Power systems optimization under uncertainty: a review of methods and applications

Line A. Roald, David Pozo, Anthony Papavasiliou, Daniel K. Molzahn, Jalal Kazempour and Antonio Conejo
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Anthony Papavasiliou: Université catholique de Louvain, LIDAM/CORE, Belgium

No 3257, LIDAM Reprints CORE from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)

Abstract: Electric power systems and the companies and customers that interact with them are experiencing increasing levels of uncertainty due to factors such as renewable energy generation, market liberalization, and climate change. This raises the important question of how to make optimal decisions under uncertainty. This paper aims to provide an overview of existing methods for modeling and optimization of problems affected by uncertainty, targeted at researchers with a familiarity with power systems and optimization. We also review some important applications of optimization under uncertainty in power systems and provide an outlook to future directions of research.

Keywords: Stochastic optimization; Robust optimization; Chance-constrained optimization; Electric power systems (search for similar items in EconPapers)
Pages: 25
Date: 2023-01-01
Note: In: Electric Power Systems Research, 2023, vol. 214, part A, 108725
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:cor:louvrp:3257

DOI: 10.1016/j.epsr.2022.108725

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