Electric Vehicle User Portrait Considering Market Response Potential

This paper proposes a method to build user portrait of electric vehicle (EV) considering market response potential. Firstly, the user portrait index system of EV is constructed from three dimensions of electricity response potential, temporal response potential and spatial response potential. Secondly, the residual capacity and time of use (TOU) price are selected as the characteristic parameters to identify the TOU price sensitive users, and the EVs that can respond to the market in time are obtained based on support vector machine (SVM). Then, the distance, time and electricity charge are selected as the characteristic parameters to identify the charging service fee sensitive users, and the EVs that can respond to the market in space are obtained based on the neural network. Finally, eight kinds of EV user portraits with different market response potentials are obtained by identifying the charging data, which verifies the effectiveness of the proposed method.