IEEE Electrification - December 2021 - 45

options (as opposed to just a subset of resources) and
then weaves those values into its modeling, PGE's 2019
IRP represents a uniquely thorough, holistic approach to
modeling energy storage and
other flexible resources. However,
because it required the internal
development and integration of
new software and steps into the
IRP process, it is also among the
most complex and costly practices
studied. PGE's gradual approach to
this challenge-developing and
refining it over multiple planning
cycles-provides a template for
managing those complexities.
NIPSCO:
Enhanced
Cost Inputs
Market
Forecast
Summary and Conclusion
A common theme among IRPs
reviewed for this work is that, as
the electric grid transitions to a
cleaner, more variable resource
mix, energy storage will be increasingly
necessary. Though traditional
IRP modeling tools lack the temporal
and spatial granularity to identify
cost-effective opportunities to
deploy energy storage, the nine
innovative practices identified in
this work demonstrate that there
are many ways to overcome those
barriers. The diversity of these practices
creates multiple access points
for a utility, regulator, or other
stakeholder seeking to improve the
treatment of energy storage in an
IRP. Figure 3 illustrates the points
where these practices improve the
IRP process.
These practices also vary in
terms of complexity and cost, from
simple measures that can be
implemented quickly at minimal
cost to highly complex measures
that may require significant cost
and take years to fully realize. This
variation ensures that incremental
steps are available to any utility,
regardless of the sophistication of
its current IRP model. These example
IRPs also demonstrate that utilities
may take an evolutionary
approach that develops and refines
practices over multiple planning
cycles. Figure 4 presents these best
practices in terms of relative complexity
and cost.
The rankings presented in Figure 4 are subjective
based on our experience. Practices are positioned in
relative terms. In general, practices that involve an
CPUC:
Storage
Potential
Study
PGE (2019):
External
BTM Storage
Study
PNM:
Reserve
Study and
ELCC
Analysis
PGE (2019):
GHG
Constraint
Resource
Assumptions
Load
Forecast
Scenario
Identification
(Scenario 1,
Scenario 2,
Scenario n)
PGE Net Cost
(2016): External
Flexibility Model
PGE (2019): Full
Integration of
Flexibility Model
CPUC: Additional
Storage Values
in SERVM
Capacity Expansion
Portfolio Identification
Production Cost Modeling
PSE:
Operational
Flexibility
Analysis
Risk Assessment and Portfolio
Comparison
Preferred
Portfolio
Selection
Inputs
Modeling
Figure 3. IRP entry points for best practices.
Outcome
PSE
(Operational Flexibility)
PGE
CPUC
(Potential Study)
PGE
(BTM Study)
NIPSCO
(RFP for
Costs)
PGE
(No-GHG
Scenario)
Net Cost
(Generic)
Increasing Complexity
Figure 4. The relative cost and complexity of identified best practices.
IEEE Electrification Magazine / DECEMBER 2021
45
CPUC
PNM
(ELCC)
(SERVM)
PGE
(Net Cost)
(ROM Enhancement)
Increasing Cost
IEEE Electrification - December 2021

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