Locating and sizing method of electric vehicle charging station based on Improved Whale Optimization Algorithm

Abstract

An Improved Whale Optimization Algorithm (IWOA) is proposed to solve the problem of poor accuracy and stability in optimizing the locating and sizing of nonconvex and nonlinear electric vehicle (EV) charging stations (CSs). The variability index of convergence factor, the differential evolution operator, and the antibody affinity are introduced in the algorithm framework. Twelve classical test functions show that IWOA significantly improves the algorithm accuracy and convergence speed compared to WOA. Finally. The Voronoi diagram based on Floyd’s shortest path is adopted to decide the service area of charging stations. With the goal of delivering cost optimization, IWOA is applied to a 45-node transportation network for case study analysis, and the results show that both the proposed model and algorithm can be effectively applied to the locating and sizing and help reduce the cost for the whole society.

Keywords

• Whale Optimization Algorithm
• Electric vehicle
• Locating and sizing
• Differential Evolution
• Artificial immune algorithm
• Convergence factor