基于动态分时电价的电动汽车有序充放电研究  

A dynamic time-of-use price based order for charging and discharging of electric vehicles

作　　者：李伟生[1] 张继龙[2] 漆建平 

机构地区：[1]山东省科学院自动化研究所,济南250014 [2]兰州理工大学电气工程与信息工程学院,兰州730050 [3]太原理工大学机械工程学院,太原030024

出　　处：《工业仪表与自动化装置》2017年第4期46-49,共4页Industrial Instrumentation & Automation

摘　　要：大规模电动汽车随机无序充电将对电网安全运行带来巨大挑战,诸如增大负荷峰谷差、加大运营成本、增加谐波污染等。该文在考虑电动汽车充放电功率约束、电池容量约束的前提下,基于动态分时电价制度,建立电动汽车多目标优化调度模型,以降低电网负荷峰谷差率和用户充电成本,并采用改进学习因子与惯性权重的粒子群优化算法对模型进行求解。仿真结果表明,基于动态分时电价的调度策略比固定电价下优化效果更优,能够更好地减小系统负荷峰谷差率,提高负荷率,增加电力设备的利用率,降低电动汽车充电成本。The out-of-order charging of electric vehicles will bring great challenges to the safe operation of power grid,such as increasing the load of the peak-valley ratio,the operating costs,the harmonic pollution etc.In this paper,considering the constraints of the charging/discharging power and the electricity quantity stored in the battery of electric vehicles,based on dynamic time-of-use price system,establishing a multi-objective optimization scheduling model for electric vehicles,in order to reduce peak -valley ratio of grid load and valley load and charge cost of user.The model is solved by modifying particle swarm optimization algorithm based on learning factor and inertia weight.Simulation results show that the scheduling strategy based on dynamic time-of-use price is better than the fixed price,and it can reduce the system load peak-valley ratio better,increasing the load rate and the utilization of power equipment,reducing the charge cost of electric vehicles.

关 键 词：电动汽车 动态分时电价 粒子群优化算法 用户充电成本 峰谷差率 

分 类 号：TM73[电气工程—电力系统及自动化]