电测与仪表2017，Vol.54Issue(13)：110-114,119,6.
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
于擎 1李菁华 1赵前扶 1邢春阳1
作者信息
- 1. 东北电力大学 电气工程学院,吉林 吉林 132012
- 折叠
摘要
Abstract
In view of the problem of the capacity and location of the electric vehicle charging station, we establish the mathematical model from the actual situation, considering of the land price, construction cost, operation cost, traffic flow, service range and service ability, and the target of the model is to minimize annual comprehensive cost, and the constraints of the model are charging ability and distance.In this paper, based on the chaotic quantum particle swarm optimization algorithm of the adaptive weight adjustment, we plan the city district in the north.In the iteration process, based on the different adaptive values of particles, the algorithm will adjust inertia weight correspondingly to adjust the search ability of particle.The ergodicity of chaotic operator is used to make the algorithm have good convergence speed and accuracy.We adopt this algorithm to solve this established mathematical model in this paper.Thorough further screening, the coordinates, capacity and the cost of charging stations in the region are determined eventually.关键词
电动汽车/权重自适应调整的混沌量子粒子群算法/充电站/选址/定容Key words
electric vehicle/chaotic quantum particle swarm optimization algorithm of adaptive weight adjustment/charging station/site selection/determining capacity分类
信息技术与安全科学引用本文复制引用
于擎,李菁华,赵前扶,邢春阳..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):110-114,119,6.
