Research on Two-Layer Optimization Demand Response Strategy for a PV-Storage-Charging Integrated Battery Swapping Station

PV -storage-charging integrated battery swapping stations (PSCIBSS) are an important direction for the future construction of battery swapping stations. However, the disorderly charging and discharging behavior of battery swapping stations can have negative impacts on the distribution network (DN), such as adding peaks to the load. To address this issue, we propose a demand response strategy that uses a two- layer optimization approach for the PSCIBSS. Firstly, we establish a model of the PSCIBSS that contains four sub-models: an EV swapping load model, a PV output model, an energy storage model, and a dynamic group management model for batteries in the station. Based on this model, we establish an outer model for dynamic time-of-use (TOU) pricing and an inner model for energy dispatch of the PSCIBSS. The outer model's goal is to reduce peak loads and fill in valleys, while the inner model's goal is to increase the PSCIBSS's revenue. The outer and inner models are solved iteratively using adaptive mutation particle swarm optimization and Gurobi Solver, respectively. Finally, we conduct simulations for a typical PSCIBSS. It is verified that the proposed method can smooth out fluctuations in the distribution network load and increase the revenue of the PSCIBSS.