基于粒子群优化算法的电压暂降监测点优化配置

An Optimum Allocation Method of Voltage Sag Monitoring Nodes Based on Particle Swarm Optimization Algorithm

为实现全网电压暂降故障点的可监测性,提出一种应用粒子群优化(PSO)算法对全网电压暂降监测点进行优化配置的方法。首先利用解析式法原理,通过线路临界故障点确定可观测区域,构建出各种短路故障情况下系统的电压暂降可观测矩阵,然后以监测点数目最少为目标函数,以全网各节点电压满足完全可观测为约束条件,建立电压暂降监测点优化配置的0-1线性规划模型。结合罚函数思想应用PSO算法进行优化求解,并综合考虑配置节点的优先级最终确定最优配置方案。通过对IEEE 39节点标准测试系统的仿真计算证明了该方法的有效性。

In order to capture all the fault positions of voltage sag in the whole system,this paper presents an approach based on particle swarm optimization(PSO) algorithm for optimal allocation of voltage sag monitoring nodes. Firstly,using the solution of analytical expressions,the monitor reach area(MRA) is defined by setting up the critical fault locations. Then the monitored reach matrix is built, which are valid for any location of faults in the power system. A 0-1 linear programming model is proposed to solve the problem of optimum allocation. The object function of the optimum problem is to minimize the number of the monitoring buses. And the key constraint is to guarantee the observability of the whole system considering any balanced or unbalanced faults. Utilizing the idea of penalty function, the PSO algorithm is applied to solve the optimum problem. The best optimal location of monitoring nodes are finally obtained by comparing the sensitive of buses. The effectiveness of proposed algorithm is verified by the case study based on IEEE-39 standard test system.