposed Carbon tax (SB
6203)
–Starts at $10 per MTCO2e in July 2019 and starting in
2021 adds $2 per year until capping at $30 in 2030.
96
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 453 of 829
97
2018 ID IRP Prices
Low –Expected –High
No Carbon Adders
$-
$2.00
$4.00
$6.00
$8.00
$10.00
$12.00
$-
$2.00
$4.00
$6.00
$8.00
$10.00
$12.00
$
p
e
r

D
t
h
ID - HH Expected Price…ID - Low HH Price…ID - High HH Price…
97
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 454 of 829
98
2018 OR IRP prices
Low –Expected –High
Including Carbon Adders
$-
$2.00
$4.00
$6.00
$8.00
$10.00
$12.00
$14.00
$-
$2.00
$4.00
$6.00
$8.00
$10.00
$12.00
$14.00
$
p
e
r

D
t
h
OR - HH Expected Price…OR - Low HH Price…OR - High HH Price…98
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 455 of 829
99
2018 WA IRP Prices
Low –Expected –High
Including Carbon Adders
$-
$2.00
$4.00
$6.00
$8.00
$10.00
$12.00
$14.00
$-
$2.00
$4.00
$6.00
$8.00
$10.00
$12.00
$14.00
$
p
e
r

D
t
h
WA - HH Expected Price
Nominal $
WA - Low HH Price
Nominal $
WA - High HH Price
Nominal $
99
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 456 of 829
100
2018 Henry Hub
Expected Price
Including Carbon Adders by State
$-
$1.00
$2.00
$3.00
$4.00
$5.00
$6.00
$7.00
$8.00
$9.00
$10.00
$-
$1.00
$2.00
$3.00
$4.00
$5.00
$6.00
$7.00
$8.00
$9.00
$10.00
$
p
e
r

D
t
h
ID - HH Expected Price
Nominal $
OR - HH Expected Price
Nominal $
WA - HH Expected Price
Nominal $100
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 457 of 829
101
Wrap Up
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 458 of 829
102102
IPUC
•Staff believes public participation could be further
enhanced through “bill stuffers, public flyers, local media,
individual invitations, and other methods.”
•Result: Avista utilized it’s Regional Business Managers
in addition to digital communications and newsletters in
all states in order to try and gain more public
participation. Previous IRP’s relied on website data and
word of mouth.
–eCommunity newsletter was sent out on January 15, 2018
102
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 459 of 829
103103
OPUC
•Staff Recommendation No. 1
–Staff recommends in Avista's 2018 IRP that Avista pursue an updated methodology, wherein the low/high
gas price curves continue to be based on low (high) historic prices in a Monte Carlo setting, but are inflated
to match the growth rate (yr/yr) of the expected price curve. The resulting curves wouid be based on historic
prices and also produce symmetric .risk profiles throughout the time horizon.
–Result: Avista updated its method as recommended by the Oregon commission. This new method deviates
from the expected price by the following method:
•Pricing starts at the expected price for the first year
•Years 2-6 the high and low price deviate +/-6% per year from the expected price
•Years 7-11 the high and low price deviate by +/-3% per year from the expected price
•Years 12 –20 the high and low price deviate by +/-1.5% per year from the expected price
•By the 20 year mark the high and low deviate from the expected price by +/-58.5%
•Staff Recommendation No. 2
–Staff recommends that Avista forecast its number of customers using at least two different methods and to
compare the accuracy of the different methods using actual data as a future task in its next IRP.
–Result: Avista analyzed the data, but there was nothing material discovered the come up with a meaningful
forecast alternative.
•Staff Recommendation No. 3
–Avista's 2018 IRP will contain a dynamic DSM program structure in its analytics.
•In, prior IRPs, it was a deterministic method based on Expected Case assumptions, in the 2018 IRP,
each portion will have the ability to select conservation to meet unserved customer demand, Avista will
explore methods to enable a dynamic analytical process for the evaluation of conservation potential
within individual portfolios and will work with Energy Trust of Oregon in the development of this
process and in producing any final results for its 2018 IRP for Oregon customers.
103
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 460 of 829
104104
OPUC cont.
•Staff Recommendation No. 4
–Staff recommends that Avista provide Staff and stakeholders with updates
regarding its discussions and analysis regarding possible regional pipeline
projects that may move forward.
•Staff Recommendation No. 5
–Staff recommends that in its 2018 IRP process Avista work with Staff and
stakeholders to establish and complete stochastic analysis that considers a
range of alternative portfolios for comparison and consideration of both cost and
risk.
104
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 461 of 829
105105
OPUC cont.
•Staff Recommendation No. 6
–Environmental Considerations
•1. Carbon Policy including federal and state regulations, specifically
those surrounding the Washington Clean Air Rule and federal Clean
Power Plan;
–Result: Carbon Policy including the Clean Power Plan and Clean Air
Rule were both reviewed and included in TAC 2 Meeting materials on
2/22/2018. An indicator of where Avista’s carbon reduction
requirements under the CAR was also included. Since the CAR was
invalidated on 12/15/2017 in Thurston County Superior Court this
analysis is intended to meet the action item in addition to showing the
potential impacts of similar policies.
•2. Weather analysis specific to Avista's service territories;
–Result: A weather analysis was included and reviewed in TAC 2
meeting materials on 2/22/2018
•3. Stochastic Modeling and supply resources; and
•4. Updated DSM methodology including the integration of ETO
105
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 462 of 829
106106
WUTC
•Include a section that discusses impacts of the Clean Air Rule (CAR).
–In its 2018 IRP expected case, Avista should model specific CAR impacts as well
as consider the costs and risk of additional environmental regulations, including a
possible carbon tax.
–Result:
•Carbon Policy including the Clean Power Plan and Clean Air Rule were both
reviewed and included in TAC 2 Meeting materials on 2/22/2018. An
indicator of where Avista’s carbon reduction requirements under the CAR
was also included. Since the CAR was invalidated on 12/15/2017 in
Thurston County Superior Court this analysis is intended to meet the action
item in addition to showing the potential impacts of similar policies.
•For the 2018 IRP Avista is utilizing SB6203 from the WA Senate energy
committee on Feb. 1 as a proxy of a possible carbon tax in Washington
State.
106
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 463 of 829
107107
WUTC
•Provide more detail on the company’s natural gas hedging strategy,
including information on upper and lower pricing points, transactions with
counterparties, and how diversification of the portfolio is achieved.
–Avista’s natural gas hedging strategy was discussed during the TAC 2 Meeting on 2/22/2018.
The upper and lower pricing points in Avista’s programmatic hedges is controlled by taking
into consideration the volatility over the past year for the specific hedging period. This
volatility is weighted toward the more recent volatility. The window length and quantity of
windows is also a part of the equation. Avista transacts on ICE with counterparties meeting
our credit rating criteria. The diversification of the portfolio is achieved through the following
methods:
–Components: The plan utilizes a mix of index, fixed price, and storage transactions.
–Transaction Dates:Hedge windows are developed to distribute the transactions throughout
the plan.
–Supply Basins:Plan to primarily utilize AECO, execute at lowest price basis at the time.
–Delivery Periods:Hedges are completed in annual and/or seasonal timeframes. Long-term
hedges may be executed.
107
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 464 of 829
108108
WUTC cont.
•Ensure that the entity performing the CPA evaluates and includes the
following information:
–All conservation measures excluded from the CPA, including those excluded
prior to technical potential determination
–The rationale for excluding any measure
–A description of Unit Energy Savings (UES) for each measure included in the
CPA, specifying how it was derived and the source of the data
–The rationale for any difference in economic and achievable potential savings,
including how the Company is working towards an achievable target of 85
percent of economic potential savings.
–A description of all efforts to create a fully-balanced cost effectiveness
metric within the planning horizon based on the TRC.
108
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 465 of 829
109109
WUTC cont.
•Discuss with the TAC:
–The results of Northwest Energy Efficiency Alliance (NEEA)
coordination, including non-energy benefits to include in the CPA.
–The appropriateness of listing and mapping all prospective distribution
system enhancement projects planned on the 20 year horizon, and
comparing actual projects completed to prospective projects listed in
previous IRP’s.
•Provide a rationale for any difference in economic and achievable
potential savings
109
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 466 of 829
110110
2017 –2018 Avista’s Action Plan
•The price of natural gas has dropped significantly since the 2014 IRP.This is primarily due to the
amount of economically extractable natural gas in shale formations,more efficient drilling
techniques,and warmer than normal weather.Wells have been drilled,but left uncompleted due
to the poor market economics.This is depressing natural gas prices and forcing many oil and
natural gas companies into bankruptcy.Due to historically low prices Avista will research market
opportunities including procuring a derivative based contract,10-year forward strip,and natural
gas reserves.
•Result:After exploring the opportunity of some type of reserves ownership,it was
determined the price as compared to risk of ownership was inappropriate to go forward with
at this time.As an ongoing aspect of managing the business,Avista will continue to look for
opportunities to help stabilize rates and/or reduce risk to our customers.
Monitor actual demand for accelerated growth to address resource deficiencies arising from
exposure to “flat demand”risk.This will include providing Commission Staff with IRP demand
forecast-to-actual variance analysis on customer growth and use-per-customer at least bi-
annually.
Result:actual demand was closely tracked and shared with Commissions in semi-annual
or quarterly meetings.
110
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 467 of 829
111111
2018 IRP Timeline
•August 31, 2017 –Work Plan filed with WUTC
•January through May 2018 –Technical Advisory Committee
meetings. Meeting topics will include:
–TAC 1: Thursday, January 25, 2018: TAC meeting expectations, review of
2016 IRP acknowledgement letters, customer forecast, and demand-side
management (DSM) update.
–TAC 2: Thursday, February 22, 2018: Weather analysis, environmental
policies, market dynamics, price forecasts, cost of carbon.
–TAC 3: Thursday, March 29, 2018 :Distribution, supply-side resources
overview, overview of the major interstate pipelines, RNG overview and future
potential resources.
–TAC 4: Thursday, May 10, 2018:DSM results, stochastic modeling and
supply-side options, final portfolio results, and 2020 Action Items.
•June 1, 2018 –Draft of IRP document to TAC
•June 29, 2018 –Comments on draft due back to Avista
•July 2018 –TAC final review meeting (if necessary)
•August 31, 2018 –File finalized IRP document
111
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 468 of 829
1
2018 Avista Natural Gas IRP
Technical Advisory Committee Meeting
March 29, 2018
Spokane, WA
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 469 of 829
22
Agenda
•Introductions & Logistics
•Williams update
•TransCanada update
•Avista’s Supply Side Resources
•Distribution
•Renewable Natural Gas
•Power to Gas
•Initial sensitivity results & proposed scenarios
Lunch will be around 12pm
2
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 470 of 829
33
2018 IRP Timeline
•August 31, 2017 –Work Plan filed with WUTC
•January through May 2018 –Technical Advisory Committee
meetings. Meeting topics will include:
–TAC 1: Thursday, January 25, 2018: TAC meeting expectations, review of
2016 IRP acknowledgement letters, customer forecast, and demand-side
management (DSM) update.
–TAC 2: Thursday, February 22, 2018: Weather analysis, environmental
policies, market dynamics, price forecasts, cost of carbon.
–TAC 3: Thursday, March 29, 2018 : Distribution, supply-side resources
overview, overview of the major interstate pipelines, RNG overview and
future potential resources.
–TAC 4: Thursday, May 10, 2018:DSM results, stochastic modeling and
supply-side options, final portfolio results, and 2020 Action Items.
•June 1, 2018 –Draft of IRP document to TAC
•June 29, 2018 –Comments on draft due back to Avista
•July 2018 –TAC final review meeting (if necessary)
•August 31, 2018 –File finalized IRP document
3
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 471 of 829
NYSE: WMB
williams.com
WE MAKE ENERGY HAPPEN
Avista TAC Meeting #3
March 29, 2018
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 472 of 829
5© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Mastio Survey
>Rated No. 2 in the Mega and Major Pipeline categories and No. 3 in the overall Interstate Pipeline category
>Northwest was ranked #1 in the following areas:
•competitive rates
•diverse supply & markets
•likelihood to recommend
>Northwest was ranked #2 in the following areas:
•honest communications
•effectiveness of contract negotiations
•expertise of reps to solve your needs
•value received for the money paid
•flexibility of gas flows
•flexibility of transport options
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 473 of 829
6© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Northwest System –Strategically Located
>Low-cost, primary service provider in the
Pacific Northwest
•3,900-mile system with 3.8 Bcf/d peak design capacity
•~120 Bcf of access to storage along pipeline, with high injection and deliverability capability in market area
•Fully Contracted with > 9 year average contract life
>Bi-directional design
•Provides flexibility (Rockies to market and Sumas to market)
•Cheapest supply drives flow patterns
•Provides operational efficiencies through displacement
>Supply and market flexibility
•65 receipt points totaling 11.6 Bcf/d of supply from Rockies, Sumas, WCSB, San Juan, emerging shales
•366 delivery points totaling 9.7 Bcf/d of delivery capacity
>Solution oriented
•History of working with our customers both creatively and collaboratively to serve their needs
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 474 of 829
7© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Supply Diversity
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 475 of 829
8© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Supply Diversity –South End
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 476 of 829
9© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Sumas South Historical
0
100,000
200,000
300,000
400,000
500,000
600,000
700,000
800,000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Chehalis Historical (Avg Dth/d)
2017 Prior 10yr Avg Prior 5yr Avg Design Capacity
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 477 of 829
10© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Stanfield West Historical
(600,000)
(400,000)
(200,000)
0
200,000
400,000
600,000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Roosevelt Historical (Avg Dth/d)
2017 Prior 10yr Avg Prior 5yr Avg Dsgn Cap Incr Dsgn Cap Decr
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 478 of 829
11© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Jackson Prairie Withdrawal Deliverability Curve
-
0.200
0.400
0.600
0.800
1.000
1.200
1.400
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63
# of Days
Jackson Prairie W/D Rights
NOTE: Deliverability curve is based on a beginning seasonal quantity of 25.6
MMDth. Withdrawal capacity starts out at 1.2 MMDth/d and declines by 2 percent
for each 1 percent the capacity drops below 60 percent.
March 9, 2017 -JP at 26% Capacity –382,720 Dth/d Deliverability
March 13, 2015 –JP at 38% Capacity –669,760 Dth/d Deliverability
March 19, 2016 –JP at 30% Capacity –478,400 Dth/d Deliverability
Lowest point of deliverability during
each of the last five heating
seasons.
March 31, 2014 –JP at 22% Capacity –287,040 Dth/d Deliverability
March 9, 2018 -JP at 28% Capacity –430,560 Dth/d Deliverability
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 479 of 829
12© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Weather Forecast –February 26, 2014
February 26 forecast for March 1 through 3, 2014
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 480 of 829
13© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Tariff Rates
Effective
12/31/2017
Effective
1/1/2018
Effective
10/1/2018
Comeback Rates
Effective
1/1/2023
TF-1 Reservation (Large Customer)0.41000 0.39294 0.39033 ?
TF-1 Volumetric (Large Customer) 0.03000 0.00832 0.00832 ?
Small Customer 0.72155 0.69427 0.69427 ?
Base Tariff Rates
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 481 of 829
14© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Avista’s Net Effective Rate
Contract
Daily
Contract
Demand
Released
Amount Receipt Delivery Rate
Reservation
Charge
Base Contract Various 190,416 0.39294 27,310,053$
Incremental CD through Segmentations to themselves
Avista 137286 9,211 Starr Road Coeur D'Alene --$
Segmented Releases to Third Parties
IGI 110203 10,000 Rockies Idaho 0.39294 (1,434,231)$
110192 10,000 Rockies Meridian/Boise 0.39294 (1,434,231)$
Clark PUD 140788 2,841 Stanfield River Road 0.39294 (407,465)$
140787 6,709 Stanfield River Road 0.39294 (962,226)$
142230 17,394 Sumas River Road 0.39294 (2,494,701)$
Puget Sound 141549 8,056 Sumas JP Delivery 0.39294 (1,155,416)$
(7,888,271)$
Net Effective Rate 199,627 0.26655 19,421,783$
Contract
Daily
Contract
Demand
Annual
Contract
Quantity Receipt
Receipt /
Delivery
Daily
Rate
Reservation
Charge
Avista 100314 91,200 2,906,266 JP Receipt Various 0.03431 1,141,935$
100315 2,623 94,462 JP Receipt Various 0.03431 37,147$
1,179,081$
Peak Day Effective Rate 293,450 0.19234 20,600,864$
Net Effective Rate
Peak Day Load Effective Rate
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 482 of 829
15© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Avista’s Segmentation to Themselves
Original Path
(R) Opal to (D) Spokane
9,211 Dth/d
Starr Road
Spokane
CDA
Retained Segment 2
(R) Rockies to (D) Spokane
9,211 Dth/d
Rockies
Retained Segment 1
(R) Starr Road to (D) CDA
9,211 Dth/d
Incremental CD through Segmentation
Segment #1 9,211
Segment #2 9,211
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 483 of 829
16© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Avista’s Segmented Release No. 1
Original Path
(R) Rockies to (D) Spokane
20,000 Dth/d
Stanfield Receipt
Spokane
IdahoReleased Segment 1
(R) Rockies to (D) Idaho
20,000 Dth/d Rockies
Retained Segment 1
(R) Stanfield to (D) Spokane
20,000 Dth/d
Annual Cost Savings
Segment #1 ~$3.0m
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 484 of 829
17© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Avista’s Segmented Release No. 2
Original Path
(R) Rockies to (D) Spokane
20,000 Dth/d
Stanfield Receipt
Spokane
IdahoReleased Segment 1
(R) Rockies to (D) Idaho
20,000 Dth/d Rockies
Retained Segment 1
(R) Stanfield to (D) Spokane
20,000 Dth/d
Annual Cost Savings
Segment #1 ~$3.0m
Segment #2 ~$1.4m
Released Segment 2
(R) Stanfield to (D) River Road
10,000 Dth/d
Retained Segment 2
(R) Palouse to (D) Lewiston
10,000 Dth/d
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 485 of 829
18© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Avista’s Segmented Release No. 3
Original Path
(R) Sumas to (D) Pullman
(6,000), Moscow (4,000), &
Coeur D’Alene (10,394)
20,394 Dth/d
Sumas Receipt
Coeur D’Alene
Pullman/
Moscow
Retained Segment 3
(R) Starr Road to (D) CDA
10,394 Dth/d
Retained Segment 3
(R) Mollalla to (D) Pullman/ Moscow
10,000 Dth/d
Mollalla Receipt
Released Segment 3
(R) Sumas to (D) River Road
17,394 Dth/d
River Road
Annual Cost Savings
Segment #1 ~$3.0m
Segment #2 ~$1.4m
Segment #3 ~$2.5m
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 486 of 829
19© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Avista’s Segmented Release No. 4
Original Path
(R) Sumas to (D) Spokane
8,056 Dth/d
Sumas Receipt
Spokane
Retained Segment 4
(R) JP to (D) Spokane
8,056 Dth/d
JP Receipt
Released Segment 4
(R) Sumas to (D) JP
8,056 Dth/dJP Delivery
Annual Cost Savings
Segment #1 ~$3.0m
Segment #2 ~$1.4m
Segment #3 ~$2.5m
Segment #4 ~$1.1m
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 487 of 829
20© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 488 of 829
21© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Firm Reliability
•2014 –99.9 percent
•2015 − 100 percent
•2016 − 99.9 percent
•2017 − 100 percent
>To determine customer impact, firm reliability percentage is calculated on flows prior, during and after posted maintenance
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 489 of 829
22© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Reliability and Integrity Programs
>Integrity Management
–In-line Inspections
–Requalifications
–Cathodic Protection
>Geo Hazard
–Strain Gauge
–River Crossing
–Land Movement
>Mainline Valve Automation
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 490 of 829
23© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Integrity Management Program
>An Integrity Management Program based on an effective framework
•Prevention, detection and remediation
•Designed to address safety, reliability and compliance related risks in a
comprehensive and systematic way
•Plan maintenance focused on minimizing customer impacts
>Three major pipeline integrity recurring programs
•Assessment Program
•In-Line Inspection (smart pigging)
•Department of Transportation Requalification Program
•Cathodic Protection Program
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 491 of 829
24© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Integrity Management Program (cont.)
>In-Line Inspection Program (smart pigging)
>The preferred assessment method to address
most integrity threats
>Means of complying with the Pipeline Safety
Improvement Act (PSIA) of 2002
>Integrity Hydro-test
>Direct Assessments
Assessments
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 492 of 829
25© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Integrity Management Program (cont.)
In-Line Inspection (ILI) Program
>Tools:
•Gauge plate pig
•Cleaning pig
•Geometry pig (dents, obstructions)
•Magnetic Flux Leakage pig (MFL)
>Specialty Tools
•Circumferential/Spiral Magnetic Flux Leakage Pig (CMFL)
•ElectroMagnetic Acoustic Transducer (EMAT)
Standard suite of tools
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 493 of 829
26© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Integrity Management Program (cont.)
In-Line Inspection Program –
Preparing the line for inspection
>Cleaning pig:
•remove liquids and debris from line and prepares line for inspection
>Gauge Plate Pig:
•inspect for obstructions such as severe dents or bends that
could stop an instrumented tool
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 494 of 829
27© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Integrity Management Program (cont.)
In-Line Inspection Program -Standard Instrumented In-line Inspection Tools
Geometry Tool:
•Locate and size dents, bends, ovality due to construction or third-
party damage
>MFL Tool:
•inspect for internal/external
corrosion or metal loss
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 495 of 829
28© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Integrity Management Program (cont.)
In-Line Inspection Program -Specialty Tools
>Circumferential/Spiral Magnetic Flux Leakage Pig (CMFL):
•Locate and size axially oriented
anomalies
>Electro Magnetic Acoustic Transducer (EMAT) Tool:
•Locate and size cracking including stress corrosion cracking (SCC)
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 496 of 829
29© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Integrity Management Program (cont.)
Benefits of Utilizing ILI Technology for Integrity Assessment
>It can assess for anomalies for the entire length of a pipeline segment vs. just the
HCA locations as a hydro test
>The line does not need to be taken out of service to complete the assessment
>It can find features that would not be found in a hydro test,(e.g. pending failures)
>Data can be compared against prior runs to determine if features are growing
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 497 of 829
30© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Integrity Assessment Program
>Asset integrity
•3,201 (83.8%) miles of first time assessment
•177 (98.6%) miles of High Consequence Area (HCA) first time assessment
•Reassess HCA’s every 7 years
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 498 of 829
31© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
DOT Compliance Program
Department of Transportation Requalification Program
>Class location change based on
population density and buildings near pipeline
>If class location changes, then either:
•Reduce pressure
•Perform a hydrostatic test
•Replace pipeline
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 499 of 829
32© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Cathodic Protection & Recoat Program
>Purpose
•Protect the pipeline against corrosion
–Williams uses impressed current systems to protect against corrosion
•All current levels are evaluated annually
–Coating protects against corrosion by providing a physical barrier from the
elements as well as making the cathodic protection current more efficient
•Recoat areas determined primarily by inline inspection run-to-run
comparisons
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 500 of 829
33© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Geologic Hazards Program
>Monitoring pipe strain at strategic locations
>Monitoring land movement in several ways
Land Movement River Crossing Strain Gauge
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 501 of 829
34© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Reliability Programs
>Strain gauge database
>ILI strain analysis
>Inclinometers
>Aerial surveys
>River crossing monitoring program
>GIS geotechnical hazards database
>LIDAR data
Northwest Geotechnical Monitoring
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 502 of 829
35© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
Department of Transportation Mainline Valve Program
>The purpose of the program is to ensure that Northwest Pipeline is in compliance with the Department of Transportation required mainline
valve spacing requirements.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 503 of 829
36© 2017 The Williams Companies, Inc. All rights reserved.Avista TAC Meeting | 3/29/18
>Questions??
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 504 of 829
TransCanada Supply Update–J. Story
AVISTA –IRP/TAC Meeting
March 29, 2018
37
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 505 of 829
2017 Supply and Market Outlook
•North American Supply and Demand
•NGTL Expansions
•Impact on GTN Supply and Capacity
38
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 506 of 829
North American Demand
2017 TransCanada Outlook
0
20
40
60
80
100
120
140
20
1
1
20
1
2
20
1
3
20
1
4
20
1
5
20
1
6
20
1
7
20
1
8
20
1
9
20
2
0
20
2
1
20
2
2
20
2
3
20
2
4
20
2
5
20
2
6
20
2
7
20
2
8
20
2
9
20
3
0
20
3
1
Bc
f
/
D
LNG Exports
Transport
Power
Generation
Industrial
Other
Residential
Commercial
39
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 507 of 829
North American Supply
2017 TransCanada Outlook
0.0
20.0
40.0
60.0
80.0
100.0
120.0
140.0
20
1
1
20
1
2
20
1
3
20
1
4
20
1
5
20
1
6
20
1
7
20
1
8
20
1
9
20
2
0
20
2
1
20
2
2
20
2
3
20
2
4
20
2
5
20
2
6
20
2
7
20
2
8
20
2
9
20
3
0
20
3
1
Bc
f
d
WCSB
Northeast
Rockies/ San Juan
Permian
Mid-Con
Gulf Coast
Gulf of Mexico
Fort Worth
Other
40
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 508 of 829
41
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 509 of 829
Western Canadian Sedimentary Basin Gas Supply
Liard
0
2
4
6
8
10
12
14
16
18
20
2010 2015 2020 2025
Solution Gas
Conventional -Vertical
Conventional -Horizontal
Horn River
CBM Montney
Bcf/d
Cordova
History Forecast
Duvernay
Liard
42
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 510 of 829
Western Canadian Production (Bcf)
13.8 14.5 14.9 15.1
0 0
15.2 15.4 15.6 15.7 15.7 15.9 16.1 16.5 16.8
5.0
10.0
15.0
20.0
25.0
20
1
3
20
1
4
20
1
5
20
1
6
20
1
7
20
1
8
20
1
9
20
2
0
20
2
1
20
2
2
20
2
3
20
2
4
20
2
5
FORECAST
WCSB
ACTUALS
FORECAST FORECAST 1 FORECAST 2 FORECAST 3
Source: Wood Mackenzie
43
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 511 of 829
Western Canadian Sedimentary Basin
•WCSB:
•Prolific and competitive resource
•Economic production in Montney and Deep
Basin resources
•NGTL System:
•Dominant basin position, capturing 75% of
WCSB production
•Strongly connected to substantive supply and
intra and ex-basin markets
•Supply to GTN and Northern Border
•400+Bcf of gas storage
•50+Bcf/d of NIT trading liquidity
44
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 512 of 829
Evolving System Supply Distribution
2011
2016
2021
North of
Bens Lake
Peace
River
Central
Area
2%
>1%
35%
60%
5%24%
15%
85%
74%
45
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 513 of 829
James River By-Pass
•Open Seasons in 2015
•Onstream June 2016
•Pipeline modification Project
•~150 TJ/d of capacity
•ABC Border Design Capability: ~2.2 Bcf/d
Sundre Crossover
•Open Seasons in January and June 2016
•Onstream 2018
•~20km of NPS 42 pipeline loop of WAS Mainline
•ABC Border Design Capability: ~2.45 Bcf/d
West Path
46
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 514 of 829
NGTL Mainline Expansions
Planned 2017 Facilities Planned 2018-19 Facilities
2017 Expansions 2018-19 Expansions
Pipe
284 km of NPS 24-48
Compression
6 units for 113.5 MW
Pipe
267 km of NPS 36-42
Compression
8 units for 195 MW
47
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 515 of 829
2019/2020 West Path Expansion
Planned 2019 FacilitiesPlanned 2020 Facilities
AB-BC Border Expansion Capacity Open Season
Expansion Capacity:408 TJ/d
Service Commencement Dates:
Nov 2019 120 TJ/d
Jun 2020 288 TJ/d
Bid Evaluation:Length of Requested Term
Minimum Term:8 years
FT-D1 Pricing Discount:10%
Closing Date:May 31, 2017
•Full alignment of TransCanada assets serving PacNW and
Western states.
•Economic production from the WCSB resources is a good fit
for Western US markets
48
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 516 of 829
GTN Overview
•Positioned to serve markets
throughout California, Nevada, and
the Pacific Northwest
•Consists of 1,350 miles of pipeline
•Kingsgate best efforts receipt
capability of approx. 2.87 Bcfd and
throughput capability of approx. 2
Bcfd thru Sta. 14
•Deliveries of up to 1.5 Bcfd to non-
California Markets
•Long-term contracts extending out as
far as 2039
•Volume throughput continues to be
strong and should continue to grow
in 2018
•NGTL continues to address the export
capability at ABC to bring into
alignment with downstream systems
49
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 517 of 829
Demand Projections
Pacific Northwest & California
1,
1
0
0

1,
6
8
0

1,
3
0
0

1,
9
8
0

1,
2
0
0

1,
9
8
0

1,
3
0
6

2,
1
7
9

1,
3
3
5

2,
2
8
7

1,
5
1
3

2,
3
5
9

1,
5
0
6

2,
3
7
0

1,
5
0
7

2,
3
7
3

1,
5
1
2

2,
3
8
7

1,
5
1
0

2,
4
0
2

1,
5
8
0

2,
4
5
0

1,
5
9
5

2,
4
6
9

1,
6
1
4

2,
5
0
5

-
500
1,000
1,500
2,000
2,500
3,000
S
1
4
W
1
4
/
1
5
S
1
5
W
1
5
/
1
6
S
1
6
W
1
6
/
1
7
S
1
7
W
1
7
/
1
8
S
1
8
W
1
8
/
1
9
S
1
9
W
1
9
/
2
0
S
2
0
W
2
0
/
2
1
S
2
1
W
2
1
/
2
2
S
2
2
W
2
2
/
2
3
S
2
3
W
2
3
/
2
4
S
2
4
W
2
4
/
2
5
S
2
5
W
2
5
/
2
6
S
2
6
W
2
6
/
2
7
Actuals Forecast
MM
c
f
d
PaCNW
Actuals Average Forecast Average Forecast 1 Average Forecast 2
6,
1
7
1

6,
5
4
0

6,
2
1
4

6,
7
8
0

5,
7
5
7

6,
9
0
0

5,
6
8
6

6,
9
0
8

5,
7
4
6

6,
9
3
4

5,
6
3
6

6,
8
1
4

5,
5
6
7

6,
8
8
7

5,
5
4
5

6,
8
9
8

5,
5
9
2

6,
9
0
6

5,
5
8
1

6,
9
3
5

5,
6
3
5

7,
1
4
8

5,
8
2
8

7,
3
0
4

5,
9
6
4

7,
3
6
6

-
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
S
1
4
W
1
4
/
1
5
S
1
5
W
1
5
/
1
6
S
1
6
W
1
6
/
1
7
S
1
7
W
1
7
/
1
8
S
1
8
W
1
8
/
1
9
S
1
9
W
1
9
/
2
0
S
2
0
W
2
0
/
2
1
S
2
1
W
2
1
/
2
2
S
2
2
W
2
2
/
2
3
S
2
3
W
2
3
/
2
4
S
2
4
W
2
4
/
2
5
S
2
5
W
2
5
/
2
6
S
2
6
W
2
6
/
2
7
Actuals Forecast
MM
c
f
d
CALIFORNIA
Actuals Average Forecast Average Forecast 1 Average Forecast 2
50
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 518 of 829
•James River By-Pass
ISD -June 2016
•150,000 Gj/d
•A/BC Border Capability –2.2 Bcf/d
•Sundre Crossover
•ISD -April 2018
•245,000 Gj/d
•A/BC Border Capability –2.43 Bcf/d
•Winchell Unite Addition
•ISD –November 2019
•120,000 Gj/d
•Estimated A/BC Border Capability –2.54 Bcf/d
•West Path Expansion
•ISD –June 2020
•288,000 Gj/d
•Estimated A/BC Border Capability –2.81 Bcf/d
NGTL West Path Expansion Summary
51
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 519 of 829
•Total Available at Kingsgate May Vary Depending upon
Foothills Markets and Fuel Usage
•Daily Kingsgate Supply Available estimated:
•Early 2018 2.33 Bcf/d*
•November 2019 2.44 Bcf/d*
•June 2020 2.71 Bcf/d*
*(estimates approx. 100,000dth/d scheduled on FTBC system)
•Current GTN Kingsgate Receipt Capability:
•Best Efforts –2.87 Bcf/d
•Capability impacted by seasonal ambient temps and physical
flow path
Impact on Kingsgate Supply
52
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 520 of 829
•Recent GTN Open Seasons to Contract Available Capacity
•Open Seasons Process Ran–December 2017 thru January 2018
•Pre-arranged –Kingsgate to Malin Path
•8 “Packages” totaling approx. 348,610 Dth/d
•Contract Start Dates of Nov. 2019 and Nov. 2020
•All contracted long-term
•All Capacity Awarded to Pre-arranged Entities
•Remaining Available Capacity –Kingsgate to Malin Path
•139,400 dth/d
•Effective Date(s) –Any Date April 1, 2018 or Later
•Unlimited Term
•All Offered Capacity Awarded
Impact of Kingsgate Supply on GTN
53
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 521 of 829
•Considerable Interest in Additional Kingsgate Sourced GTN Capacity
•GTN Exploring Expansion Options
•“Market Pull” Required
•Mainline
•New Pipelines or Laterals –Trail West
•ROFR Open Season Process
•Contract Renewals
•2023 Contract Cliff
•GTN Rate Case Update
•GTN Full Haul Rate Drops to $0.285 Effective 1/1/2020 thru 12/31/2021
•Kingsgate to Stanfield -$0.146 Dth/d
•Kingsgate to Spokane -$0.076 Dth/d
•“Come Back” Provision Requires New Rates Effective 1/1/2022
•Rate Case Preparation in 2021
•Recent Contracting and Facility Upgrades will Impact Rates
Impact of Kingsgate Supply on GTN
54
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 522 of 829
NGTL and Foothills Pipelines Update
55
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 523 of 829
56
Avista -Supply Side Resources
Eric Scott
Manager of Natural Gas Resources
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 524 of 829
5757
Interstate Pipeline Resources
•The Integrated Resource Plan (IRP) brings together the various
components necessary to ensure proper resource planning for
reliable service to utility customers.
•One of the key components for natural gas service is interstate
pipeline transportation. Low prices, firm supply and storage
resources are rendered meaningless to a utility customer without
the ability to transport the gas reliably during cold weather events.
•Acquiring firm interstate pipeline transportation provides the most
reliable delivery of supply.
57
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 525 of 829
5858
Pipeline Overview
58
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 526 of 829
595959
Pipeline Overview
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 527 of 829
60
Avista holds firm transportation capacity on 6 interstate
pipelines:
Avista’s Transportation Contract Portfolio
60
Pipeline Expirations Base Capacity Dth
Williams NWP 2019 –2042 (2035)290,000
Westcoast
(Enbridge)
2026 10,000
TransCanada -
NGTL
2019-2028 208,000
TransCanada -
Foothills
2020-2028 204,000
TransCanada -
GTN
2023-2028 240,000 –321,000
166,000 –212,000
TransCanada -
Tuscarora
2020 200
*Includes Thermal Transport
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 528 of 829
6161
Contract Provisions -NWP
61
•Grandfathered Unilateral Evergreen (TF-1, TF-2, SGS-2F)
–Roll-over 1 year
–Shipper has sole option to extend or renew
•Standard Unilateral Evergreen
–Roll-over 1 year
–5 year termination provision
•Standard Bilateral Evergreen
–Either transporter OR shipper may terminate
•Right of First Refusal (ROFR)
–Provides “last look”
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 529 of 829
6262
Contract Provisions -GTN
62
•Unilateral Evergreen
–Shipper alone may terminate contract
•Bilateral Evergreen
–Either transporter OR shipper may terminate contract
•Right of First Refusal (ROFR)
–Provides “last look”
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 530 of 829
63
Pipeline Contracting
Simply stated: The right to move (transport) a
specified amount of gas from Point A to Point B
A B
63
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 531 of 829
6464
Contract Types
64
•Firm transport
–Point A to Point B
•Alternate firm
–Point C to Point D
•Seasonal firm
–Point A to Point B but only in winter
•Interruptible
–Maybe it flows, maybe it doesn’t
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 532 of 829
6565
Rate Design
65
•Postage stamp (NWP)
–1 mile or a thousand miles –same price
–Plus variable
•Mileage (GTN)
–Fee per mile
–Plus variable
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 533 of 829
66
NWP Rate Case Settlement
•New rates in effect January 1, 2018
–Good through September 30, 2018
•Rates further reduced October 1, 2018 –December 31, 2022
•Mandatory come-back –January 1, 2023
•No stay-out after October 2, 2018
66
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 534 of 829
67
GTN Rate Case Settlement
•New rates in effect January 1, 2016
–Good through December 31, 2019
•Rates further reduced January 2020 –December 2021
•Mandatory come-back –January 1, 2022
•No stay-out
67
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 535 of 829
686868
Pipeline Capacity –Segmented Releases
Example
Sipi
JP
Spokane
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 536 of 829
6969
Northwest Pipeline Tariff Rate:$0.400
Effective rate –segmentation example:$0.133
Effective Rate -#100010
Contract CD Rate Path Annual $
#100010 19,432 Dth $0.40 Sumas -Spokane $2,837,000
Released (19,432 Dth)$0.40 Sumas -Spokane ($2,837,000)
#1 19,432 Dth $0.40 JP -Spokane $2,837,000
#2 19,432 Dth -0-Sumas -JP -0-
Released (19,432 Dth)-0-Sumas -JP -0-
#2a 19,432 Dth -0-Sumas -Sipi -0-
#2b 19,432 Dth -0-Sipi -JP -0-
Total 58,296 Dth $2,837,000
69
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 537 of 829
7070
Capacity Releases
70
During 2017, AVA received $9.6mm in release “revenue”
Example:
AVA released 35,000 Dths/day at full tariff rate to Clark PUD
until 10/31/2025 recapturing over $5.2mm annually all of
which goes to customers.
Time Duration Rate
Annual 1 year Full rate
Long-term 1+ year –31.5 years Full rate
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 538 of 829
7171
Storage –A valuable asset
•Peaking resource
•Improves reliability
•Enables capture of price spreads between time
periods
•Enables efficient counter cyclical utilization of
transportation (i.e. summer injections)
•May require transportation to service territory
•In-service territory storage offers most flexibility
71
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 539 of 829
72
Washington and Idaho
Owned Jackson Prairie
•7.7 Bcf of Capacity with approximately 346,000 Dth/d of
deliverability
Oregon
Owned Jackson Prairie
•823,000 Dth of Capacity with approximately 52,000 Dth/d of
deliverability
Leased Jackson Prairie
•95,565 Dth of Capacity with approximately 2,654 Dth/d of
deliverability
Avista’s Storage Resources
72
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 540 of 829
7373
The Facility
•Jackson Prairie is a
series of deep,
underground reservoirs
–basically thick,
porous sandstone
deposits. •The sand layers lie
approximately 1,000 to
3,000 feet below the
ground surface. •Large compressors and
pipelines are employed
to both inject and
withdraw natural gas at
54 wells spread across
the 3,200 acre facility.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 541 of 829
7474
1.2 Bcf per day (energy equivalent)
•10 coal trains with 100 -50 ton cars each
•29 -500 MW gas-fired power plants
•13 Hanford-sized nuclear power plants
•2 Grand Coulee-sized hydro plants (biggest in US)
46 Bcf of stored gas
•12” pipeline 11,000,000 miles long (226,000 miles to the moon)
•1,400 Safeco Fields (Baseball Stadiums)
•Average flow of the Columbia River for 2 days
•Cube -3,550 feet on a side
Jackson Prairie Interesting Energy Comparisons
74
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 542 of 829
75
Natural Gas Liquids -Extraction
•Gas from the Western Canadian
Sedimentary Basin has many
“liquids” that can be extracted and
sold
•Nearly $2,100,000
Methane Molecule
75
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 543 of 829
76
Distribution System Planning
Terrence Browne PE,
Senior Gas Planning Engineer
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 544 of 829
7777
Mission
•Using technology to plan and design a safe, reliable, and
economical distribution system
77
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 545 of 829
7878
Gas Distribution Planning
•Service Territory and Customers
•Scope of Gas Distribution Planning
•SynerGi Load Study Tool
•Planning Criteria
•Interpreting Results
•Long-term Planning Objectives
•Historical Temperatures
•Monitoring Our System
•Solutions
•Gate Station Capacity Review
•Project Examples
78
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 546 of 829
79
–Population of service area 1.5 million
371,000 electric customers
348,000 natural gas customers
Service Territory and Customer Overview
•Serves electric and natural gas customers in eastern Washington and northern Idaho,
and natural gas customers in southern and eastern Oregon
79
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 547 of 829
80
Seasonal Demand Profiles
80
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 548 of 829
8181
Our Planning Models
•122 cities
•40 load study models
81
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 549 of 829
8282
__
Pup Pdown
Q
L ||
D
__
5 Variables for Any Given Pipe
82
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 550 of 829
8383
Scope of Gas Distribution Planning
Supplier Pipeline
High Pressure Main
Reg.
Distribution Main and Services
Reg.Reg.
Gate
Sta.
83
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 551 of 829
8484
Scope of Gas Distrib. Planning cont.
Gate
Sta.
Reg.Reg.Reg.
Reg.Reg.
Gate
Sta.
Gate
Sta.
84
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 552 of 829
8585
SynerGi (SynerGEE, Stoner) Load Study
•Simulate distribution behavior
•Identify low pressure areas
•Coordinate reinforcements with expansions
•Measure reliability
85
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 553 of 829
86
35 DD
30’ F
86
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 554 of 829
87
Preparing a Load Study
•Estimating Customer Usage
•Creating a Pipeline Network
•Join Customer Loads to Pipes
•Convert to Load Study
87
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 555 of 829
8888
Estimating Customer Usage
•Gathering Data
–Days of service
–Degree Days
–Usage
–Name, Address, Revenue Class, Rate Schedule…
88
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 556 of 829
8989
Estimating Customer Usage cont.
•Degree Days
–Heating (HDD)
–Cooling (CDD)
•Temperature -Usage Relationship
–Load vs. HDD’s
–Base Load (constant)
–Heat Load (variable)
–High correlation with residential
Avg. Daily Heating Cooling
Temperature Degree Days Degree Days
('Fahrenheit) (HDD) (CDD)
85 20
80 15
75 10
70 5
65 0 0
60 5
55 10
50 15
45 20
40 25
35 30
30 35
25 40
20 45
15 50
10 55
5 60
4 61
0 65
-5 70
-10 75
-15 80
-17 82
89
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 557 of 829
90
90
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 558 of 829
91
Heat Base
91
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 559 of 829
9292
Estimating Customer Usage cont.
•Peaking Factor
–Peaking Factor = 6.25% of daily load
–“Observed ratio” of greatest hourly flow to total daily flow at
Gate Stations
•Industrial Customers
–Model maximum hourly usage per Contractual Agreement
–Firm Transportation customers only
–Low Temperature-Usage correlation
92
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 560 of 829
9393
Creating a Pipeline Model
•Elements
–Pipes, regulators, valves
–Attributes: Length, internal diameter,
roughness
•Nodes
–Sources, usage points, pipe ends
–Attributes: Flow, pressure
93
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 561 of 829
9494
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 562 of 829
9595
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 563 of 829
9696
Join Customer Loads to a Model
•Residential and commercial loads are assigned to pipes
•Industrial or other large loads are assigned to nodes
96
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 564 of 829
9797
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 565 of 829
9898
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 566 of 829
9999
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 567 of 829
100100
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 568 of 829
101101
Balancing Model
•Simulate system for any temperature
–HDD’s
•Solve for pressure at all nodes
101
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 569 of 829
102
35 DD
30˚F
102
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 570 of 829
103103
Validating Model
103
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 571 of 829
104
Validating Model cont.
104
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 572 of 829
105
Validating Model cont.
105
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 573 of 829
106
Validating Model cont.
106
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 574 of 829
107107
•Simulate recorded condition
•Electronic Pressure Recorders
–Do calculated results match field data?
•Gate Station Telemetry
–Do calculated results match source data?
•Possible Errors
–Missing pipe
–Source pressure changed
–Industrial loads
Validating Model cont.
107
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 575 of 829
108108
•Reliability during design HDD
–Spokane 82 HDD
–Medford 61 HDD
–Klamath Falls 72 HDD
–La Grande 74 HDD
–Roseburg 55 HDD
•Maintain minimum of 15 psig in system at all times
–5 psig in lower MAOP areas
Planning Criteria
108
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 576 of 829
109109
•Reliability during design HDD
–Spokane 82 HDD (avg. daily temp. -17’ F)
–Medford 61 HDD (avg. daily temp. 4’ F)
–Klamath Falls 72 HDD (avg. daily temp. -7’ F)
–La Grande 74 HDD (avg. daily temp. -9’ F)
–Roseburg 55 HDD (avg. daily temp. 10’ F)
•Maintain minimum of 15 psig in system at all times
–5 psig in lower MAOP areas
Planning Criteria
109
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 577 of 829
110
35 DD
30˚F
110
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 578 of 829
111
50 DD
15˚F
111
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 579 of 829
112
65 DD
0˚F
112
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 580 of 829
113113
Interpreting Results
•Identify Low Pressure Areas
–Number of feeds
–Proximity to source
•Looking for Most Economical Solution
–Length (minimize)
–Construction obstacles (minimize)
–Customer growth (maximize)
113
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 581 of 829
114114114
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 582 of 829
115115115
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 583 of 829
116
65 DD
0’ F
116
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 584 of 829
117
65 DD
0’ F
R
117
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 585 of 829
118
82 DD
-17’ F
R
118
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 586 of 829
119119
Long-term Planning Objectives
•Future Growth/Expansion
•Design Day Conditions
•Facilitate Customer Installation Targets
119
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 587 of 829
120120
Historical Temperatures
120
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 588 of 829
121121
•La Grande 74 HDD
•Roseburg 55 HDD
•Spokane 82 HDD
•11/23/10: 64 HDD “Artic Blast”
•Medford 61 HDD
•Klamath Falls 72 HDD
Historical Temperatures
121
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 589 of 829
122122
•La Grande 74 HDD
•12/8/13: 65 HDD “Polar Vortex”
•Roseburg 55 HDD
•12/8/13: 44 HDD“Polar Vortex”
•Spokane 82 HDD
•11/23/10: 64 HDD “Artic Blast”
•12/6/13 and 12/8/13: 58 HDD “Polar Vortex”
•Medford 61 HDD
•12/8/13: 52 HDD “Polar Vortex”
•Klamath Falls 72 HDD
•12/8/13: 72 HDD “Polar Vortex”
Historical Temperatures
122
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 590 of 829
123123
•La Grande 74 HDD
•12/8/13: 65 HDD “Polar Vortex”
•Roseburg 55 HDD
•12/8/13: 44 HDD“Polar Vortex”
•Spokane 82 HDD
•11/23/10: 64 HDD “Artic Blast”
•12/6/13 and 12/8/13: 58 HDD “Polar Vortex”
•1/1/16: 55 HDD
•Medford 61 HDD
•12/8/13: 52 HDD “Polar Vortex”
•Klamath Falls 72 HDD
•12/8/13: 72 HDD “Polar Vortex”
•1/2/16: 62 HDD
Historical Temperatures
123
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 591 of 829
124124
•La Grande 74 HDD
•12/8/13: 65 HDD “Polar Vortex”
•1/5/17: 65 HDD
•Roseburg 55 HDD
•12/8/13: 44 HDD“Polar Vortex”
•1/5/17: 38 HDD
•Spokane 82 HDD
•11/23/10: 64 HDD “Artic Blast”
•12/6/13 and 12/8/13: 58 HDD “Polar Vortex”
•1/1/16: 55 HDD
•1/5/17: 59 HDD
•Medford 61 HDD
•12/8/13: 52 HDD “Polar Vortex”
•1/5/17: 42 HDD
•Klamath Falls 72 HDD
•12/8/13: 72 HDD “Polar Vortex”
•1/2/16: 62 HDD
•1/5/17: 71 HDD
Historical Temperatures
124
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 592 of 829
125125
Monitoring Our System
•Electronic Pressure Recorders
•Daily Feedback
•Real time if necessary
•Validates our Load Studies
125
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 593 of 829
126126
Real-time Pressure & Flow Monitoring
126
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 594 of 829
127127
ERX #015
Loon Lake, WA
127
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 595 of 829
128128
ERX #015: Loon Lake, WA
12/17/2016
01/05/2017
12/29/2016
128
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 596 of 829
129129
ERX #007
West Medford 6
psig System
129
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 597 of 829
130130
ERX #007: West Medford 6 psig System, OR
12/18/2016
12/26/2016
01/06/2017
130
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 598 of 829
131131
Solutions: short-term
131
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 599 of 829
132132
Solutions: long-term
State Feet of pipe
Idaho 37,800
Oregon 62,300
Washington 121,100
1-5
years
next
132
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 600 of 829
133133
Gas Planning Layers
•Gas Planning Proposals
•Gas Planning AOI
133
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 601 of 829
134134
Gas Planning Proposals
Add
4”
134
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 602 of 829
135135
Gas Planning AOI
Low
pressure
Future
Growth
135
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 603 of 829
136136
Gate Station Capacity Review
136
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 604 of 829
137137
y = 0.1278x + 3.5481
R² = 0.64840
5
10
15
20
25
30
35
0 10 20 30 40 50 60 70 80 90 100
Fl
o
w

(
m
c
f
h
)
HDDCity Gate Station # X
Daily Peak Flow (mcfh)
GTN Physical Capacity
(31 mcfh)
Design Day Peak Flow
(14.0 mcfh; 82 HDD)
Contractual Amount
(21.9 mcfh, Diversity
Factor = 1.5)
Linear (Daily Peak Flow
(mcfh))
82 HDD
Gate Station Capacity Review (example)
137
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 605 of 829
138138
y = 2.1146x + 65.605
R² = 0.63080
50
100
150
200
250
300
0 10 20 30 40 50 60 70 80 90 100
Fl
o
w

(
m
c
f
h
)
HDD
City Gate Station # Y
Daily Peak Flow (mcfh)
NWP Physical Capacity
(206.0 mcfh, Diversity
Factor = 1.44)
Design Day Peak Flow
(239.0 mcfh; 82 HDD)
Contractual Amount
(121.8 mcfh, Diversity
Factor = 1.44)
Linear (Daily Peak Flow
(mcfh))
82 HDD
Gate Station Capacity Review (example)
138
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 606 of 829
139
Current Projects and
Examples
139
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 607 of 829
140
Hayden Lake HighPressure
Reinforcement
Coeur d’Alene, ID
140
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 608 of 829
141
< 1.900
Facilities Color By:Internal Diameter (inches)
1.900 –2.800
2.800 –3.670
3.670 –5.400
5.400 –7.900
7.900 –10.000
10.000 –12.000
12.000 –13.000
> 13.000
Hayden Lake
Completed Proposal:
17,300’ 6” HP steel
2 new regulator
stations
141
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 609 of 829
142142
End of existing 6” HP
R
R
17,300’ of 6” Steel HP
and two regulator
stations
Tie-in to
4” IP
Main
Tie-in to
4” IP
Main
142
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 610 of 829
143
Rathdrum
Post Falls
Coeur d’Alene
0.01 –15.00
Facilities Color By:Pressure (psig)
15.01 –30.00
30.01 –45.00
45.01 –60.00
> 60.01
0.00
Hayden Lake HP Reinforcement
Before reinforcement
143
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 611 of 829
144
Hayden Lake HP Reinforcement
Before reinforcement
Rathdrum
Post Falls
Coeur d’Alene
0.01 –15.00
Facilities Color By:Pressure (psig)
15.01 –30.00
30.01 –45.00
45.01 –60.00
> 60.01
0.00
144
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 612 of 829
145
Hayden Lake HP Reinforcement
Before reinforcement
Rathdrum
Post Falls
Coeur d’Alene
0.01 –15.00
Facilities Color By:Pressure (psig)
15.01 –30.00
30.01 –45.00
45.01 –60.00
> 60.01
0.00
145
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 613 of 829
146
Hayden Lake HP Reinforcement
Before reinforcement
Rathdrum
Post Falls
Coeur d’Alene
0.01 –15.00
Facilities Color By:Pressure (psig)
15.01 –30.00
30.01 –45.00
45.01 –60.00
> 60.01
0.00
146
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 614 of 829
147
Hayden Lake HP Reinforcement
Before reinforcement
Rathdrum
Post Falls
Coeur d’Alene
0.01 –15.00
Facilities Color By:Pressure (psig)
15.01 –30.00
30.01 –45.00
45.01 –60.00
> 60.01
0.00
147
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 615 of 829
148
Completed Proposal:
17,300’ 6” HP steel
2 new regulator stations
Hayden Lake HP Reinforcement
After reinforcement
Rathdrum
Post Falls
Coeur d’Alene
0.01 –15.00
Facilities Color By:Pressure (psig)
15.01 –30.00
30.01 –45.00
45.01 –60.00
> 60.01
0.00
148
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 616 of 829
149
Hayden Lake HP Reinforcement
After reinforcement
Completed Proposal:
17,300’ 6” HP steel
2 new regulator stations
Rathdrum
Post Falls
Coeur d’Alene
0.01 –15.00
Facilities Color By:Pressure (psig)
15.01 –30.00
30.01 –45.00
45.01 –60.00
> 60.01
0.00
149
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 617 of 829
150150
Portable Pressure Monitor
Monitors
the system
pressure
150
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 618 of 829
151151
Hayden Lake Pressures Before & After
After Reinforcement
Before
Reinforcement
12 ˚F
31 psig
11 ˚F
43 psig
151
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 619 of 829
152152
Hayden Lake H.P. Reinforcement
152
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 620 of 829
153
East Medford H.P.
Reinforcement
Medford, OR
153
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 621 of 829
154154
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 622 of 829
155
Medford
Completed
Proposal:
16,000’ 12” HP steel < 1.900
Facilities Color By:Internal Diameter (inches)
1.900 –2.800
2.800 –3.670
3.670 –5.400
5.400 –7.900
7.900 –10.000
10.000 –12.000
12.000 –13.000
> 13.000
155
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 623 of 829
156
285 psig
272 psig
283 psig
End of HP
Line 272
psig
East Medford HP Reinforcement
Before reinforcement
3.01 –15.00
Facilities Color By:Pressure (psig)
15.01 –30.00
30.01 –45.00
45.01 –60.00
> 60.01
0.00 –3.00
156
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 624 of 829
157
East Medford HP Reinforcement
Before reinforcement
End of HP
Line 216
psig
270 psig
280 psig
217 psig
3.01 –15.00
Facilities Color By:Pressure (psig)
15.01 –30.00
30.01 –45.00
45.01 –60.00
> 60.01
0.00 –3.00
157
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 625 of 829
158
East Medford HP Reinforcement
Before reinforcement
End of HP
Line 50 psig246 psig
271 psig
55 psig
3.01 –15.00
Facilities Color By:Pressure (psig)
15.01 –30.00
30.01 –45.00
45.01 –60.00
> 60.01
0.00 –3.00
158
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 626 of 829
159
Medford
Completed Proposal:
16,000’ 12” HP steel
East Medford HP Reinforcement
After reinforcement
281 psig
282 psig
443 psig
3.01 –15.00
Facilities Color By:Pressure (psig)
15.01 –30.00
30.01 –45.00
45.01 –60.00
> 60.01
0.00 –3.00
159
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 627 of 829
160
East Medford HP Reinforcement
After reinforcement
277 psig
278 psig
436 psig
3.01 –15.00
Facilities Color By:Pressure (psig)
15.01 –30.00
30.01 –45.00
45.01 –60.00
> 60.01
0.00 –3.00
Medford
Completed Proposal:
16,000’ 12” HP steel
160
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 628 of 829
161161
East Medford H.P. Reinforcement
161
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 629 of 829
162
North Spokane H.P.
Reinforcement
Spokane, WA
162
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 630 of 829
163
North Spokane
Completed Proposal:
11,500’ 8” HP steel
1 new regulator station < 1.900
Facilities Color By:Internal Diameter (inches)
1.900 –2.800
2.800 –3.670
3.670 –5.400
5.400 –7.900
7.900 –10.000
10.000 –12.000
12.000 –13.000
> 13.000
163
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 631 of 829
164164
< 1.900
Facilities Color By:Internal Diameter (inches)
1.900 –2.800
2.800 –3.670
3.670 –5.400
5.400 –7.900
7.900 –10.000
10.000 –12.000
12.000 –13.000
> 13.000
North Spokane
Proposed 6” route
(approx. 2 miles)
Kaiser
Property
164
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 632 of 829
165
North Spokane HP Reinforcement
Before reinforcement
0.01 –15.00
Facilities Color By:Pressure (psig)
15.01 –30.00
30.01 –45.00
45.01 –60.00
> 60.01
0.00
165
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 633 of 829
166
North Spokane HP Reinforcement
Before reinforcement
0.01 –15.00
Facilities Color By:Pressure (psig)
15.01 –30.00
30.01 –45.00
45.01 –60.00
> 60.01
0.00
166
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 634 of 829
167
North Spokane HP Reinforcement
Before reinforcement
0.01 –15.00
Facilities Color By:Pressure (psig)
15.01 –30.00
30.01 –45.00
45.01 –60.00
> 60.01
0.00
167
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 635 of 829
168
North Spokane HP Reinforcement
Before reinforcement
0.01 –15.00
Facilities Color By:Pressure (psig)
15.01 –30.00
30.01 –45.00
45.01 –60.00
> 60.01
0.00
168
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 636 of 829
169
North Spokane HP Reinforcement
Before reinforcement
0.01 –15.00
Facilities Color By:Pressure (psig)
15.01 –30.00
30.01 –45.00
45.01 –60.00
> 60.01
0.00
169
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 637 of 829
170
North Spokane
Completed Proposal:
11,500’ 8” HP steel
1 new regulator station
North Spokane HP Reinforcement
After reinforcement
0.01 –15.00
Facilities Color By:Pressure (psig)
15.01 –30.00
30.01 –45.00
45.01 –60.00
> 60.01
0.00
170
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 638 of 829
171
North Spokane
Completed Proposal:
11,500’ 8” HP steel
1 new regulator station
North Spokane HP Reinforcement
After reinforcement
0.01 –15.00
Facilities Color By:Pressure (psig)
15.01 –30.00
30.01 –45.00
45.01 –60.00
> 60.01
0.00
171
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 639 of 829
172172
North Spokane H.P. Reinforcement
172
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 640 of 829
173
Questions and Discussion
Mission
Using technology to plan and design a
safe, reliable, and economical distribution
system
173
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 641 of 829
174
Renewable Natural Gas
Jody Morehouse
Director of Natural Gas
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 642 of 829
175175
What is Renewable Natural Gas (RNG)?
Renewable
Natural Gas =
Natural Gas
175
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 643 of 829
176176
Carbon (CO2) Emission Reduction
•Carbon reduction
–LDC pathway to reduce emissions
through “de-carbonized” gas stream
–Can provide customers a new energy
choice
–Gives communities another means in
meeting ambitious climate change
commitments
•Renewable Fuel Standard (RFS) & Low
Carbon Fuel Standards (LCFS)
–Significant value for RNG in
transportation sector in CA and OR
Why does RNG matter?
Source: State of Washington Deep Decarbonization Pathways Project 12/16/2016
176
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 644 of 829
177177
Other
•Reduces waste remediation costs
•Reduces odors, water & air pollution,
pathogens originating from waste
streams
•Creates local jobs and generates
revenue for cities and businesses
•New local sources for gas supply
Other Benefits of RNG
“It reminds me of the Mr. Fusion Home Energy
Reactor in the movie Back to the Future”
Dan Kirschner, NWGA Executive Director, on WA HB 2580 RNG Bill
177
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 645 of 829
178178
Federal Renewable Fuel Standard Program
**D3**D4-
D5
**D6
Source: EIA
**D-codes are an approximation; actual code determined by EPA formula
Mandates renewable fuel to replace % of petroleum-based
transportation fuel
178
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 646 of 829
179179
RFS and LCFS Effect on RNG Value
RIN = renewable identification number
Source: CARB
Source: EPA
179
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 647 of 829
180180
GHG CO2 Reductions
180
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 648 of 829
181181
Potential RNG Production
About
420 Bcf
181
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 649 of 829
182182
RNG Projects in North America
•Approx. 120 RNG
projects in North America
•13 of these are located in
the Pacific Northwest
182
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 650 of 829
183183
Oregon SB 344 DOE RNG Update
•Development of an inventory of RNG resources
•Characterization of the opportunities
•Identify barriers to production and utilization
•Policies to promote RNG and remove barriers
•Report due by September 2018
As a means toward feasible reductions in greenhouse gas emissions,
committee to provide recommendations to ODOE regarding:
183
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 651 of 829
184184
Washington SB 2580 RNG Bill
•Requires the Washington State University Extension Energy Program and the Department of
Commerce, in consultation with the Utilities and Transportation Commission, to submit
recommendations on how to promote the sustainable development of RNG to the Governor and
the Legislature by September 1, 2018
“Governor Inslee and Department of Commerce were pleased to request this bill, which received
near unanimous, bipartisan support from the Legislature,” said Peter Moulton, Energy Policy
Section Manager, Washington Department of Commerce.
•Requires the Department of Commerce, in consultation with natural gas utilities and other state
agencies, to explore the development of voluntary gas quality standards for the injection of RNG
into the state’s natural gas pipeline systems
•Reinstate and expand incentives in order to stimulate investment in biogas capture and
conditioning, compression, nutrient recovery, and use of RNG for heating, electricity generation
and transportation fuel
184
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 652 of 829
185185
Oregon and Washington RNG Studies
Source: ODOE RNG Feb. 22, 2018 Presentation
Oregon and
Washington
RNG Production
Potential Info
Coming Soon
Source: Washington State Department of Ecology, 2015. Solid Waste in Washington State: 24th Annual Status Report 185
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 653 of 829
186186
Regional RNG Policies
•California SB 1383: Goal to reduce the economic uncertainty associated
with RNG. Requires LDCs to interconnect at least five dairy projects to the
natural gas pipeline system by January 1, 2018.
–Allows LDCs to recover the costs associated with projects
•British Columbia Green House Gas Reduction Regulation
–Allows for 5% RNG on LDC system
–Allows LDCs to invest and recover costs associated with projects
British Columbia
185
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 654 of 829
187187
Are Avista customers interested in RNG?
Source: Interest expressed through Rogue Valley Clean Cities Coalition per Dry Creek Landfill
Supply
Demand
•Rogue Disposal
•Rogue Valley Transit
•Southern Oregon University
•City of Medford
•City of Ashland
•US Postal Service
•United Parcel Service
•DSU Peterbilt
•Butler Ford
187
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 655 of 829
188188
What are the challenges & barriers?
•California RNG market ($30/Dth v. $2/Dth)
–Vehicle emission incentives shut-out other potential end users
–RIN market is volatile
–No forward pricing for RNG RINs in carbon market
–RFS future beyond 2022 uncertain
–Vehicle market may be approaching saturation in CA
–Too expensive for LDCs to purchase; LDCs could produce RNG cheaper
•Financing for producers challenging
–Future RNG value unknown
–Producer/LDC partnerships for product
•Policies for LDC cost recovery or purchase of not least cost fuel
source
188
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 656 of 829
189189
Next Steps for RNG
•Model various RNG scenarios for 2018 IRP
•Participate in ODOE SB 344 Advisory Council
•Support efforts with WSU and WA SB 2580
•Evaluate customer interest in RNG products
•Evaluate potential RNG projects in Avista
service territory
189
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 657 of 829
190
Power to Gas
Tom Pardee
Manager of Natural Gas Planning
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 658 of 829
191191
Power to Gas
•Power to Gas (PtG)is a process using power to separate water into
hydrogen and oxygen
•Both hydrogen and methane can be stored, as a % of gas, in the existing
gas grid or used in the mobility sector (blend up to 20%)
•PtG can help to balance excess power from intermittent sources like wind
and solar
•PtG can decarbonize the direct use of natural gas
•PtG economics will advance as more renewables are added and the
technology matures
•Short term and seasonal energy storage
•Stored in the existing gas pipeline
https://youtu.be/lQWIubQyaao191
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 659 of 829
192
PtG Process
Source: http://www.europeanpowertogas.com/about/power-to-gas
192
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 660 of 829
193193
Hydrogen
•The energy factor of H2 Low Heating Value (LHV) is
roughly equivalent to a gallon of gasoline or 114,000btu
–This equates to 8.78 kg of H2LHV per Dth
•Most H2 is currently made from reforming natural gas
•The US Department of Energy expects that over the long
term the production of hydrogen will be increased with
production from renewables
193
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 661 of 829
194194
Water Electrolysis for PtG
•Water electrolysis is a mature and well understood
technology with 3 different types of electrolysis
technologies in these PtG processes
–Alkaline electrolysis (AEL)
•Most mature and well understood technology
•Best when coupled with an intermittent power supply
–Polymer electrolyte membrane (PEM)
•Fast cold start with a high purity of H2
•Limited Life expectancy
–Solid oxide electrolysis (SOEC)
•High electrical efficiency
•Currently not as stable when paired with intermittent power supply
194
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 662 of 829
195
PtG Comparison
Benefits
•Cleans up the grid using
excess power
•Stores the energy for future
use
•Hydrogen is relatively safe as if
it is released it quickly dilutes
into a non-flammable
concentration
Obstacles
•High cost (currently) when
compared to energy in a Dth
combined with current prices of
natural gas
•Hydrogen can only be stored in
the pipeline as a % of gas though
this is primarily cause by end-use
restrictive conditions
–Risks increase significantly if
over 50% mix
•Hydrogen is lighter than air and
diffuses rapidly (3.8x faster than
natural gas) making it more
difficult to contain
195
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 663 of 829
Fuel Cell Technologies Office |5
Cost Status and Targets: Dispensed H2
Continued R&D is needed to reduce H2 production & delivery costs
High-
Volume*
Cost Status
$16/kg
to
$10/kg
$7.5/kg
to
$5/kg
$4/kg
Ultimate
Target
Early Market
Target
$7/kg
Targets
*high-volume projections assume economies of scale
(untaxed)
Low-
Volume
earlymarkets
using NG
LOW-VOLUME
Early market status based on low-cost
H2 from NG (<$2/kg) plus delivery &
dispensing
R&D innovations are essential to
reduce H2 delivery & dispensing costs
HIGH-VOLUME
Projected status based on large-scale
deployments of a portfolio of H2
production, delivery & dispensing
options
R&D of diverse, sustainable hydrogen
production pathways remains vital
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 664 of 829
197197
Next Steps
•Model at an estimated rate of $4 per kg of H2
based on DOE technical target by 2020
–This is the untaxed cost of hydrogen produced,
delivered, and dispensed to the vehicle
•It does not include off-board cooling or regeneration of
chemical hydrogen storage materials
–Source: https://www.energy.gov/eere/fuelcells/doe-technical-targets-onboard-hydrogen-storage-light-duty-vehicles
•Look for a consultant or ways to more accurately
estimate the cost of H2 in Avista’s territory
197
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 665 of 829
198
Initial Results and Proposed Scenarios
Kaylene Schultz
Natural Gas Analyst
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 666 of 829
199199
First Year Peak Demand Unserved
Washington
199
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 667 of 829
200200
First Year Peak Demand Unserved
Idaho
200
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 668 of 829
201201
First Year Peak Demand Unserved
Medford
201
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 669 of 829
202202
First Year Peak Demand Unserved
Roseburg
202
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 670 of 829
203203
First Year Peak Demand Unserved
Klamath Falls
203
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 671 of 829
204204
First Year Peak Demand Unserved
La Grande
204
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 672 of 829
205205205
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 673 of 829
206206206
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 674 of 829
207207207
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 675 of 829
208208208
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 676 of 829
209209209
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 677 of 829
210210210
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 678 of 829
211211211
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 679 of 829
212212212
*Assumes average yearly reduction starting in 2018 to achieve 2050 target of 80% below 1990 emissions Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 680 of 829
213213
2018 Proposed Scenarios
213
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 681 of 829
214214
2018 IRP Timeline
•August 31, 2017 –Work Plan filed with WUTC
•January through May 2018 –Technical Advisory Committee
meetings. Meeting topics will include:
–TAC 1: Thursday, January 25, 2018: TAC meeting expectations, review of
2016 IRP acknowledgement letters, customer forecast, and demand-side
management (DSM) update.
–TAC 2: Thursday, February 22, 2018: Weather analysis, environmental
policies, market dynamics, price forecasts, cost of carbon.
–TAC 3: Thursday, March 29, 2018 : Distribution, supply-side resources
overview, overview of the major interstate pipelines, RNG overview and
future potential resources.
–TAC 4: Thursday, May 10, 2018: DSM results, stochastic modeling and
supply-side options, final portfolio results, and 2020 Action Items.
•June 1, 2018 –Draft of IRP document to TAC
•June 29, 2018 –Comments on draft due back to Avista
•July 2018 –TAC final review meeting (if necessary)
•August 31, 2018 –File finalized IRP document
214
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 682 of 829
215
Questions?
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 683 of 829
1
2018 Avista Natural Gas IRP
Technical Advisory Committee Meeting # 4
May 10, 2018
Olympia, WA
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 684 of 829
22
Agenda
•Introductions
•AEG –Idaho and Washington DSM
•ETO –Oregon DSM
•Lunch
•Dynamic DSM
•Sendout Modeling
•Assumptions Review
•Solving for Unserved Demand
•Stochastics
•2016 IRP Action Items
•2018 Highlights
•Wrap-Up and Review schedule
2
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 685 of 829
33
2018 IRP Timeline
•August 31, 2017 –Work Plan filed with WUTC
•January through May 2018 –Technical Advisory Committee
meetings. Meeting topics will include:
–TAC 1: Thursday, January 25, 2018: TAC meeting expectations, review of
2016 IRP acknowledgement letters, customer forecast, and demand-side
management (DSM) update.
–TAC 2: Thursday, February 22, 2018: Weather analysis, environmental
policies, market dynamics, price forecasts, cost of carbon.
–TAC 3: Thursday, March 29, 2018 :Distribution, supply-side resources
overview, overview of the major interstate pipelines, RNG overview and future
potential resources.
–TAC 4: Thursday, May 10, 2018: DSM results, stochastic modeling
and supply-side options, final portfolio results, and 2020 Action Items.
–June 21, 2018–TAC final review meeting to review final stochastics (if
necessary)
•July 2, 2018 –Draft of IRP document to TAC
•July 13, 2018 –Comments on draft due back to Avista
•August 31, 2018 –File finalized IRP document
3
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 686 of 829
Energy solutions. Delivered.
2018 CONSERVATION POTENTIAL
ASSESSMENT
Study Results, Prepared for the Avista DSM Advisory Group
May 10, 2018
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 687 of 829
| 5Applied Energy Group · www.appliedenergygroup.com
CONTENTS
CPA-Related Action Plan Activities
•Measure Screening
•Measure Documentation
•Fully-Balanced TRC
•Barriers To DSM Uptake
Potential Study Summary
•LoadMAP Modeling Approach
•Levels of Potential
Potential Results
•Summary of Potential
•Comparison with Existing Programs
•Comparison with 2016 CPA
Sector-Level Potential, WA and ID (Supplemental Slide Deck)
•Residential
•Commercial
•Industrial
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 688 of 829
CPA-Related Action Plan Activities
Discussion of Action Items
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 689 of 829
| 7Applied Energy Group · www.appliedenergygroup.com
New Activities for 2018 IRP
In the 2018 IRP, ensure that the entity performing the Conservation
Potential Assessment (CPA) evaluates and includes the following
information:
•All conservation measures excluded from the CPA, including those excluded
prior to technical potential determination;
•Rationale for excluding any measure;
•Description of Unit Energy Savings (UES) for each measure included in the CPA; specify
how it was derived and the source of the data;
•Explain the efforts to create a fully-balanced TRC cost effectiveness metric within the
planning horizon. Additionally, while evaluating the effort to eventually revert back to
the TRC, Avista should consult the DSM Advisory Group and discuss appropriate non-
energy benefits to include in the CPA.
In developing the 2018 IRP, discuss with the TAC:
•Discuss the barriers surrounding the uptake of DSM and how Avista can
improve an increased level of achievable potential.(percentage of baseline
dropped from 1.2 (economic) to 0.3 (achievable))
2017-2018 ACTION PLAN
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 690 of 829
| 8Applied Energy Group · www.appliedenergygroup.com
Exclusions from CPA
Recommended Activity:
In the 2018 IRP, ensure that the entity performing the Conservation
Potential Assessment (CPA) evaluates and includes the following
information:
•All conservation measures excluded from the CPA, including those excluded
prior to technical potential determination;
•Rationale for excluding any measure;
Handling in CPA:
•Very few measures were excluded from the current CPA prior to estimation of
technical potential. Those explicitly excluded were highly custom commercial
and industrial controls/process measures that were instead captured under a
retrocommissioning or strategic energy management program.
•Measures that did not pass the economic screen were still counted in within
achievable technical potential, allowing Avista to review for inclusion in
programs if portfolio-level cost-effectiveness allows.
MEASURE SCREENING
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 691 of 829
| 9Applied Energy Group · www.appliedenergygroup.com
Achievable Technical Top Measures in 2018
MEASURE SCREENING
Rank Measure / Technology Achiev.
Technical
UCT Achiev.
Economic Difference
1 Res -Furnace -Direct Fuel -AFUE 95%22,707 19,091 3,616
2 Res -Windows -High Efficiency -Double Pane LowE CL22 9,426 9,426 -1
3 Com -Thermostat -WiFi Enabled -Wi-Fi/interactive thermostat installed 7,719 0 7,719
4 Com -Boiler -AFUE 97%6,337 6,337 0
5 Res -Water Heater <= 55 gal. -Instantaneous -ENERGY STAR (UEF 0.87)4,193 4,193 0
6 Com -Retrocommissioning -HVAC -Optimized HVAC flow and controls 2,809 661 2,148
7 Res -Gas Furnace -Maintenance -Restored to nameplate 80% AFUE 2,203 0 2,203
8 Com -Water Heater -Solar System -Solar system installed 1,812 0 1,812
9 Com -Fryer -ENERGY STAR 1,775 1,775 0
10 Com -Destratification Fans (HVLS) -Fans Installed 1,494 0 1,494
11 Res -Thermostat -Wi-Fi/Interactive -Interactive/learning thermostat 1,343 1,344 -1
12 Com -Gas Boiler -Insulate Steam Lines/Condensate Tank 1,152 1,152 0
13 Res -Insulation -Floor/Crawlspace -R-30 1,132 1,132 0
14 Com -Gas Boiler -Hot Water Reset -Reset control installed 1,123 1,123 0
15 Com -HVAC -Demand Controlled Ventilation -DCV enabled 1,033 1,033 0
16 Com -Thermostat -Programmable -Programmable thermostat installed 937 0 937
17 Res -Water Heater -Solar System -40 sq ft supplemental solar system 858 0 858
18 Com -Insulation -Roof/Ceiling -R-38 847 850 -3
19 Com -Water Heater -TE 0.94 838 838 0
20 Com -Steam Trap Maintenance -Cleaning and maintenance 820 820 0
Subtotal 70,558 49,774 20,784
Total Savings in Year 86,389 61,279 25,110Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 692 of 829
| 10Applied Energy Group · www.appliedenergygroup.com
Documentation of Savings and Other Assumptions
Recommended Activity:
•Description of Unit Energy Savings (UES) for each measure included in the
CPA; specify how it was derived and the source of the data;
Handling in CPA:
•The measure list developed during the CPA includes descriptions of each
measure included. AEG will provide this as an appendix to the final report.
•Source documentation for assumptions, including UES, lifetime, and costs
(including NEIs) may be found in the “Measure Summary” spreadsheet
delivered as an appendix to the final report.
This will include the name of the source and version (if applicable)
MEASURE DOCUMENTATION
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 693 of 829
| 11Applied Energy Group · www.appliedenergygroup.com
Non-Energy Impacts
Recommended Activity:
•Explain the efforts to create a fully-balanced TRC cost effectiveness metric within the planning horizon. Additionally, while evaluating the effort to eventually revert back to the TRC, Avista should consult the DSM Advisory Group and discuss appropriate non-energy benefits to include in the CPA.
Addressed in CPA:
•As we will discuss throughout this presentation, TRC potential was estimated alongside UCT for each measure analyzed. In this study, we expanded the scope of non-energy/non-gas impacts to include the following:
1.10% Conservation Credit in Washington
2.Quantified and monetized non-energy impacts (e.g. water, detergent, wood)
3.Projected cost of carbon in Washington
4.Heating calibration credit for secondary fuels (12% for space heating, 6% for secondary heating)
5.Electric benefits for applicable measures (e.g. cooling savings for smart thermostats, lighting and refrigeration savings for retrocommissioning)
FULLY-BALANCED TRC
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 694 of 829
| 12Applied Energy Group · www.appliedenergygroup.com
Non-Energy Impacts
Recommended Activity:
•Discuss the barriers surrounding the uptake of DSM and how Avista can improve an increased level of achievable potential. (percentage of baseline dropped from 1.2 (economic) to 0.3 (achievable))
Addressed in CPA:
•In 2018, Washington achievable technical potential is at 40% of technical, compared to roughly 25% in the 2016 CPA.
•By 2038, Washington achievable technical potential is at 84% following the Council’s 85% long-term achievability assumption.
Idaho potential is slightly lower due to a program start-up period
•Many measures currently in Avista programs are on fast ramp rates (such as heating and food preparation equipment)
Others may be newer programs or experience substantial implementation barriers (contractors may be less willing to install measures that require crawlspace work)
•Barriers may possibly be alleviated by bundling measures, “cross-selling” additional measures to active participants, and assisting in market transformation initiatives
BARRIERS TO DSM UPTAKE
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 695 of 829
Potential Study Summary
Overview of Objectives, Approach, and Levels of Potential
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 696 of 829
| 14Applied Energy Group · www.appliedenergygroup.com
Space
Heating
75%
Second
ary
Heating
3%
Water Heating
19%
Appliances
1%
Miscellaneous
2%
Residential Gas Use by End Use,
2015
Overview
LOADMAP MODELING APPROACH
Market
Characterization
•Baseline studies
•Utility data
•Secondary data
Identify Demand-side Resources
•EE equipment
•EE measures
•Emerging tech.
Baseline
Projection
•Utility forecasts
•Standards andbuilding codes
Potential
Estimation
•Technical
•Achievable Tech.
•Economic Achiev.
-
2
4
6
8
10
12
14
2015 2019 2023 2027 2031 2035
Dth
Mi
l
l
i
o
n
s
Residential Baseline Projection
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
2018 2019 2022 2028 2038
Dth
Mi
l
l
i
o
n
s
Residential Cumulative Natural Gas
Savings
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 697 of 829
| 15Applied Energy Group · www.appliedenergygroup.com
LEVELS OF POTENTIAL
Technical
Achievable
Technical
UCT and TRC
Economic
Achievable
We estimate three levels of
potential. These are standard
practice for CPAs in the Northwest:
•Technical: everyone chooses the
efficient option when equipment fails
regardless of cost
•Achievable Technical is a subset of
technical that accounts for
achievable participation within utility
programs as well as non-utility
mechanisms, such as regional
initiatives and market transformation
•Achievable Economic is a subset of
achievable technical potential that
includes only cost-effective
measures. Tests considered within
this study include UCT, and TRC. Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 698 of 829
| 16Applied Energy Group · www.appliedenergygroup.com
Three Cost-Effectiveness Tests
ECONOMIC SCREENING
In assessing cost-effective,
achievable potential within Avista’s
Washington and Idaho territories,
AEG utilized two cost tests:
•Utility Cost Test (UCT): Assesses cost-
effectiveness from a utility or
program administrator’s perspective.
•Total Resource Cost Test (TRC):
Assesses cost-effectiveness from the
utility’s and participant’s
perspectives. Includes non-energy
impacts if they can be quantified and
monetized.
Component UCT TRC
Avoided Energy Benefit Benefit
Non-Energy Benefits*Benefit
Incremental Cost Cost
Incentive Cost
Administrative Cost Cost Cost
Non-Energy Costs* (e.g. O&M)Cost
*Council methodology includes monetized
impacts on other fuels within these categories
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 699 of 829
Potential Results
Combined Results Avista’s Residential, Commercial, and Industrial Sectors
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 700 of 829
| 18Applied Energy Group · www.appliedenergygroup.com
Cumulative and Incremental
Over the following slides, we will display potential both as a cumulative
impact on baseline as well as in annual increments
Cumulative potential includes the impacts of potential acquired from the
first year of the study period (2018) through the year of interest, including
effects of measures persistence
•We begin in 2018 for alignment with the current IRP period and to capture
similarities with Avista programs and accomplishments
•This is particularly important in Idaho where programs are restarting and
ramping up
Incremental potential summarizes new impacts realized in any given year
of interest, excluding the effects of measure repurchases
Due to the effect of repurchases, the sum of incremental savings will
always be greater than or equal to the cumulative potential in any given
year
DEFINITIONS OF POTENTIAL
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 701 of 829
| 19Applied Energy Group · www.appliedenergygroup.com
Achievability
All potential “ramps up” over time –all ramp rates are based
on those found within the NWPCC’s Seventh Power Plan
Achievable technical potential reaches 85% of technical by
the end of the study, consistent with the Council assumptions
•Please note Power Council’s ramp rates include potential
realized from outside of utility DSM programs, including regional
initiatives and market transformation
POTENTIAL ESTIMATES
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 702 of 829
| 20Applied Energy Group · www.appliedenergygroup.com
Total Avista Washington, Cumulative Potential
POTENTIAL ESTIMATES
Scenario 2018 2019 2022 2028 2038
Baseline Forecast (Dth)17,221,900 17,418,177 17,878,550 18,517,630 19,498,948
Cumulative Savings (Dth)
UCT Achievable Economic 61,279 133,576 500,422 1,916,441 4,139,016
TRC Achievable Economic 33,893 73,100 276,379 1,297,679 2,420,649
Achievable Technical 86,389 186,065 655,389 2,405,890 4,901,043
Technical 217,202 434,037 1,189,331 3,251,362 5,804,041
Energy Savings (% of Baseline)
UCT Achievable Economic Potential 0.4%0.8%2.8%10.3%21.2%
TRC Achievable Economic Potential 0.2%0.4%1.5%7.0%12.4%
Achievable Technical Potential 0.5%1.1%3.7%13.0%25.1%
Technical Potential 1.3%2.5%6.7%17.6%29.8%
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 703 of 829
| 21Applied Energy Group · www.appliedenergygroup.com
Total Avista Idaho, Cumulative Potential
POTENTIAL ESTIMATES
Scenario 2018 2019 2022 2028 2038
Baseline Forecast (Dth)8,557,178 8,667,149 8,958,733 9,352,011 9,975,077
Cumulative Savings (Dth)
UCT Achievable Economic 26,340 58,352 235,414 965,825 2,107,684
TRC Achievable Economic 9,846 22,432 108,249 635,250 1,204,809
Achievable Technical 37,324 81,526 310,222 1,218,944 2,514,049
Technical 103,071 206,214 582,638 1,660,809 2,993,151
Energy Savings (% of Baseline)
UCT Achievable Economic Potential 0.3%0.7%2.6%10.3%21.1%
TRC Achievable Economic Potential 0.1%0.3%1.2%6.8%12.1%
Achievable Technical Potential 0.4%0.9%3.5%13.0%25.2%
Technical Potential 1.2%2.4%6.5%17.8%30.0%
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 704 of 829
| 22Applied Energy Group · www.appliedenergygroup.com
Total Avista Washington, Cumulative Potential
As the largest sector, residential represents the largest portion of cumulative UCT achievable economic potential (AEP) throughout the study period.
The industrial sector only includes customers eligible for programs, which represent a very small percentage of total industrial consumption.
Some residential measures are not cost-effective on a TRC basis. This is due to the use of full measure costs rather than just a utility’s portion. Inclusion of a heating calibration credit and non-gas impacts somewhat mitigates this effect.
POTENTIAL BY SECTOR
UCT Savings (Dth)2018 2019 2022 2028 2038
Residential 39,979 88,051 345,801 1,362,078 3,107,847
Commercial 20,731 44,393 151,733 547,834 1,021,211
Industrial 569 1,132 2,887 6,528 9,957
Total 61,279 133,576 500,422 1,916,441 4,139,016
0%
20%
40%
60%
80%
100%
2018 2022 2026 2030 2034 2038
UCT AEP Share of Total Savings by Sector
Residential Commercial Industrial
TRC Savings (Dth)2018 2019 2022 2028 2038
Residential 14,920 32,308 139,361 824,953 1,573,939
Commercial 18,376 39,603 134,004 465,827 836,014
Industrial 597 1,188 1,785 6,899 10,696
Total 33,893 73,100 276,379 1,297,679 2,420,649Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 705 of 829
| 23Applied Energy Group · www.appliedenergygroup.com
Total Avista Idaho, Cumulative Potential
As the largest sector, residential represents the largest portion of cumulative UCT achievable economic potential (AEP) throughout the study period. This is slightly larger in Idaho than Washington.
The industrial sector only includes customers eligible for programs, which represent a very small percentage of total industrial consumption.
Some residential measures are not cost-effective on a TRC basis. This is due to the use of full measure costs rather than just a utility’s portion. Inclusion of a heating calibration credit and non-gas impacts somewhat mitigates this effect.
POTENTIAL BY SECTOR
UCT Savings (Dth)2018 2019 2022 2028 2038
Residential 18,354 41,176 174,333 720,226 1,615,844
Commercial 7,417 16,035 58,160 239,015 481,888
Industrial 569 1,140 2,922 6,584 9,952
Total 26,340 58,352 235,414 965,825 2,107,684
TRC Savings (Dth)2018 2019 2022 2028 2038
Residential 3,744 9,243 62,156 458,445 833,329
Commercial 5,529 12,039 43,123 169,784 360,683
Industrial 573 1,150 1,738 7,021 10,797
Total 9,846 22,432 108,249 635,250 1,204,809
0%
20%
40%
60%
80%
100%
2018 2022 2026 2030 2034 2038
UCT AEP Share of Total Savings by Sector
Residential Commercial Industrial
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 706 of 829
| 24Applied Energy Group · www.appliedenergygroup.com
Washington, Comparison with Current Avista Programs
2018 UCT achievable economic estimates are lower than Avista’s 2017 accomplishments and 2018 Plan
•Furnaces potential is lower, but unit installations are similar to current levels -indicating a drop in unit energy savings due to new construction installations and the 2015 WSEC.
•Smart thermostat potential is mapped to the Council’s electric ramp rate
•Windows represent substantial potential, in line with 2017 accomplishments.
•ENERGY STAR home savings in Washington have are lower due to the impacts of 2015 WSEC –but not to the level of the RTF, who assumes everyone will be installing high-efficiency water heaters
Anecdotal evidence from builders indicates that this is not the case
RESIDENTIAL ACCOMPLISHMENTS
2018 UCT Achievable
Economic (Dth)
2017
Accomplish
2018
Plan
LoadMAP
2018 ATP
Furnace 40,003 28,600 19,091
Boiler 453 0 619
Water Heater 6,621 1,042 4,257
ENERGY STAR Homes 122 365 294
Smart Thermostat 4,884 2,340 1,344
Programmable TStat.0 55 0
Ceiling Insulation 540 280 1,072
Wall Insulation 218 240 904
Floor Insulation 66 266 1,135
Doors 40 63 0
Windows 8,911 15,940 9,426
Air Sealing 207 112 0
Duct Insulation 30 144 367
Duct Sealing 48 0 0
Showerheads 0 954 575
Miscellaneous 14 0 893
Total 62,156 50,402 39,979Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 707 of 829
| 25Applied Energy Group · www.appliedenergygroup.com
Effective since the middle of 2016, the 2015 WSEC results in a much more efficient new construction baseline
•Mandatory, very efficient, shell measures substantially reduce heating loads, which lowers furnace usage by 30%
e.g. 650*.7 = 455 therms
•Since usage is down, savings from upgrading to an efficient system are reduced proportionally
Credits are also required to meet section R406.2
•Although high efficiency equipment is allowed under this section, we have heard that builders are opting for cheaper methods of compliance, such as designing homes with interior ductwork
Impact on Residential New Construction
For a new home of average size:
•Ceiling Insulation: R49
•Wall Insulation: R21
•Floor Insulation: R30 –R38
•Window U-Factor: 0.28-0.30
•Air Leakage: 3-5 ACH50
For optional credits, the following may be utilized:
•94% AFUE furnace
•0.95 EF water heater
•1.75 GPM showerheads
•Inside ducting
RTF Analysis: https://rtf.nwcouncil.org/standard-protocol/new-homes
2015 WASHINGTON ENERGY CODE
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 708 of 829
| 26Applied Energy Group · www.appliedenergygroup.com
Idaho, Comparison with Current Avista Programs
2018 UCT achievable economic
estimates are very similar to
Avista’s 2018 Plan and 2017
accomplishments
•Furnace potential is very similar
to current accomplishments –
mainly due to new construction
potential
•Smart thermostats and windows
pass UCT screening
•ENERGY STAR Homes reflect
Idaho building codes, which do
not lower space heating savings
due to a substantially tighter
building shell
RESIDENTIAL ACCOMPLISHMENTS
2018 UCT Achievable
Economic (Dth)
2017
Accomplish
2018
Plan
LoadMAP
2018 ATP
Furnace 12,783 11,716 11,816
Boiler 134 0 307
Water Heater 1,775 2,077 2,014
ENERGY STAR Homes 41 41 146
Smart Thermostat 1,628 1,040 664
Programmable Tstat.0 0 0
Ceiling Insulation 129 56 534
Wall Insulation 17 102 452
Floor Insulation 29 119 774
Doors 11 19 0
Windows 1,407 1,708 820
Air Sealing 87 48 0
Duct Insulation 56 153 181
Duct Sealing 59 0 0
Showerheads 0 233 286
Miscellaneous 2 0 362
Total 18,158 17,311 18,354Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 709 of 829
| 27Applied Energy Group · www.appliedenergygroup.com
Washington, Comparison with Current Avista Programs
Program potential is similar to current Avista programs
•LoadMAP UCT Achievable Economic is between 2017 accomplishments and 2018 plan
•Even with very high ramp rates, food preparation potential is lower than current programs (LO50Fast)
•Many HVAC-specific measures would be considered “Custom” but assigned to this category since that is where those savings are ultimately realized
•Industrial adds an additional 569 Dth to the “Custom” program in the 2018 LoadMAP Projections
C&I ACCOMPLISHMENTS
2018 UCT Achievable
Economic (Dth)
2017
Accomplish
2018
Plan
LoadMAP
2018 UCT
AEP
HVAC 14,000 3,214 11,925
Weatherization 1,657 2,080 1,694
Appliances 380 0 838
Food Preparation 3,987 4,956 2,761
Custom 2,381 10,000 4,082
Total 22,405 20,251 21,300
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 710 of 829
| 28Applied Energy Group · www.appliedenergygroup.com
Idaho, Comparison with Current Avista Programs
Program potential is higher than
2017 accomplishments and
similar to 2018 plan
•Idaho programs ramped up
between 2017 and 2018 due to
recent restarting of offerings
•Industrial adds an additional 569
Dth to the “Custom” program in
the 2018 LoadMAP Projections
(similar to WA when rounded)
C&I ACCOMPLISHMENTS
2018 UCT Achievable
Economic (Dth)
2017
Accomplish
2018
Plan
LoadMAP
2018 UCT
AEP
HVAC 1,390 805 3,769
Weatherization 874 940 941
Appliances 35 0 198
Food Preparation 1,359 1,490 1,045
Custom 0 4,100 2,033
Total 3,657 7,336 7,986
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 711 of 829
| 29Applied Energy Group · www.appliedenergygroup.com
Residential, First-Year Potential
Comparison of first-year UCT Achievable economic potential between 2016 and 2018 CPAs for the residential sector
Measures mapped to current Avista programs similarly to current CPA
COMPARISON WITH 2016 CPA
Program Washington Idaho Notes2017201820172018
Furnace 9,524 19,091 3,209 11,816 Accelerated from 2017 per Avista accomplishments
Boiler 251 619 112 307
Water Heater 718 4,257 254 2,014 Accelerated from 2017 per Avista accomplishments
ENERGY STAR Homes 0 294 0 146 Now passing cost-effectiveness
Smart Thermostat 445 1,344 213 664 More mature measure, higher starting point
Programmable Thermostat 0 0 0 0
Ceiling Insulation 1,218 1,072 577 534
Wall Insulation 0 904 0 452 Now cost-effective
Floor Insulation 0 1,135 0 774 Now cost-effective
Doors 0 0 0 0
Windows 8,491 9,426 4,044 820 $/sqft is low as percent of measure cost, slowed in ID as a result,
but demand for measure appears high in WA
Air Sealing 0 0 0 0
Duct Insulation 0 367 0 181
Duct Sealing 939 0 0 0
Showerheads 1,627 575 736 286 No accomplishments in 2017, allowing time for program to
"ramp up"
Miscellaneous 4,387 893 1,992 362 Maintenance measures no longer cost-effective due to updated
labor cost calculations.
Total 27,598 39,979 11,138 18,354 Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 712 of 829
| 30Applied Energy Group · www.appliedenergygroup.com
C&I, First-Year Potential
Comparison of first-year UCT Achievable economic potential between
2016 and 2018 CPAs for the commercial sector
Custom measures reduce the most. This was due to retrocommissioning,
which was cost-effective in the prior CPA
COMPARISON WITH 2016 CPA
Program Washington Idaho Notes2017201820172018
HVAC 8,065 11,925 3,400 3,769 Similar to prior study, slightly accelerated
Weatherization 1,636 1,694 540 941
Appliances 953 838 453 198
Food Preparation 577 2,761 228 1,045 Heavily accelerating measures due to program accomplishments,
particularly fryers and ovens
Custom 12,130 4,082 4,997 2,033 Retrocommissioning was a top measure in prior CPA, but no
longer cost-effective after to UES update.
Total 23,362 21,300 9,618 7,986
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 713 of 829
| 31Applied Energy Group · www.appliedenergygroup.com
COMPARISON WITH 2016 CPA
Current Study:
2027 Potential
(Dth)
Prior Study:
2026 Potential
(Dth)
Change from
Prior Study (Dth)
Washington
Residential 1,131,013 497,074 633,939
Commercial 476,648 413,219 63,429
Industrial 5,974 4,050 1,924
WA Total 1,613,635 914,343 699,292
Idaho
Residential 596,450 208,875 387,575
Commercial 205,064 170,883 34,181
Industrial 6,034 4,411 1,623
ID Total 807,547 384,169 423,378
Avista
Residential 1,727,462 705,949 1,021,513
Commercial 681,712 584,102 97,610
Industrial 12,007 8,461 3,546
Avista Total 2,421,181 1,298,512 1,122,669
•10-year cumulative UCT Achievable
Potential increased substantially
•In the prior CPA, we gradually
increased ramp rates over time and
did not max out ramp rates at 85%
•This is causing a spike in mid-year
potential since many of the faster
rates are already at 85%
10-year Cumulative UCT Achievable Potential
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 714 of 829
Ingrid Rohmund, Senior Vice [e-mail]
Kurtis Kolnowski, Senior Project [e-mail]
Ken Walter, Senior Analyst
[e-mail] Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 715 of 829
Energy Trust of Oregon
Energy Efficiency Resource Assessment Study
May 10th, 2018
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 716 of 829
Agenda
•About Energy Trust
•2017 Achieved Savings
•Resource Assessment
Overview and Background
•Methodology
•Results
•Questions/Discussion
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 717 of 829
Independent nonprofit
Providing access to affordable energy
Generating homegrown, renewable power
Serving 1.6 million customers of Portland General Electric, Pacific Power, NW Natural, Cascade Natural Gas and Avista
Building a stronger Oregon and SW Washington
About us
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 718 of 829
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 719 of 829
Nearly 660,000
sites transformed
into energy
efficient, healthy,
comfortable
and productive
homes and
businesses
From Energy Trust’s investment of $1.5 billion in utility customer funds:
10,000 clean
energy systems
generating
renewable power
from the sun,
wind, water,
geothermal heat
and biopower
$6.9 billion in
savings over time
on participant
utility bills
from their
energy-efficiency
and solar
investments
20 million tons
of carbon dioxide
emissions kept
out of our air,
equal to removing
3.5 million cars
from our roads
for a year
15 years of affordable energy
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 720 of 829
607 average megawatts saved
121 aMW generated
52 million annual therms saved
Enough energy to power 564,000 homes
and heat 100,000 homes for a year
Avoided 20 million tons of carbon dioxide
A clean energy power plant
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 721 of 829
Energy Trust’s 2017 Achievements for Avista
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 722 of 829
Energy Trust Savings
Achievements –2017
•Our first full year serving
Avista customers in Oregon
•Overall achieved 107% of goal
•Goal 318k Therms
•Achieved 341k Therms
•Anticipate continued success as we move into year 2 and
Trade Ally networks expand
Energy Trust achieved 107% of goal in Avista service territoryExhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 723 of 829
Resource Assessment:
Purpose, Overview and Background
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 724 of 829
Resource Assessment (RA)
Purpose
•Provides estimates of energy
efficiency potential that will result in a
reduction of load on Avista’s system
for use in Avista’s Integrated
Resource Plan (IRP).
•The purpose is to help Avistastrategically plan future investment in both supply side and demand side resources.
•Estimates of energy efficiency
potential are in ‘gross’ savings, not
‘net’, as gross savings are what will
be reflected on the Avista system. Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 725 of 829
Resource Assessment Overview
•What is a resource assessment?
•Model that provides an estimate of energy efficiency resource potential achievable over a 20-year period
•‘Bottom-up’ approach to estimate potential starting at the measure level
and scaling to a service territory
•Energy Trust uses a model in Analytica that was
developed by Navigant Consulting in 2014
•The Analytica RA Model calculates Technical, Achievable and Cost-Effective Achievable Energy Efficiency Potential.
•Final program/IRP targets are established via a deployment protocol exogenous of the model.
•Data inputs and assumptions in the model are updated in
conjunction with IRP about every two years.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 726 of 829
Additional RA Background
•Informs utility IRP work & Energy Trust strategic and program planning.
•Does not dictate source or measure mix of annual
energy savings acquired by programs
•Does not set incentive levels
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 727 of 829
20-Year Forecast Methodology
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 728 of 829
Not
Technically
Feasible
Technical Potential
Calculated
within RA
Model
Market
Barriers
Achievable Potential
(85%of Technical Potential)
Not Cost-
Effective
Cost-Effective Achiev.
Potential
Program Design &
Market Penetration
Final Program
Savings
Potential
Developed
with
Programs
& Market
Information
Forecasted Potential Types
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 729 of 829
20-Year IRP EE Forecast Flow Chart
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 730 of 829
RA Model inputs
Measure Level Inputs
Measure Definition and Application:
•Baseline/Efficient equip. definition
•Applicable customer segments
•Installation yype (RET/ROB/NEW)*
•Measure Life
Measure Savings
Measure Cost
•Incremental cost for ROB/NEW
measures
•Full cost for retrofit measures
Market Data (for scaling)
•Density
•Baseline/efficient equipment
saturations
•Suitability
Utility ‘Global’ Inputs
Customer and Load Forecasts
•Used to scale measure level
savings to a service territory
•Residential Stocks: # of homes
•Commercial Stocks: 1000s of Sq.Ft.
•Industrial Stocks: Customer load
Avoided Costs (provided by Avista)
Customer Stock Demographics:
•Heating fuel splits
•Water heat fuel splits
* RET = Retrofit; ROB = Replace on
Burnout; NEW = New ConstructionExhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 731 of 829
Model Updates
•The RA Model is a ‘living’ model and Energy Trust makes continuous improvements to it.
•Measure updates, new measures and new emerging technologies included in model
•More alignment with high-level NWPCC 7th Power Plan deployment methodologies to obtain cost-effective achievable savings within market sectors and replacement types.
•Cost-effective potential may be realized through programs or codes and standards.
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 732 of 829
Key Measure Inputs:
•Baseline: 0.60 EF gas water heater
•Replacement Type: Replacement on Burnout / New
•Measure Incremental Cost: $193
•Conventional (not emerging, no risk adjustment)
•Lifetime:13 years
•Savings: 31.5 therms (annual)
•Non-Energy Benefits: $5.95
•Customer Segments: SF, MF, MH
•Density, Saturation, Suitability
•Competing Measures: All efficient gas water heaters
Example Measure: Residential Gas Tank
Water Heater (>0.70 EF)
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 733 of 829
Incremental Measure Savings Approach
(Competition groups –Gas water heaters)
En
e
r
g
y

S
a
v
i
n
g
s

(
Th
e
r
m
s
)
EF = 0.67 EF > 0.70
En
e
r
g
y

S
a
v
i
n
g
s

(
Th
e
r
m
s
)
EF = 0.67 EF > 0.70
TRC 1.5
(Numbers are
for illustrative
purposes
only)TRC 1.1 Inc. SavingsAll Savings
Savings potential
for competing
technologies are
incremental to one
another based on
relative TRCs
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 734 of 829
•Energy Trust utilizes the Total Resource Cost (TRC) test
to screen measures for cost effectiveness
•If TRC is > 1.0, it is cost-effective
•Measure Benefits:
•Avoided Costs (provided by Avista)
•Annual measure savings x NPV avoided costs per therm
•Quantifiable Non-Energy Benefits
•Water savings, etc.
Total Measure Costs:
•The customer cost of installing an EE measure (full cost if retrofit, incremental over baseline if replacement)
Cost-Effectiveness Screen
TRC =𝑴𝒆𝒂𝒔𝒖𝒓𝒆𝑩𝒆𝒏𝒆𝒇𝒊𝒕𝒔
𝑻𝒐𝒕𝒂𝒍𝑴𝒆𝒂𝒔𝒖𝒓𝒆𝑪𝒐𝒔𝒕
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 735 of 829
Cost-Effectiveness Override
in Model
Energy Trust applied this feature to measures found to be NOT Cost-Effective in the model
but are offered through Energy Trust programs.
Reasons:
1.Blended avoided costs may produce different results than utility specific
avoided costs
2.Measures offered under an OPUC exception per UM 551 criteria.
The following measures had the CE override
applied (all under OPUC exception):
•Res Insulation (ceiling, floor, wall)
•Res Tank Water Heater (0.67-0.69
only)Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 736 of 829
Emerging Technologies
•Model includes savings potential from emerging technologies
•Factors in changing performance, cost over time
•Use risk factors to hedge against uncertainty
Residential Commercial Industrial
• Path 5 Emerging Super
Efficient Whole Home
• Advanced Ventilation
Controls
• Gas-fired HP Water
Heater
• Window Replacement
(U<.20), Gas SF
• DOAS/HRV -GAS
Space Heat
• Wall Insulation-VIP,
R0-R35
• Absorption Gas Heat
Pump Water Heaters
• DHW Circulation
Pump
• Advanced Insulation • Gas-fired HP HW
•Behavior Competitions • Gas-fired HP, Heating
• Zero Net Energy Path
• AC Heat Recovery,
HW
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 737 of 829
Risk Factors for Emerging Technologies
Risk Category 10%30%50%70%90%
Market Risk
(25%
weighting)
Requires new/changed
business model
Start-up, or small manufacturer
Significant changes to
infrastructure
Requires training of
contractors. Consumer
acceptance barriers exist.
Training for
contractors
available.
Multiple
products in
the market.
Trained contractors
Established business models
Already in U.S. Market
Manufacturer committed to
commercialization
Technical Risk
(25%
weighting)
Prototype in first
field tests.
A single or
unknown
approach
Low volume
manufacturer.
Limited
experience
New product
with broad
commercial
appeal
Proven technology in
different application
or different region
Proven
technology in
target
application.
Multiple
potentially
viable
approaches.
Data Source
Risk
(50%
weighting)
Based only on
manufacturer
claims
Manufacturer
case studies
Engineering
assessment
or lab test
Third party case study
(real world
installation)
Evaluation
results or
multiple third
party case
studiesExhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 738 of 829
Results
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 739 of 829
Not
Technically
Feasible
Technical Potential
Calculated
within RA
Model
Market
Barriers
Achievable Potential
(85%of Technical Potential)
Not Cost-
Effective
Cost-Effective Achiev.
Potential
Program Design
& Market
Penetration
Final
Program
Savings
Potential
Developed
with
Programs
& Other
Market
Information
The RA Model estimates the in Technical, Achievable and Cost-Effective
Achievable potential
Final Program Savings Potential is deployed exogenously of the model using
the Cost-Effective Achievable potential from the RA model in combination with
program expertise on what can actually be achieved
Outputs of Potential Type
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 740 of 829
Overall Cumulative Savings Results –
Millions of Therms
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
Technical Achievable Cost-effective
achievable
Energy Trust
Savings Projection
Mi
l
l
i
o
n
s

o
f

T
h
e
r
m
s
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 741 of 829
RA Model Results
Technical, Achievable, and Cost-Effective
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 742 of 829
Model Output Cumulative Potential by Type
and Year (2018-2037)
-
5
10
15
20
25
30
35
40
Mi
l
l
i
o
n
s

o
f

Th
e
r
m
s
Technical Achievable Cost-Effective Achievable Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 743 of 829
Cumulative Emerging Technology
Contribution –Millions of Therms
23%
23%
5%
-
5.00
10.00
15.00
20.00
25.00
30.00
35.00
40.00
Technical Achievable Cost-Effective
Achievable
Mi
l
l
i
o
n
s

o
f

T
h
e
r
m
s
Conventional Emerging Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 744 of 829
Cumulative Potential by Sector and Type –
Millions of Therms
-
5
10
15
20
25
Residential Commercial Industrial
Mi
l
l
i
o
n
s

o
f

Th
e
r
m
s
Technical Achievable Cost-effective achievable Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 745 of 829
Proportion of Cumulative Cost-effective
Potential by End Use
Appliance0.4%Behavioral
14%
Cooking
4%
Water Heating
31%
Other2%
Process Heating1%
Weatherization
20%
HVAC28%
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 746 of 829
Cost-Effective Override Effect –
Cumulative CE Potential (Millions of Therms)
Sector
Potential
with CE
Override
Potential with
NO CE
Override
Difference
(total CE
potential with
override)
Residential 10.63 8.33 2.3
Commercial 6.32 6.32 -
Industrial 0.26 0.26 -
Total DSM: 17.21 14.91 2.30
Measures with CE Override in Model
•Res Insulation (ceiling, floor, wall)
•Res Tank Water Heater (0.67-0.69 only)
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 747 of 829
Top-20 Measures –Cost-Effective
Cumulative Potential
- 0.5 1.0 1.5 2.0 2.5
Res - Path 2 MECH + DHW Gas Heat Gas DHW
Com - SEM
Res - Smart Tstat - Gas FAF
Res -Window Replacement Tier 2 (U ≤ 0.27), Gas SPHT
Res - 0.70+ EF Gas Storage Water Heater
Com - Demand Control Ventilation
Res - Path 3 MECH + DHW 2 Gas Heat Ele DHW
Com - DDC HVAC Controls
Res - Window Replacement Tier 1 (U =0.28 -> 0.30),…
Res - Gas Fireplace - 70-74 FE
Com - DHW Condensing Tankless
Res - Attic insulation GAS SPHT (R13-R18 starting…
Res - Floor insulation GAS SPHT HZ1
Com - ZNE
Com - DOAS/HRV - GAS SH
Res - Attic insulation GAS SPHT (R0-R12 starting…
Res - Behavior Savings (RET)
Res - Showerhead, 1.50 GPM - Gas
Res - Wall insulation GAS SPHT HZ1
Com - Gas Combi Oven
MILLIONS OF THERMS
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 748 of 829
Final Savings Projections -
Deployed Results
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 749 of 829
Energy Trust sets the first five years of energy
efficiency acquisition to program performance and
budget goals.
Final Savings Projection Methodology
Years 1-2
•Program forecasts –they know what is happening short term best
Years 3-5
•Planning and Programs work together to create forecast
Years 6-20
•Planning forecasts long-term acquisition rate to generally align NWPCC
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 750 of 829
20-Year Cumulative Potential by Type –
Millions of Therms
Technical
Potential
Achievable
Potential
Ach. Cost-
Effective
Potential
Energy Trust
Savings
Projection
Residential 20.0 17.0 10.6 5.7
Commercial 13.3 11.3 6.3 3.3
Industrial 0.3 0.3 0.3 0.2
All Sectors 33.5 28.5 17.2 9.2
Not all Cost-Effective Potential is projected to be achieved because:
•Lost opportunity with ‘Replacement’ and ‘New Constr.’ measures
•Hard to reach measures (e.g. insulation)
•Other market barriers identified by programs & new service territoryExhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 751 of 829
Cost-Effective Avista Savings Projection 2018-2037
–Millions of Therms
-
0.10
0.20
0.30
0.40
0.50
0.60
Gr
o
s
s

S
a
v
i
n
g
s

(
M
i
l
l
i
o
n
s

o
f

T
h
e
r
m
s
)
Mega-Project
Adder
RES-ROB
RES-RET
RES-NEW
Ind-ROB
Ind-RET
Com-SEM
Com-ROB
Com-RET
Com-NEW
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 752 of 829
Annual Projected Savings as Percent of Avista’s
Annual Load Forecasts
0.00%
1.00%
2.00%
3.00%
4.00%
5.00%
6.00%
7.00%
8.00%
9.00%
10.00%
0.00%
0.10%
0.20%
0.30%
0.40%
0.50%
0.60%
%
o
f

L
o
a
d

(
C
u
m
u
l
a
t
i
v
e

S
a
v
i
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g
s
)
%
o
f

A
n
n
u
a
l

L
o
a
d

(
A
n
n
u
a
l

S
a
v
i
n
g
s
)

Annual % of Load Savings Cumulative % of Load Savings
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 753 of 829
2018 Supply Curve –20 Year Technical Potential
by Levelized Cost of Energy ($/Therm)
Approximate
Cost-Effective
Cutoff (~$0.97)
-
5.00
10.00
15.00
20.00
25.00
30.00
35.00
-$
3
.
5
4
-$
2
.
4
8
-$
0
.
6
0
$0
.
0
0
$0
.
0
0
$0
.
0
0
$0
.
0
1
$0
.
0
2
$0
.
0
3
$0
.
0
4
$0
.
0
5
$0
.
0
8
$0
.
1
5
$0
.
1
7
$0
.
1
9
$0
.
2
2
$0
.
2
6
$0
.
2
7
$0
.
2
8
$0
.
3
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3
9
$0
.
4
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.
4
6
$0
.
4
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$0
.
6
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$0
.
9
9
$1
.
0
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$1
.
2
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.
4
4
$1
.
6
2
$1
.
7
0
$2
.
0
6
$3
.
1
6
$4
.
8
6
$6
.
2
9
$6
.
3
5
$7
.
5
7
$1
0
.
2
6
$1
4
.
0
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$2
0
.
2
9
$8
5
.
1
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$8
5
.
1
8
Mi
l
l
i
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s

o
f

T
h
e
r
m
s
Levelized Total Resource Cost ($/Therm)
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 754 of 829
Thank you
Jack Cullen
Sr. Project Manager, Planning
[e-mail]
503.548.1596
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 755 of 829
7373
WUTC 2016 IRP comments
•Discuss with the TAC:
–The results of Northwest Energy Efficiency Alliance (NEEA) coordination,
including non-energy benefits to include in the CPA.
–The appropriateness of listing and mapping all prospective distribution system
enhancement projects planned on the 20 year horizon, and comparing actual
projects completed to prospective projects listed in previous IRP’s.
73
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 756 of 829
74
Dynamic DSM
Kaylene Schultz
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 757 of 829
7575
Sendout and Dynamic DSM
•Action Plan: Avista’s 2018 IRP will contain a dynamic
DSM program structure in its analytics. In prior IRP’s, it
was a deterministic method based on Expected Case
assumptions. In the 2018 IRP, each portfolio will have
the ability to select conservation to meet unserved
customer demand. Avista will explore methods to enable
a dynamic analytical process for the evaluation of
conservation potential within individual portfolios.
75
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 758 of 829
7676
DSM Example
Com
Ind
WA
GTN
245
Measures
658
Measures
54 Measures
957 Total Measures
76
Res
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 759 of 829
7777
Needed Measures
WA GTN
WA NWP
ID GTN
ID NWP
Medford
GTN Roseburg
Klamath
Falls
Demand Areas
11 demand areas X 957 measures
per area = 10,527 needed measures
to solve
77
Medford
NWP La Grande
WA Both ID Both
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 760 of 829
7878
Sendout and DSM Issues
•Attempts to group measures
–Unique measures can have different curves and
device lives
–Intent of modeling DSM as a resource is to provide
individual resources the ability to fill demand along
the demand curve and not lump assumptions
–As the model works today, we would have to solve for
individual area and class, each in a separate model;
this would miss the mark on system optimization and
peak day events
78
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 761 of 829
7979
2020 Action Plan
•Avista will use the same software our electric
IRP team has as a solution to this action plan
–The solution is outside of the Sendout model in an
enhanced Excel solver, meaning we will rebuild our
system model in Sendout into excel
–This solution is known to our WA and ID commissions
as “PRiSM”, which is used to solve and create
Avista’s DSM goals in each jurisdiction
79
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 762 of 829
80
Modeling in Sendout
Kaylene Schultz
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 763 of 829
8181
Modeling Transportation In SENDOUT®
•Start with a point-in-time look at each jurisdiction’s resources
•Contracts –Receipt and Delivery Points
•Rates
•Contractual vs. Operational
•Contractual can be overly restrictive
•Operational can be overly flexible
•Incorporating operational realities into our modeling can defer
the need to acquire new resources
•Gas Supply’s job is to get gas from the supply basin to the
pipeline citygate
•Gas Engineering/Distribution’s job is to take gas from the
pipeline citygate to our customers
•The major limiting factor is receipt quantity –how much can you
bring into the system?
81
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 764 of 829
82
Modeling Challenges
•Supply needs to get gas to the gate
•Contracts were created years ago, based on demand projections at that
point in time
•Stuff happens (i.e. growth differs from forecast)
•Sum of receipt quantity and aggregated delivery quantity don’t identify
resource deficiency for quite some time however…..
•The aggregated look can mask individual city gate issues, and the
disaggregated look can create deficiencies where they don’t exist
•In many cases, operational capacity is greater than contracted
•Transportation resources are interconnected (two pipes can serve one
area)
•WARNING –we need to be mindful of the modeling limitations
82
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 765 of 829
8383
What is in SENDOUT®?
Inside:
•Demand forecasts at an aggregated level
•Existing firm transportation resources and current
rates
•Receipt point to aggregated delivery
points/“zone”
•Jurisdictional considerations
•Long term capacity releases
•Potential resources, both supply and demand side
83
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 766 of 829
8484
What is outside SENDOUT®?
Outside:
•Gate station analysis
•Forecasted demand behind the gate
•Growth rates consistent with IRP assumptions
•Actual hourly/daily city gate flow data
•Gate station MDDO’s
•Gate station operational capacities
84
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 767 of 829
85
Supply Interconnect Demand
Transport
Storage
85
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 768 of 829
86
Assumptions Review
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 769 of 829
8787
1.Customer annual growth rates:
2.Use per customer coefficients –3 year average use per HDD per customer
3.Weather planning standard –coldest day on record
WA/ID 82; Medford 61; Roseburg 55; Klamath 72; La Grande 74
Developing a Reference Case
Customer
count
forecast
Use per
customer
coefficients
Weather Reference
Case Demand
87
System Base-Case High Low
Residential 1.2%1.6%0.9%
Commercial 0.7%1.0%0.3%
Industrial -0.3%2.2%-3.3%
Total 1.2%1.5%0.8%
WA Base-Case High Low
Residential 1.2%1.5%0.9%
Commercial 0.7%1.0%0.4%
Industrial -0.8%1.9%-3.1%
Total 1.2%1.5%0.8%
ID Base-Case High Low
Residential 1.5%2.0%1.0%
Commercial 0.6%1.1%0.1%
Industrial 0.1%1.7%-2.7%
Total 1.4%1.9%0.9%
OR Base-Case High Low
Residential 1.0%1.3%0.6%
Commercial 0.7%1.1%0.4%
Industrial 0.1%4.7%-7.8%
Total 0.9%1.3%0.6%
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 770 of 829
8888
WA-ID Region Firm Customers: 2018 IRP and 2016 IRP
220,000
230,000
240,000
250,000
260,000
270,000
280,000
290,000
300,000
310,000
320,000
20
1
8
20
1
9
20
2
0
20
2
1
20
2
2
20
2
3
20
2
4
20
2
5
20
2
6
20
2
7
20
2
8
20
2
9
20
3
0
20
3
1
20
3
2
20
3
3
20
3
4
20
3
5
20
3
6
20
3
7
WA-ID Base 2016 WA-ID Base 2018
IRP Avg.Annual Growth
2018-2037
2016 1.1%
2018 1.3%
≈
+16,500
88
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 771 of 829
8989
95,000
100,000
105,000
110,000
115,000
120,000
125,000
130,000
20
1
8
20
1
9
20
2
0
20
2
1
20
2
2
20
2
3
20
2
4
20
2
5
20
2
6
20
2
7
20
2
8
20
2
9
20
3
0
20
3
1
20
3
2
20
3
3
20
3
4
20
3
5
20
3
6
20
3
7
OR Base 2016 OR Base 2018
OR Region Firm Customers: 2018 IRP and 2016 IRP
IRP Avg.Annual Growth
2018-2037
2016 1.1%
2018 0.9%
≈ -4,700
89
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 772 of 829
9090
System Firm Customer Range, 2018-2037
Variable Low
Growth
Base
Growth
High
Growth
Customers 0.8%1.2%1.5%
Population 0.5%0.9%1.2%
90
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 773 of 829
91
Base Coefficients
July and August Average91
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 774 of 829
92
$-
$1.00
$2.00
$3.00
$4.00
$5.00
$6.00
$7.00
$8.00
$9.00
$10.00
$11.00
$12.00
$-
$1.00
$2.00
$3.00
$4.00
$5.00
$6.00
$7.00
$8.00
$9.00
$10.00
$11.00
$12.00
$
p
e
r

D
t
h
2018 Henry Hub Prices -Nominal
High HH Price…Low HH Price…HH Expected Price…
92
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 775 of 829
93
Price Elasticity: What does the research
show?
93
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 776 of 829
9494
Price Elasticity Proposed Assumptions
•The data is a mixed bag at best:
•8 of 9 super regions have statistically significant short
and long run elasticity's.
•At a state level only 10 of 50 show statistical
significant elasticity's.
•In some cases, the estimated elasticity's are positive.
–We incorporated a -.10 price elastic response for our
expected elasticity assumption as found in our Medford
and Roseburg service areas.
94
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 777 of 829
9595
Carbon Tax Summary
•ID –None
•OR –Cap and Investment Program SB1070
–Avista’s price assumption are based on CA cap and
trade program (2018 annual price of $14.53)
•Begins in 2021 at $17.86 and increases by 5% plus inflation
each year until reaching $51.58 in 2037
•WA –Governor Inslee proposed Carbon tax (SB
6203)
–Starts at $10 per MTCO2e in July 2019 and in 2021
adds $2 per year until capping at $30 in 2030.
95
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 778 of 829
9696
Carbon Price by Jurisdiction
*Idaho has no carbon price adder96
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 779 of 829
97
2018 Henry Hub
Expected Price
Including Carbon Adders by State
$-
$1.00
$2.00
$3.00
$4.00
$5.00
$6.00
$7.00
$8.00
$9.00
$10.00
$-
$1.00
$2.00
$3.00
$4.00
$5.00
$6.00
$7.00
$8.00
$9.00
$10.00
$
p
e
r

D
t
h
ID - HH Expected Price
Nominal $
OR - HH Expected Price
Nominal $
WA - HH Expected Price
Nominal $97
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 780 of 829
98
Coldest on Record Dates
WA/ID –December 30, 1968
Medford –December 9, 1972
Roseburg –December 22, 1990
Klamath Falls –January 6, 2017
La Grande –January 23, 1996
Area Coldest in 20 Year
HDD
Coldest on Record
HDD
WA-ID 76 82
Klamath Falls 72 72
La Grande 66 74
Medford 52 61
Roseburg 48 55
98
Planning Standard Assumptions
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 781 of 829
9999
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 782 of 829
100100
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 783 of 829
101
Scenario Analysis
101
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 784 of 829
102102
2018 Proposed Scenarios
102
Proposed Scenarios Expected Cold Day 20yr Average Low Growth 80 % below 1990 emissions High Growth
INPUT ASSUMPTIONS Case Weather Std Case & High Prices
(Oregon and Washington
only)& Low Prices
Customer Growth Rate Low Growth Rate
Reference Case growth with
emissions 80% below 1990
target
High Growth Rate
Demand Side Management
Weather Planning Standard Historical Coldest Day Coldest in 20 years 20 year average
Prices
Price curve
RESULTS
First Gas Year Unserved
WA/ID N/A N/A N/A N/A N/A 2032
Medford N/A N/A N/A N/A N/A 2031
Roseburg N/A N/A N/A N/A N/A 2031
Klamath N/A N/A N/A N/A N/A N/A
La Grande N/A N/A N/A N/A N/A 2032
Scenario Summary
Most aggressive peak
planning case utilizing
Average Case
assumptions as a
starting point and
layering in coldest
weather on record.
The likelihood of
occurrence is low.
Evaluates adopting an
alternate peak weather
standard. Helps
provide some bounds
around our sensitivity
to weather.
Case most
representative of
our average
(budget, pga,
rate case)
planning criteria.
Stagnant growth
assumptions in order to
evaluate if a shortage
does occur. Not likely to
occur.
Reduction of the use of natural
gas to 80% below 1990 targets
in OR and WA by 2050. The
case assumes the overall
reduction is an average goal
before applying figures like
elasticity and dsm.
Aggressive growth
assumptions in order to
evaluate when our
earliest resource
shortage could occur.
Not likely to occur.
Reference Case Cust Growth Rates
None
$10-$30 WA
$17.86-$51.58 OR
$0 ID
Historical Coldest Day
Expected High
Yes
3 yr Flat + Price
Elasticity3 yr Flat + Price Elasticity
Low
Use per Customer
Carbon Legislation
($/Metric Ton)
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 785 of 829
103103
Existing Resources vs. Peak Day Demand
Expected Case –Washington/Idaho (DRAFT)
103
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 786 of 829
104104
Existing Resources vs. Peak Day Demand
Expected Case –Medford/Roseburg (DRAFT)
104
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 787 of 829
105105
Existing Resources vs. Peak Day Demand
Expected Case –Klamath Falls (DRAFT)
105
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 788 of 829
106106
Existing Resources vs. Peak Day Demand
Expected Case –La Grande (DRAFT)
106
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 789 of 829
107107
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 790 of 829
108108
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 791 of 829
109109
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 792 of 829
110
Solving for unserved demand
Tom Pardee
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 793 of 829
111
When unserved demand does show up……
There are a few questions we need to ask:
1.Why is the demand unserved?
2.What is the magnitude of the short? (i.e Are we 1 Dth or 1000
Dth’s short?)
3.What are my options to meet it?
111
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 794 of 829
112112
When current resources don’t meet demand
what could we consider?
•Transport capacity release recalls
•“Firm” backhauls
•Contract for existing available transportation
•Expansions of current pipelines
•Peaking arrangements with other utilities (swaps/mutual assistance
agreements) or marketers
•In-service territory storage
•Satellite/Micro LNG (storage inside service territory)
•Large scale LNG with corresponding pipeline build into our service
territory
•Structured products/exchange agreements delivered to city gates
•Biogas (assume it’s inside Avista’s distribution)
•Hydrogen blend (assume it’s inside Avista’s distribution)
•Avista distribution system enhancements
•Demand side management
112
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 795 of 829
113113
New Resource Risk Considerations
•Does is get supply to the gate?
•Is it reliable/firm?
•Does it have a long lead time?
•How much does it cost?
•New build vs. depreciated cost
•The rate pancake
•Is it a base load resource or peaking?
•How many dekatherms do I need?
•What is the “shape” of resource?
•Is it tried and true technology, new technology, or yet to be discovered?
•Who else will be competing for the resource?
113
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 796 of 829
114114
Potential New Supply Resources
Considerations
•Availability
–By Region –which region(s) can the resource be utilized?
–Lead time considerations –when will it be available?
•Type of Resource
–Peak vs. Base load
–Firm or Non-Firm
–“Lumpiness”
•Usefulness
–Does it get the gas where we need it to be?
–Last mile issues
•Cost
114
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 797 of 829
115115
$ per kg vs $ per Dth
*1 kg is roughly equivalent to a gallon of gasoline
LHV
USDOE target is below $4 (excludes compression and delivery)
Source: https://www.energy.gov/eere/fuelcells/doe-technical-targets-onboard-hydrogen-storage-light-duty-vehicles
National Renewable Energy Laboratory (NREL) estimates hydrogen fuel prices from around
$8 -$10 per kg by 2020 to 2025 period.
$ per kg $ per DTh
$ 1.00 $ 8.78
$ 2.00 $ 17.55
$ 3.00 $ 26.33
$ 4.00 $ 35.11
$ 5.00 $ 43.88
$ 6.00 $ 52.66
$ 7.00 $ 61.44
$ 8.00 $ 70.21
$ 9.00 $ 78.99
$ 10.00 $ 87.77
$-
$10.00
$20.00
$30.00
$40.00
$50.00
$60.00
$70.00
$80.00
$90.00
$100.00
1 2 3 4 5 6 7 8 9 10
$ per kg $ per DTh
115
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 798 of 829
116116
Supply Resources -Modeled
Additional Resource Size Cost/Rates Availability Notes
Unsubscribed GTN Capacity Up to 50,000
Dth GTN Rate Now Currently available unsubscribed capacity
from Kingsgate to Stanfield
Medford Lateral Exp 50,000 Dth /
Day
$35M capital + GTN
Rate 2018 Additional compression to facilitate more gas
to flow from mainline GTN to Medford.
*Hydrogen 20% of heat
content of a Dth
or 200,000 btu
$10 kg
1 LHV kg = 113,937
btu
2030 Roughly 20% of yearly gas demand to mix
with natural gas in current pipeline. Cost is
from the DOE target for cost of Hydrogen.
Costs from a consultant will be utilized in the
final document, but were unavailable for
modeling in time for TAC #4
*Renewable Natural Gas –
Landfill, Dairy, Waste Water,
Food waste to (RNG)
1,370 Dth / Day $10, $12, $14, $16/
Dth equivalent
2030 Dairy Farm estimate. Costs from a
consultant for each specific type of RNG will
be utilized in the final document, but were
unavailable for modeling in time for TAC #4
Plymouth LNG 241,700 Dth
w/70,500 Dth
deliverability
2018 Provides for peaking services and alleviates
the need for costly pipeline expansions.
-Pair with excess pipeline MDDO’s to create
firm transport
116
*Avista has retained a consultant to estimate costs for RNG & Hydrogen
and will be included in Avista’s 2018 IRP
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 799 of 829
117117
Future Supply Resources –Not Modeled
Other Resources to Consider
Additional Resource Size Cost/Rates Availability Notes
Co. Owned LNG 600,000 Dth w/
150,000 of
deliverability
$75 Million plus
$2 Million annual
O&M
2022 On site, in service territory liquefaction and
vaporization facility
Various pipelines –Pacific
Connector, Trails West, NWP
Expansion, GTN Expansion,
etc.
Varies Precedent
Agreement Rates
2020 Requires additional mainline capacity on
NWPL or GTN to get to service territory
Large Scale LNG Varies Commodity less Fuel 2020 Speculative, needs pipeline transport
In Ground Storage Varies Varies Varies Requires additional mainline transport to
get to service territory
117
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 800 of 829
118
Stochastic Analysis
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 801 of 829
119119
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 802 of 829
120120
Monte Carlo Simulations
•A way to estimate the probability of potential
future outcomes by allowing for a random set of
variables
•Uses historical price and weather data
•Avista’s Sendout model uses RMIX to help
choose an optimal resource stack and costs
under varying conditions
120
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 803 of 829
121121
Unserved Demand and Stochastic
Analysis
•Avista has no unserved demand in its resource
stack using a deterministic analysis in our
Expected case (coldest on record every year in
every location for 20 years)
•In order to show how we would solve for a
shortage we will utilize our high growth & low
prices case
–This models new potential resources and allows
Sendout to solve using an resource mix (RMIX)
option to select a least cost portfolio and run it
through a monte carlo simulation at 200 draws to
measure risk and uncertainty121
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 804 of 829
122122
Expected Case distribution
*200 Simulations
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 805 of 829
123
High Growth and Low Prices Scenario
(Example of determining additional resources to unserved demand)
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 806 of 829
124
Network Diagram for additional
resources
124
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 807 of 829
125
Spokane Weather Monte Carlo example
0
10
20
30
40
50
60
70
80
90
Nov-17 Nov-19 Oct-21 Oct-23 Oct-25 Oct-27 Oct-29 Oct-31 Oct-33 Oct-35 Oct-37
He
a
t
i
n
g

D
e
g
r
e
e

D
a
y
s

(
H
D
D
'
s
)
1 27 54 155 156 187
125
Draw #Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 808 of 829
126126
Monte Carlo weather draw examples
Max of Draw 155
Max of Draw 156126
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 809 of 829
127127
AECO Monte Carlo Draw Example
127
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 810 of 829
128
High Growth & Low Prices
200 Draws
$-
$10,000
$20,000
$30,000
$40,000
$50,000
$60,000
System Cost (thousands)
Ri
s
k

(
t
h
o
u
s
a
n
d
s
)
128
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 811 of 829
129
High Growth & Low Prices
Variability by Month by Gas Year
129
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 812 of 829
130
High Growth & Low Prices
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0
5
10
15
20
25
30
35
40
2.679 2.702 2.726 2.750 2.774 2.797 2.821 2.845 2.868 2.892 2.916 2.940 2.963 2.987
Cu
m
u
l
a
t
i
v
e
Fr
e
q
u
e
n
c
y
$ Billions
Frequency
Cumulative
Mean 90th 95th
5%
P(Cost>2.881)=5%
10%
P(Cost>2.845)=10%
Average: 2.783
StdDev: 0.054
Min: 2.664
90% percentile: 2.845
95% percentile: 2.881
Max: 2.970
Expected: 3.288
130
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 813 of 829
131
Supply by source and Area
December 20th
131
0
50
100
150
200
250
300
350
Dt
h

(
t
h
o
u
s
a
n
d
s
)
AECO Stanfield ID RNG_Dairy Kingsgate KlamFalls: RNG_Dairy
LaGrande: RNG_Dairy Malin RoseMed: RNG_Dairy Spokane STN2
Sumas WA RNG Landfill WYP: RMP JP PlymouthExhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 814 of 829
132
Supply by source and Area
February 15th
132
0
50
100
150
200
250
300
350
400
450
Dt
h

(
t
h
o
u
s
a
n
d
s
)
AECO Stanfield ID RNG_Dairy Kingsgate
KlamFalls: RNG_Dairy LaGrande: RNG_Dairy Malin RoseMed: RNG_Dairy
Spokane STN2 Sumas WA RNG Landfill
WYP: RMP JP Plymouth Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 815 of 829
133133
Summary
•Plymouth, Kingsgate and RNG are selected as a
solve to unserved demand
•Another 200 draw simulation of the High Growth
& Low prices case will be done once final costs
are provided by consultant
*This information will be provided in the draft IRP unless the TAC would like to
review during an additional meeting
133
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 816 of 829
134
Key Issues / Document Discussion
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 817 of 829
135135
IPUC
•Staff believes public participation could be further
enhanced through “bill stuffers, public flyers, local media,
individual invitations, and other methods.”
•Result: Avista utilized it’s Regional Business Managers
in addition to digital communications and newsletters in
all states in order to try and gain more public
participation. Previous IRP’s relied on website data and
word of mouth.
–eCommunity newsletter was sent out on January 15, 2018
135
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 818 of 829
136136
OPUC
•Staff Recommendation No. 1
–Staff recommends in Avista's 2018 IRP that Avista pursue an updated methodology, wherein the low/high
gas price curves continue to be based on low (high) historic prices in a Monte Carlo setting, but are inflated
to match the growth rate (yr/yr) of the expected price curve. The resulting curves wouid be based on historic
prices and also produce symmetric .risk profiles throughout the time horizon.
–Result: Avista updated its method as recommended by the Oregon commission. This new method deviates
from the expected price by the following method:
•Pricing starts at the expected price for the first year
•Years 2-6 the high and low price deviate +/-6% per year from the expected price
•Years 7-11 the high and low price deviate by +/-3% per year from the expected price
•Years 12 –20 the high and low price deviate by +/-1.5% per year from the expected price
•By the 20 year mark the high and low deviate from the expected price by +/-58.5%
•Staff Recommendation No. 2
–Staff recommends that Avista forecast its number of customers using at least two different methods and to
compare the accuracy of the different methods using actual data as a future task in its next IRP.
–Result: Avista analyzed the data, but there was nothing material discovered the come up with a meaningful
forecast alternative.
136
Exhibit No. 14 Case No. AVU-G-21-01 J. Morehouse, Avista
Schedule 1a, Page 819 of 829
137137
OPUC cont.
•Staff Recommendation No. 3
–Avista's 2018 IRP will contain a dynamic DSM program structure in its analytics.
•In, prior IRPs, it was a deterministic method based on Expected Case assumptions, in the 2018 IRP,
each portion will have the ability to select conservation to meet unserved customer demand, Avista will
explore methods to enable a dynamic analytical process for the evaluation of conservation potential
within individual portfolios and will work with Energy Trust of Oregon in the development of this
process and in producing any final results for its 2018 IRP for Oregon customers.
–Result –After attempting to get dynamic dsm into the Sendout model we determined an alternate method is necessary.
–1 –The total dsm measures has a maximum of 999 measures.If we were to model our areas as is combined with 400 measures by area we would come up with a total need of 4400 measures.
–2 –If we were able to group them by dollars or efficiency levels it takes away the desired approach of measure by measure.
–3 –We have every bit of data both ETO and AEG can provide and the model is not acting appropriately and cannot determine a stopping point
for taking a single measure.This means it would take the maximum, if cheaper than gas, to fill the entire demand.Clearly, this won’t
work.There are other issues with the program we will discuss during TAC 4.Another factor in this decision is the vendor does not know the dsm module and cannot provide assistance.We cannot see the code behind the application so it’s all a guess as to how to input the
measures.
–4 –The output data from ETO and AEG is very different and we need to understand it better before modeling.Avista has used AEG in some
form for the past 4 IRPs so we are comfortable with it. ETO, in Oregon only, has a different model and method and is still rather foreign to us.
•Staff Recommendation No. 4
–Staff recommends that Avista provide Staff and stakeholders with updates regarding its discussions and
analysis regarding possible regional pipeline projects that may move forward.
•Regional pipeline projects were discussed during TAC #3 meeting on March 29th, 2018. Avista does not have a shortage of resources for the 2018
Expected case. The regional pipelines take many years to place into service affording Avista the time to consider resources should they come into our
territory. New pipeline builds are expensive with unofficial quotes averaging $1 / Dth.
•Staff Recommendation No. 5
–Staff recommends that in its 2018 IRP process Avista work with Staff and stakeholders to
establish and complete stochastic analysis that considers a range of alternative portfolios for
comparison and consideration of both cost and risk.
•Result –This was shown in detail and with risk and cost in TAC 4 on May 10, 2018. Potential resources were
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OPUC cont.
•Staff Recommendation No. 6
–Environmental Considerations
•1. Carbon Policy including federal and state regulations, specifically
those surrounding the Washington Clean Air Rule and federal Clean
Power Plan;
–Result: Carbon Policy including the Clean Power Plan and Clean Air
Rule were both reviewed and included in TAC 2 Meeting materials on
2/22/2018. An indicator of where Avista’s carbon reduction
requirements under the CAR was also included. Since the CAR was
invalidated on 12/15/2017 in Thurston County Superior Court this
analysis is intended to meet the action item in addition to showing the
potential impacts of similar policies.
•2. Weather analysis specific to Avista's service territories;
–Result: A weather analysis was included and reviewed in TAC 2
meeting materials on 2/22/2018
•3. Stochastic Modeling and supply resources; and
•4. Updated DSM methodology including the integration of ETO
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WUTC
•Include a section that discusses impacts of the Clean Air Rule (CAR).
–In its 2018 IRP expected case, Avista should model specific CAR impacts as well
as consider the costs and risk of additional environmental regulations, including a
possible carbon tax.
–Result:
•Carbon Policy including the Clean Power Plan and Clean Air Rule were both
reviewed and included in TAC 2 Meeting materials on 2/22/2018. An
indicator of where Avista’s carbon reduction requirements under the CAR
was also included. Since the CAR was invalidated on 12/15/2017 in
Thurston County Superior Court this analysis is intended to meet the action
item in addition to showing the potential impacts of similar policies.
•For the 2018 IRP Avista is utilizing SB6203 from the WA Senate energy
committee on Feb. 1 as a proxy of a possible carbon tax in Washington
State.
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WUTC
•Provide more detail on the company’s natural gas hedging strategy,
including information on upper and lower pricing points, transactions with
counterparties, and how diversification of the portfolio is achieved.
–Avista’s natural gas hedging strategy was discussed during the TAC 2 Meeting on 2/22/2018.
The upper and lower pricing points in Avista’s programmatic hedges is controlled by taking
into consideration the volatility over the past year for the specific hedging period. This
volatility is weighted toward the more recent volatility. The window length and quantity of
windows is also a part of the equation. Avista transacts on ICE with counterparties meeting
our credit rating criteria. The diversification of the portfolio is achieved through the following
methods:
–Components: The plan utilizes a mix of index, fixed price, and storage transactions.
–Transaction Dates:Hedge windows are developed to distribute the transactions throughout
the plan.
–Supply Basins:Plan to primarily utilize AECO, execute at lowest price basis at the time.
–Delivery Periods:Hedges are completed in annual and/or seasonal timeframes. Long-term
hedges may be executed.
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WUTC cont.
•Ensure that the entity performing the CPA evaluates and includes the
following information:
–All conservation measures excluded from the CPA, including those excluded
prior to technical potential determination
–The rationale for excluding any measure
–A description of Unit Energy Savings (UES) for each measure included in the
CPA, specifying how it was derived and the source of the data
–The rationale for any difference in economic and achievable potential savings,
including how the Company is working towards an achievable target of 85
percent of economic potential savings.
–A description of all efforts to create a fully-balanced cost effectiveness
metric within the planning horizon based on the TRC.
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WUTC cont.
•Discuss with the TAC:
–The results of Northwest Energy Efficiency Alliance (NEEA)
coordination, including non-energy benefits to include in the CPA.
–The appropriateness of listing and mapping all prospective distribution
system enhancement projects planned on the 20 year horizon, and
comparing actual projects completed to prospective projects listed in
previous IRP’s.
•Provide a rationale for any difference in economic and achievable
potential savings
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2017 –2018 Avista’s Action Plan
•The price of natural gas has dropped significantly since the 2014 IRP.This is primarily due to the
amount of economically extractable natural gas in shale formations,more efficient drilling
techniques,and warmer than normal weather.Wells have been drilled,but left uncompleted due
to the poor market economics.This is depressing natural gas prices and forcing many oil and
natural gas companies into bankruptcy.Due to historically low prices Avista will research market
opportunities including procuring a derivative based contract,10-year forward strip,and natural
gas reserves.
•Result:After exploring the opportunity of some type of reserves ownership,it was
determined the price as compared to risk of ownership was inappropriate to go forward with
at this time.As an ongoing aspect of managing the business,Avista will continue to look for
opportunities to help stabilize rates and/or reduce risk to our customers.
Monitor actual demand for accelerated growth to address resource deficiencies arising from
exposure to “flat demand”risk.This will include providing Commission Staff with IRP demand
forecast-to-actual variance analysis on customer growth and use-per-customer at least bi-
annually.
Result:actual demand was closely tracked and shared with Commissions in semi-annual
or quarterly meetings.
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Avista’s 2020 IRP Action Plan
•Avista’s 2020 IRP will contain a dynamic DSM program structure in its
analytics. In prior IRP’s, it was a deterministic method based on based on
Expected Case assumptions. In the 2020 IRP, each portfolio will have the
ability to select conservation to meet unserved customer demand. Avista
will explore methods to enable a dynamic analytical process for the
evaluation of conservation potential within individual portfolios.
•Work with Staff to get clarification on types of natural gas distribution system
analyses for possible inclusion in the 2020 IRP
•Work with Staff to clarify types of distribution system costs for possible
inclusion in our avoided cost calculation
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Highlights of the 2018 IRP
•No resource needs in the Expected Case
•Higher long term customer growth rates
•Increased DSM potential and resultant avoided
costs
•Carbon costs broken out by jurisdiction
•Higher for WA and OR as compared to the 2016 IRP
•Washington and Idaho separated in Sendout
•Lower use per customer
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2018 IRP Timeline
•August 31, 2017 –Work Plan filed with WUTC
•January through May 2018 –Technical Advisory Committee
meetings. Meeting topics will include:
–TAC 1: Thursday, January 25, 2018: TAC meeting expectations, review of
2016 IRP acknowledgement letters, customer forecast, and demand-side
management (DSM) update.
–TAC 2: Thursday, February 22, 2018: Weather analysis, environmental
policies, market dynamics, price forecasts, cost of carbon.
–TAC 3: Thursday, March 29, 2018 :Distribution, supply-side resources
overview, overview of the major interstate pipelines, RNG overview and future
potential resources.
–TAC 4: Thursday, May 10, 2018:DSM results, stochastic modeling and
supply-side options, final portfolio results, and 2020 Action Items.
–June 21, 2018–TAC final review meeting to review final stochastics (if
necessary)
•July 2, 2018 –Draft of IRP document to TAC
•July 13, 2018 –Comments on draft due back to Avista
•August 31, 2018 –File finalized IRP document
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