System Flexibility Assessment for the Western Interconnection
RAWG Meeting W ESTERN E LECTRICITY C OORDINATING C OUNCIL
Slide 2
Flexibility Wide-spread production simulation modeling Results
from past TEPPC studies 2013 Plan - Recommendation 3: Assess Future
Operational Flexibility 2 W ESTERN E LECTRICITY C OORDINATING C
OUNCIL
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About the Study Need to understand power system flexibility
needs under higher renewable penetration in planning timeframe
Stakeholder requests: Further integrate and expand planning tools
WECC engaged E3 and NREL to study operational needs using E3s
Renewable Energy Flexibility Model (REFLEX) Funding for E3 work
from WECC and WIEB (through ARRA) Funding for NREL work from
DOE
Slide 4
Project Team Partnership between WECC, WIEB, NREL and E3 WECC
& WIEB provide project oversight and direction E3 directs
technical work NREL provides data, HPC resources and technical
support E3 NREL WECC WIEB Stakeholders
Slide 5
Stakeholder Input Technical Advisory Group provides input on
data, methodologies and assumptions Includes representatives of
utilities, advocacy groups, National Labs, Northwest Power and
Conservation Council, EPRI Executive Advisory Group helps ensure
studys relevance to Western decision-makers Jim Robb (WECC), Mark
Rothleder (CAISO), Rebecca Wagner (NVPUC), Doug Larson (WIEB),
Kimberly Harris (PSE), Mike Hummel (SRP), Gregg Lemler (PG&E),
Bill Gaines (TCPL), Stacey Kusters (NVE), Stephan Bird (PAC),
Elliot Manzier (BPA), Tom Imbler (Xcel) Periodic reporting to
WIEB/SPSC, TEPPC, and other WECC committees
Slide 6
Study Goals Assess the ability of the fleet of resources in the
Western Interconnection to accommodate high renewable penetration
while maintaining reliable operations Quantify the size, magnitude
and duration of operating challenges resulting from high renewable
penetration Investigate potential flexibility solutions, including:
Renewable curtailment as an operational strategy Regional
coordination Diverse renewable portfolio Flexible supply and
demand-side resources Transmission Energy storage Learn about how
to do flexibility modeling and planning Institutional solutions
Physical solutions
Slide 7
Cases Studied 2024 Common Case Few reliability or flexibility
issues anticipated Primary purpose of case is calibration 2024 High
Renewables Case(s) Want to study a case with renewable penetration
that is high enough to show interesting operational challenges
Composition of case TBD in consultation with technical and
executive groups Sensitivities to understand how composition of
case affects flexibility challenges Alternative levels of wind,
solar, & baseload renewables
Slide 8
Strawman High Renewables Case High renewables case should have
enough wind and solar generation to illuminate significant
flexibility constraints Test simulations of this Strawman case,
while preliminary, provide some useful insights into challenges at
higher penetrations to be shared today
Slide 9
Flexibility Study Sequence 1.Identify flexibility constraints
under conservative assumptions Demonstrate the magnitude and
frequency of potential flexibility violations under the worst case
2.Relax constraints and demonstrate the efficacy of solutions that
are available in the absence of investment Renewable curtailment,
flexible ties, increase ramp rates, decrease Pmin 3.Additional
studies, depending on time and resources, exploring the benefits of
investments in power system flexibility Transmission, flexible
generation & loads, energy storage
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Schedule 10 W ESTERN E LECTRICITY C OORDINATING C OUNCIL Jul
2014: Project kickoff Aug 2014: Common case review complete Sep
2014: First technical and executive group meeting Oct 2014: RECAP
analysis of Common Case complete Nov 2014: RECAP analysis of High
Renewables Case April 2015: REFLEX analysis of Common Case Apr
2015: REFLEX analysis of High Renewables Case May 2015: Final
report X X X X X X
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Current Status 11 W ESTERN E LECTRICITY C OORDINATING C OUNCIL
Insights from Model Testing REFLEX constraints can be applied to
multiple regions simultaneously Platform for flexibility analysis
has been expanded to allow multi-zone simulation Boundary
conditions in each region are endogenous to the model Running
REFLEX using a full nodal transmission topology is not feasible
Achieving reasonable computation time requires simplifications to
transmission representation Three-day optimization window is
infeasible due to model runtime Study will use two sequential
one-day optimizationseach with a one-day look- ahead periodto
simulate unit commitment in the second day of each draw
Slide 12
Timeline for REFLEX Analysis 12 W ESTERN E LECTRICITY C
OORDINATING C OUNCIL Completion of the first full simulations of
the Common Case is the next stepthe remaining pieces of analysis
should follow directly (schedule is relative to completion of
initial Common Case runs): TRC Meeting Common Case results +2 weeks
High Renewable Case complete +4 weeks TRC Meeting High Renewable
Case +6 weeks Analysis of solutions +8 weeks Draft report +10 weeks
TRC Meeting report review +12 weeks Final report +16 weeks Current
goal is to meet this key milestone by Aug 15
Slide 13
Development of High Renewable Case Assumptions 13 W ESTERN E
LECTRICITY C OORDINATING C OUNCIL Development of assumptions for
the High Renewable Case has been shifted and will take place in
parallel to work on the REFLEX Common Case Goal in developing High
Renewable Case: establish renewable portfolios that are
interestingbut not extreme from the perspective of system
flexibility Largest challenge is expected to be oversupply: when a
regions must- take generation exceeds its demand for energy E3 will
analyze patterns in net load for a range of portfolios to help
inform mix/penetrations; to be shared with TRC early April Example
April Day
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Questions 14 W ESTERN E LECTRICITY C OORDINATING C OUNCIL
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RECAP MODEL RESULTS
Slide 16
E3 Renewable Energy Capacity Planning Model (RECAP) Flexibility
Assessment utilizes RECAP, E3s non-proprietary model for evaluating
power system reliability and resource capacity value under high
renewable penetration Initially developed to support CAISO
renewable integration modeling Used by a number of utilities and
state commissions Will be transferred to WECC as part of study
process
Slide 17
Calculating LOLP LOLP is determined by comparing the
distributions of potential load and resource states and calculating
the probably that load exceeds generation Gross load distribution
Net thermal generation distribution LOLP comes from the chance that
net load exceeds net thermal generation Gross load Net thermal
generation LOLP
Slide 18
Adding Renewables After adding renewables to the system, net
loads are reduceddistribution shifts to left LOLP decreases in
every hour (nearly) Gross load distribution Net thermal generation
distribution Net load distribution with renewables Renewable net
load Gross load Thermal generation Reduction in LOLP with increase
in renewables
Slide 19
Calculating ELCC Since LOLE has decreased with the addition of
renewables, adding load will return the system to the original LOLE
The amount of load that can be added to the system is the effective
load carrying capability (ELCC) Original system LOLE LOLE after
renewables Additional load to return to original system LOLE =
ELCC
Slide 20
Portfolio vs. Marginal ELCC Values 1.The cumulative portfolio
capacity value is used for resource adequacy planning Due to the
complementarity of different resources the portfolio value will be
higher than the sum of each individual resource measured alone May
need to attribute the capacity value of the portfolio to individual
resources There are many options, but no standard or rigorous way
to do this 2.The marginal capacity value, given the existing
portfolio, is used in procurement Provides a measure of the value
of the next resource to be procured This value will change over
time with the mix of system needs & resources Individual Solar
Capacity Value Individual Wind Capacity Value Combined Capacity
Value
Slide 21
Reliability Metrics The RECAP model calculates conventional
power system reliability metrics: Loss of Load Probability (LOLP)
Loss of Load Expectation (LOLE) Loss of Load Frequency (LOLF)
Expected Unserved Energy (EUE) RECAP also calculates effective
capacity of renewables, demand response, and other dispatch-limited
resources: Effective Load Carrying Capability (ELCC) LOLE Marginal
ELCC Cumulative ELCC
Slide 22
Renewable penetration in the Common Case is approximately 20%
of load (U.S. portion); wind and solar serve approximately 13% of
load: E3 and NREL have developed production profiles to reflect the
operational characteristics of these resources Common Case
Renewable Mix
Slide 23
Target Planning Reserve Margins RECAP estimates reserve margins
needed to achieve a target reliability threshold LOLF = 1 event in
10 years Target PRM needed to meet standard varies by region Common
Case above Target PRM for all regions TypeTarget PRM Common Case
PRM Basin14%17% California13%25% Northwest15%32% Rockies17%19%
Southwest15%32%
Slide 24
Marginal ELCC Curves by Technology and Region
SouthwestCalifornia Marginal ELCC = capacity contribution of next
increment of capacity of a given type Curves are illustrative they
assume a single technology
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Marginal ELCC Curves by Technology and Region (Cont.)
BasinRockies Northwest
Slide 26
Observations on ELCC Values Marginal ELCC of solar PV at low
penetrations is 50-60% of nameplate capacity (except in NW) Aligns
well with commonly used heuristics At low penetrations, marginal
ELCC values for wind range from 15-30% of nameplate capacity
Slightly higher than common heuristics ELCC values exhibit
significant diminishing returns to scale, particularly solar PV
which shifts net load peak into the evening As penetration
increases, heuristics become increasingly inaccurate
Slide 27
Effect of Diversity on ELCC Values For a diverse portfolio,
ELCC of combined portfolio is higher than individual ELCC values At
20% of load: W = 3041, S = 6172, W+S = 12,861
Slide 28
Ongoing uses for RECAP by WECC The need for ELCC in WECCs
planning studies will increase as the penetration of variable
generation increases As part of the flexibility assessment project,
the RECAP model will be transferred to WECC staff to help support
modeling efforts TEPPC Common Case development Summer load
assessments Section 111(d) impacts As an open-source tool, RECAP
can also be shared with or modified by stakeholders
Slide 29
REFLEX MODEL STATUS
Slide 30
E3s Renewable Energy Flexibility (REFLEX) Model REFLEX answers
critical questions about flexibility need through stochastic
production simulation Captures wide distribution of operating
conditions through Monte Carlo draws of operating days Illuminates
the significance of the operational challenges by calculating the
likelihood, magnitude, duration & cost of flexibility
violations Assesses the benefits and costs of investment to avoid
flexibility violations Implemented as an add-on to Plexos for Power
Systems
Slide 31
WECC Flexibility Assessment Distinguishing Characteristics The
use of REFLEX for PLEXOS in this study is different from
conventional production cost modeling of the WECC in several
important respects: 1.Economic tradeoff between upward (loss of
load) and downward (curtailment) flexibility violations
2.Endogenous determination of load following reserves as function
of expected within-hour flexibility deficiencies 3.Stochastic
sampling of load, wind, solar, and hydro conditions 4.Sub-regional
study footprints with specified boundary conditions Import/export
limitations and maximum ramp rates
Slide 32
Renewable Dispatch is Used to Solve Upward Ramping Shortages
Model needs robust information on cost of upward vs. downward
shortages Cost of unserved energy due to ramping shortfall: very
high ($5,000-50,000/MWh) Cost of renewable dispatch: replace the
lost production ($50-$150/MWh) Limited Ramping Capability Unserved
Energy Limited Ramping Capability Renewable Curtailment Strategy to
Minimize Downward ViolationsStrategy to Minimize Upward
Violations
Slide 33
Stochastic Sampling From a Range of Conditions In order to
ensure robust sampling results, RECAP and REFLEX sample from a
broad range of load, wind, & solar conditions Historical data
matched up based on month of year, day type (i.e. load level) Range
of available data
Slide 34
Capturing Transmission in Flexibility Assessment Multiple
options for representing interregional power flows have been tested
123 Original project plan Single-Zone Models Each region modeled
independently with no internal transmission Imports and exports
captured through supply curves Offers simplest modeling framework,
but difficult to represent interregional power exchange Single-Zone
Models Each region modeled independently with no internal
transmission Imports and exports captured through supply curves
Offers simplest modeling framework, but difficult to represent
interregional power exchange Zonal Model Loads and resources
grouped together by region Regions linked together by transport
model Provides macro level view of interregional power exchange,
but ignores individual line and path flow limits Zonal Model Loads
and resources grouped together by region Regions linked together by
transport model Provides macro level view of interregional power
exchange, but ignores individual line and path flow limits Nodal
Model All nodes in WECC (25,000) represented Dispatch solution is
constrained by DC OPF and enforced line limits Provides greatest
fidelity of transmission system, but requires significant
development and is computationally intensive Nodal Model All nodes
in WECC (25,000) represented Dispatch solution is constrained by DC
OPF and enforced line limits Provides greatest fidelity of
transmission system, but requires significant development and is
computationally intensive Model Complexity Final project plan
Slide 35
Zonal Topology Zonal topology chosen based on aggregations of
interregional WECC paths California Northwest Basin Rocky Mountain
Southwest NW to CA P65 P66 CA to BS P24 P28 P29 SW to CA P46 RM to
SW P31 BS to SW P35 P78 P79 All Paths P14: ID to NW P18: NT - ID
P24: PG&E - Sierra P28: Intermtn - Mona P29: Intermtn Gonder
P30: TOT 1A P31: TOT 2A P35: TOT 2C P38: TOT 4B P46: WOR P65: COI
P66: PDCI P76: Alturas Project P78: TOT 2B1 P79: TOT 2B2 P80: MT SE
BS to NW P14 P18 P76 P80 BS to RM P30 P38
Slide 36
Strawman High Renewables Case High renewables case should have
enough wind and solar generation to illuminate significant
flexibility constraints Test simulations of this Strawman case,
while preliminary, provide some useful insights into challenges at
higher penetrations to be shared today
Slide 37
Strawman Limited-Draw Results: California Curtailment: ~6% RG
Overgeneration occurs regularly and periodically, especially in the
spring months Overgeneration is solar-driven and occurs in the
middle of the day Hydro, pumped storage, and imports help to meet
nighttime load April Day Strawman High Renewables All dispatchable
plants reduce output to minimum levels Curtailment due to solar
oversupply
Slide 38
Strawman Limited-Draw Results: Northwest Curtailment: ~3% of RG
Overgeneration conditions occur during high hydro and/or high wind
conditions Curtailment may be concentrated during nighttime or
could persist through day if wind output remains high More
day-to-day variability in conditions within seasons compared to
regions with high solar penetration April Day Strawman High
Renewables Curtailment due to simultaneous high wind & hydro
conditions
Slide 39
Strawman Limited-Draw Results: Northwest Curtailment: ~3% of RG
Overgeneration conditions occur during high hydro and/or high wind
conditions Curtailment may be concentrated during nighttime or
could persist through day if wind output remains high More
day-to-day variability in conditions within seasons compared to
regions with high solar penetration April Day #2 Strawman High
Renewables During lower hydro conditions, high wind may not result
in curtailment
Slide 40
Strawman Limited-Draw Results: Southwest Curtailment: ~3% of RG
Coal plants are cycled down the middle of the day to accommodate
solar, but curtailment still occurs Steep morning down-ramp and
evening up- ramp of coal, hydro, and gas are challenging
operational conditions April Day Strawman High Renewables Large
coal ramps require further investigation Curtailment due to solar
oversupply