An optimization framework for capacity allocation and energy management of fast electric vehicle charging stations‐wind photovoltaic energy using artificial transgender longicorn algorithm

Abstract

Summary This paper proposes the optimal design for fast electric vehicle charging stations for the capacity configuration of components and the power scheduling strategy. The proposed approach is the artificial transgender longicorn algorithm, which is a simple and powerful controller. The optimal capacity of the system components and the optimal power scheduling approach are determined. First, an electric vehicle charging simulation model is built considering the demand response, which dynamically modified the charging expectation based on the electricity price at the time of use. Second, based on the system design, a multi‐objective optimization model is proposed with minimal objectives for the electricity cost and polluting emissions. Finally, a scenario analysis is carried out and it is concluded that renewable energy supplies, connection to the utility grid and demand response may help improve the performance of the optimization objectives. By then, the performance of the proposed technique is implemented in the MATLAB platform and compared with several existing approaches.