Configuration and operation combined optimization for EV battery swapping station considering PV consumption bundling

Abstract Integration of electric vehicles (EVs), demand response and renewable energy will bring multiple opportunities for low carbon power system. A promising integration will be EV battery swapping station (BSS) bundled with PV (photovoltaic) power. Optimizing the configuration and operation of BSS is the key problem to maximize benefit of this integration. The main objective of this paper is to solve infrastructure configuration of BSS. The principle challenge of such an objective is to enhance the swapping ability and save corresponding investment and operation cost under uncertainties of PV generation and swapping demand. Consequently this paper mainly concentrates on combining operation optimization with optimal investment strategies for BSS considering multi-scenarios PV power generation and swapping demand. A stochastic programming model is developed by using state flow method to express different states of batteries and its objective is to maximize the station’s net profit. The model is formulated as a mixed-integer linear program to guarantee the efficiency and stability of the optimization. Case studies validate the effectiveness of the proposed approach and demonstrate that ignoring the uncertainties of PV generation and swapping demand may lead to an inappropriate batteries, chargers and swapping robots configuration for BSS