基于PSO的电动汽车规模化充电接入配电网柔性负荷多目标优化控制

Multi-Objective Optimization Control of Flexible Loads for Large-Scale Charging of Electric Vehicles Connected to Distribution Networks Based on PSO

为了降低电动汽车大规模接入配电网后产生的负荷波动和网损,提出了基于粒子群优化(PSO)算法的电动汽车规模化充电接入配电网柔性负荷多目标优化控制方法。首先,建立交通网-配电网耦合模型,并结合出行链模型分析用户的充电需求,搭建接入电动汽车能量状态预测模型;其次,以最小化配电网负荷波动标准差和网损作为优化目标,设计电动汽车规模化充电接入配电网柔性负荷多目标优化函数,同时引入分布熵设计惯性权重更新策略,优化PSO算法;最后,采用改进的PSO算法在函数约束条件的基础上实现配电网的柔性负荷控制。测试结果表明,所提出的方法可准确分析用户的充电需求,降低配电网负荷波动峰值及网损。

In order to reduce load fluctuations and network losses caused by large-scale electric vehicles connected to the distribution network,this paper proposed a multi-objective optimization control method based on Particle Swarm Optimization(PSO)algorithm for flexible loads of large-scale electric vehicle charging connected to the distribution network.Firstly,a coupling model between transportation network and distribution network was established,and combine it with the travel chain model to analyze users’charging needs,and a prediction model for the energy state of connected electric vehicles was established;Secondly,the minimized standard deviation of load fluctuations and network losses in the distribution network was taken as the optimization objective,and a multi-objective optimization function was established for the flexible load integration of large-scale charging of electric vehicles into the distribution network,meanwhile distribution entropy was introduced to design inertia weight update strategy and optimize PSO algorithm.Finally,the improved PSO algorithm was used to achieve flexible load control of the distribution network based on functional constraints.The test results show that the proposed method can accurately analyze the charging needs of users,and reduce the peak load fluctuation and network loss of the controlled distribution network.