摘要
随着能源和环境问题逐渐受到重视,电动汽车产业迎来了发展的契机。电动汽车的普及程度与充电设施的建设情况密切相关,而电动汽车充电站具有公共服务设施和用电设施两重属性,因此既需要考虑交通网络,也需要考虑电力系统对其规划的影响[1]。采用考虑最短路径和次短路径的截流选址模型描述交通网络流量因素,以最大化充电站截获的交通流量,最小化充电站投资成本和最小化节点电压偏移为目标,建立电动汽车充电站多目标规划模型,并采用非支配排序遗传算法-Ⅱ(NSGA-Ⅱ)对IEEE 33节点配电系统和25节点交通网络构成的算例进行求解。通过算例结果说明所提出的模型和求解方法的基本特征。
Three objective functions of the electric vehicle charging station placement optimal model are defined to maximize the cap- tured traffic flow, to minimize the investment cost and to minimize the average voltage deviation. The flow refueling location model is a- dopted to describe the traffic network considering the shortest and the second shortest paths. The non-dominated sorting genetic algo- rithm- II is used to solve the multi-objective model. With the example of the IEEE 33-node power distribution network and the 25-node traffic network, the basic characteristics of the presented model and solving method are illustrated.
出处
《东北电力技术》
2017年第5期35-39,共5页
Northeast Electric Power Technology
关键词
充电站模型
多目标优化算法
遗传算法
the flow refueling model
multi-objective optimization
genetic algorithm
