20230629Attachment No 1 - On-Site Generation Study.pdf

Attachment No. 1
Rocky Mountain Power’s On-Site Generation Study

ROCKY MOUNTAIN POWER’S ON-
SITE GENERATION STUDY
PAC-E-19-08 Net Metering IPUC Order No. 34753
June 2023

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Table of Contents
Table of Contents ........................................................................................................................... i
List of Tables ................................................................................................................................ iii
List of Figures ............................................................................................................................... iv
List of Appendices ......................................................................................................................... v
Study Scope .................................................................................................................................. vi
Glossary ....................................................................................................................................... xi
1.0 Executive Summary ................................................................................................................. 1
2.0 Introduction ............................................................................................................................ 1
2.1 Current Net Metering Summary .......................................................................................... 1
2.2 Regulatory History ............................................................................................................... 3
3.0 Netting Period ......................................................................................................................... 4
3.1 Summary of Instantaneous, Monthly, and Hourly Billing .................................................... 4
3.2 Class Revenue Requirement ................................................................................................ 4
3.3 Class Export Payment .......................................................................................................... 7
3.4 Bill Impacts .......................................................................................................................... 7
3. 5 Administrative Costs ........................................................................................................... 8
4.0 Export Credit Rate ................................................................................................................... 9
4.1 Modeled Data as a Proxy for Actual Customer Export Data .............................................. 10
4.2 Model Validation Method ................................................................................................. 11
4.3 Avoided Energy Value ....................................................................................................... 15
4.3.1 Supporting Documentation for Avoided Energy Value ................................................... 16
4.3.2 Supporting Documentation for Non-Firm Energy ........................................................... 17
4.4 Avoided Capacity Value ..................................................................................................... 20
4.4.1 Loss of Load Probability Study .................................................................................... 20
4.4.2 Historical Peak Conditions .......................................................................................... 22
4.4.3 Time-Differentiated Capacity Values .......................................................................... 22
4.5 Avoided Risk ...................................................................................................................... 23
5.0 Project Eligibility Cap ............................................................................................................. 23
6.0 Avoided Transmission and Distribution Costs ....................................................................... 24
7.0 Avoided Line Losses .............................................................................................................. 24

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8.0 Integration Costs ................................................................................................................... 26
9.0 Avoided Environmental Costs and Other Benefits ................................................................ 28
9.1 Grid Stability, Resiliency, and Cybersecurity ..................................................................... 28
9.1.1 Grid Benefits of On-Site Generation with Storage ...................................................... 28
9.1.2 Community Resiliency Benefits of Customer Generation with Storage ..................... 29
9.1.3 Customer Generation and Cybersecurity Protection .................................................. 29
9.2 Public Health and Safety ................................................................................................... 30
9.3 Economic Benefits ............................................................................................................. 31
9.4 Possible Net Value of Renewable Energy Credits .............................................................. 31
9.5 Reduced Risk from End-of-Life Disposal ............................................................................ 32
10.0 Recovering Export Credit Rates in the ECAM ...................................................................... 32
10.1 Current Export Credit Recovery ....................................................................................... 32
10.2 Recovery Allocation ......................................................................................................... 32
10.3 Export Credit Price Scenarios .......................................................................................... 33
11.0 Schedule 136 Implementation Issues .................................................................................. 34
11.1 Billing Structure ............................................................................................................... 34
11.1.1 Time-of Delivery Pricing ........................................................................................... 34
11.1.2 Economic Evaluation for Customer-Generators and On-Site Generation System
Installers .............................................................................................................................. 35
11.1.3 Residential Solar Energy Disclosure Act .................................................................... 36
11.2 Export Credit Expiration .................................................................................................. 36
11.2.1 Accumulated Export Credits ..................................................................................... 36
11.2.2 Impact to Customers over Various Expiration Periods ............................................. 37
11.2.3 Export Credit Expiration Policy ................................................................................. 40
11.3 SAR Energy Rates Updates and IRP Cycle Impact to Export Credit Updates .................... 41
12.0 Smart Inverter Study .......................................................................................................... 42

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List of Tables
Name Location
Table 2.1: Idaho On-site Generation Customer Count as of 12/31/2022 2.1

Table 2.2: Average Size of On-Site Generation Customer’s System 2.1

Table 3.1: Comparison of Generation to Exports under Different Netting Scenarios 3.2
Table 3.2: Revenue Requirement Changes from Traditional Net Metering 3.2
Table 3.3: Export Payments by Class 3.3
Table 3.4: Bill Impacts by Class 3.4
Table 4.1: Summary of Export Credit Costs 4.0
Table 4.2: Northern Utah Customers and Idaho System Size (Installed Capacity) 4.2
Table 4.3: Northern Utah Customers and Idaho Average 2022 Monthly Exports 4.2
Table 4.4: Solar Production Difference - Weighted Mean Absolute Percentage Errors 4.2
Table 4.5: Customer Generation Exports During Peak Loads 4.4.2
Table 7.1: Idaho 2018 Demand and Energy Loss Summary 7.0
Table 10.1: Net Metering Reduction in Revenue by Class 10.2
Table 10.2: Annual Export Costs by Rate 10.3
Table 11.1: Excess kWh Total as of 8/1/2020 11.0
Table 11.2: Percentage of Customers Overproducing Annually 11.2
Table 11.3: Weighted Average of Customer Overproduction 11.2
Table 11.4: Impact of Different Update Cycles 11.3

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List of Figures
Name Location
Figure 2.1: On-site Generation Customer Adoption 2.1
Figure 4.1: Northern Utah Customers and Idaho Monthly Exports Comparison 4.2
Figure 4.2: Weighted LOLP Distribution 4.4.1
Figure 7.1: Transmission, Primary, and Secondary Components of an Electrical System 7.0
Figure 11.1: Frequency of Export Credit Updates 11.1

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List of Appendices
Name
Relevant Study
Location
Appendix 3.1: Idaho NEM Class Production 3.0
Appendix 4.1: Export Profile Jan21-Dec22 4.0
CONF Appendix 4.2: ID EE Cost-Effectiveness 4.0
CONF Appendix 4.3: ID Export Credit Calculations 4.0
Appendix 4.4: Idaho Export Profile Validation Avg Capacity 4.2
Appendix 4.5: ID Export Profile Validation Monthly Exports 4.2
Appendix 4.6: ID Export Profile Validation PV Watts Production 4.2
Appendix 4.7: Appendix K - Capacity Contribution - 2021 IRP 4.4.1
Appendix 8.1: Appendix F - Flexible Reserve Study- 2021 IRP 8.0
Appendix 8.2: Wind and Solar Integration Charges Approved in Order No. 34966 8.0
Appendix 11.1: Weighted Average Overproduction 11.2.1
Appendix 11.2: Idaho Expired Credit Analysis 2012-2022 11.2.1
Appendix 11.3: Customer Impact at 2-, 5-, and 10-Year Expiration 11.2.2
Appendix 11.4: SAR Export Credit Analysis 11.3
Appendix 12.0: Utah STEP - Smart Inverter Study 12.0

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Study Scope
Item
Number Subject Order No. 34753 – Attachment A: Scope of Rocky Mountain Power’s On-Site Generation Study
1 Netting Period
existing customer-generators netted their energy
exports: a. Monthly
b. Hourly
each of the existing customer-generators net their
energy exports: a. Monthly
b. Hourly
stratified by usage, if energy exports are netted: a.
Monthly
b. Hourly
c. Instantaneously
(Modeled Data as a
Proxy for Actual
Customer Export
Data)
will be available for customer-generators.

(Modeled Data as a
Proxy for Actual
Customer Export
Data)
validating the accuracy of its model and modeled
customer export data.
(Avoided Energy
Value)
the energy price assumptions in the Company’s most
recently acknowledged Integrated Resource Plan
(Avoided Energy
Value)
why the avoided cost of exported energy produced by
customer-generators should only be valued at 85% of

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Item
Number Subject Order No. 34753 – Attachment A: Scope of Rocky Mountain Power’s On-Site Generation Study
8 Export Credit Rate
(Avoided Capacity
Value)
provided by customer-generators on a class basis
using one of two methods:
a. a Loss of Load Probability Study, or
b. Determine the power that is reliably exported to
the grid by net metering during peaking events. Use
the top 100 peaking events from each of the past 10
years (1,000 peaking events). Use a reliability
threshold of 99.5%. If, for example, the study
determines that customer-generators provide no less
than 1.5 MW of power during 99.5% of the peaking
events, then use 1.5 MW as the basis for determining
the capacity avoided by the customer-generator class.
(Avoided Capacity
Cap
project eligibility cap according to a customer’s
demand as opposed to predetermined caps of 25 kW
and 100 kW. a. Analyze at 100% of demand.
Transmission and
Distribution Costs

costs that could be avoided by energy exported to the
grid by net metering customers using the
methodology for calculating the avoided transmission
and distribution costs provided by energy efficiency
costs of net metering customers as a class. Calculate
the dollar impact of deferring a study of the
integration charges for net metering customers until
AMI data is available, and if different, calculate the
dollar value of using a zero placeholder until AMI data

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Item
Number Subject Order No. 34753 – Attachment A: Scope of Rocky Mountain Power’s On-Site Generation Study
15 Avoided
Environmental
Costs and Other
Benefits
resiliency, and cybersecurity protection provided by
on-site generators as a class and different penetration
levels.
Environmental
Costs and Other
Benefits

from reduced local impacts of global warming such as
reduced extreme temperatures, reduced snowpack
variation, reduced wildfire risk, and other impacts
that can have direct impacts on Rocky Mountain
Environmental
Costs and Other
Benefits
creation and increased economic activity in the
immediate service territory.
Environmental
Costs and Other
Benefits
Credit sales produced by net metering exported
energy.
Environmental
Costs and Other
Benefits
concerns for the Company compared to fossil-fueled
resources.
Credit Rates in the
ECAM
metering bill credit costs.
Credit Rates in the
ECAM metering costs allocated to each class.
Credit Rates in the
ECAM allocated and recovered between rate classes for the
past five years.
Credit Rates in the
ECAM that the Export Credit Rate is the retail rate, 7.4
cents/kWh, 5 cents/kWh, or 2.23 cents/kWh.

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Item
Number Subject Order No. 34753 – Attachment A: Scope of Rocky Mountain Power’s On-Site Generation Study
24 Recovering Export
Credit Rates in the
ECAM recovered by rate class through the Company’s
proposed ECAM method going forward.
Implementation
Issues (Billing
Structure)
differences will be used to help align customer
generated exported energy with the Company’s
Implementation
Issues (Billing
Structure)
for differentiating energy and capacity credits could
be used to more closely align customer-generated
Implementation
Issues (Billing
Structure)
site generation system installers will have accurate
and adequate data and information to make informed
choices about the economics of on-site generation
Implementation
Issues (Billing
Structure)
be able to comply with the Residential Solar Energy
Disclosure Act if hourly or instantaneous netting
and/or granular time-differentiated export rates are
Implementation
Issues (Export accumulated export credits as of August 1, 2020.
Implementation
Issues (Export
and 10-year expiration periods.
Implementation
Issues (Export
Credit Expiration)
a. Show how the Company does or does not benefit
from the expiration of customer export credits.
b. Show how non net bill customers are harmed or
benefited from the expiration of customers export
Implementation
Issues (Frequency
of Export Credit
Updates)
to annual updates of the Export Credit Rate by
comparing the changes in the SAR energy rate, line
losses, and integration costs using historical data over
one year, one IRP cycle (two years), and two IRP

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Item
Number Subject Order No. 34753 – Attachment A: Scope of Rocky Mountain Power’s On-Site Generation Study
33 Smart Inverter
Study
inverter policy and quantify the benefits of applying
that policy in its Idaho service territory, in particular,

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Glossary
90/110 performance band – A PURPA generator’s energy deliveries plus or minus 10% from its
forecasted performance.
Automated Meter Infrastructure (AMI) – Integrated system of smart meters, communications
networks, and data management systems that enables two-way communication between
utilities and customers.
Distributed Energy Resource (DER) – A small-scale supply or demand resource that is usually
situated near sites of electricity use.
Energy Imbalance Market (“EIM”) – The EIM automatically balances demand every five
minutes with the lowest cost energy available across the participating grids.
Export Credit Rate (ECR) – The total credit to the customer once a customer’s generation is
netted by either real-time billing or interval netting.
Flexible Reserve Study (FRS) – Estimates the regulation reserve required to maintain
PacifiCorp’s system reliability and comply with North American Electric Reliability Corporation
(NERC) reliability standards as well as the incremental cost of this regulation reserve.
Instantaneous Billing – Method of calculating customer-generator billing where the customer’s
financial credit for exports and the customer’s retail charges are calculated separately and the
net result is either charged or credited to the customer.
Integrated Resource Plan (IRP) – The IRP is a comprehensive decision support tool and
roadmap for meeting the company's objective of providing reliable and least-cost electric
service to all our customers. Developed with involvement from state utility commission staff,
state agencies, customer and industry advocacy groups, project developers, and other
stakeholders the IRP focuses on the first 10 years of a 20-year planning period and includes the
preferred portfolio of supply-side and demand-side resources to meet this need. PacifiCorp
prepares its integrated resource plan on a biennial schedule, filing its plan with state utility
commissions during each odd numbered year.
Integration Costs – The additional expense when variable energy resources are added to a
portfolio. Typically includes costs related to the uncertainty and variation in variable energy
resource output from moment to moment. For distributed resources, integration costs could
potentially include equipment and/or operational changes to manage impacts on the
distribution system.
Interval Netting – Method of calculating customer billing where the total electricity consumed
and generated is calculated for a given interval and the output of that calculation is included on
a customer’s bill.
Line Losses – Loss of electricity due to the resistance of the conductor, or line, against the flow
of the current, or electricity.

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Loss of Load Probability (“LOLP”) – Likelihood of a risk of loss of load event where system load
and/or reserve obligations could not be met with available resources.
Net Billing – As defined by Electric Service Schedule 136, charges for all electricity supplied by
the Company and netted by the export credit for the electricity generated by an eligible
customer and fed back to the electric grid over the applicable billing period. Net billing differs
from net metering because net billing customers do not get a credit in kWh but instead all net
energy exports are credited to the customer at the exported customer-generated energy credit
rate.
Net Metering – As defined by Electric Service Schedule 135, the difference between the
electricity supplied by the Company and the electricity generated by an eligible customer and
fed back to the grid over the applicable billing period. Net metering may also refer to on-site
generation or a distributed energy resource in general.
The Public Utility Regulatory Policies Act of 1978 (“PURPA”) – Enacted following the energy
crisis of the 1970s to encourage cogeneration and renewable resources and promote
competition for electric generation.
Qualifying Facility (“QF”) – a generation facility that meets certain ownership, operating, and
other criteria established by the Federal Energy Regulatory Commission (“FERC”) according to
the Public Utility Regulatory Policies Act of 1978 (“PURPA”)
Renewable Energy Certificates (“RECs”) – The property rights to the environmental, social, and
other non-power attributes of renewable electricity generation. RECs are issued when one
megawatt-hour (MWh) of electricity is generated and delivered to the electricity grid from a
renewable energy resource.
Surrogate Avoided Resource ("SAR") Methodology – Method for determining avoided costs for
standard qualifying facility resources up to at least 100 kW in nameplate capacity. Under the
SAR Methodology, avoided energy costs reflect forecast prices for natural gas and the assumed
heat rate of a combined cycle combustion turbine. Monthly weighting factors are used to
differentiate avoided costs by month, and an adjustment of 85 percent is applied to non-firm
resources.

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1.0 Executive Summary
Rocky Mountain Power, a division of PacifiCorp (“PacifiCorp” or the “Company”) presents this
study (“Study”) to evaluate methods, inputs, and assumptions for valuing on-site generation
that is exported to the grid. The Idaho Public Utilities Commission (“Commission”) approved the
scope of this study (“Study Scope") of on-site generation on August 26, 2020.1
The Study provides the Commission and stakeholders with the information needed to evaluate
changes to the export credit rate (“ECR") for on-site customer generators in the future. The
purpose of this Study is not to propose a specific ECR at this time but to initiate a review and
obtain feedback on potential considerations for valuing an ECR.
The Study gives a snapshot of its current approximately 2,200 on-site customer generation
customers in Idaho. Data for modeling different components of the ECR was based on proxy
Utah customers in the same climate zone as Idaho customers.
The effects of netting imports monthly, hourly, and instantaneously were analyzed to show the
revenue requirement impact for each scenario. As guided by the Commission’s Study Scope, the
avoided cost of exported energy was calculated using the same price assumptions as the
Company’s most recently acknowledged integrated resource plan (“IRP”) and the capacity value
of exported energy was analyzed using the loss of load probability (“LOLP”) study. The avoided
capacity value of on-site generators was modeled during PacifiCorp’s highest risk-of-loss-of-
load-event hours to evaluate potential contribution of on-site generation during the grid’s most
strained hours. Different export credit scenarios were analyzed to show the annual export costs
at various ECRs. The Study concludes by looking at the different implementation issues for an
ECR including how different customers would be affected by expired credits and the effects of
updating the ECR at different frequencies.
2.0 Introduction
2.1 Current Net Metering Summary
As of December 31, 2022, there are 2,196 on-site generating customers connected to
PacifiCorp’s system in Idaho. The majority of those customers are residential using solar
photovoltaic (“PV”) systems. There are also 61 wind generation customers and five customers
with a mix of electricity sources or with hydro generators.

1 In the Matter of the Application of Rocky Mountain Power to Close the Net Metering Program to New Service &
Implement a Net Billing Program to Compensate Customer-Generators for Exported Generation. Case No. PAC-E-19-08, Order No. 34753.

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Table 2.1: Idaho On-Site Generation Customer Count as of 12/31/2022
Other
2,055 54 5 2,114
63 5 - 68
8 2 - 10
4 - - 4

Net metering customers participate in the Company’s customer generation programs through
Schedules 135 or 136. Residential and general service customers taking service on Schedules 1,
23, 23A, or 36 must not have a generating capacity greater than 25 kilowatts (kV). All other
customers are limited to a generating capacity of 100 kW. Schedule 135 closed to new
applicants as of October 2, 2020. The average size of a residential customer’s solar PV system is
8.1 kW, as of December 31, 2022.2
Table 2.2: Average Size of On-Site Generation Customer’s System
(average) (average) kW (average)
8.1 3.75 12.35
16.95 9.44 -
44.74 2.4 -
21.58 - -

On-site generation customer growth has increased steadily over the last 10 years with an
annual average growth rate of 40%. While customer growth has moderated slightly during the
last 3 years in percentage terms, 2022 saw the most on-site customers connecting to the
system with a total of 500 new customers added.

2 For more detail on the customer size, generation type, and customer system size, see the system size tab of Appendix 11.2: Idaho Expired Credit Analysis 2012-2022.

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Figure 2.1: On-Site Generation Customer Adoption

2.2 Regulatory History
PacifiCorp began offering Electric Service Schedule 135 - Net Metering Service, in 2003, as
approved by Order No. 29260 in Case No. PAC-E-03-4. The case was initiated following a
petition by the NW Energy Coalition which requested a net metering schedule in Idaho
following approval of net metering schedules for Idaho Power Company and Avista. In that
case, PacifiCorp proposed Schedule 135, which was patterned from Idaho Power’s net metering
Schedule 84.
Schedule 135, as approved by Order No. 29260, limited participation on Schedule 135 to no
more than 25 kilowatts for customers taking service on Schedules 1, 36, 23, or 23A and to 100
kilowatts for all other customers. Customers taking service on Schedules 1, 36, 23 or 23A were
to be credited for excess net energy at the customer’s standard service rate and all other
customers would be credited net excess energy at a rate that equals 85 percent of the monthly
weighted average of the daily on-peak and off-peak Dow Jones Mid-Columbia Electricity Price
Index (Dow Jones Mid-C Index).
On June 14, 2019, PacifiCorp submitted an application to close Electric Service Schedule 135
and to implement a net billing program to compensate customer-generators for exported
generation.3 On August 26, 2020, the Idaho Public Utilities Commission issued Order No. 34753
which required this on-site generation study to be completed. On October 2, 2020, the Idaho
Public Utilities Commission issued Order No. 34798 initiating Electric Service Schedule 136 - Net

3 See In the Matter of the Application of Rocky Mountain Power to Close the Net Metering Program to New Service
& Implement a Net Billing Program to Compensate Customer-Generators for Exported Generation. Case No. PAC-E-19-08.
0
500
1000
1500
2000
2500
On-Site Customer Count
Irrigation
Large Commercial
Small Commercial
Residential

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Billing Service. Order No. 34798 also adopted Order No. 34752, which granted existing Electric
Service Schedule 135 customers grandfathered status for a period of 25 years.
3.0 Netting Period
3.1 Summary of Instantaneous, Monthly, and Hourly Billing
There are three different methods of “netting” that may be used to calculate the amount of
electricity that a customer consumes and exports: instantaneous, hourly, and monthly. In a
“real time” or “instantaneous” calculation, the meter exports and consumption are measured
separately. With instantaneous netting, all of the consumption from the electric grid is
measured and charged the retail rate and all exports to the electric grid are also measured and
credited to the customer.
Interval netting, on the other hand, does not calculate instantaneously but instead calculates
the total net electricity consumed or generated over the specified interval. While on first look it
may appear that instantaneous and interval netting would result in similar outcomes, this is not
the case. To the extent a customer was consuming power from the electric grid during part of
an hour, and exporting during the rest of an hour, hourly netting would result in an equal
reduction to both consumption and exports, relative to instantaneous netting. With monthly
netting, even larger amounts of consumption and exports can be offset, as the customer’s
consumption may be days or weeks earlier or later than their exports.
Using an interval over which exports and imports are netted masks the intertemporal reality of
the service that Rocky Mountain Power provides. One benefit of a net billing program without
interval netting is that it sends a price signal for customer-generators to align their usage with
their generation output. This can benefit other non-participating customers by accurately
accounting for the load that the customers with generation draw from the system. Netting over
an interval period, such as 15 minutes or an hour, sends a weaker price signal for customer-
generators to match usage with generation. With the scale of customer generation that has
been adopted in the Company’ service territory, encouraging alignment of loads with
intermittent generation has never been more important. When a cloud rolls by an area where
extensive customer generation is present, their energy production will suddenly drop, and the
Company must provide the power demanded. Indeed, every fraction of a second the Company
must serve the load requirements of its customers as loads fluctuate in real time. Sending a
robust price signal to match customer generation with load as in the net billing program
provides a greater opportunity for customer-generators to benefit the system.
3.2 Class Revenue Requirement
The tables and analysis below address Study Scope Item 1.

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Study Scope Item 1
their energy exports:
a. Monthly
b. Hourly
c. Instantaneously

To estimate the revenue requirement for each of the netting regimes listed for the Study, the
Company analyzed the monthly billing and metering data from customer-generators in 2022
from which the Company could determine values for the monthly netting and instantaneous
netting scenarios. The Company did not include irrigation customer-generators, because there
were only two irrigation customers with on-site generation, and they did not have a full 12
months of revenue in 2022.
Automated meter infrastructure (“AMI”) installations are being finalized during the second
quarter of 2023 and the Company does yet not have enough hourly profile data available for
customer-generators in Idaho for hourly loads. Instead, the Company used proxy profile data
from its customer-generators in northern Utah which are in the same climate zone as the
Company’s Idaho service territory. To estimate hourly netting values, the monthly percentage
differences in hourly as compared to instantaneous netting from the Northern Utah dataset
were applied to metered data from Idaho customer-generators. The following table 3.1 shows
the exported energy volumes under each netting scenario in total and also expressed as a
percentage of generation:

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Table 3.1: Comparison of Generation to Exports under Different Netting Scenarios
(kWh) Netting Netting Netting
2,111,780 8,062,620 8,554,724 16,422,970
551,492 2,058,027 2,182,649 4,124,398
244,599 534,099 565,335 1,512,638
58,760 116,414 123,320 522,963

Netting Netting Netting Generation
13% 49% 52% 100%
13% 50% 53% 100%
16% 35% 37% 100%
11% 22% 24% 100%

To estimate the revenue requirement impact by class of different netting scenarios, the
Company estimated the change in revenue from traditional net metering. Increased revenue
from the class lowers the overall revenue requirement. Assuming a generic 3¢ per kWh export
credit, the Company estimates the following revenue requirement changes from traditional net
metering (increased net revenue from customer generation participants) for the different
netting scenarios:
Table 3.2: Revenue Requirement Changes from Traditional Net Metering
Netting Netting Netting Net Metering
$1,253,784 $1,716,364 $1,756,739 $1,090,937
$384,917 $462,434 $468,933 $333,476
$156,402 $172,883 $174,728 $141,635
$296,204 $296,925 $297,011 $295,469
$2,091,307 $2,648,606 $2,697,411 $1,861,517
-$229,791 -$787,089 -$835,895 -
(Δ from Traditional Net Metering)

Based on Table 3.2 above, monthly netting would result in $230k reduction in the revenue
requirement when compared with traditional net metering, meaning that an additional $230k is
recovered from customer generators and not required from other customers. Hourly netting

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would see a larger $787k reduction and instantaneous netting would see a $836k reduction in
the revenue requirement when compared with traditional net metering.
3.3 Class Export Payment
In addition to the class revenue requirement, the Study Scope required the Company to
calculate the export credits for each class at different intervals.

Study Scope Item 2
net their energy exports:
a. Monthly
b. Hourly
c. Instantaneously

Using the same assumptions as the revenue requirement analysis above, the Company
estimates the following class export payments for the different netting scenarios.
Table 3.3: Export Payments by Class
Netting Netting Netting
$63,353 $241,879 $256,642
$16,545 $61,741 $65,479
$7,338 $16,023 $16,960
$1,763 $3,492 $3,700

3.4 Bill Impacts
The Study Scope required the Company to calculate the bill impacts to existing customer-
generators.

Study Scope Item 3
netted:
a. Monthly
b. Hourly
c. Instantaneously

Using the same assumptions from the previous sections, the Company estimates the following
average bills for the different netting scenarios.

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Table 3.4: Bill Impacts by Class
Netting Netting Netting Net Metering
$14.49 $44.44 $47.28 -$2.66
$77.92 $97.97 $99.38 $77.49
$128.66 $144.73 $145.83 $128.55
$179.33 $193.98 $194.99 $179.33
$247.76 $261.38 $262.37 $247.76
$372.39 $383.30 $384.07 $372.39
$624.67 $632.67 $633.28 $624.67
$2,553.63 $2,559.70 $2,560.04 $2,553.63

3. 5 Administrative Costs
Instantaneous billing provides administrative benefits compared to interval netting. Using the
meters for exported and delivered energy instead of relying upon profile data to bill customers
is less administratively burdensome for the Company. Without netting, the Company’s meters
simply record energy delivered and energy exported and send those registers to the Company’s
billing system to calculate a bill for the customer. While the Company has automated much of
the process for billing customers taking service on Schedule 136 , based upon 15-minute
intervals, there still is some backend manual work that is required to accurately bill customers.
15-minute interval netting requires profile data for each meter which on average includes 2,920
reads for each monthly billing period. Most of the time, there are no issues with this data, but
when there is, Company employees must resolve it. Some of the issues that may require
intervention include:
• Meter aggregations require manual calculation using a billing calculation sheet. The
Company estimates 0.25 – 0.50 hours per month aggregating meter data depending on
number of meters involved.
• Interval data issues such as from gaps in data or when meters are exchanged also
require manual reconciliation. It is hard to quantify the time spent on missing data as it
only occasionally happens and now AMI exchanges are mostly complete in Idaho. Going
forward, meter exchanges will happen less frequently. Assuming a one percent failure
of billings each year and 0.5-1.0 hours to resolve for each 100 customers in net billing,
then the following time requirement is estimated:
100 customers x 12 billings = 1200 x 1% = 12 accounts x 0.5 – 1.0 hour = 6
- 12 hours annually

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At the current volume of 2,200 customer-generators, this would scale to a 132 to 264 hours of
activity per year for the Company. In addition, using total exported energy and total delivered
energy in the billing calculation is a simpler concept to explain to customers than netting over
each 15-minute or hour interval. It is much easier for someone to understand that all energy
sent to the grid will get a certain export price and all energy delivered to the customer will be
billed at standard tariff rates than to describe how energy is netted in every interval period.
4.0 Export Credit Rate
The ECR determines the total credit to the customer once a customer’s generation is netted by
either real-time billing or interval netting. The ECR is established through a method that looks
at the costs the Company avoids as a result of the exported energy. These costs are broken into
five parts:
• Avoided Energy Costs
• Avoided Capacity or Generation Costs
• Avoided Fuel Risk Costs
• Avoided Transmission and Distribution Costs
• Avoided Line Losses
Once all the costs from the parts listed above are combined, they are adjusted to account for
the costs incurred by integrating the customers into the system. A summary of these costs by
component is provided in table 4.1 below, and descriptions of each component are provided in
the following sections. Note that these values have not been adjusted to reflect the reduced
value of non-firm deliveries, as discussed in Section 4.3.2.

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Table 4.1: Summary of Export Credit Costs
¢/kW
h

Year
Energy
Value
(Forecast)
EIM
Energy
Value
(Actual)
Risk
Value Gen
Capacity
Trans
Capacity
Dist
Capacity
Losses Cost Export
Credit
4.08 2.83 0.00 0.00 0.03 0.07 0.29 -0.02 4.44
3.38 4.35 0.71 0.00 0.03 0.07 0.29 -0.02 4.46
3.25 0.51 0.00 0.03 0.07 0.27 -0.61 3.53
1.99 0.08 0.00 0.03 0.07 0.15 -0.19 2.14
2.03 0.03 0.00 0.03 0.07 0.15 -0.12 2.19
2.01 0.02 0.40 0.03 0.08 0.18 -0.09 2.62
2.12 0.02 0.40 0.03 0.08 0.19 -0.24 2.60
2.34 0.03 0.41 0.03 0.08 0.21 -0.23 2.86
2.84 0.02 0.41 0.03 0.08 0.24 -0.04 3.58
2.99 0.02 0.42 0.03 0.08 0.25 -0.05 3.74
3.07 0.02 0.42 0.03 0.08 0.26 -0.02 3.86
3.16 0.02 0.43 0.03 0.09 0.27 -0.03 3.97
3.18 0.02 0.43 0.03 0.09 0.27 -0.01 4.01
3.34 0.02 0.44 0.03 0.09 0.28 -0.01 4.19
3.47 0.02 0.44 0.03 0.09 0.29 -0.01 4.34
3.80 0.02 0.45 0.03 0.09 0.31 -0.01 4.70
4.43 0.03 0.45 0.04 0.10 0.36 -0.005 5.40
5.22 0.10 0.46 0.04 0.10 0.42 -0.005 6.33
5.68 0.09 0.46 0.04 0.10 0.45 -0.005 6.82
5.53 0.11 0.47 0.04 0.10 0.44 -0.03 6.66

4.1 Modeled Data as a Proxy for Actual Customer Export Data
In relation to using modeled data as a proxy for actual customer data, the Study Scope asked
for a date when a full year of hourly AMI export data will be available.
Study Scope Item 4
Confirm when a full year of hourly AMI export data will be available for customer-generators.

As of April 27, 2023, deployment of AMI meters in Idaho is 97 percent complete. A full year of
hourly AMI export data for Idaho customers for nearly all customer-generators will be available
one year from this date.

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4.2 Model Validation Method
The Study Scope required the Company to explain its method for verifying and validating the
accuracy of its model and modeled customer data.
Study Scope Item 5
Explain the Company’s method for verifying and validating the accuracy of its model and
modeled customer export data.

As detailed in the discussion of the netting period, the export profiles were derived from a total
census of customer-generators taking service on Schedule 136 in northern Utah that are in the
same climate zone as the Company’s Idaho service territory.
While the Company maintains a load research sample for Idaho customer-generators, the
profile derived from Utah customers in northern Utah is more suited for this Study for several
reasons. First, the Idaho customer generation load research sample was implemented in 2014
and sampled from a very different mix of customers than what we see today. Roughly one-half
of the generation systems in the 2014 Idaho sample were wind; however, most customer-
generator systems are now operating solar PV. Second, the Idaho customer generation load
research sample consists of 44 sites and is subject to sampling uncertainty. A sample this size
produces estimates with sampling errors of 10 to 20 percent. Estimates derived from a census
of northern Utah customers are not subject to sampling error. Finally, the Company’s northern
Utah and Idaho service territories have similar climates and geographic characteristics. The
Company used the International Energy Conservation Code (IECC) climate zone map to identify
Utah customers in climates similar to that of the Company’s Idaho service territory.4 Nearly all
Idaho customers are in climate zone 6B. The Company identified Utah customers taking service
on Schedule 136 also in climate zone 6B and calculated an average export profile from these
customers (“Northern Utah Customers”).
To validate the accuracy of export profiles derived from a census of the Company’s Northern
Utah Customers, the Company first reviewed sources of statistical error and bias. Sampling and
measurement error are two major sources of statistical error. By definition, estimates derived
from a census are not subject to sampling error. Measurement errors are small—the Company
purchases meters with accuracy certified by the manufacturer to be in compliance with the
American National Standard Code for Electricity Metering (ANSI C12.1).
The Company also examined sources of bias. Estimates are biased if the population of interest
is systematically different from the proxy used to represent that population. Possible
systematic differences and sources of bias between these two groups include:

4 See the 2021 International Energy Conservation Code (IECC) “Section C301 Climate Zones” for a map and a list of climate zones for each county. Counties in the Company’s Idaho service territory are in climate zone 6B (cold and dry). https://codes.iccsafe.org/content/IECC2021P1/chapter-3-ce-general-requirements#IECC2021P1_CE_Ch03_SecC301

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Differences in photovoltaic system sizes: If customer demand were otherwise equal, a
larger photovoltaic system size would result in a greater portion of the total production
of the system being exported, and smaller portion consumed onsite.
Differences in actual monthly exports and deliveries: Building size and the mixture of
end uses can contribute to differences in total customer demand, which would
contribute to a difference in actual monthly exports and deliveries. Higher full
requirements consumption, with equal production, would result in lower exports.
Different amounts of solar irradiance and PV production in the two regions: Idaho
customer-generators are concentrated primarily in counties surrounding Idaho Falls.
This is 150 miles north of Logan, Utah, where most of the Northern Utah Customers are
concentrated. Geographic differences could produce different levels of solar irradiance
and PV production.
The Company first compared the installed capacity of customer generation systems of Northern
Utah Customers and Idaho to determine if there was a systematic difference in system sizes.
The Company found a small difference in system sizes—the installed capacity of Idaho
customers’ systems is 5.2 percent lower than the capacities of Northern Utah Customers. Table
4.2 presents the mean installed capacity for each of these groups.
Table 4.2: Northern Utah Customers and Idaho System Size (Installed Capacity)5
Population Installed Capacity (kW)
Average Northern Utah Customers
Average Idaho
Percent Difference -5.2%

Next, the Company compared actual average monthly deliveries and exports from Idaho
customer-generators against Northern Utah Customers in 2022. The distribution of exports
across months for Idaho and Northern Utah Customers is similar as shown in Table 4.3 and
Figure 4.1.6

5 Supporting data provided in Appendix 4.4: Idaho Export Profile Validation Avg Capacity.
6 Supporting data for Table 4.3 and Figure 4.1 provided in Appendix 4.5: ID Export Profile Validation Monthly Exports.

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Table 4.3: Northern Utah Customers and Idaho Average 2022 Monthly Exports
139 95 2% 2%
375 199 6%3%
Mar 426 412 7%7%
Apr
May 677 644 11%11%
Jun 804 776 13%13%
Jul
Aug 549 655 9%11%
Sep 575 651 9%11%
Oct
Nov 434 383 7%6%
Dec 189 143 3%2%
Total 6,136 5,980 100% 100%

Figure 4.1. Northern Utah Customers and Idaho Monthly Exports Comparison

The Company found that Idaho customers exported slightly less than Utah customers in winter
and shoulder months, while exporting more in summer months. The weighted average absolute
difference in monthly exports between Idaho and Northern Utah Customers is approximately
11 percent (weighted by monthly exports).
Finally, the Company used PV production models to compare the hourly shape of systems in
Idaho against those customers located in Utah climate zone 6B. This involved first determining
the geographic concentration of customer-generators in Utah climate zone 6B and Idaho. Sixty-

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nine percent of all the customer generation capacity in Idaho is concentrated in the counties
surrounding Idaho Falls including Bonneville (37 percent), Jefferson (20 percent), and Madison
(12 percent) counties. In Utah climate zone 6B, counties near Logan; Cache (33 percent),
Summit (28 percent), and Box Elder (20 percent), account for 82 percent of the installed
capacity.
The Company used the National Renewable Energy Laboratory’s PVWatts7 calculator to
estimate the hourly solar PV production for a typical system located in Idaho Falls, ID and
Logan, UT. PVWatts is a publicly available online calculator that estimates the amount of
electricity produced by a typical PV system. It uses solar irradiance data and assumptions for
latitude, longitude, array type, tilt, azimuth, and weather to estimate PV system output.
For each location, the Company estimated the hourly output of an 8 kW, south-facing, fixed
array, standard crystalline silicon PV system with a 20-degree tilt. The Company then calculated
each location’s distribution of solar PV production across the year and within each month. The
Company then summarized these profiles into 12-month by 24-hour shapes and calculated the
Weighted Mean Absolute Percentage Error (“wMAPE”) between the Idaho and Utah production
profiles for each time interval. To understand the total difference across months and the hourly
difference within months, two versions of wMAPES were calculated:
Monthly Weighted Mean Absolute Error: This statistic captures differences in the total
Utah and Idaho monthly across months. If one location produces more than another in a
specific month, this wMAPE will be higher for that month.
Hourly Weighted Mean Absolute Error: This statistic measures the difference between
Idaho and Utah hourly production profiles within months. It compares the average 24-
hour shape for each month, ignoring differences in production across months. If PV
systems in one location produce more later in the day than the other, these wMAPEs
will be higher.
Table 4.4 shows the wMAPES for each month from the monthly and hourly perspectives.
Months with higher monthly wMAPEs have a larger difference in both total PV production for
the month and across hours within the month. Months with higher hourly wMAPEs exhibit
differences in 24-hour shapes (ignoring differences across months).
Winter months exhibit the greatest mean absolute percentage errors, which reflect both
differences in latitude and the number of sunny days. This finding is consistent with the prior
comparison of monthly exports. Overall, the wMAPEs are 7.9% across the year and 5.4% within
months.

7 See https://pvwatts.nrel.gov/

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Table 4.4: Solar Production Difference - Weighted Mean Absolute Percentage Errors8
Percentage error Percentage Error
18.7% 14.0%
8.7% 9.5%
4.6% 4.7%
7.7% 3.9%
8.3% 7.4%
7.5% 3.5%
5.0% 2.4%
5.7% 4.7%
5.2% 3.9%
5.3% 3.9%
14.8% 8.3%
26.5% 13.8%

The Company concludes from this analysis:
• System sizes for Idaho customer-generators are like those of Northern Utah Customers.
The Company found that the Idaho systems have installed capacities that are
approximately 5 percent lower than northern Utah systems.
• Both models and actual monthly data indicate that winter months exhibit a larger
difference in total PV production (greater than 10 percent wMAPE).
• Within months and across hours, the difference between the Logan and Idaho Falls
production profiles is small—mostly less than 10 percent, on average.
The Company expects that differences in hourly export profiles between Northern Utah
Customers and Idaho will be like the differences found in the Logan and Idaho Falls production
profiles. While the Company expects a greater difference in exports in the winter months and a
smaller difference in the summer months, its analysis indicates that the overall difference will
be small.
4.3 Avoided Energy Value
To evaluate the best method for calculating the avoided energy value, the Study Scope
requested the avoided energy value be calculated using the energy price assumptions in the
Company’s most recently acknowledged IRP.

8 Supporting data provided in Appendix 4.6: ID Export Profile Validation PV Watts Production.

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Study Scope Item 6
Calculate the avoided cost of exported energy using the energy price assumptions in the
Company’s most recently acknowledged Integrated Resource Plan (“IRP”).

The Commission acknowledged the Company’s 2021 IRP in August 2022. The 2021 IRP included
a variety of price and policy scenarios, with the main scenario including a medium gas price
forecast and medium greenhouse gas costs. These assumptions are embodied in hourly market
price forecasts, based on input assumptions used in the Company’s September 2020 official
forward price curve. Within the IRP models, energy value varies by location because of
transmission constraints and the balance of supply and demand. As a result, energy value in the
Company’s Idaho service territory will vary from the price at distant market points. With that in
mind, for the purpose of calculating the energy value and cost-effectiveness of energy
efficiency measures, the Company uses hourly marginal resource costs reported by its IRP
models.
The Company notes that energy price assumptions in the 2021 IRP will be three years out of
date in September 2023. The Commission’s acknowledgment of the 2021 IRP does not touch
upon these assumptions, so there is little basis to conclude that relying upon the outdated
assumptions in the 2021 IRP is more aligned with Commission direction than a more recent
forecast or actual historical results would be.
The Company also notes that there is an important relationship between customer generation
exports and the Company’s marginal costs that is not captured by the forward price curve.
Specifically, customer generation exports will tend to be lower when customer load is high
because a greater portion of the customer’s production can be devoted to the customer’s own
needs under those conditions. If, for example, the customer’s load is high because of effects
that impact the system as a whole, such as regional weather conditions, this would manifest as
lower exports when demand and energy costs are highest. This relationship between exports
and system conditions is not reflected in the forecast modeled using 2021 IRP results, but it is
present in historical data. Specifically, by weighting actual Energy Imbalance Market (“EIM”)
prices by the actual customer generation export volumes in each interval, an accurate
representation of energy value can be identified. Because EIM prices are public, do not require
complicated modeling assumptions, and more accurately capture the relationship between
customer exports and system conditions, they are a strong candidate for identifying energy
value. Energy values based on 2021 IRP results and historical EIM prices are presented in Table
4.1.
4.3.1 Supporting Documentation for Avoided Energy Value
The Study Scope requested the supporting documentation for the Company’s avoided energy
value calculation.

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Study Scope Item 6(a)
Provide supporting documentation.

The 2021 IRP energy values shown in Table 4.1: Summary of Export Credit Costs reflect the
value of customer exports using the hourly marginal energy prices for the Goshen location from
the Company’s 2021 IRP preferred portfolio results, which were also used for the Idaho energy
efficiency cost-effectiveness evaluation. The EIM energy values shown in Table 4.1 reflect the
value of customer exports using hourly average of historical EIM prices in the Real-Time Pre-
Dispatch market (15-minute market) for the PacifiCorp East Load Aggregation Point location (a
weighted average for load points in PacifiCorp’s East Balancing Authority Area).
4.3.2 Supporting Documentation for Non-Firm Energy
The Study Scope requested the Company provide calculations and documentation showing why
the avoided cost of exported energy produced by customer-generators should be valued at 85%
of the total avoided energy value.
Study Scope Item 7
Provide the calculations and documentation showing why the avoided cost of exported
energy produced by customer-generators should only be valued at 85% of the total avoided
energy value.

Customer-generators are non-firm energy and should be valued at 85% of the total avoided
energy value in line with the commission practices for pricing qualifying facilities (“QF”).
Because customer-generators make no commitment to export particular volumes to the
system, they are considered non-firm energy. An 85 percent adjustment is similar to current
practices for both the surrogate avoided resource (“SAR”) methodology when pricing qualifying
facilities and for the customer generation net billing credit for PacifiCorp customers taking
service on Schedule 135.9
However, the SAR Methodology does have some limitations since it does not have hourly detail.
Based on this limitation, the Company recommends using EIM prices for the avoided energy
value because it is available in a higher granularity and can be used to value the particular
pattern of customer exports. Because EIM prices are set shortly before delivery, they do not
have the same risk as firm delivery commitments made in advance and may not require as large
of a non-firm adjustment as would be appropriate for a forward market product. EIM prices are

9 In addition to the 85 percent adjustment made for non-firm energy under the SAR Methodology, Schedule 135’s
Net Metering Rate Credit for non-residential customers is calculated at 85 percent of the monthly weighted average
of the daily on-peak and off-peak Mid-Columbia Intercontinental Exchange Electricity Price Index (Mid-C ICE
Index) prices for non-firm energy.

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also public, which allows for greater transparency, and reflect actual relationships between
exports and prices, which can be difficult to assess in a forecast.
Idaho Regulatory History of SAR Methodology and Non-Firm Energy Pricing
The Commission has approved the SAR Methodology for determining avoided costs for
standard qualifying facility resources up to at least 100 kW in nameplate capacity. Under the
SAR Methodology, avoided energy costs reflect forecast prices for natural gas and the assumed
heat rate of a combined cycle combustion turbine. 10
In Order No. 29632, the Commission found that energy “delivered outside of the 90/110
performance band (i.e., non-conforming energy) would be priced at 85 percent of the non-firm
market price or the contract price, whichever is less.”11 The non-firm market price has been
found by the Commission to equal to the 82.4 percent of the firm market price.12 Based on the
foregoing, the formula for non-firm energy delivered outside the performance band can be
expressed as:
Non-firm market price outside of performance band = 85% * non-firm market price; where
Non-firm market price = 82.4% * firm market price
The Company agrees with a non-firm market price adjustment and will explain why non-firm
energy is less valuable than firm energy in more detail below.
Firm Energy and Non-Firm Energy Characteristics
To better understand how the customer-generators differ from firm market transactions, it is
helpful to understand some key aspects of firm market transactions. At present, most firm
market transactions reflect a limited set of market products such as:
• Blocks of hours at a constant volume, typically Heavy Load Hours (HLH), Light Load
Hours (LLH), or all hours.13
• Monthly products (covering every day in a month) are available prior to the start of a
month, while transactions for individual days are only available a day or two before
delivery.
• Typically traded in increments of 25 MW.

10 In the Matter of the Commission's Review of PURPA QF Contract Provisions Including the Surrogate Avoided
Resource and Integrated Resource Planning Methodologies for Calculating Avoided Cost Rates, Case No. GNR-E-Il-03, Order No. 32697 at 7-8 (Dec. 18, 2012).
11 In the Matter of Rocky Mountain Power’s Application for Approval of Power Purchase Agreement between PacifiCorp and Birch Hydro Company, Case No. PAC-E-20-07, Order No. 34889 at 2 (Jan. 14, 2021).
12 In the Matter of Rocky Mountain Power’s Application for Approval of Power Purchase Agreement between PacifiCorp and Birch Hydro Company, Case No. PAC-E-20-07, Order No. 34889 at 2 (Jan. 14, 2021).
13 HLH is 6:00 a.m. to 10:00 p.m. (Pacific Prevailing Time) Monday through Saturday, excluding certain holidays. LLH is all other hours, namely 10:00 p.m. to 6:00 a.m. nightly, and all day on Sundays and holidays.

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• Only a few locations have many market participants, such as Mid-Columbia or Palo
Verde. Few entities are available at most delivery points, and they may not have interest
in transacting for a given product.
• Such market products are considered firm because the seller is subject to costs for
damages if it fails to provide deliveries as agreed.
Exports from customer-generators vary significantly from market products. Customer-
generators exports:
• Vary from moment to moment
• Are not committed in advance
• Are not delivered to liquid market locations
• Provide no commitment to deliver. A customer may not have excess power to sell back
to the utility, either because its generation is low or because its own needs are high.
A utility must instantaneously dispatch sufficient resources to equal its customer load at all
times. Both resources and loads are uncertain, as wind and solar output varies, load varies, and
traditional resources experience unplanned outages. Under nearly all conditions, a utility must
have sufficient resources to balance its loads with enough extra energy to meet its reliability
obligations, such as contingency reserve requirements.
Since exported volumes may not actually be delivered as expected, a utility must maintain
adequate resources to serve load. Such resources cannot support firm market transactions if
exported volumes are delivered as expected, because such transactions would have to have
been finalized at least a day in advance, if not longer. In addition, if resources are only available
for a few hours, they may not be able to support the entire duration and quantity of a market
product.
The differential between firm market transactions and as-delivered energy varies based on a
variety of factors, including the as-delivered energy profile, the supply and demand
expectations of market participants, and the uncertainty in supply and demand, along with
market participant’s next best alternatives. Such factors can only be measured indirectly, and it
is difficult to distinguish expectations due to uncertainty and risk from actual outcomes.
With the advent of EIM, significantly more market data is available that better aligns with
export profiles. EIM prices reflect:
• Individual intervals (five or fifteen minutes).
• Delivery begins a few minutes after a dispatch instruction is received.
• No minimum quantity.
• Location-specific values for utility-scale resources, or aggregate values specific to
PacifiCorp loads.

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While no single market price can reflect the intertwined month-ahead, day-ahead, hour-ahead,
and intra-hour planning and operations used to balance PacifiCorp’s load and resources, EIM
prices are the most direct representation of the actual value of customer exports. The Company
stands by the EIM as the best source for exported energy credit; however, the Company would
also consider using the SAR methodology with adjustments made for non-firm energy
consistent with prior QF filings.
4.4 Avoided Capacity Value
The Study Scope requested the Company analyze the capacity value of exported energy
provided by customer-generators using either the LOLP study or by evaluating the amount of
power exported to the grid by customer-generators during the top 100 peaking events in the
last 10 years.
Study Scope Item 8
8. Analyze the capacity value of exported energy provided by customer-generators on a class
basis using one of two methods:
a. Loss of Load Probability Study, or
b. Determine the power that is reliably exported to the grid by net metering during
peaking events. Use the top 100 peaking events from each of the past 10 years (1,000
peaking events). Use a reliability threshold of 99.5%. If, for example, the study determines
that customer-generators provide no less than 1.5 MW of power during 99.5% of the
peaking events, then use 1.5 MW as the basis for determining the capacity avoided by the
customer-generator class.

The Company has analyzed the capacity value of energy using the LOLP study from its IRP. The
Company also looked at the top 100 peaking events from the past two years.
4.4.1 Loss of Load Probability Study
The Company’s LOLP study from its 2021 IRP, is used to estimate the generation capacity
contribution of customer generation exports. The study is discussed in the 2021 IRP in Volume
II, Appendix K: Capacity Contribution14, and reflects a 2030 test period including resource
additions from PacifiCorp’s 2021 IRP preferred portfolio which were projected to be in service
by that time.
The capacity factor approximation methodology described as the “CF Method” in Appendix K of
the 2021 IRP can be used to translate LOLP results for the PacifiCorp system into a generation
capacity contribution that is specific to a particular hourly generation profile (or export profile
in this instance). The CF Method calculates a capacity contribution based on a resource’s

14 Included with this Study as Appendix 4.7: Appendix K - Capacity Contribution - 2021 IRP.

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expected availability during periods when the risk of loss of load events is highest, based on the
LOLP in each hour.
An important aspect of the capacity factor approximation methodology is that the LOLP results
reasonably reflect the relationship between periods of high demand, and periods with low
resources, as these are most likely to lead to loss of load conditions. For accurate capacity
contribution values, this relationship also must be maintained within a resource profile being
evaluated. Many of these relationships are broadly a result of weather, but weather is complex
and multi-faceted, so it is difficult to align the weather conditions underlying historical exports
with the forecasted weather conditions within PacifiCorp’s 2021 IRP, as manifested in the load
forecast and renewable resource generation profiles. In general, peak-producing weather
conditions would be expected to increase customer demand, reducing the amount available for
export, but the effect of weather on customer generation production, system demand, and
renewable supply could also influence LOLP.
In the absence of better data on the influence of weather on exports relative to system supply
and demand, PacifiCorp opted to calculate a capacity contribution based on average exports in
the last two years (2021-2022) by month and hour (a “12x24 profile”), i.e. assuming that
customer exports were neither higher, nor lower, than average during hours with LOLP. The
hours with higher LOLP are shown shaded in red below.
Figure 4.2: Weighted LOLP Distribution

As shown on LOLP tab of CONF Appendix 4.2: ID EE Cost-Effectiveness, this results in a capacity
contribution for customer generation exports equal to 3.0% of their nameplate capacity, prior
to accounting for avoided line losses. By comparison, the 2021 IRP identified an annual capacity
contribution of 13% for utility-scale solar resources in Idaho. The results are not directly
comparable because customer generation exports are net of a customer’s onsite demand and
the utility-scale solar reflects a profile incorporating tracking technology, which increases its
output in the morning and evening when LOLP is higher.

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4.4.2 Historical Peak Conditions
PacifiCorp has compared evaluated historical customer generation exports and the top 10
percent load conditions over the past two years, spanning 2021-2022. During all hours in the
top 10 percent of annual Idaho load, exports provided an average capacity factor of 12.7
percent, while during all hours in the top 10 percent of annual system load, exports provided an
average capacity factor of 14.4 percent. Many of the top hours have significantly lower exports,
as shown in Table 4.5 below. At a 99.5 percent exceedance level, exports are well below a 1
percent capacity factor.15
Table 4.5: Customer Generation Exports During Peak Loads
Load
4.73% 0.58% 0.0387% 0.0097% 0.0020% 0.0013% 0.0005% 0.0002%
9.98% 4.29% 0.9985% 0.0460% 0.0110% 0.0042% 0.0012% 0.0005%

Note that these load-based results do not account for reliability and risk related to resource
supply. The 2021 IRP results account for periods when loads are high and resource availability is
low. The resource availability aspect is particularly important as solar resources are becoming a
greater share of PacifiCorp’s portfolio, and the incremental reliability benefits from customer
exports (which are primarily solar) are reduced as a result.
4.4.3 Time-Differentiated Capacity Values
The Study Scope requested the Company provide hourly time-differentiated capacity values
Study Scope Item 9
Provide hourly time-differentiated capacity values.

PacifiCorp has prepared hourly generation, transmission, and distribution capacity values (in
$/MWh) based on the 2021 IRP LOLP capacity analysis described above and provided them in
CONF Appendix 4.2: ID EE Cost-Effectiveness. Hourly capacity values are proportionate with the
weighted LOLP by month and time of day shown in Figure 4.2. Capacity and reliability are
probabilistic and involve discrete resource commitments. For instance, the addition of a simple
cycle combustion turbine, which impacts many hours at once, cannot be acquired for select
hours. While it is reasonable to spread capacity compensation across the hours with capacity
shortfalls, it should be recognized that this is more of a rate design exercise than a true
representation of hourly capacity values. The portfolio as a whole must have sufficient
resources in each and every hour despite resources increasing or decreasing reliability based on
their availability in particular hours.

15 Data for analysis provided in Appendix 4.1: Export Profile Jan21-Dec22.

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4.5 Avoided Risk
The Study Scope requested the Company to evaluate avoided risk by analyzing whether there is
a fuel price guarantee value provided by on-site generators as a class.
Study Scope Item 10
Analyze whether there is a fuel price guarantee value provided by on-site generators as a
class.

PacifiCorp’s 2021 IRP included stochastic analysis, which evaluated portfolio costs considering
variations in load, hydro output, electricity and natural gas prices, and thermal unit forced
outages. PacifiCorp’s calculation of the energy value and cost-effectiveness of energy efficiency
measures used these stochastic results to identify the incremental value associated with these
risks, and PacifiCorp has calculated the avoided risk associated with customer exports using the
same risk values applied to energy efficiency. Over the 2021 IRP horizon, this increases the
energy value of customer exports by 3.9 percent, or $1.24/MWh as shown on summary tab of
CONF Appendix 4.2: ID EE Cost-Effectiveness.
5.0 Project Eligibility Cap
An evaluation of the pros and cons of setting a customer’s project eligibility cap at different
predetermined caps and demand levels was requested by the Study Scope.
Study Scope Item 11
Analyze the pros and cons of setting a customer’s project eligibility cap according to a
customer’s demand as opposed to predetermined caps of 25 kW and 100 kW.
a. Analyze at 100% of demand.
b. Analyze at 125% of demand.

Per the load research information used in the Company’s last general rate case16, the estimated
maximum non-coincident peak is 8.4 kW for the typical residential customer taking service on
Schedule 1 and 11.5 kW for the typical residential customer taking service on Schedule 1. At 25
kW, the current cap is well above 125 percent of the typical customer’s demand. Setting a
capacity level that is based upon an individual customer’s demand could be administratively
burdensome and could create frustration for smaller customers who want to install a larger
facility. It could also create a perverse incentive by encouraging customers to have a higher
peak load before they request to interconnect an onsite generation system. The complications
of setting a capacity level based on the individual customer’s demand would be the same at
100% of demand and at 125% of demand.

16 In the Matter of the Application of Rocky Mountain Power for Authority to Increase its Rates and Charges in Idaho and Approval of Proposed Electric Service Schedules and Regulations. Case No. PAC-E-21-07.

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6.0 Avoided Transmission and Distribution Costs
The Study Scope requested the Company to calculate the value of transmission and distribution
costs that could be avoided by customer-generator exports to the grid.
Study Scope Item 12
Quantify the value of transmission and distribution costs that could be avoided by energy
exported to the grid by net metering customers using the methodology for calculating the
avoided transmission and distribution costs provided by energy efficiency programs.

PacifiCorp’s evaluation of energy efficiency measures includes assumed deferral of local
transmission and distribution upgrades. Unlike system LOLP, where a variety of resources may
be used to ensure reliable operation in different times of day and seasons of the year, the local
electrical grid needs to be capable of delivering the maximum demand after accounting for
energy efficiency and customer generation. As a result, the capacity contribution for
transmission and distribution system deferral is likely to differ from the generation capacity
contribution based on system LOLP and may be specific to a particular circuit or transmission
system element.
When the Company provides electric service to a new subdivision it utilizes standard system
designs based on the number and size of expected homes in the new subdivision. It does not
assume any level of self-generation because doing so would risk under-sizing the equipment.
In the absence of specific information about transmission and distribution capacity needs and
their relationship with expected customer exports, PacifiCorp has estimated the potential
avoided transmission and distribution costs using the system LOLP-based generation capacity
contribution value of 3.0 percent, as previously discussed. Using the same avoided transmission
and distribution upgrade costs applied in PacifiCorp’s calculation of the energy value and cost-
effectiveness of energy efficiency measures based on the 2021 IRP results in a value of
$1.10/MWh for the 2021 IRP horizon.
7.0 Avoided Line Losses
The Study Scope requested the Company the avoided line loss calculations at a level that an
average customer could understand.
Study Scope Item 13
Explain the avoided line loss calculations at a level that an average customer can understand.

All electrical lines have impedance or constraint against conducting electricity, due to the
conducting material, air temperature, and distance. Electricity is converted to heat while trying
to overcome these constraints, and this loss of energy is referred to as line losses. The primary

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cause of transmission and distribution line losses are due to the resistance of the conductor, or
line, against the flow of the current, or electricity. This resistance results in heat produced in
the conductor increasing the temperature of the conductor making it less efficient to transfer
electricity. The heat is generated on the microscale when electrons collide with and transfer
energy to the conductor’s atoms.
Line losses are calculated as the difference between the total generation injected into the grid
and the total metered volume at customer sites. The line losses are separated into three
categories: transmission, primary and secondary. Transmission line losses account for those line
losses that occur over the transmission system. Primary line losses include those losses that
occur on distribution voltages in the range from 2.2kV to 34.5 kV with most circuits at 12.4 kV.
Secondary line losses include those losses that occur on distribution systems that are low
voltage in the 120V to 480V range.
Figure 7.1: Transmission, Primary, and Secondary Components of an Electrical System17
The line losses incorporated in the Company’s current rates are from its 2018 Line Loss study.
That study identified “Demand” loss factors, based on losses during peak conditions, as well as
“Energy” loss factors, based on loss averaged over all conditions. The 2018 Line Loss Study
identified line losses in Idaho specific to the following interconnection levels:
Table 7.1: Idaho 2018 Demand and Energy Loss Summary
Voltage Class Demand Loss Factor Energy Loss Factor
Transmission 3.816% 3.503%
Primary 8.121% 7.082%
Secondary 9.834% 9.061%

17 Transmission Line FAQ, GATEWAY WEST Transmission Line Project, http://www.gatewaywestproject.com/faq_general_transmission.aspx (last visited Feb. 20, 2023).

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For customer-generators, the Company expects to apply the export credit to resources
interconnected at secondary voltage levels, and to meter the exports before they go onto the
secondary distribution system. The energy exported from the customer-generators will then
incur some line losses traveling across the secondary distribution system to other customers, so
it will not avoid the entire line losses associated with serving load on the secondary distribution
system. Therefore, the Company proposes crediting exports for avoiding line losses on the
transmission and primary distribution systems. If customer exports and customer generation
exceeded the load on a particular distribution circuit, electricity could potential be transferred
back up to higher voltages and could incur higher losses. For distribution capacity, avoided line
losses are measured relative to losses at the transmission demand level, as losses incurred on
the transmission system would not have been transferred across the distribution system.
8.0 Integration Costs
Integration costs refer to the additional expense when variable energy resources are added to a
portfolio. Integration typically includes costs related to the uncertainty and variation in variable
energy resource output from moment to moment, and these system impacts have been
estimated in the 2021 IRP as described in more detail below. For distributed resources,
integration costs could potentially include equipment and/or operational changes to manage
impacts on the distribution system, particularly at high penetration levels, but the Company has
not identified any specific costs associated with distribution system impacts from customer-
generators in Idaho.
The Study Scope requested the Company to calculate the dollar impact of deferring a study of
the integration charges for net metering customer until AMI data is available.
Study Scope Item 14
Study other methods for determining the integration costs of net metering customers as a
class. Calculate the dollar impact of deferring a study of the integration charges for net
metering customers until AMI data is available, and if different, calculate the dollar value of
using a zero placeholder until AMI data is available.

The 2021 IRP includes an analysis of wind and solar integration costs in its Flexible Reserve
Study (“FRS”) which is included in this Study as Appendix 8.1: Appendix F – Flexible Reserve
Study- 2021 IRP. That analysis estimates the regulation reserve required to maintain
PacifiCorp’s system reliability and comply with North American Electric Reliability Corporation
("NERC”) reliability standards as well as the incremental cost of this regulation reserve.
On April 23, 2007, Rocky Mountain Power filed an application requesting Commission approval
of utility-specific wind integration adjustment to the published avoided costs rates. The
Commission reviewed the facts and the settlement stipulation of the case and determined that
a utility-specific wind integration cost adjustment to that utility's published avoided costs,

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among other adjustments, was appropriate.18 With respect to the cost of integrating wind
generation into existing utility systems, the Commission found in Order No. 29839, Case No.
IPC-E-05-22 that the supply characteristics of wind generation and related integration costs
could provide a basis for adjustment of the published avoided cost rates.19 Since then, the
Company has continued to refine the FRS to accurately capture the cost of integrating
renewable resources into the grid in light of changes in available data, resource mix, and
reliability standards.
On August 28, 2017, the Company filed Case No. PAC-E-17-11 to update the wind integration
rate and implement an integration rate for solar. The Commission determined that there is a
cost to integrate variable resources in Order No. 33937 where integration rates for both wind
and solar were approved.
Regulation reserves must compensate for two aspects of supply and demand: changes within
an hour, where some periods are higher and some periods are lower, and changes from
forecast, where generation does not reach the level forecasted roughly an hour prior. The FRS
accounts for these factors by using the hour-ahead resource-specific forecasts from actual
operations, and actual deviations from those forecasts, at a five-minute granularity.
PacifiCorp does not have a real-time forecast of customer generation exports that could be
used to identify specific integration requirements, but it is possible to measure deviations
within each hour, relative to the hourly average. During 2021-2022, the historical customer
export data has a mean average percent error (“MAPE”) of 8.6 percent, when comparing 15-
minute values to the hourly averages. By comparison, the utility-scale solar in the FRS had a
lower MAPE of 7.2 percent, indicating the utility-scale has a proportionately smaller
contribution to regulation reserve requirements than customer exports. Note that this does not
necessarily indicate that customer generation production has higher variability than utility-scale
production. A significant portion of the customer generation production is used behind the
customer meter, but to the extent production exceeds onsite demand throughout an hour, all
of the variability is exported to the electric grid. That variation is thus higher as a percentage of
customer generation exports and would be lower as a percentage of customer generation
production. Customer load generally does not respond to changes in onsite production (e.g.,
decrease consumption when customer generation production falls) and exports may have even
more variability as a result of changes in a customer’s demand.
Because the variation in customer generation exports exceeds that of utility-scale generation, it
is reasonable to expect integration costs for customer generation exports to be higher. In light

18 In the Matter of the Petition of Rocky Mountain Power for an Order Revising Certain Obligations to Enter into Contracts to Purchase Energy Generated by Wind-Powered Small Power Generation Qualifying Facilities. Case No. PAC-E-07-07, Order No. 30497. 19 In the Matter of the Petition of Idaho Power Company for an Order Temporarily Suspending Idaho Power’s
PURPA Obligation to Enter into Contracts to Purchase Energy Generated by Wind-Powered Small Power Production Facilities. Case No. IPC-E-05-22, Order No. 29839 at p. 8.

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of this, the use of the utility-scale solar integration costs likely understates the actual cost but is
reasonable. Using the latest utility-scale solar integration costs approved in Order No. 34966 in
PAC-E-20-14, the solar integration costs for 2023 is currently $0.24/MWh20. Assuming an
average annual exports of 5,000 kWh per customer, the dollar impact of using a zero
placeholder for integration costs until AMI data is available is $1.20 per customer per year.
9.0 Avoided Environmental Costs and Other Benefits
9.1 Grid Stability, Resiliency, and Cybersecurity
The Study Scope requested the Company to quantify the value of grid stability, resiliency, and
cybersecurity provided by on-site generators.
Study Scope Item 15
Quantify the potential value of grid stability, resiliency, and cybersecurity protection provided
by on-site generators as a class and different penetration levels.

The Federal Energy Regulatory Commission (“FERC”) defines resilience as “the ability to
withstand and reduce the magnitude and/or duration of disruptive events, which includes the
capability to anticipate, absorb, adapt to, and /or rapidly recover from such an event”. To
achieve any resiliency or grid stability benefits as defined above, on-site generation must be
paired with storage since on-site generators, on their own, are susceptible to and can even
enhance disruptive events.
Without storage, on-site generation does not provide grid benefits because in the event of an
outage, systems are designed to power down for safety at any penetration level of on-site
generation. The Company has also found that on-site generation does not provide cybersecurity
benefits and can create additional cybersecurity risk because on-site generation creates more
potential access points to the grid.
9.1.1 Grid Benefits of On-Site Generation with Storage
The grid can benefit from on-site generation when it is paired with solar. Battery management
programs, like Wattsmart Batteries, provide four primary grid service benefits: 1) frequency
regulation services 2) peak load management 3) circuit congestion relief, and 4) backup power.
In 2019, the Company was part of a partnership that developed a 600-unit all-electric
residential community in Utah, where each apartment was outfitted with batteries paired with
rooftop solar. The project provides 12.6 MWh of storage that is dispatchable by RMP through
the Distributed Battery Grid Management System. An evaluation of this project identified the
four primary grid service benefits listed above.

20 See Appendix 8.2: Wind and Solar Integration Charges Approved in Order No. 34966.

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Without battery storage, on-site customer generation does not provide either frequency
regulation services, peak load management, circuit congestion relief or backup power.
9.1.2 Community Resiliency Benefits of Customer Generation with Storage
When a catastrophic disaster strikes, backup power paired with storage can ensure emergency
services, such as fire, medical, and shelter services, continue to operate. On-site generation
with storage provides value to the community from avoided property damage, injuries,
fatalities, and lost productivity. While there is no standard method for determining the
community resiliency value of customer generation some tools can help determine the value
for individual sites.
An evaluation of Pacific Power’s Community Resiliency Pilot used the Federal Emergency
Management Agency’s (“FEMA”) benefit-cost analysis tool to determine the potential resiliency
value for customer generation and batteries at specific sites that provide vital services—fire
stations, data centers and designated shelters. FEMA’s calculator determines the value of
maintaining these services based on the type of emergency and the facility category. For
example, analysis for a fire station considers the probability of property loss, the dollar value of
the loss, and the number of fire incident prior to and during the outage. The tool also
determines avoided injuries and deaths from maintaining fire service. The resiliency benefits
can vary significantly from site-to-site depending on the unique characteristics of the facility,
the community the facility serves, and the type of disaster.
None of the community resiliency benefits outlined above is possible without battery and
storage paired together since battery storage provides the backup power required during a
disaster. Also, the benefits outlined above are not relevant to the purposes of this Study, which
is focused on the benefits of on-site generators connected to the grid, as a whole, and not any
one site and the benefits it might give to a community in the event of a disaster. Further, those
benefits are unquantifiable and do not accrue specifically to customers of the utility in their
capacity as consumers of energy.
9.1.3 Customer Generation and Cybersecurity Protection
Cyber-attacks are potential resiliency events. Thus, the cybersecurity protection benefits of
customer generation with storage are the same as those described above. In the event of a
catastrophic cyberattack, customer generation and storage could provide sustained power to
vital services.
However, increasing penetration of customer generation could increase cybersecurity risks. The
U.S. DOE’s report on “Cybersecurity Consideration for Distributed Energy Resources on the U.S.

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Electric Grid” identifies several cybersecurity risks from distributed energy resources.21 When a
customer-generator connects to the grid, it creates a new access point, which adds incremental
risk for cyberattacks. Most customer generation systems use solid-state inverters to produce
output and sync with the grid. These inverters are software-driven and digitally controlled. The
improper application of this software—such as through a cyberattack—could affect reliability
and grid stability.
9.2 Public Health and Safety
The Study Scope requested the Company to quantify the value to local public health and safety
from reduced local impacts of global warming.
Study Scope Item 16
Quantify the value to local public health and safety from reduced local impacts of global
warming such as reduced extreme temperatures, reduced snowpack variation, reduced
wildfire risk, and other impacts that can have direct impacts on Rocky Mountain Power
customers.

The value of customer generation exports with respect to global warming harm reduction is
difficult to quantify. The greenhouse gas costs in the 2021 IRP represent possible federal policy
that would impact the dispatch of emitting resources, and do not represent local impacts,
which are much more complex. Some of the referenced global warming impacts, including
impacts on retail load and hydropower production, directly impact PacifiCorp’s loads and
resources, and climate-related effects on these inputs have been incorporated in PacifiCorp’s
2023 IRP.
Though it is imperfect for identifying local impacts, PacifiCorp’s avoided energy value,
addressed in section 4.3 of this Study, includes the impact of assumed medium greenhouse gas
costs, consistent with assumptions from the 2021 IRP. Medium greenhouse gas costs are
reflected in market prices, as well as in the dispatch cost of PacifiCorp’s coal and natural gas-
fired resources, but it is not possible to differentiate greenhouse gas costs from energy and
other variable costs within the reported hourly energy value. PacifiCorp’s 2021 IRP also
included analysis using a social cost of greenhouse gases (“SCGHG”); however, this represents
global public health and safety impacts, rather than local impacts.
Another possible value of customer generation exports is via Renewable Energy Certificates
(“RECs”), which are addressed in section 9.4 of this Study below.

21 Cybersecurity Considerations for Distributed Energy Resources on the U.S. Electric Grid, U.S. DOE Office of Cybersecurity, Energy Security, and Emergency Response and the Office of Energy Efficiency and Renewable Energy, October 2022. https://www.energy.gov/sites/default/files/2022-10/Cybersecurity%20Considerations%20for%20Distributed%20Energy%20Resources%20on%20the%20U.S.%20Electric%20Grid.pdf

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9.3 Economic Benefits
The Study Scope requested the Company to quantify the value to local economic benefits from
on-site customer generation.
Study Scope Item 17
Quantify local economic benefits, including local job creation and increased economic activity
in the immediate service territory.

Quantifying local economic benefits of increased economic activity is difficult, if not impossible,
to quantify with a degree of certainty. In addition, the Company’s generation, transmission, and
distribution activities in its current service territories provide economic benefits. However, the
Company does not charge customers for these benefits in electric rates. Allowing difficult-to-
quantify economic benefits in the ECR would not be fair to non-participating customers.
9.4 Possible Net Value of Renewable Energy Credits
The Study Scope requested the Company to quantify the net value of RECs sales from on-site
generation.
Study Scope Item 18
Quantify the possible net value of Renewable Energy Credit sales produced by net metering
exported energy.

Currently, Idaho does not have a renewable portfolio standard (“RPS”), so the benefits of RECs
would come from REC sales. Only renewable output delivered to the electric grid can qualify for
RECs, and there are administrative requirements to certify renewable resources and assign
RECs to their production.
To create RECs, the renewable energy generator must be registered with the Western
Electricity Coordinating Council (“WECC”) and the Western Renewable Energy Generating
Information System (“WREGIS”). Renewable energy cannot be monetized through REC sales
without this process in the WECC region. Coordinating the certification and tracking of the RECs
would be an administrative complex and could require a full-time employee to administer. The
Company expects the administrative costs would exceed any revenues generated from REC
sales.
At present, PacifiCorp does not sell all the RECs it generates on behalf of its Idaho retail
customers, as the market for RECs is limited. To the extent that there were other parties
interested in purchasing RECs from Idaho customer-generator exports, a $1/MWh REC price
would equate to approximately $5 per year in incremental export credit value for an Idaho
customer-generator, assuming 5,000 kWh of exports annually, which represents approximately
half of their annual production.

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9.5 Reduced Risk from End-of-Life Disposal
The Study Scope requested the Company to quantify the reduced risk from end-of-life disposal
concerns for the Company compared to fossil-fueled resources.
Study Scope Item 19
Quantify the reduced risk from end-of-life disposal concerns for the Company compared to
fossil-fueled resources.

Investment in utility scale resources considers end-of-life closure costs to determine least cost
resources. To the extent capacity benefits displace a new generation resource, this potential
benefit is already captured in that category.
10.0 Recovering Export Credit Rates in the ECAM
10.1 Current Export Credit Recovery
To better understand how export credit rates may be recovered in the Energy Cost Adjustment
Mechanism (“ECAM”), the Study Scope asked the Company to explain the method currently
used to record net metering bill credit costs.
Study Scope Item 20
Explain the method currently used to record net metering bill credit costs.

Currently, bill credits for net metering are used to reduce the energy charges that are paid to
the Company. These net metering bill credits therefore reduce the Company’s retail revenue.
10.2 Recovery Allocation
The Study Scope asked the Company to quantify the current amount of net metering costs
allocated to each class.
Study Scope Item 21
Quantify the current annual amount of the net metering costs allocated to each class.

Table 10.1 below shows the reduction in revenue for each class attributable to exported energy
that is valued at retail energy charges:

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Table 10.1: Net Metering Reduction in Revenue by Class
Sch 1 Sch 36 Sch 23 Service Sch 6
(MWh)

8,555 2,183 565 123 11,426
Value at Retail Rate

The Study Scope required the Company to explain how these costs have been allocated and
recovered between rate classes for the past five years.
Study Scope Item 22
Present and explain how these costs have been allocated and recovered between rate classes
for the past five years.

In between rate cases, the Company absorbs the cost of reduced revenue from net metering. In
2021, the Company filed a rate case that updated class revenues and that took effect January 1,
2022. The rate case before the 2021 rate case occurred ten years before and took effect on
January 10, 2012, with a second-year price change that took effect on January 1, 2013. During
that timeframe, onsite generation adoption was still in its infancy and was a small portion of
retail revenue situs directly assigned to each customer class. Exported energy from on-site
customer-generators reduces net power cost (“NPC”) by reducing purchases or fuel costs.
While these cost savings reduce NPC which is captured in the ECAM, the cost of paying for
exported energy that is above what is built into the revenue for a general rate case is absorbed
by the Company. The cost of the ECAM is allocated to customer classes on the basis of energy
sales adjusted for line losses.
10.3 Export Credit Price Scenarios
The Study Scope asked the Company to quantify the annual export costs for each customer
class and different assumed export rates.
Study Scope Item 23
Quantify these annual costs under the assumptions that the Export Credit Rate is the retail
rate, 7.4 cents/kWh, 5 cents/kWh, or 2.23 cents/kWh.

Assuming an instantaneous netting regime, the export credit payments by class are show in
Table 10.2 for the different specified levels of export credit price

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Table 10.2: Annual Export Costs by Rate
Residential
Sch 1 Sch 36 Service Sch 23 Service Sch 6
8,555 2,183 565 123 11,426
$916,330 $269,067 $51,091 $5,242 $1,241,731
$633,050 $161,516 $41,835 $9,126 $845,526
$427,736 $109,132 $28,267 $6,166 $571,301
$190,770 $48,673 $12,607 $2,750 $254,800

The Study Scope called for an analysis how these costs would be allocated and recovered by
each rate class through the Company’s ECAM.
Study Scope Item 24
Analyze how these costs would be allocated and recovered by rate class through the
Company’s proposed ECAM method going forward.

Going forward, the Company recommends that the export credits paid to customer-generators
on the net billing program would be recorded as a purchased power expense and tracked in the
ECAM like all other energy purchases. This would align the cost to acquire this energy with any
reductions to net power costs by avoided purchases or reduced fuel expense. The Company
recommends that the cost of export credits would be allocated on energy sales adjusted for line
losses, which is consistent with how other ECAM costs are treated.
11.0 Schedule 136 Implementation Issues
The Study Scope asks the Company to consider several implementation issues such as billing
structure for on-site generators, export credit expiration scenarios, and the frequency of export
credit updates.
11.1 Billing Structure
11.1.1 Time-of Delivery Pricing
The Study Scope requested an explanation of how seasonal and time-of-delivery prices
differences will be used to help align customer generated exported energy with the Company’s
needs and how using more granular time periods for differentiating energy and capacity credits
could be used to align customer-generated exports more closely with the Company’s system
needs.
Study Scope Item 25
Explain if and how seasonal and time-of-delivery price differences will be used to help align
customer generated exported energy with the Company’s system needs.

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Study Scope Item 26
Explain if and how using more granular time periods for differentiating energy and capacity
credits could be used to more closely align customer-generated exports with the Company’s
system needs.

The Company recommends a seasonal export credit price that is not of time-of-use
differentiated. The difference in time of use periods can be confusing for customers with most
of the Company’s customers not currently enrolled in a time varying pricing option. The
differential between an on-peak versus an off-peak export credit is not as significant as the
difference in the retail price versus the export credit. All customers in Idaho, however, are
subject to seasonal pricing and consistency with an export credit will send appropriate price
signals to customers. To best align export credit pricing to the highest cost period of the year,
the Company proposes a summer period of June through September. Winter months would
include October through May. These seasons are consistent with seasonal pricing for almost all
rate schedules. Presently for Schedule 36, the summer season includes May. The Company
recommends that the seasons for export credit pricing would align with the seasons in Schedule
36 for participating net billing customers served under that schedule, until such time as the
seasons for Schedule 36 are updated.
11.1.2 Economic Evaluation for Customer-Generators and On-Site Generation System
Installers
The Study Scope requested an explanation of how potential customer-generators and on-site
generation system installers can have accurate and adequate data and information to make
informed choices about the economics of on-site generation systems over the expected life of
the system.
Study Scope Item 27
Explain how potential customer-generators and on-site generation system installers will have
accurate and adequate data and information to make informed choices about the economics
of on-site generation systems over the expected life of the system.

The purpose of customer generation programs like net metering or net billing is to offset part
or all the Customer’s own electrical requirements and not to enable customers to become an
independent power producer. If the customer’s intent is to offset its own usage, then
customer-generators and system installers have the same customer usage information and
pricing to make informed choices about the economics of on-site generation systems as they do
to make decisions about other energy investments like conservation focused measures such as
more efficient windows or air conditioning equipment. Under net billing, customer-generators
would be incentivized to align their usage with generation. This can be done behaviorally
through actions such as running appliances like dishwashers during the middle of the day, sizing

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their systems at levels that reduce exports, or installing onsite storage. With the installation of
AMI, customers will be able to view their hourly usage online which should allow determined
customers to analyze their usage patterns.
11.1.3 Residential Solar Energy Disclosure Act
The Study Scope requested an explanation of how on-site generation system installers will be
able to comply with the Residential Solar Energy Disclosure Act if hourly or instantaneous
netting and/or granular time-differentiated export rates are adopted and updated annually.
Study Scope Item 28
Explain how on-site generation system installers will be able to comply with the Residential
Solar Energy Disclosure Act if hourly or instantaneous netting and/or granular time-
differentiated export rates are adopted and updated annually.

As explained in response to Study Scope item 27, the intent of net metering or net billing is not
for customers to become developers of qualifying renewable generation resources or to get
into the business of selling energy to the Company. The purpose is to offset the customer’s own
usage. Inasmuch, as net billing customers use the generation they produce onsite, they will
avoid paying the retail price for energy. When customer-generators on bet billing export
energy to the utility grid, they will be compensated at the export credit price which would
update periodically. The value of exported energy could change over time. Before committing
to install onsite generation, customer-generators should take note that all investments
including rooftop solar have risks. While under net billing, a customer-generator will save on
their utility bill from producing energy, those savings may go up or down with time. In many
ways installing onsite generation is like choosing to purchase a hybrid or electric vehicle. An
individual who makes this choice would save on gasoline over time, but those savings levels
fluctuate with the changing price of gasoline. Under the Residential Solar Energy Disclosure Act,
installers will need to document for their potential customers the assumptions used in their
projection of savings for the system.
11.2 Export Credit Expiration
To evaluate different scenarios for export credit expiration, the Study first evaluated the
current magnitude of accumulated export credits and generation. Then, the effects of different
expiration periods were analyzed to see how customers would be affected. Finally, the Study
looked at how the Company and non-participating customers are impacted by expired credits.
11.2.1 Accumulated Export Credits
The Study Scope requested the magnitude, duration, and value of accumulated export credits
as of August 1, 2020, be quantified.

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Study Scope Item 29
Quantify the magnitude, duration, and value of accumulated export credits as of August 1,
2020.

As of August 1, 2020, there was a total of 4,530,405 kWh in excess generation for all customers
as detailed in Table 10.1 below
Table 11.1: Excess kWh Total as of 8/1/2020
Class
Residential
21,729 46,758 59,349 140,598 215,748 631,720 1,141,045 1,226,213 3,483,160
Small
Commercial

41,462 70,153 61,235 92,809 158,167 245,993 195,306 163,280 1,028,405
Large
Commercial

- 80 240 440 320 1,040 2,560 14,160 18,840
Irrigation
- - - - - - - - -
Total
63,191 116,991 120,824 233,847 374,235 878,753 1,338,911 1,403,653 4,530,405

To better understand the magnitude, duration, and value of the excess generation, the
Company valued each year’s excess generation by customer class and rate. In addition to the
table above, the Company evaluated expired generation from August 1, 2020, to December 31,
2022, to provide a more current portrait of expired credits. The detail of this analysis is
provided on the summary tab of Appendix 11.2: Idaho Expired Credit Analysis 2012-2022. The
estimated value of all excess generation is $325,386.06 for all 2,196 net metering customers
from 2012 to 2022.
11.2.2 Impact to Customers over Various Expiration Periods
The Study Scope requested the impact to customers of a 2-year, 5-year, and 10-year expiration
periods be quantified.
Study Scope Item 30
Quantify the impact to customers of a 2-year, 5-year, and 10-year expiration periods.

The impact to customers for credits expiring at either 2-years, 5-years, and 10-years, will vary
depending on each customer’s load and system size. Customers with systems that consistently

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overproduce, will be most affected by expiring credits. As shown on the Table 11.2 below, 14
percent of on-site generation systems overproduced in 2022.22
Table 11.2: Percentage of Customers Overproducing Annually
2 8 10 21 29 59 122 212 215 281
Commercial
4 4 4 5 5 9 12 19 23 16
Commercial
- - - - - - - 1 - -
- - - - - - - - - 2
5% 9% 9% 12% 10% 10% 12% 16% 14% 14%

The average annual compensation for net overproducers has been $294 over the last 5 years.23
A breakdown of the weighted average for each customer class for the last 5 years is included in
Table 11.3 below. The net value of overproduction for each of the overproducers is provided in
detail in Appendix 11.1: Weighted Average Overproduction.

22 Additional analysis included on the customer count tab of Appendix 11.2: Idaho Expired Credit Analysis 2012-2022. 23 See summary tab of Appendix 11.1: Weighted Average Overproduction.

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Table 11.3: Weighted Average of Customer Overproduction
Year Ending 2018 2019 2020 2021 2022
Residential Count
Avg Annual
Compensation/Customer
$276.02 $209.22 $196.26 $207.12 $200.37
9 12 19 23 16
Compensation/Customer
$1,937.71 $875.56 $785.77 $499.72 $615.28
- - 1 - -
Compensation/Customer
- - $842.27 - -
- - - - 2
Compensation/Customer
- - - - $54.08
68 134 232 238 299
Compensation/Customer
$495.95 $268.89 $247.33 $235.40 $221.60

To better understand how the overproducing customers would be impacted by different
expiration periods, the Company took a sample of the overproducing customers and calculated
the value of credits that could be subject to expiration over the different time periods. The
results of this analysis can be seen on Appendix 11.3: Customer Impact at 2-, 5-, and 10-Year
Expiration.
As shown on the residential tab of Appendix 11.3, only two customers overproduced for the
year in 2013. At the end of the 10-year period, those two customers would have $1,177.5 in
combined credits that would begin to expire, on a rolling basis.
For the 5-year analysis, the two customers from the 10-year analysis were analyzed again along
with the largest overproducer in 2018. The overproducing site was selected to show how
customers with both large and small amounts of overproduction would be affected by expired
credits. As shown on the residential tab of Appendix 11.3, two of the customers would not have
any expired credits when looking at the last five years, however the largest overproducer would
have $9,927.32 in credits that would begin to expire on a rolling basis of approximately $2k
annually. While the impact to this customer could potentially be significant, most customers
would not be heavily impacted by the expiration of credits over a 5-year period.
For the 2-year analysis, the customers from the 5-year analysis were included and added a
customer that was at the median range for overproducers to analyze the impact to the

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broadest possible range of overproducers. The average annual credit of the four selected
customers was $82 that would expire on a rolling basis.
In summary, over 85 percent customers will not be affected by expiring credits. For those
overproducers with credits at risk of expiration, the impact will vary depending on system size
and load. The most over-sized customer could see credits valued at approximately $2k expiring
annually. In contrast, the average overproducer would not have more than $100 in credits
expire on an annual average basis.
11.2.3 Export Credit Expiration Policy
The Study Scope requested an explanation of the need for credits to expire.
Study Scope Item 30
Explain the need for credits to expire.
a. Show how the Company does or does not benefit from the expiration of customer
export credits.
b. Show how non net bill customers are harmed or benefited from the expiration of
customers export credits.

Customer generation programs are intended for customers to offset some or all of their energy
bill with onsite generation and not for a customer to become a power producer. To encourage
customers to appropriately size their generation systems to match actual usage at the site of
the system, the Company recommends that export credits may be rolled over until March of
each year for most customers and until October for irrigation customers. This would allow
customers a reasonable opportunity to accumulate and use credits to offset actual energy use
at the location of the customer generation system.
The Company’s recommendation is for expired export credits to go to a qualified charitable
organization. There is no benefit to the Company.
When establishing net metering the Commission confirmed that: “The purpose of net metering
is not to encourage excess generation. Developers of qualifying renewable generation
resources who wish to get into the business of selling energy to the Company should, under
PURPA, request firm or non-firm energy purchase contracts.”24 The net metering rate is not
intended to encourage participants to become independent power producers. If the ECR is not
set at a level that holds other customers economically indifferent from paying for the exports or
another comparable source of energy, other customers are harmed by having to pay an
unreasonable rate.

24 In the Matter of the Petition of NW Energy Coalition and Renewable Northwest Project to Establish Net Metering Schedules for PacifiCorp. Case No. PAC-E-03-4, Order No. 29260 at p. 6.

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11.3 SAR Energy Rates Updates and IRP Cycle Impact to Export Credit Updates
The Study Scope requested the impact of biennial updates, as compared to annual updates of
the ECR, by comparing the changes in the SAR energy rate, line losses, and integration costs
using historical data over one year, one IRP cycle and two IRP cycles be quantified.
Study Scope Item 32
Quantify the impact of biennial updates as compared to annual updates of the Export Credit
Rate by comparing the changes in the SAR energy rate, line losses, and integration costs using
historical data over one year, one IRP cycle (two years), and two IRP cycles (four years).

Assuming the ECR is updated based upon non-levelized annual prices, the Company analyzed
how compensation would vary for a customer-generator who exports 5,000 kWh per year
under different update scenarios – annual, biennial, and every 4 years. The chart below in
figure 11.1 shows how the price would have varied under these cycles starting with the prices
effective around June 1, 2012, for a ten-year period:
Figure 11.1: Frequency of Export Credit Updates25

Table 11.4 shows how compensation for an annual 5 MWh of exports over this ten-year period
would have compared for the different update cycle scenarios:

25 See Appendix 11.4: SAR Export Credit Analysis for calculation.
20
25
30
35
40
45
50
55
60
$/
M
W
h
Annual Update Price Biennial Update Price 4-Year Update Price

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Table 11.4: Impact of Different Update Cycles
Price Price Price
$1,735 $1,446

The results for the annual update and the biennial update are nearly identical. The 4-year
update is lower primarily, because it misses capturing higher prices that occurred in 2014 and
2015 that get picked up in annual and biennial updates. Depending upon when updates begin
could make a large difference for multi-year updates in the future. The Company recommends
the ECR be updated annually, which would provide customer-generators with more accurate
compensation.
12.0 Smart Inverter Study
The Study Scope requested an explanation of the Company’s Utah smart inverter policy and a
quantification of the benefits of applying that policy to its Idaho service territory.
Study Scope Item 33
Explain the key aspects of the Company’s Utah smart inverter policy and quantify the benefits
of applying that policy in its Idaho service territory, in particular, the potential benefits of
reactive power control.

In 2017, Rocky Mountain Power took part in a Smart Inverter Project as part of the Utah
Sustainable Transportation and Energy Plan (“STEP”) to investigate the capabilities and impacts
of smart inverters on the Company's distribution system. The Company's project partners
included the Electric Power Research Institute and Utah State University and resulted in the
study of: (1) IEEE 1547 smart inverter standards and policy, (2) laboratory selection and testing,
(3) hosting capacity results, with and without smart inverters, (4) settings determination, (5)
deployment best practices, and (6) Technical Policy 138, interconnection standard updates. The
Smart Inverter Study was produced from the efforts of the STEP project in Utah docket 19-035-
17 and is included with this Study as Appendix 12.0: Utah STEP - Smart Inverter Study.
This research produced the smart inverter policy that the Company has implemented for its
Utah customers. That policy was considered in a Utah Public Service Commission proceeding to
determine how the value provided by customer smart inverters should be included in the ECR,
Utah Docket No. 17-035-61, and no specific export credit value was applied to account for the
benefits of smart inverter technology.
While smart inverters are not expected to impact export credit rates, including minimum
requirements for inverter technology can ensure the hosting capacity and power quality of the
distribution system do not deteriorate as customer generation is added.
The following Appendices are voluminous and provided in their native format via Box:

Appendix 3.1 - ID NEM Class Production.xlsx
Appendix 4.1 - Export Profile Jan21-Dec22.xlsx
CONF Appendix 4.2 - ID EE Cost-Effectiveness.xlsb
CONF Appendix 4.3 - ID Export Credit Calculations.xlsb
Appendix 4.4 - Idaho Export Profile Validation Avg Capacity .xlsx
Appendix 4.5- ID Export Profile Validation Monthly Exports.xlsx
Appendix 4.6 - ID Export Profile Validation PV Watts Production.xlsx
Appendix 4.7 - Appendix K - Capacity Contribution - 2021 IRP.pdf
Appendix 8.1 - Appendix F - Flexible Reserve Study - 2021 IRP.pdf
Appendix 8.2 - Wind and Solar Integration Charges Approved in Order No. 34966.pdf
Appendix 11.1 - Weighted Average Overproduction.xlsx
Appendix 11.2 - Idaho Expired Credit Analysis 2012-2022.xlsx
Appendix 11.3 - Customer Impact at 2-, 5-, and 10-Year Expiration.xlsx
Appendix 11.4 - SAR Export Credit Analysis.xlsx
Appendix 12.0 - Utah STEP - Smart Inverter Study.pdf