电力系统保护与控制Issue(2)：55-62,8.
基于改进自适应遗传算法的PMU优化配置
Optimal PMU configuration based on improved adaptive genetic algorithm
徐岩 1郅静1
作者信息
- 1. 新能源电力系统国家重点实验室 华北电力大学，河北 保定 071003
- 折叠
摘要
Abstract
For the purpose of using the least number of phasor measurement unit (PMU) to ensure the power system complete observability under the normal circumstances and with an N-1 fault of transmission line, an optimal PMU configuration method based on improved adaptive genetic algorithm (IAGA) is put forward. The configuration of PMU is divided into two stages. The first stage takes the minimum number of installed PMUs and the system observability under the normal circumstances as targets to configurate PMU. The second stage continues to install PMU in order to ensure the system observability with an N-1 fault of transmission line. The calculation formulas of crossover probability and mutation probability of IAGA are modified, which overcome the shortcoming of evolutionary stagnation when the largest fitness value and the average fitness value in the group are equal. Besides, it optimizes the evolutionary process and makes the mathematical calculations convenient. The preventing premature operation is employed on each individual to eliminate the premature convergence resulting from the chance and randomness of the crossover and mutation. The results show that this method has significant advantages in the installed PMU number, the diversity of solution, the astringency and the practicability. The correctness and superiority of the method are verified.关键词
电力系统/相量测量单元(PMU)/遗传算法/防早熟操作/N-1故障Key words
power system/phasor measurement unit (PMU)/genetic algorithm/preventing premature operation/N-1 fault分类
信息技术与安全科学引用本文复制引用
徐岩,郅静..基于改进自适应遗传算法的PMU优化配置[J].电力系统保护与控制,2015,(2):55-62,8.
