摘要
为了合理确定电动汽车充电站的规模和布局,引入了电动汽车投资周期费用和用户便利性指标的概念,在此基础上,以投资商和用户费用最小为目标,确定充电站的规模和布局。该目标函数以高峰期的交通状况模拟电动汽车,以线路传输功率、无功补偿上下限、站内电池数量和服务半径为约束条件,以初期建设投资、网损费用和新建线路投资作为投资周期费用,以用户到电池充电站的行驶耗电费用衡量用户便利性,综合考虑了投资商成本、用户成本和电网运行限制。应用混沌粒子群算法优化充电站布局,利用混沌对初值的敏感性和混沌遍历性初始化种群;再通过逻辑自映射函数形成混沌序列和优化变量取值范围的对应关系。用某小区作为算例,通过与粒子群算法的对比,证明了该算法的有效性。
In order to rationally determine the scale and layout of charging station for electric vehicle, the index of investment cycle cost （ICC） and user convenience of electric vehicles are presented. On this basis, taking the minimum cost of investors and user as target, the scale and layout of charging station was determined. The electric vehicle in rush hour traffic was simulated by the objective function; taking the power of transmission line, the upper and lower limit of reactive power compensation, as well as the battery number and service radius of charging station as constraints, the initial construction investment, network loss and the investment of new transmission line as ICC, the user convenience was measured according to the electrical power consumption expense from user to charging station, and the cost of investor and user cost was comprehensively considered, as well as the operating limits of power grid. The layout of charging station was optimized with using Chaos Particle Swarm Optimization algorithm, and the sensitivity to initial value and ergodicity of chaos were used to initialize the population; then, the chaotic sequence was formed and the corresponding relationship of variable range was optimized through logical mapping function. Taking a district as an example, the effectiveness of the algorithm was demonstrated, compared with Particle Swarm Optimization.
出处
《电力建设》
2014年第4期132-136,共5页
Electric Power Construction
关键词
电动汽车
充电站
混沌粒子群算法
周期投资费用
用户便利性指标
electric vehicle
charging station
Chaos Particle Swarm Optimization
investment cycle costs
userconvenience index
