基于粒子群优化算法的电压暂降监测点优化配置

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摘要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。

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	周超
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关键词 ：电压暂降, 监测点, 解析式法, 可观测矩阵, 优化配置, 粒子群优化, 罚函数

Abstract：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.

Key words： Voltage sag monitoring node method of analytical expressions monitored reach matrix optimum allocation particle swarm optimization(PSO) penalty function

收稿日期: 2011-09-22 出版日期: 2014-06-27

PACS:

TM712

基金资助:山东省自然科学基金资助项目(ZR2012EEM026)

作者简介: 周超, 男, 1986年生, 硕士研究生, 主要从事电网电能质量分析与控制方面的研究; 田立军, 男, 1964年生, 教授, 硕士生导师, 主要从事电力系统运行与控制、电网电能质量分析与控制等方面的研究。(通讯作者)

引用本文:

周超, 田立军. 基于粒子群优化算法的电压暂降监测点优化配置[J]. 电工技术学报, 2014, 29(4): 181-187. Zhou Chao, Tian Lijun. An Optimum Allocation Method of Voltage Sag Monitoring Nodes Based on Particle Swarm Optimization Algorithm. Transactions of China Electrotechnical Society, 2014, 29(4): 181-187.

链接本文:

http://dgjsxb.ces-transaction.com/CN/Y2014/V29/I4/181

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