Yi Zhang, Bin Chen, Yue Xiang, Wei Yang, Junyong Liu, You-bo Liu
{"title":"长期充电需求建模与分析","authors":"Yi Zhang, Bin Chen, Yue Xiang, Wei Yang, Junyong Liu, You-bo Liu","doi":"10.1109/EPEC.2017.8286142","DOIUrl":null,"url":null,"abstract":"Long-term charging demand modeling of the plug-in electric vehicles (PEVs) is essential for various sectors involved to promote the proliferation of PEVs and friendly integrate large population of PEVs into power systems. Considering the market penetration development of PEVs will drive the evolution of charging demand, a long-term PEVs charging demand model based on agent-based technology is proposed in this paper, which modeling individual heterogeneous consumers displaying different preferences when making vehicle purchase decisions and charging behaviors as intelligent agents, and the interactions among consumers due to social dynamics are also taken into consideration. Case studies demonstrate the feasibility and effectiveness of the proposed methodology. Furthermore, the factors that affect the market evolution of PEVs and different charging strategies are also analyzed.","PeriodicalId":141250,"journal":{"name":"2017 IEEE Electrical Power and Energy Conference (EPEC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Long-term charging demand modeling and analysis\",\"authors\":\"Yi Zhang, Bin Chen, Yue Xiang, Wei Yang, Junyong Liu, You-bo Liu\",\"doi\":\"10.1109/EPEC.2017.8286142\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Long-term charging demand modeling of the plug-in electric vehicles (PEVs) is essential for various sectors involved to promote the proliferation of PEVs and friendly integrate large population of PEVs into power systems. Considering the market penetration development of PEVs will drive the evolution of charging demand, a long-term PEVs charging demand model based on agent-based technology is proposed in this paper, which modeling individual heterogeneous consumers displaying different preferences when making vehicle purchase decisions and charging behaviors as intelligent agents, and the interactions among consumers due to social dynamics are also taken into consideration. Case studies demonstrate the feasibility and effectiveness of the proposed methodology. Furthermore, the factors that affect the market evolution of PEVs and different charging strategies are also analyzed.\",\"PeriodicalId\":141250,\"journal\":{\"name\":\"2017 IEEE Electrical Power and Energy Conference (EPEC)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE Electrical Power and Energy Conference (EPEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EPEC.2017.8286142\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Electrical Power and Energy Conference (EPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EPEC.2017.8286142","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Long-term charging demand modeling of the plug-in electric vehicles (PEVs) is essential for various sectors involved to promote the proliferation of PEVs and friendly integrate large population of PEVs into power systems. Considering the market penetration development of PEVs will drive the evolution of charging demand, a long-term PEVs charging demand model based on agent-based technology is proposed in this paper, which modeling individual heterogeneous consumers displaying different preferences when making vehicle purchase decisions and charging behaviors as intelligent agents, and the interactions among consumers due to social dynamics are also taken into consideration. Case studies demonstrate the feasibility and effectiveness of the proposed methodology. Furthermore, the factors that affect the market evolution of PEVs and different charging strategies are also analyzed.