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Title: Variable Renewable Energy in Long-Term Planning Models: A Multi-Model Perspective

Abstract

Long-term capacity expansion models of the U.S. electricity sector have long been used to inform electric sector stakeholders and decision makers. With the recent surge in variable renewable energy (VRE) generators - primarily wind and solar photovoltaics - the need to appropriately represent VRE generators in these long-term models has increased. VRE generators are especially difficult to represent for a variety of reasons, including their variability, uncertainty, and spatial diversity. To assess current best practices, share methods and data, and identify future research needs for VRE representation in capacity expansion models, four capacity expansion modeling teams from the Electric Power Research Institute, the U.S. Energy Information Administration, the U.S. Environmental Protection Agency, and the National Renewable Energy Laboratory conducted two workshops of VRE modeling for national-scale capacity expansion models. The workshops covered a wide range of VRE topics, including transmission and VRE resource data, VRE capacity value, dispatch and operational modeling, distributed generation, and temporal and spatial resolution. The objectives of the workshops were both to better understand these topics and to improve the representation of VRE across the suite of models. Given these goals, each team incorporated model updates and performed additional analyses between the first and second workshops.more » This report summarizes the analyses and model 'experiments' that were conducted as part of these workshops as well as the various methods for treating VRE among the four modeling teams. The report also reviews the findings and learnings from the two workshops. We emphasize the areas where there is still need for additional research and development on analysis tools to incorporate VRE into long-term planning and decision-making.« less

Authors:
 [1];  [1];  [1];  [1];  [2];  [2];  [2];  [3];  [3];  [4];  [5];  [5];  [5];  [6]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
  2. Electric Power Research Inst., Palo Alto, CA (United States)
  3. Energy Information Administration, Washington, DC (United States)
  4. Environmental Protection Agency, Washington, DC (United States)
  5. Environmental Protection Agency
  6. U.S. Department of Energy
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Strategic Programs (EE-SP)
OSTI Identifier:
1411514
Report Number(s):
NREL/TP-6A20-70528
DOE Contract Number:
AC36-08GO28308
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; ReEDS; NEMS; REGEN; IPM; capacity expansion; modeling

Citation Formats

Cole, Wesley J., Frew, Bethany A., Mai, Trieu T., Sun, Yinong, Bistline, John, Blanford, Geoffrey, Young, David, Marcy, Cara, Namovicz, Chris, Edelman, Risa, Meroney, Bill, Sims, Ryan, Stenhouse, Jeb, and Donohoo-Vallett, Paul. Variable Renewable Energy in Long-Term Planning Models: A Multi-Model Perspective. United States: N. p., 2017. Web. doi:10.2172/1411514.
Cole, Wesley J., Frew, Bethany A., Mai, Trieu T., Sun, Yinong, Bistline, John, Blanford, Geoffrey, Young, David, Marcy, Cara, Namovicz, Chris, Edelman, Risa, Meroney, Bill, Sims, Ryan, Stenhouse, Jeb, & Donohoo-Vallett, Paul. Variable Renewable Energy in Long-Term Planning Models: A Multi-Model Perspective. United States. doi:10.2172/1411514.
Cole, Wesley J., Frew, Bethany A., Mai, Trieu T., Sun, Yinong, Bistline, John, Blanford, Geoffrey, Young, David, Marcy, Cara, Namovicz, Chris, Edelman, Risa, Meroney, Bill, Sims, Ryan, Stenhouse, Jeb, and Donohoo-Vallett, Paul. Fri . "Variable Renewable Energy in Long-Term Planning Models: A Multi-Model Perspective". United States. doi:10.2172/1411514. https://www.osti.gov/servlets/purl/1411514.
@article{osti_1411514,
title = {Variable Renewable Energy in Long-Term Planning Models: A Multi-Model Perspective},
author = {Cole, Wesley J. and Frew, Bethany A. and Mai, Trieu T. and Sun, Yinong and Bistline, John and Blanford, Geoffrey and Young, David and Marcy, Cara and Namovicz, Chris and Edelman, Risa and Meroney, Bill and Sims, Ryan and Stenhouse, Jeb and Donohoo-Vallett, Paul},
abstractNote = {Long-term capacity expansion models of the U.S. electricity sector have long been used to inform electric sector stakeholders and decision makers. With the recent surge in variable renewable energy (VRE) generators - primarily wind and solar photovoltaics - the need to appropriately represent VRE generators in these long-term models has increased. VRE generators are especially difficult to represent for a variety of reasons, including their variability, uncertainty, and spatial diversity. To assess current best practices, share methods and data, and identify future research needs for VRE representation in capacity expansion models, four capacity expansion modeling teams from the Electric Power Research Institute, the U.S. Energy Information Administration, the U.S. Environmental Protection Agency, and the National Renewable Energy Laboratory conducted two workshops of VRE modeling for national-scale capacity expansion models. The workshops covered a wide range of VRE topics, including transmission and VRE resource data, VRE capacity value, dispatch and operational modeling, distributed generation, and temporal and spatial resolution. The objectives of the workshops were both to better understand these topics and to improve the representation of VRE across the suite of models. Given these goals, each team incorporated model updates and performed additional analyses between the first and second workshops. This report summarizes the analyses and model 'experiments' that were conducted as part of these workshops as well as the various methods for treating VRE among the four modeling teams. The report also reviews the findings and learnings from the two workshops. We emphasize the areas where there is still need for additional research and development on analysis tools to incorporate VRE into long-term planning and decision-making.},
doi = {10.2172/1411514},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri Nov 03 00:00:00 EDT 2017},
month = {Fri Nov 03 00:00:00 EDT 2017}
}

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