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假设电动汽车的使用不改变用户的行驶习惯,采用随机概率事件表示不确定性充电行为,将电动汽车集群的充电行为用二项分布表示,单台电动汽车的充电行为通过随机数与二项分布参数比较确定,建立了规模化电动汽车充电负荷计算模型;并基于充电负荷的概率分布特性,建立了电网接纳电动汽车能力的优化计算模型,采用机会约束规划(Chance Constrained Programming,CCP)和粒子群优化算法(Particle Swarm Optimization,PSO)相结合的方法进行求解。以北京市汽车行驶特性和IEEE—30电网系统为例,分析了电网接纳电动汽车的能力,并通过对比计算验证了提出方法的准确性。
Assuming that the use of electric vehicles does not change the user’s driving habits, a random probability event is used to represent the uncertain charging behavior, the charging behavior of the electric vehicle cluster is expressed by a binomial distribution, and the charging behavior of a single electric vehicle is represented by a random number and a binomial distribution Based on the probability distribution of charging load, an optimal computing model of grid capacity for EVs was established. By using Chance Constrained Programming (CCP) and particle swarm optimization Particle Swarm Optimization (PSO) is used to solve the problem. Taking Beijing automobile driving characteristics and IEEE-30 grid system as an example, the capability of grid acceptance of electric vehicles is analyzed, and the accuracy of the proposed method is verified through comparative calculation.