IEEE Electrification - December 2021 - 43

After a certain point, 4-h storage
devices can only meet a portion of
the peak demand, which diminishes
the value of the capacity that they
provide. The study that the CPUC
commissioned used an ELCC
approach similar to PNM's. But rather
than identify the inflection points at
which ELCC values would decline,
the objective of the CPUC's study was
to quantify the total amount of 4-h
energy storage that could contribute
to California's capacity needs in a
high-renewables future before those
diminishing returns would render
additional investments uneconomic.
The study's authors determined that,
because of the aggressive projected buildout of solar and
wind generation in California in the next decade, the
state could add more than 10 GW of 4-h energy storage
before reaching that point (Carden and Wintermantel
2019). This practice of identifying the technical potential
of a resource to inform planning assumptions has been a
common practice for energy efficiency measures in many
states for years.
The institution of these changes increased the amount
of energy storage selected in the RSP from 2,104 MW by
2030 in the 2018 plan to 11,384 MW by 2030 in the 2020
plan. (The CPUC's RSP is available at http://docs.cpuc.
ca.gov/PublishedDocs/Published/G000/M331/
K772/331772681.PDF.)
Relative to other measures presented in this article,
the two actions taken by the CPUC fall at different points
on the spectrum. Developing and refining granular
modeling software represents a costly and complex
The IRP process in
California is unique,
as it is performed on a
statewide basis, and
state regulators-who
normally review and
respond to utility
IRPs-instead actively
lead the process.
undertaking. The external study, on
the other hand, was a relatively lowcost
and simple means of informing
planning assumptions regarding the
potential for energy storage on the
California grid.
Portland General Electric
In its last two IRP cycles, Portland General
Electric (PGE) has taken major
steps to improve its modeling of energy
storage technologies. Because of the
evolutionary approach the utility has
employed in this process, it has developed
multiple distinct practices that
will be discussed here.
PGE's 2016 IRP: Net Cost Analysis
Recognizing that its traditional, hourly capacity expansion
model was not capturing the granular benefits of
flexible resources, PGE developed a secondary model to
study those benefits in its 2016 IRP. The Resource Optimization
Model (ROM) was designed to dispatch resources
at both subhourly and real-time resolution while
accounting for the system's ancillary service needs, thereby
capturing the intrahour benefits of energy storage and
other flexible options.
Once those benefits were identified, PGE projected
them for an entire year to generate an annual " operational
value " for each studied asset. PGE looked at six
different battery configurations with various capacity
and duration characteristics and, for comparison purposes,
also studied the operational value of a 25-MW
combustion turbine (CT). Where PGE's traditional modeling
tools indicated that the cost of a 25-MW, 4-h battery
25,000
24,000
23,000
22,000
21,000
20,000
19,000
18,000
17,000
16,000
15,000
Initial Load Shape
Load Shape With Incremental 192 MW of 0.5-1-h Storage
Load Shape With Incremental 1,069 MW of 1.5-2-h Storage
Load Shape With Incremental 735 MW of 2.5-3-h Storage
Load Shape With Incremental 763 MW of 3.5-4-h Storage
18 18:30 19 19:30 20 20:30
21 21:30 22 22:30 23 23:30 24
Time of Day
Figure 2. Increased duration requirements for incremental energy storage assets to reduce peak generation needs in CAISO. (Source: Data
from the International Energy Agency: https://www.iea.org/data-and-statistics/charts/the-california-duck-curve.)
IEEE Electrification Magazine / DECEMBER 2021
43
CAISO Load (MW)

http://docs.cpuc.ca.gov/PublishedDocs/Published/G000/M331/K772/331772681.PDF http://docs.cpuc.ca.gov/PublishedDocs/Published/G000/M331/ K772/331772681.PDF http://docs.cpuc.ca.gov/PublishedDocs/Published/G000/M331/K772/331772681.PDF https://www.iea.org/data-and-statistics/charts/the-california-duck-curve

IEEE Electrification - December 2021

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