Energy management between electric vehicle charging stations and electric distribution system considering quality of service using IACSO‐MPA approach

Abstract

In this manuscript, an energy management system (EMS) is proposed for the performance of Electric Vehicle Charging Station (EVCS) and Electric Distribution System (DS) using a hybrid approach. The proposed hybrid approach is the combined execution of Improved Artificial Cell swarm optimization (ACSO) and Marine Predators Algorithm (MPA) called IACSO-MPA approach. The searching behaviour of ACSO is enhanced through crossover and mutation operator; hence it is named as IACSO. Here, the updating behaviour of the IACSO is enhanced by MPA. The major purpose of this work is to maximize the ability of DS for assigning charging plans to EVCS and minimizing the purchase cost. Based on this objective the proposed IACSO-MPA technique is established for analysing the energy management interactive process in EVCS and DS and also for locating equilibrium solution. The proposed system is activated in MATLAB/Simulink site, then the efficiency is compared to various existing techniques, viz Crow search optimization (CSO), BAT algorithm, Particle swarm optimization. Moreover, the performance evaluation of EVCS and distribution system (DS) is assessed using the proposed existing technique. The proposed technique achieves for the EVCS 1 is 621.73. EVCS 2 is 3576.90, EVCS 3 is 4441.72, and DS is 4391.26. The experimental results show that the integrated energy system (IES) costs can be decreased using 3.89% and gains linked by EVCS can be maximized at least 7.8%. Furthermore, the proposed algorithm can locate the optimal global solutions effectively with accurately over the existing techniques.