20180102PAC to Monsanto 3.pdf

RECElVEDROCKYMOUNTAINPOWER2018JAN-
I PM 4:30Amsionoreacwco""1407 W North Temple,Suite 330
i D U SU C Salt Lake City,Utah 84116
COMMiŠŠlON
January 2,2018
Randall C.Budge,ISB No.1949
Thomas J.Budge,ISB No.7465
RACINE,OLSON,NYE &BUDGE,CHARTERED
P.O.Box 1391;201 E.Center
Pocatello,Idaho 83204-1391
[e-mail] (C)
[e-mail](C)(W)
RE:ID PAC-E-17-07
Monsanto 3rd Set Data Request (3)
Please find enclosed Rocky Mountain Power's Response to Monsanto 3rd Set Data Request 3.3.
If you have any questions,please feel free to call me at [phone].
Sincerely,
J.Ted Weston
Manager,Regulation
Enclosures
C.c.:Diane Hanian/IPUC [e-mail] (C)
Ronald L.Williams/PIIC [e-mail] (C)
Brad Mullins/PIIC [e-mail] (C)
Jim Duke/PIIC [e-mail] (C)(W)
Kyle Williams/PIIC [e-mail] (C)(W)
Val Steiner/[e-mail] (C)(W)
Brian C.Collins/Brubaker &Associates bcollins consultbai.com (C)(W)
James R.Smith/Monsanto [e-mail] (C)(W)
Maurice Brubaker/[e-mail] (C)(W)
Katie Iverson/[e-mail] (C)
Eric Olsen/IIPA [e-mail] (C)
AnthonyYankel/IIPA [e-mail](C)
PAC-E-17-07/Rocky Mountain Power
January 2,2018
Monsanto 3rd Set Data Request 3
Monsanto Data Request 3
Please describe precisely and in detail how PacifiCorp has considered all other
alternative sources for long-term electric supply or transmission,including energy
efficiency,demand-side management and other feasible alternative sources of
supply or transmission;and,how each alternative sources compares with the
proposed "Wind Projects"in this filing.
Response to Monsanto Data Request 3
The Company objects to the data request as vague,ambiguous and overly broad.
Without waiving the objection,the Company uses two highly specialized
optimization models to analyze alternatives for meeting system requirements:the
System Optimizer model (SO model)and the Planning and Risk (PaR)model.
The SO model is a capacity expansion model.PaR provides stochastic cost and
risk data,taking the SO model's capacity expansion results as an input.
The SO model includes a broad range of expansion resources,including load-
control demand-side management (DSM),energy efficiency (EE),gas and coal
plants,solar power,energy storage,wind power,nuclear power,geothermal,
biomass and front office transactions (FOT).Key information regarding resource
options available to the SO model are providedin PacifiCorp's 2017 Integrated
Resource Plan (IRP),Chapter 6 (Resource Options).Please refer to:
http://www.pacificorp.com/content/dam/pacificorp/doc/EnergySources/Integrate
d Resource Plan/2017 IRP/2017 IRP Volumel IRP Final.pdf.
All included options can be selected to meet resource requirements,including a
13-percent planning-reserve margin (PRM)and energy requirements serving all
customer loads,to minimize the present value of revenue requirements (PVRR).
The SO model produces a portfolio that simultaneously optimizes all of these
factors over the entire study period,in this case from 2017 through 2036.The
Wind Projects were consistently a least-cost option for meeting both peak-load
requirements and energy requirements over the entire study timeframe relative to
other resource alternatives,recognizing eligibility for 100 percent of production
tax credits (PTC)by being placed in service by December 31,2020.
Each PaR study inherits its portfolio from the corresponding SO model portfolio,
performing stochastic iterations to inform the analysis of risk against changing
stochastic parameters,such as load and price variances.The PaR model
consistently identified the Wind Projects as least-cost,least-risk.
Note that the Wind Projects were not selected to meet state-specific policy
objectives,such as requirements to meet state renewable portfolio standards
(RPS).No state-specific RPS constraints were included in the studies.
PAC-E-17-07/Rocky Mountain Power
January 2,2018
Monsanto 3rd Set Data Request 3
PacifiCorp's economic analysis filed in this docket compares the system costs
with resource portfolios that include the Wind Projects to the system costs with
portfolios that exclude the Wind Projects,thereby requiring other,higher-cost
resource alternatives to meet projected resource needs.