The DOI matches its Crossref record; 113 of the 113 references it cites were found in a registry or an index.
Power systems optimization under uncertainty: A review of methods and applications
Open accessAbstract
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.
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Cites
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Optimization of conditional value-at-risk
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Monotone Operators and the Proximal Point Algorithm
Rockafellar, R. T. (1976) · SIAM Journal on Control and Optimization · doi:10.1137/0314056 · Cited by 3,559
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Solving two-stage robust optimization problems using a column-and-constraint generation method
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Metadata
- Authors
- Roald, L. A., Pozo, D., Papavasiliou, A., Molzahn, D. K., Kazempour, J., & Conejo, A.
- Venue
- Electric Power Systems Research
- Publisher
- Elsevier BV
- Published
- 2023-01
- Volume
- 214
- Pages
- 108725
- ISSN
- 0378-7796 (ISSN-L)
- OpenAlex
- W4298152141
- Cited by
- 317
- References
- 113
- FWCI
- 16.66
- Type
- journal article
- Language
- en
- Open access
- green
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- Roald, L. A., Pozo, D., Papavasiliou, A., Molzahn, D. K., Kazempour, J., & Conejo, A. (2023). Power systems optimization under uncertainty: A review of methods and applications. Electric Power Systems Research. https://doi.org/10.1016/j.epsr.2022.108725
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