电力系统自动化Issue(17)：176-182,7.DOI:10.7500/AEPS20150323009
基于 LCC 和量子遗传算法的电动汽车充电站优化规划
Optimal Planning of Electric Vehicle Charging Stations Based on Life Cycle Cost and Quantum Genetic Algorithm
摘要
Abstract
Optimal planning of electric vehicle charging stations is an important research area in the study of flexible interaction between electric vehicle and smart grid.The calculation method of cost-benefit and life cycle cost of electric vehicle charging stations is analyzed in the operation period of electric vehicle charging stations,based on which,a method of calculating charging station capacity using the data from the traffic flow is proposed,and an optimal objective of the operator gaining best net present value is proposed.With the traffic flow,the power quality and economy of grid and charging demand of customer as constraints,the location and capacity of charging stations can be determined.In addition,the optimal planning model of charging stations considering life cycle cost theory is proposed,with the quantum genetic algorithm used to solve the model. The simulation of the example has confirmed that the optimal planning model and solving method are effective.关键词
充电站/优化规划/电网/量子遗传算法/全寿命周期成本Key words
charging station/optimal planning/power grid/quantum genetic algorithm/life cycle cost引用本文复制引用
黄小庆,杨夯,陈颉,江磊,曹一家..基于 LCC 和量子遗传算法的电动汽车充电站优化规划[J].电力系统自动化,2015,(17):176-182,7.基金项目
国家科技支撑计划资助项目(2013BAA01B01) （2013BAA01B01）
国家自然科学基金资助项目(51137003,61104090)。This work is supported by National Key Technologies R&D Program(No.2013BAA01B01)and National Natural Science Foundation of China(No.51137003,No.61104090) （51137003,61104090）
