Prediction of temporal and spatial distribution of electric vehicle charging load considering coupling factors

Abstract

One of the components to realize the mutual benefit and win-win between electric vehicle (EV) and power grid is to effectively predict the charging load of EVs while the difficulty of charging load prediction is increased because of the randomness of temporal and spatial transfer of EV and a variety of coupling factors in the transfer process. In this paper,a method for predicting the spatial and temporal distribution of EV charging load considering dynamic transfer planning and coupling factors is proposed. Firstly,an individual travel mathematical model with multiple types of EVs is established based on travel chain technology. On this basis,considering the traffic flux,road conditions and temperature,the mathematical model of energy consumption per mileage of EV is constructed. Secondly,based on Markov decision process theory,considering the residual path and road network congestion information,the road network information is dynamically updated and the temporal and spatial transfer path of EVs is randomly planned. Finally,based on an example,the temporal and spatial distribution of EV and its charging load are compared and analyzed under different strategies,functional areas and travel days. The results show that the proposed method can fully reflect the travel decision of EV owners,and the prediction results can truly reflect the differences in the amplitude and distribution of charging load due to EV types and functional areas.

Keywords

• electric vehicle (ev)
• markov decision process theory
• travel chain
• energy consumption model
• charging load
• temporal and spatial distribution