于擎,李菁华,赵前扶,邢春阳.（12期拿下）基于权重自适应调整的混沌量子粒子群算法的城市电动汽车充电站优化布局[J].电测与仪表,2017,54(13):. yuqing,lijinghua,zhaoqianfu,xingchunyang.Optimal Planning of Charging Station for Electric Vehicle Based on Quantum ACQPSO Algorithm[J].Electrical Measurement & Instrumentation,2017,54(13):.
（12期拿下）基于权重自适应调整的混沌量子粒子群算法的城市电动汽车充电站优化布局
Optimal Planning of Charging Station for Electric Vehicle Based on Quantum ACQPSO Algorithm
In view of the problem of the capacity and location of the electric vehicle charging station, we establish the mathematical model considered of the land price, construction cost, operation cost, traffic flow, service range and service ability, starting from the actual situation. The target of the model is to minimum annual comprehensive cost, and the constraints of the model are charging ability and distance. In this paper, based on adaptive weight adjusting the chaotic quantum particle swarm optimization algorithm, we plan the city district in the north. In the iteration process, basing on the different adaptive values of particles, the algorithm will adjust inertia weight correspondingly to adjust the search ability of particle. Using the ergodicity of chaotic operator makes the algorithm have good convergence speed and accuracy. We use this algorithm to solve this established mathematical model in this paper. Eventually, the coordinates and capacity of charging stations in the region are determined.
