{"title":"Optimal Allocation of SVC in Power Networks Considering Wind Energy Uncertainty","authors":"Numan Khan, R. Sirjani","doi":"10.1109/ICEEE52452.2021.9415951","DOIUrl":null,"url":null,"abstract":"Herein, we determine the optimal configuration (location and size) of a static Var compensator (SVC) considering the intermittent nature of wind power in the transmission system. A probabilistic load flow (PLF) integrated using a five-point estimation method was used to model the wind power uncertainties by discretizing wind power distribution into five discrete points. Consolidating the PLF using a multi-objective non-dominated sorting genetic algorithm (NSGA-II), the location and size of an SVC can be optimally allocated considering wind power uncertainties. This method aims to minimise system operation cost, power loss reduction, and voltage profile enhancement. To demonstrate the viability of the applied method, we validated it using the IEEE 30 bus system. Simulation outcomes demonstrate the viability of the applied method in minimizing different objective functions under the unpredictable nature of wind power.","PeriodicalId":429645,"journal":{"name":"2021 8th International Conference on Electrical and Electronics Engineering (ICEEE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 8th International Conference on Electrical and Electronics Engineering (ICEEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEEE52452.2021.9415951","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Herein, we determine the optimal configuration (location and size) of a static Var compensator (SVC) considering the intermittent nature of wind power in the transmission system. A probabilistic load flow (PLF) integrated using a five-point estimation method was used to model the wind power uncertainties by discretizing wind power distribution into five discrete points. Consolidating the PLF using a multi-objective non-dominated sorting genetic algorithm (NSGA-II), the location and size of an SVC can be optimally allocated considering wind power uncertainties. This method aims to minimise system operation cost, power loss reduction, and voltage profile enhancement. To demonstrate the viability of the applied method, we validated it using the IEEE 30 bus system. Simulation outcomes demonstrate the viability of the applied method in minimizing different objective functions under the unpredictable nature of wind power.