Heterogeneous Aggregation and Control Modeling for Electric Vehicles With Random Charging Behaviors
Xin Wu, Lijuan Yao, Yawen Yu, Xinyu Jiang, Ruofan Wu, Gangjun Gong
Abstract
Electric vehicles (EVs) with both power consumption and energy storage are important load resources involved in the adjustment of supply and demand. The aggregation and control of a large number of EVs is a way to make the energy structure upgrade. This paper plans to explore the cluster response mechanism, group effect and coordination ability of distributed EVs in the regional power grid on the basis of solving the following problems. Firstly, the EV cluster presents heterogeneous characteristics due to differences of physical parameters. Secondly, EVs participating in the aggregation dynamically change in real time because of the stochastic charging behaviors. In this paper, a heterogeneous aggregation model for EVs with random charging behaviors is proposed based on the changing relation of charging power to remaining electric quantity. And a variable sliding mode control model is constructed to address the randomness of the charging process and realize stable responses in a short-time scale. Besides, the battery module and the user strategy are proposed to coordinate with the heterogeneous cluster to improve the adjustment capacity and flexibility. Finally, A clean energy output tracking simulation is provided to verify the effectiveness of the heterogeneous aggregation and control model.