{"title":"Joint Planning of Distributed Generation, Electric Vehicle Charging Station, and Active Distribution Network Framework","authors":"Xue Li, Yanlong Song, Weilu Shan","doi":"10.1109/ISKE47853.2019.9170289","DOIUrl":null,"url":null,"abstract":"A bi-level joint planning model of distributed generation (DG), electric vehicle charging station (EVCS) and active distribution network (ADN) framework is proposed by considering demand side management (DSM). The upper ADN framework planning model is established by taking the lowest annual comprehensive cost as the upper level objective, which is solved by the improved partheno-genetic algorithm (IPGA). Based on the upper framework scheme, the lower DG and EVCS planning model is established to minimum the annual construction maintenance cost, and is solved by the biogeography-based optimization (BBO) algorithm. Simulation results confirm the effectiveness of the proposed joint planning method of DG, EVCS and ADN framework.","PeriodicalId":399084,"journal":{"name":"2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"586 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISKE47853.2019.9170289","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
A bi-level joint planning model of distributed generation (DG), electric vehicle charging station (EVCS) and active distribution network (ADN) framework is proposed by considering demand side management (DSM). The upper ADN framework planning model is established by taking the lowest annual comprehensive cost as the upper level objective, which is solved by the improved partheno-genetic algorithm (IPGA). Based on the upper framework scheme, the lower DG and EVCS planning model is established to minimum the annual construction maintenance cost, and is solved by the biogeography-based optimization (BBO) algorithm. Simulation results confirm the effectiveness of the proposed joint planning method of DG, EVCS and ADN framework.
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