Optimal integration of long- and short-term operational planning decisions to design and manage electronic vehicle charge stations by CQOCRO technique

Abstract

This article proposes a hybrid method to design and manage the electronic vehicle payment station network in the event of power demand uncertainty. The proposed method is an integrated process with confusing virtual-anticipation and chemical reaction enhancement, hence named as chaotic quasi-oppositional chemical reaction optimization (CQOCRO) method. The key objective of the CQOCRO method is to develop a reliable model to assist in the design and management of an EVCS location, power supply line hazard and power demand entropy. The CQOCRO method creates a random nonlinear model of disruption that includes equivalent tactical outcomes and operational outcomes for designing and managing a stable EVCS network in the event of power demand uncertainty. Because of the extreme electricity flow, the power line is overheated which is handled by the proposed method. The proposed method addresses the possibility that excessive current flow-related line overheating could result in power line failure. The design of EVCS is based on the factors like type of power supply network, location and opening hours of charging stations, limited resources, potential for power supply line failure due to high load, and uncertainty of power demand. Accordingly, the performance of the CQOCRO method is done in MATLAB platform and the performance utilizes the existing techniques.