Open AccessLocation planning of electric vehicle charging station based on HPSO-TS
Author(s) -
Lei Liu,
Pei Liang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1650/2/022097
Subject(s) - particle swarm optimization , tabu search , mathematical optimization , range (aeronautics) , premature convergence , electric vehicle , convergence (economics) , charging station , computer science , metaheuristic , multi swarm optimization , vehicle routing problem , algorithm , engineering , mathematics , routing (electronic design automation) , computer network , economic growth , economics , aerospace engineering , power (physics) , physics , quantum mechanics
Aiming at the optimization problem of electric vehicle (EV) charging station layout, an optimization model is constructed which takes the cost of all charging stations within the planning range as the objective function. Combining particle swarm optimization (PSO) and tabu search algorithm (TS), a hybrid algorithm of particle swarm optimization and tabu search (HPSO-TS) was proposed to solve the problem of EV charging station location. This algorithm increases the particle diversity by mutating the individual extremum, and uses TS in the later iteration to improve the late search ability of PSO and overcome premature convergence. Simulation results show that when solving the layout optimization problem of EV charging stations with service requirements and user demand constraints, HPSO-TS is superior to the computational results of PSO and mutation particle swarm optimization (MPSO). Compared with the basic algorithm, the improved algorithm has better efficiency and convergence, which proves the effectiveness and feasibility of the improved algorithm.