Planning of Electric Vehicle Charging Facilities on Highways Based on Chaos Cat Swarm Simulated Annealing Algorithm

Abstract

Aiming at the layout planning of electric vehicle (EV) charging facilities on highways, this study builds a multi-objective optimization model with the minimum construction cost of charging facilities, minimum access cost to the grid, minimum operation and maintenance cost, and maximum carbon emission reduction benefit by combining the state of charge (SOC) variation characteristics and charging demand characteristics of EVs. A chaos cat swarm simulated annealing (CCSSA) algorithm is proposed. In this algorithm, chaotic logistic mapping is introduced into the cat swarm optimization (CSO) algorithm to satisfy the planning demand of EV charging facilities. The location information of the cat swarm is changed during iteration, the search mode and tracking mode are improved accordingly. The simulated annealing method is adopted for global optimization search to balance the whole swarm in terms of local and global search ability, thus obtaining the optimal distribution strategy of charging facilities. The case of the Xi’an highway network in Shanxi Province, China, shows that the optimization model considering carbon emission reduction benefits can minimize the comprehensive cost and balance economic and environmental benefits. The facility spacing of the obtained layout scheme can meet the daily charging demand of the target road network area.