Location and Capacity Determination Method of Electric Vehicle Charging Station Based on Simulated Annealing Immune Particle Swarm Optimization

As the number of electric vehicles (EVs) continues to grow and demand for charging infrastructure is also increasing, how improve has become a bottleneck restricting development EVs. In other words, reasonably planning location capacity stations important EV industry safe stable operation power system. Considering construction maintenance station, distribution network loss economic on user side EV, this paper takes node station as control variables minimum cost system comprehensive objective function, thus proposes model station. Based problems low efficiency insufficient global optimization ability current algorithm, simulated annealing immune particle swarm algorithm (SA-IPSO) adopted in paper. The used update (PSO), mechanism introduced participate iterative particles, so speed PSO. Voronoi diagram divide service area joint solution process SA-IPSO proposed. By example analysis, results show that optimal corresponding optimisation method proposed overall cost, while average waiting time only 1.8 min pile utilisation rate 75.5%. simulation comparison verifies improved improves operational by 18.1% basically does not fall into local convergence.