微网中电动汽车有序充放电的粒子群优化控制  

Control Strategy Based on Particle Swarm Optimization for Orderly Charging and Discharging of Electric Vehicle in Microgrids

作　　者：廖碧莲[1] 林秀清 宋绍剑[1] 程根 罗任志 王腾 LIAO Bi-lian;LIN Xiu-qing;SONG Shao-jian;CHENG Gen;LUO Ren-zhi;WANG Teng(School of Electrical Engineering,Guangxi University,Nanning 530004,China)

机构地区：[1]广西大学电气工程学院,广西南宁530004

出　　处：《电气开关》2018年第6期13-18,22,共7页Electric Switchgear

摘　　要：针对大规模电动汽车进行无序充电将会影响电网的稳定性问题,本文首先对影响电动汽车充电需求的有关因素进行深入分析,并通过蒙特卡洛的方法计算出大规模电动汽车的充电需求。其次,将电动汽车作为一种可移动的储能装置,以一天中不同时期的充放电功率为控制对象,以区域内24h总负荷需求与光伏发电出力之间差值最小化为目标函数,建立调度策略的数学模型并使用种群间相互学习的粒子群优化算法来获取最优日调度策略。最后,仿真结果验证了本文所提出算法的有效性。结果表明:IIL-PSO算法能够克服粒子群最优算法易陷入局部最优的不足,能够较快地收敛于最优解。通过对电动汽车的充放电过程进行优化控制,不但能改善光伏发电的消纳能力,还能降低微电网储能装置的容量需求及减少投资。Aimed at the problem that large-scale electric vehicles charging disorderly may influence the stability of the power grid,this paper firstly makes in-depth analysis of the relevant factors which affect the electric vehicles charging demand,and by using the Monte Carlo method to calculate the large-scale electric vehicles charging power requirement.Secondly,the electric vehicles as a kinds of removable storage equipment,and to take charge and discharge power in different periods of a certain day as the control object,to take the difference between the total load demand and PV output of the region in24hours being minimum as the objective function,set up a mathematical model of dispatching strategy and use the particle swarm optimization with interswarm interactive learning strategy to achieve the daily optimal dispatching strategy optimization.Finally,simulation's result verifies the effectiveness of the proposed algorithm.The result indicates that the IIL-PSO algorithm can overcome the deficiency of the particle swarm optimization which being easy to sink into local optimum and converge to the optimal solution in high-speed.Though the optimal control of the process of the electric vehicles'charging and discharging,not only can the absorptive capacity of the photovoltaic power generation be improved,but also the capacity demand of the microgrid energy storage device can be reduced and the investment can be decreased.

关 键 词：电动汽车 微电网 蒙特卡洛方法 分布式发电 基于种群间互相学习策略的粒子群优化算法(IIL-PSO) 

分 类 号：TM72[电气工程—电力系统及自动化]