Collaborative optimization of electric-vehicle battery swapping stations based on energy storage sharing

Due to the extensive integration of distributed renewable energy resources, the Active Distribution Network (ADN) faces numerous challenges, including, for example, renewable energy curtailment and overloading. This paper proposes a collaborative optimization control method for electric-vehicle battery swapping stations that mitigates the mismatching between generation and load demand in the ADN. Energy storage sharing is considered in this study, that allows stations to exchange batteries via the traffic network, and this extends the capacity of Battery-Transferable Swapping Stations (BTSSs). First, the operational principles of the energy storage shared BTSS are carefully analyzed, including external and internal control mechanisms and energy storage sharing. Subsequently, a bi-level optimization model is proposed, whereby the upper level aims to minimize the total operational cost of the ADN and the lower level seeks to maximize the benefit of each BTSS. A two-stage transactive control is introduced to decompose the bi-level situation into two stages: the day-ahead stage and the real-time stage and this facilitates easier problem-solving. Finally, an IEEE 15-node system is utilized to verify the proposed method. The results indicate that the proposed method reduces the renewable energy curtailment, power shortages, and operational costs of the ADN, while at the same time increasing the earnings of BTSSs.