2019 Standard Scenarios Report: A U.S. Electric Sector Outlook
Wesley Cole, Nathaniel Gates, Trieu Mai, Daniel Greer, and Paritosh Das
January 9, 2020
W. Cole et al., “2019 Standard Scenarios Report: A U.S. Electricity Sector Outlook,” NREL/TP-6A20-74110, 69 pp. (December 2019).
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What are the “Standard Scenarios?”
• Suite of forward-looking scenarios (projections) of the U.S. power sector
• NREL report that identifies themes from the scenarios
• Companion product of the Annual Technology Baseline– https://atb.nrel.gov/
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Why do we do the Standard Scenarios?
• Internal Value– Consistency across analyses– Improved efficiency
• External Value– Share our input assumptions and model results– Provide an additional perspective on power sector
evolution– Inform stakeholder decision-making
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Changes from Last Year
• ReEDS 2.0 Model Version - https://www.nrel.gov/analysis/reeds/• Scenario changes
– New scenarios:• Endogenous Retirements• Perfect Foresight• Shortened Cost Recovery• Individual High RE Cost scenarios
– Several scenarios removed• Model, input, and policy updates
– See Appendix A.2 of the report
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Webinar Outline
• Summary of the Standard Scenarios• Insights and perspectives from the 2019 Standard Scenarios
(i.e., what is in the report)• How to access the scenario data and model
The Standard Scenarios
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Tools & Method
dGenRooftop PV adoption
Bass diffusion
ReEDSCapacity expansion
Minimize total system cost
PLEXOS*Production cost
Minimize production cost
Scenarios Definitions
Standard Scenario Results
*Only a subset of scenarios were run in PLEXOS
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The Mid-case Scenario
• Fuel prices: EIA Annual Energy Outlook (AEO) 2019• Demand growth: AEO 2019• Technology cost and performance: 2019 Annual Technology Baseline (ATB)• Current policies as of July 31, 2019• Current fleet characteristics: EIA NEMS Plant Database
01234567
2018 2028 2038 2048
Fuel
Pric
e (2
018$
/MM
Btu
)
00.20.40.60.8
11.21.41.6
2018 2028 2038 2048D
eman
d G
row
thNatural Gas
CoalUranium
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U.S. Power Sector Evolution Over Time
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System Evolution by State in the Mid-case
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How theMid-case Compares
Comparisons:• Bloomberg New
Energy Finance (BNEF)
• Energy Information Administration (EIA)
• International Energy Agency (IEA)
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Sensitivity Scenarios
• Mid-case uses first entry in each category
• 36 total scenarios using the sensitivities shown at right
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Generation by Fuel Type Across the Scenarios
Theme #1: Changes in Technology Revenue with Evolutions in the Grid Mix
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Recent Trends
Source: EIA (various datasets)
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CAISO Example: PV Deployment and Energy Prices
05
101520253035404550
2012 2014 2016 2018
Aver
age
Ener
gy P
rice
($/M
Wh)
Noon
Midnight
Annual
0
5
10
15
20
25
2012 2014 2016 2018
PV C
apac
ity (G
WD
C)
As PV capacity increases, energy prices during the middle of the day declineSource: ABB Velocity Suite
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Grid Service Prices Across
Scenarios
Grid service prices, coupled with the contribution of a technology toward that service, determine the value of the technology
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Fraction of Revenue by Technology Type
2030 2050
0%10%20%30%40%50%60%70%80%90%
100%W
ind
Nuc
lear
Hyd
ro PV Geo
CSP
Coa
lN
G-C
CBa
ttery
NG
-CT
Frac
tion
of R
even
ue
0%10%20%30%40%50%60%70%80%90%
100%
Win
dN
ucle
arH
ydro PV Geo
CSP
Coa
lN
G-C
CBa
ttery
NG
-CT
StatePolicyOperatingReservePlanningReserveEnergy
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Average Curtailment Tends to Increase with VRE Penetration
Theme #2: Planning Reserve Provision in an Evolving Grid
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Planning Reserve
• Different from operating reserve
• Ensures sufficient capacity during peak periods
• “Resource Adequacy”
0
20
40
60
80
100
120
Peak Demand Planning ReserveProvision
Capa
city
(GW
)
Planning Reserve
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Capacity Credit
• Capacity credit is the fraction of a nameplate capacity that is counted toward the planning reserve margin
RTO Wind PVPJM 12.3% 45.1%ERCOT Summer: 15% Non-Coastal / 58% Coastal
Winter: 20% Non-Coastal / 43% CoastalSummer: 74%
Winter: 12%CAISO Summer: 35%
Winter: 15%Summer: 43%Winter: 0.8%
ISO-NE Summer: 13.2%Winter: 39%
29%
NYISO Summer: 10%Winter: 30%
Summer: 39%Winter: 1%
MISO 15.2% 50%SPP Summer: 24%
Winter: 16%70%
Summary of Current or Proposed Market Rules –Subject to Change
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VRE Penetration Increases across the Scenarios
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Non-variable Capacity is Flat or Increasing
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Hourly Dispatch during Peak in Mid-case (2050)
Peak Net Load Day (August 8)Peak Load Day (July 26)
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Planning Reserve Provision is Largely from Non-Dispatchable Techs
Solar and wind still contribute, but to a much lesser degree than to the total capacity
Solar contributes very little in winter months
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Across all Scenarios, most Planning Reserve Capacity is from Non-Variable Technologies
0
0.2
0.4
0.6
0.8
1
Total PlanningReserve
Total PlanningReserve
Total PlanningReserve
Non-variable Techs Wind PV
Frac
tion
of C
apac
ity in
205
0
RangeMid-case
Theme #3: Regional Generation Mix Trends
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Historical Changes in State-level Generation Mix
Source: EIA (various datasets)
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Marginal Curtailment Rate in 2050 in the Mid-case
Marginal Curtailment %
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Zero-price Hours in 2050
Percent of Hours at or Below $0/MWh Price
Accessing the Data and Model
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https://openei.org/apps/reeds/
Standard Scenario Results Viewer available at
Cloud icon downloads data into csv file
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ReEDS Model Available Now,dGen to Follow
https://www.nrel.gov/analysis/reeds/
https://www.nrel.gov/analysis/dgen/
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Summary
• Standard Scenarios provides a framework to– Improve analysis and modeling– Provide a perspective on the U.S. electricity sector evolution– Get access to state-level projections
• Themes from 2019:– How the revenue of technologies changes with the evolving
generation mix – How resource adequacy is maintained across scenarios as the
generation mix evolves to include more variable generation– How technology costs, policies, resource quality, and other factors
are leading to potential changes in regional-level generation mixes
www.nrel.gov
Questions or [email protected]
Full Report: https://www.nrel.gov/docs/fy20osti/74110.pdf
Results Viewer: https://openei.org/apps/reeds/
This work was authored by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Office of Strategic Programs. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes.
NREL/PR-6A20-75798