基于二进制粒子群的充电桩故障定位系统配置与定位方法

电动汽车充电桩网络作为泛在电力物联网的重要组成部分,其电能采集终端配置和故障定位问题已成为一项重要课题.文中提出了一种基于整数线性规划的充电桩网络电能采集终端优化配置模型和故障定位模型.所建立的配置模型以配置成本最低为目标函数,通过规划采集终端的接入位置保证系统各节点电压和各支路电流的可测性;故障定位模型能够针对系统故障时的扰动功率准确定位到故障发生支路.采用二进制粒子群算法对所建立的模型进行求解.仿真结果表明,所建立的模型能够在满足系统故障检测和定位的前提下提升经济性,二进制粒子群算法相比于基本粒子群算法,对所建立的模型求解性能更优.

Fault Location System Configuration and Location Method of Charging Pile Based on Binary Particle Swarm Optimization

As an important part of the ubiquitous power internet of things, the configuration and fault location of electric energy acquisition terminal for electric vehicle charging pile network has become an important issue. An optimal configuration model and fault location model based on integer linear programming for charging pile network electric energy acquisition terminal were proposed. The objective function of the configuration model was to minimize the cost of configuration. By planning the access location of the acquisition terminal, the measurability of each node voltage and branch current can be guaranteed. The fault location model can accurately locate the fault branch according to the disturbance power when the system is in fault. The model was solved by binary particle swarm optimization. The simulation results show that the proposed model can improve the economy on the premise of satisfying the system fault detection and location. Compared with the basic particle swarm optimization, the binary particle swarm optimization algorithm has better performance in solving the established model.