E3S Web of Conferences (Jan 2021)

Spatial Load Prediction Considering Spatiotemporal Distribution of Electric Vehicle Charging Load

  • Gao Xiang,
  • Wei Lingyan,
  • Wang Bing,
  • Chen Guiru,
  • Wu Xiaoyue

DOI
https://doi.org/10.1051/e3sconf/202125601001
Journal volume & issue
Vol. 256
p. 01001

Abstract

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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.