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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
