Two-Layer Optimal Control Model with Compensation Mechanism of Charging Price for Large-Scale Electric Vehicles Participating in Deep Peak Regulation

With the rapid development of grid-connected renewable energy generation systems, the pressure and cost of deep peak regulation (DPR) in the power system have increased sharply. Electric vehicle (EV) is a special load with double characteristics of load and energy storage, which is growing most rapidly in power system in recent years. Therefore, in order to guide EVs to charge during DPR scenario and lower the pressure and cost of DPR in the power system, this paper provides a two-layer optimum control model with the compensation mechanism of the charging price for EVs to participate in DPR. The model aims to maximize the DPR interests of thermal power units for DPR (DPR-TPU) and EVs and minimize the shared cost of renewable power plants and regular thermal power units. Through cooperative or non-cooperative games, the EV dynamic charging price and compensation price for DPR, stepwise compensation price for DPR-TPU, and thermal power units output at different periods are optimized. Using 50,000 dispatchable EVs participating in DPR as an example, the proposed model is tested in a regional power grid. The results show that the optimal strategies can improve the technical and economic indicators of DPR-TPU while increasing the benefits of EVs.