Spatial and temporal electric vehicle demand forecasting in central London

摘要: If electricity infrastructures are to make the most of electric vehicle (EV) technology it is paramount understand how mobility can enhance management assets and delivery energy. This research builds on a proof concept model that focuses simulating EV movements in urban environments which serve forecast loads networks. Having performed this analysis for test environment, paper details case study London using an activity-based predictions be validated against measured transport data. Results illustrate optimal charging impact load profiles two areas central - St. John's Wood & Marylebone/Mayfair. Transport data highlights flexibility fleet EVs have daily basis one stressed networks world, while power flow manages best times day charge EVs. presents valuable information help begin addressing pressing infrastructure issues such as point planning network control reinforcement. (4 pages)