20170609Kalich Direct.pdf

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

BEFORE THE IDAHO PUBLIC UTILITIES COMMISSION

IN THE MATTER OF THE APPLICATION ) CASE NO. AVU-E-17-01
OF AVISTA CORPORATION FOR THE )
AUTHORITY TO INCREASE ITS RATES )
AND CHARGES FOR ELECTRIC AND )
NATURAL GAS SERVICE TO ELECTRIC ) DIRECT TESTIMONY
AND NATURAL GAS CUSTOMERS IN THE ) OF
STATE OF IDAHO ) CLINT G. KALICH
)

FOR AVISTA CORPORATION

(ELECTRIC ONLY)

Kalich, Di 1
Avista Corporation
I. INTRODUCTION 1
Q. Please state your name, the name of your employer, 2
and your business address. 3
A. My name is Clint Kalich. I am employed by Avista
Corporation at 1411 East Mission Avenue, Spokane,
Washington.
Q. In what capacity are you employed? 7
A. I am the Manager of Resource Planning & Power
Supply Analyses in the Energy Resources Department of Avista
Utilities.
Q. Please state your educational background and 11
professional experience. 12
A. I graduated from Central Washington University in
1991 with a Bachelor of Science Degree in Business Economics.
Shortly after graduation, I accepted an analyst position
with Economic and Engineering Services, Inc. (now EES
Consulting, Inc.), a Northwest management-consulting firm
located in Bellevue, Washington. While employed by EES, I
worked primarily for municipalities, public utility
districts, and cooperatives in the area of electric utility
management. My specific areas of focus were economic
analyses of new resource development, rate case proceedings
involving the Bonneville Power Administration, integrated

Kalich, Di 2
Avista Corporation
(least-cost) resource planning, and demand-side management
program development.
In late 1995, I left Economic and Engineering Services,
Inc. to join Tacoma Power in Tacoma, Washington. I provided
key analytical and policy support in the areas of resource
development, procurement, and optimization, hydroelectric
operations and re-licensing, unbundled power supply rate-
making, contract negotiations, and system operations. I
helped develop, and ultimately managed, Tacoma Power’s 9
industrial market access program serving one-quarter of the
company’s retail load.
In mid-2000 I joined Avista Utilities and accepted my
current position assisting the Company in resource analysis,
dispatch modeling, resource procurement, integrated resource
planning, and rate case proceedings. Much of my career has
involved resource dispatch modeling of the nature described
in this testimony.
Q. What is the scope of your testimony in this 18
proceeding? 19
A. My testimony will describe the Company’s use of 20
the AURORAXMP dispatch model, or “Dispatch Model.” I will
explain the key assumptions driving the Dispatch Model’s 22
market forecast of electricity prices. The discussion
includes the variables of natural gas, Western Interconnect

Kalich, Di 3
Avista Corporation
loads and resources, and hydroelectric conditions. I will
describe how the model dispatches its resources and
contracts to maximize customer benefit and tracks their
values for use in pro forma calculations. Finally, I will
present the modeling results provided to Company witness Mr.
Johnson for his power supply pro forma adjustment
calculations.
Q. Are you sponsoring any exhibits in this 8
proceeding? 9
A. Yes. I am sponsoring one exhibit marked Exhibit
No. 5, Confidential Schedule 1C. It provides summary output
from the Dispatch Model and data that are used by Mr. Johnson
as input for his work. All information contained in the
exhibit was prepared under my direction.
15
II. THE DISPATCH MODEL 16
Q. What model is the Company using to dispatch its 17
portfolio of resources and obligations? 18
A. The Company uses EPIS, Inc.’s AURORAXMP market
forecasting model (“Dispatch Model”) and its associated
database for determining power supply costs.1 The Dispatch
Model optimizes Company-owned resource and contract dispatch

1 The Company uses AURORAXMP version 12.2.1050 with a Windows 7 operating
system.

Kalich, Di 4
Avista Corporation
during each hour of the January 1, 2018 through December 31,
2018 pro forma year.
Q. Please briefly describe the Dispatch Model. 3
A. The Dispatch Model was developed by EPIS, Inc. of
Sandpoint, Idaho. It is a fundamentals-based tool
containing demand and resource data for the entire Western
Interconnect. It employs multi-area, transmission-
constrained dispatch logic to simulate real market
conditions. Its true economic dispatch captures the
dynamics and economics of electricity markets—both short-
term (hourly, daily, monthly) and long-term. On an hourly
basis the Dispatch Model develops an available resource
stack, sorting resources from lowest to highest cost. It
then compares this resource stack with load obligations in
the same hour to arrive at the least-cost market-clearing
price for the hour. Once resources are dispatched and market
prices are determined, the Dispatch Model singles out Avista
resources and loads and values them against the marketplace.
Q. What experience does the Company have using 19
AURORAXMP? 20
A. The Company purchased a license to use the
Dispatch Model in April 2002. AURORAXMP has been used for
numerous studies, including each of its integrated resource
plans and rate filings after 2001. The tool is also used

Kalich, Di 5
Avista Corporation
for various resource evaluations, market forecasting, and
requests-for-proposal evaluations.
Q. Who else uses AURORAXMP? 3
A. AURORAXMP is used all across North America, Europe,
and the Middle East. In the Northwest specifically, AURORAXMP
is used by the Bonneville Power Administration, the
Northwest Power and Conservation Council, Puget Sound
Energy, Idaho Power, Portland General Electric, PacifiCorp,
Seattle City Light, Grant County PUD, and Snohomish County
PUD.
Q. What benefits does the Dispatch Model offer for 11
this type of analysis? 12
A. The Dispatch Model generates hourly electricity
prices across the Western Interconnect, accounting for its
specific mix of resources and loads. The Dispatch Model
reflects the impact of regions outside the Northwest on
Northwest market prices, limited by known transfer
(transmission) capabilities. Ultimately, the Dispatch Model
allows the Company to generate price forecasts in-house
instead of relying on exogenous forecasts.
The Company owns a number of resources, including
hydroelectric plants and natural gas-fired peaking units
serving customer loads during more valuable on-peak hours.
By optimizing resource operation on an hourly basis, the

Kalich, Di 6
Avista Corporation
Dispatch Model is able to appropriately value the
capabilities of these assets. Forward prices for the pro
forma 2018 period are 32% higher in the on-peak hours than
off-peak hours at the time this case was prepared. The
Dispatch Model forecasts on-peak prices for the pro forma
period to average 35% higher than off-peak prices, a figure
very close to forwards. A graphical representation of the
differences in on- and off-peak prices over the pro forma
period is shown below in Illustration No. 1.
Illustration No. 1 – Monthly AURORA modeled versus forward 10
Mid-C Prices 11

Forward Mid-Columbia prices shown are the latest one
month average (March 1, 2017 through Mar 31, 2017) of
Intercontinental Exchange (ICE) quarterly prices at the time
the study was prepared.
-
5
10
15
20
25
30
35
1 2 3 4 5 6 7 8 9 10 11 12
2018 2018 2018 2018 2018 2018 2018 2018 2018 2018 2018 2018
$/
M
W
h
AURORA Off-Peak Forwards Off Peak
AURORA On-Peak Forwards On Peak

Kalich, Di 7
Avista Corporation
Dispatch Model and forward prices can and sometimes
will differ, as forward prices are based on market
expectations whereas the data used in the Dispatch Model are
normalized for hydro, loads, and resource outages. Where
the market expects a low hydro year forthcoming, forward
market prices could be higher than Dispatch Model prices.
Referring back to Illustration No. 1, the average price for
the 2018 forward period is $21.53 per MWh; the Dispatch model
result is $21.84 per MWh. These results explain that the
market is not forecasting a bias in future conditions (e.g.,
a low hydro year). The Dispatch Model therefore provides a
very close approximation to what the actual market is
predicting, and provides a good data set for the pro forma.
Q. On a broader scale, what calculations are being 14
performed by the Dispatch Model?
A. The Dispatch Model’s goal is to minimize overall 16
system operating costs across the Western Interconnect,
including Avista’s portfolio of loads and resources. The
Dispatch Model generates a wholesale electricity market
price forecast by evaluating all Western Interconnect
resources simultaneously in a least-cost equation to meet
regional loads. As the Dispatch Model progresses from hour
to hour, it “operates” those least-cost resources necessary
to meet load. With respect to the Company’s portfolio, the 24

Kalich, Di 8
Avista Corporation
Dispatch Model tracks the hourly output and fuel costs
associated with Avista’s portfolio generation. It also
calculates hourly energy quantities and values for the
Company’s contractual rights and obligations. In every 4
hour, the Company’s loads and obligations are compared to
available resources to determine a net position. This net
position is balanced using the simulated wholesale
electricity market. The cost of energy purchased from or
sold into the market is determined based on the electric
market-clearing price for the specified hour and the amount
of energy necessary to balance loads and resources.
Q. How does the Dispatch Model determine electricity 12
market prices, and how are the prices used to calculate 13
market purchases and sales? 14
A. The Dispatch Model calculates electricity prices
for the entire Western Interconnect, separated into various
geographical areas such as the Northwest and Northern and
Southern California. The load in each area is compared to
available resources, including resources available from
other areas that are linked by transmission connections, to
determine the electricity price in each hour. Ultimately,
the market price for an hour is set based on the last
resource in the stack to be dispatched. This resource is
referred to as the “marginal resource.” Given the prominence 24

Kalich, Di 9
Avista Corporation
of natural gas-fired resources on the margin, this fuel is
a key variable in the determination of wholesale electricity
prices.
Q. How does the Dispatch Model operate regional 4
hydroelectric projects?
A. The model begins by “peak shaving” loads using 6
hydro resources with storage. When peak shaving, the
Dispatch Model determines the hours with the highest loads
and allocates to them as much hydroelectric energy within
the constraints of the hydro system. Remaining loads are
then met with other available resources.
Q. Has the Company made any modifications to the EPIS 12
database for this case? 13
A. Yes. As we have in the past, Avista’s resource 14
portfolio is modified from EPIS’ default database to reflect 15
actual project operating characteristics. Also, natural gas
prices are modified to match the latest one month average of
forward prices over the pro forma period, regional resources
and loads are modified where better information is made
available, and Northwest hydro data are replaced with
Bonneville Power Administration data. The EPIS database is
modified to include various assumptions used in the
Company’s 2017 Integrated Resource Planning process and
other new resource information where available.

Kalich, Di 10
Avista Corporation
Q. Has the Company made any changes to the way it 1
models hydro in this case compared to prior cases?
A. No it has not.
Q. How does the AURORAXMP Dispatch Model operate 4
Company-controlled hydroelectricity generation resources? 5
A. The Dispatch Model dispatches all hydro resources
first through an algorithm that matches generation to load.
To account for the actual flexibility of Company
hydroelectricity resources, Avista develops individual hydro
operations logic for each of its facilities. This separation
ensures that the flexibility inherent in these resources is
credited to customers in the pro forma exercise.
Q. Please compare the operating statistics from the 13
Dispatch Model to recent historical hydroelectric plant 14
operations. 15
A. Over the pro forma period the Dispatch Model
generates 67% of Clark Fork hydro generation during on-peak
hours (based on average water). Since on-peak hours
represent only 57% of the year, this demonstrates a
substantial shift of hydro resources to the more expensive
on-peak hours. This is identical to the five-year historical
average of on-peak hydroelectric generation at the Clark
Fork through December 2016. Similar relative performance is
achieved for the Spokane and Mid-Columbia projects.

Kalich, Di 11
Avista Corporation
III. OTHER KEY MODELING ASSUMPTIONS 1
Q. Please describe your update to pro forma period 2
natural gas prices. 3
A. Consistent with past general rate case filings,
natural gas prices are based on a one-month average of
forward prices; in this case from March 1, 2017 through March
31, 2017 for calendar-year 2018 monthly forward prices.
Natural gas prices used in the Dispatch Model are presented
below in Table No 1. 9
Table No. 1 – Pro Forma Natural Gas Prices 10
11
12
13
14
15
Q. What is the Company’s assumption for rate period 16
loads?
A. Consistent with prior general rate case
proceedings, historical loads are weather-adjusted. For
this filing weather normalized 2016 load is 1,042.9 average
megawatts compared to actual loads of 1,030.3. In addition
to the load adjustment, loads were reduced by 2.3 aMW each
month to adjust for reduction of load at a large Idaho
industrial customer. Table No. 2 below details data included
Basis
Price
($2018/dth) Basis
Price
($2018/dth)

Kalich, Di 12
Avista Corporation
in this proceeding. Further information on the weather
normalization is within Company witness Ms. Knox’s
testimony.
Table No. 2 – Pro Forma Loads 4

6
7
8
Q. Please discuss your outage assumptions for the 9
Colstrip units. 10
A. As with our assumptions for other plants, and
consistent with prior cases, Avista uses the most recent
available five-year average forced outage rate to estimate
long-run performance at the Colstrip plant. The 11.21%
forced outage rate is based on the average outages for 2012
through 2016. Maintenance outages use the six-year average
of planned outages. Six years is used because the plant
maintenance schedule is every three years.
Q. Are there any other significant modeling changes 19
from the last rate filing? 20
A. No. 21
Month
Actual
Load
Customer
Adjustment
Weather
Adjustment
Modeled
Load Month
Actual
Load
Customer
Adjustment
Weather
Adjustment
Modeled
Load
Jan-18 1,187.2 -2.3 18.7 1,203.6 Jul-18 1,017.9 -2.3 31.2 1,046.8
Feb-18 1,130.5 -2.3 51.8 1,180.0 Aug-18 1,063.2 -2.3 -25.2 1,035.7
Mar-18 1,021.8 -2.3 28.0 1,047.5 Sep-18 918.0 -2.3 23.4 939.1
Apr-18 921.2 -2.3 50.4 969.3 Oct-18 952.3 -2.3 4.4 954.4
May-18 910.0 -2.3 29.0 936.7 Nov-18 1,018.3 -2.3 55.7 1,071.7
Jun-18 979.6 -2.3 -35.7 941.7 Dec-18 1,244.7 -2.3 -49.4 1,193.0

Kalich, Di 13
Avista Corporation
IV. RESULTS
Q. Please summarize the results from the Dispatch 2
Model. 3
A. The Dispatch Model tracks the Company’s portfolio 4
during each hour of the pro forma study. Fuel costs and
generation for each resource are summarized by month. Total
market sales and purchases, and their revenues and costs,
are also determined and summarized by month. These values
are contained in Exhibit No. 5, Confidential Schedule 1C and
were provided to Mr. Johnson for use in his calculations.
Mr. Johnson adds resource and contract revenues and expenses
not accounted for in the Dispatch Model (e.g., fixed costs)
to determine net power supply expense.
Q. Does this conclude your pre-filed direct 14
testimony? 15
A. Yes, it does.