Journal
ENERGY
Volume 238, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2021.122049
Keywords
Multisector dynamics; Power systems; Power system operational models; Review; Taxonomy
Categories
Funding
- U.S. Department of Energy, Office of Science, research in the MultiSector Dynamics, Earth and Environmental System Modeling Program
- U.S. Department of Energy [DE-AC05-76RL01830]
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This article discusses the opportunities for multisector adaptation and tradeoffs in power system operational models, focusing on four core processes and proposing model-agnostic research directions.
Power grid operations increasingly interact with environmental systems and human systems such as transportation, agriculture, the economy, and financial markets. Our objective is to discuss the modelling gaps and opportunities to advance the science for multisector adaptation and tradeoffs. We focus on power system operational models, which typically represent key physical and economic aspects of grid operations over days to a year and assume a fixed power grid infrastructure. Due to computational burden, models are typically customized to reflect regional resource opportunities, data availability, and applications of interest. We conceptualize power system operational models with four core processes: physical grid assets (generation, transmission, loads, and storage), model objectives and purpose, in-stitutions and decision agents, and performance metrics. We taxonomize the representations of these core processes based on a review of 23 existing models. Using science questions around grid and short term uncertainties, long term global change, and multisectoral technological innovation as examples, we report on tradeoffs in process fidelity and tractability that have been adopted by the research community to represent multisectoral interactions in power system operational models. Our recommendations for research directions are model-agnostic, focusing on core processes, their interactions with other human systems, and consider computational tradeoffs. (c) 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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