CAJ | 학술논문

综合分析了影响电动汽车充电站规划的若干因素，建立了电动汽车充电站规划的最大收益模型。根据电动汽车充电特性和出行特征，计算电动汽车充电功率需求期望值，从而得出规划区充电站的容量需求。根据电动汽车的分布特点，通过调节加权伏罗诺伊图的权重，使得服务区域划分更合理，同时保持各充电站负载率的均衡。利用粒子群优化算法的全局寻优能力，结合加权伏罗诺伊图，对充电站进行选址定容和服务区域划分的优化规划。算例分别针对不同电动汽车数量和不同分布方式的情况进行计算，结果验证了所述模型和方法的有效性和可行性。
종합분석료영향전동기차충전참규화적약간인소，건립료전동기차충전참규화적최대수익모형。근거전동기차충전특성화출행특정，계산전동기차충전공솔수구기망치，종이득출규화구충전참적용량수구。근거전동기차적분포특점，통과조절가권복라낙이도적권중，사득복무구역화분경합리，동시보지각충전참부재솔적균형。이용입자군우화산법적전국심우능력，결합가권복라낙이도，대충전참진행선지정용화복무구역화분적우화규화。산례분별침대불동전동기차수량화불동분포방식적정황진행계산，결과험증료소술모형화방법적유효성화가행성。
Abstract： This paper comprehensively analyzes several factors that influence the charging station planning for electric vehicles, and then an income optimization model of charging station planning for electric vehicles is developed. In order to meet the capacity requirement of charging station in the planning area, the electric vehicles＇ expected power demand is calculated based on the charging characteristics and trip characteristics of electric vehicles. The weights of Voronoi diagram are adjusted to make the service areas divided more rationally and the load rate better balanced based on the distribution characteristic of electric vehicles. Combining the weighted Voronoi diagram, the global searching ability of the particle swarm optimization algorithm is used to locate and size the charging stations and optimally plan the service areas. By calculating different numbers of electric vehicles and different ways of distribution, the results verify the effectiveness and feasibility of the proposed model and algorithm.