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电动出租车充电基础设施的科学布局与建设对于电动出租车的推广具有重要的意义。考虑到对于以收益最大为目的的电动出租车驾驶员而言,时间价值具有重要的意义,以充电站建设及运行维护年费用、出租车前往充电站耗时年成本、充电等待时间年成本及配电网网络损耗年费用构建全社会年总成本目标函数,以配电网安全运行为充电站布局规划的约束条件建立模型。在量子遗传算法中引入自适应调整策略,并与Voronoi图法相结合对模型进行求解,基于Voronoi图划分的充电站服务范围,采用排队论的M/G/c对充电站容量进行优化配置,从而实现电动出租车充电站的选址定容。最后,以36节点的路网和33节点的配电网络为例说明了模型和方法的有效性和实用性。
Electric taxi charging infrastructure and the scientific layout of the promotion of electric taxi is of great significance. Taking into account that for the purpose of maximizing revenue for the purpose of electric taxi drivers, the time value of great significance, with the charging station construction and operation and maintenance costs, the taxi to the charging station time-consuming cost, charging the annual cost of waiting time and Annual cost of distribution network loss Construct the objective function of annual total cost of the whole society and set up the model for the constraint of distribution station layout planning with the safe operation of distribution network. In the quantum genetic algorithm, an adaptive adjustment strategy is introduced and the model is solved by combining with the Voronoi diagram. Based on the service range of the Voronoi diagram divided charging station, queuing M / G / c is used to optimize the configuration of the charging station capacity Achieve electric taxi charging station siting. Finally, the effectiveness and practicability of the model and the method are illustrated by taking the 36-node road network and the 33-node power distribution network as an example.