Optimal power flow of power systems with controllable wind-photovoltaic energy systems via differential evolutionary particle swarm optimization

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dc.authoridDuman, Serhat/0000-0002-1091-125X
dc.authoridwu, lei/0000-0002-0722-5769
dc.authorwosidDuman, Serhat/O-9406-2014
dc.authorwosidRivera, Sergio/AAJ-3765-2020
dc.contributor.authorDuman, Serhat
dc.contributor.authorRivera, Sergio
dc.contributor.authorLi, Jie
dc.contributor.authorWu, Lei
dc.date.accessioned2021-12-01T18:50:24Z
dc.date.available2021-12-01T18:50:24Z
dc.date.issued2020
dc.department[Belirlenecek]en_US
dc.description.abstractThe produced energy from varied sources in modern power systems is to be optimally planned for planning and operating of power system under the determined limit conditions. Recently, the rising overall people population of the world, the increasing of people requirements, improvements of technology, and ecosystem and global climate changes have caused with the increasing of electric energy demand. One of the most important solution methods to meet this energy demand is considered as utilization of renewable energy sources (RESs) in power systems. The structure of power systems has become with the usage of RESs more complex. The optimal power flow (OPF) from planning and operation problems has converted to difficult problem with RESs integrated into modern power systems. This paper presents the OPF problem of power systems with a high penetration of controllable renewable sources. These kinds of sources are able to inject a determined power since they have a back-up unit (storage). Uncertain solar irradiance and wind speed are simulated via log-normal and Rayleigh probability distributions, respectively. The proposed OPF problem with controllable renewable sources is solved by the differential evolutionary particle swarm optimization (DEEPSO) algorithm. Simulations conducted on various test systems illustrate the effectiveness and efficiency of DEEPSO as compared with other algorithms including moth swarm algorithm, backtracking search algorithm, and differential search algorithm. In addition, the Wilcoxon signed-rank test is applied to show the supremacy, effectiveness, and robustness of DEEPSO algorithm.en_US
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK)Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [BIDEB 2219, 1059B191700888]en_US
dc.description.sponsorshipDr Serhat Duman would like to thank the support provided by Scientific and Technological Research Council of Turkey (TUBITAK) BIDEB 2219 Postdoctoral Research Program under application number 1059B191700888.en_US
dc.identifier.doi10.1002/2050-7038.12270
dc.identifier.issn2050-7038
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85077053044en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org/10.1002/2050-7038.12270
dc.identifier.urihttps://hdl.handle.net/20.500.12684/10872
dc.identifier.volume30en_US
dc.identifier.wosWOS:000502478400001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherWileyen_US
dc.relation.ispartofInternational Transactions On Electrical Energy Systemsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectoptimal power flowen_US
dc.subjectoptimizationen_US
dc.subjectpower system planningen_US
dc.subjectsolar energyen_US
dc.subjectwind energyen_US
dc.subjectIncorporating Stochastic Winden_US
dc.subjectThermal Poweren_US
dc.subjectAlgorithmen_US
dc.subjectSolaren_US
dc.subjectDispatchen_US
dc.subjectVoltageen_US
dc.subjectMicrogridsen_US
dc.subjectOperationsen_US
dc.subjectEmissionen_US
dc.subjectCosten_US
dc.titleOptimal power flow of power systems with controllable wind-photovoltaic energy systems via differential evolutionary particle swarm optimizationen_US
dc.typeArticleen_US

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