Meta-heuristics in microgrid management: A survey

dc.cclicenceCC BYen
dc.contributor.authorZheng, Zedong
dc.contributor.authorYang, Shengxiang
dc.contributor.authorGuo, Yinan
dc.contributor.authorJin, Xiaolong
dc.contributor.authorWang, Rui
dc.date.acceptance2023-01-24
dc.date.accessioned2023-03-09T16:16:52Z
dc.date.available2023-03-09T16:16:52Z
dc.date.issued2023-02-07
dc.descriptionopen access articleen
dc.description.abstractAs a small energy system, microgrid plays an important role in utilizing distributed energy resources, improving traditional energy networks, and building intelligent integrated energy systems. However, microgrid management is always a challenging optimization problem due to different factors. Meta-heuristics have been widely used to solve complex optimization problems in many fields, including energy systems. However, there is a lack of a systematic summary of the application of meta-heuristics in microgrid management. This paper aims to review the application of meta-heuristics in microgrid management, summarize the contributions and influences of different methods, and provide further insights and suggestions for future research.en
dc.funderOther external funder (please detail below)en
dc.funder.otherNational Natural Science Foundation of Chinaen
dc.funder.otherRoyal Society International Exchanges 2020 Cost Share (NSFC)en
dc.identifier.citationZ. Zheng, S. Yang, Y. Guo, X. Jin, and R. Wang. (2023) Meta-heuristics in microgrid management: A survey. Swarm and Evolutionary Computation, 78, 101256en
dc.identifier.doihttps://doi.org/10.1016/j.swevo.2023.101256
dc.identifier.urihttps://hdl.handle.net/2086/22592
dc.language.isoen_USen
dc.peerreviewedYesen
dc.projectid61973305en
dc.projectidIEC\NSFC\201085en
dc.publisherElsevieren
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en
dc.subjectMeta-heuristicsen
dc.subjectMicrogrid managementen
dc.subjectDeploymenten
dc.subjectOperationen
dc.subjectOptimization applicationen
dc.titleMeta-heuristics in microgrid management: A surveyen
dc.typeArticleen

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