Variable Renewable Energy in Long-Term Planning Models [electronic resource] : A Multi-Model Perspective
- Washington, D.C. : United States. Dept. of Energy. Office of Energy Efficiency and Renewable Energy, 2017. and Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy
- Physical Description:
- 43 pages : digital, PDF file
- Additional Creators:
- National Energy Technology Laboratory (U.S.), United States. Department of Energy. Office of Energy Efficiency and Renewable Energy, and United States. Department of Energy. Office of Scientific and Technical Information
- Restrictions on Access:
- Free-to-read Unrestricted online access
- 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. This report summarizes the analyses and model experiments that were conducted as part of two workshops on modeling VRE for national-scale capacity expansion models. It discusses the various methods for treating VRE among four modeling teams from the Electric Power Research Institute (EPRI), the U.S. Energy Information Administration (EIA), the U.S. Environmental Protection Agency (EPA), and the National Renewable Energy Laboratory (NREL). The report reviews the findings from the two workshops and emphasizes 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. This research is intended to inform the energy modeling community on the modeling of variable renewable resources, and is not intended to advocate for or against any particular energy technologies, resources, or policies.
- Published through SciTech Connect., 11/01/2017., "nrel/tp--6a20-70528", "7829", and Wesley Cole; Bethany Frew; Trieu Mai; Yinong Sun; John Bistline; Geoffrey Blanford; David Young; Cara Marcy; Chris Namovicz; Risa Edelman; Bill Meroney; Ryan Sims; Jeb Stenhouse; Paul Donohoo-Vallett.
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