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  • 标题:Spatial Load Prediction Considering Spatiotemporal Distribution of Electric Vehicle Charging Load
  • 本地全文:下载
  • 作者:Xiang Gao ; Lingyan Wei ; Bing Wang
  • 期刊名称:E3S Web of Conferences
  • 印刷版ISSN:2267-1242
  • 电子版ISSN:2267-1242
  • 出版年度:2021
  • 卷号:256
  • 页码:1-6
  • DOI:10.1051/e3sconf/202125601001
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:In view of the influence of large-scale electric vehicle access to the distribution network on spatial load prediction, this paper proposes a spatial load prediction method for urban distribution network considering the spatial and temporal distribution of electric vehicle charging load. Firstly, electric vehicles are classified according to charging mode and travel characteristics of various types of vehicles. Secondly, the probability distribution function is fitted to the travel rules of electric vehicles according to the travel survey and statistical data of residents. Then, the model of electric vehicle travel chain is constructed, and the charging load in different regions and different times is calculated by Monte Carlo method. Finally, based on the actual data of a certain area, the predicted spatial load values of different functional communities in one day are obtained, which can provide reference for future urban distribution network planning.
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