Joint planning of electric vehicle battery swapping stations and distribution grid with centralized charging

This paper presents a framework for optimal planning of battery swapping stations (BSS) in centralized charging mode. In this mode, the batteries are charged at a central charging station (CCS). Then they will be distributed among BSSs. Moreover, there is no charging equipment at BSSs, and depleted batteries are returned to the CCS to recharge. In this context, firstly, a probabilistic model is developed to estimate the power consumption profile of the CCS. Then, a planning framework comprised of linear and nonlinear parts is introduced to minimize the total investment and operation costs. In the linear part, a binary integer linear programing (BILP) model is proposed to determine the optimal place and grade of BSSs, considering the investment cost of BSSs as well as the batteries transportation costs. In the nonlinear part, which is solved by genetic algorithm (GA), a model is developed to find out which branches of the distribution network need to be reinforced to minimize the network reinforcement and energy loss costs. The developed models are implemented on the IEEE 69-bus network, and the results are examined under different scenarios. The obtained results verify the efficiency of the developed models.

Automated summary

This paper presents a framework for optimal planning of battery swapping stations (BSS) in centralized charging mode. In this mode, the batteries are charged at a central charging station (CCS). Then they will be distributed among BSSs. Moreover, there is no charging equipment at BSSs, and depleted batteries are returned to the CCS to recharge. Firstly, a probabilistic model is developed to estimate the power consumption profile of the CCS. Then, a planning framework comprised of linear and nonlinear parts is introduced to minimize the total investment and operation costs.