Intelligent Regulation on Demand Response for Electric Vehicle Charging: A Dynamic Game Method

It has become an urgent problem to be solved that how to make electric vehicle (EV) give full play to shift the power grid peak load through the regulation of demand response (DR). Game theory is often used to provide a new solution for the optimal decision-making among multi-stakeholders. As a dynamic game, differential game can describe the dynamic changes of time-sharing electricity price (TOU price) about power grid and charging power about EV in real time. Considering the problem of “peak on top of peak” caused by a large number of electric vehicles' disordered charging, this paper makes the dispatching strategy of EVs entering the grid based on the TOU price, and establishes a dynamic differential game model for the power grid and EV decision makers. The model is solved by taking the TOU price of power grid and the charging power of EV as the strategy, and smoothing the peak valley difference of power grid and minimizes the charging cost of EV as the goal. In the end, DR for optimizing power grid load and reducing user's low cost is adopted to simulate the proposed model. The simulation results show that the peak-valley difference rate of the optimized power grid is reduced by 6.93%, and the cost of EV users is reduced by 71.52%. The simulation results verify the peak load regulation effect and the economic benefit of the differential game model on the power grid side.