Optimal participation of battery swapping stations in frequency regulation market considering uncertainty

Electric vehicle battery swapping stations (BSS) have significant potential in power system frequency regulation. However, uncertainties of swapping demand and regulation signals introduce risks to operational benefits and regulation performances. Aming to enhance overall profitability, this study proposes day-ahead bidding and real-time scheduling strategies for BSS to participate in frequency regulation. In the day-ahead stage, the BSS scheduling model is established. Then, the information-gap decision theory (IGDT) is employed to determine the optimal reserve capacities. The randomness of regulation signals is captured by designing a new uncertainty set based on statistical analysis. Additionally, a boundary autonomous selection (BAS) method is developed to solve the IGDT model, making the selected scenarios more consistent with real-world situations. In the intra-day stage, a real-time response strategy is proposed to track the regulation signals considering the BSS operation economy. Simulations are conducted using historical data from Pennsylvania, Jersey, and Maryland (PJM). The results demonstrate that the reserve capacities and response ratios obtained by the proposed strategies yield higher profits for BSS while ensuring regulation performance.