基于系统不完全可观的PMU优化配置新算法

摘要

Considering of the limitation of PMU in power system,the method of optimal placement is proposed by taking quantum genetic algorithm under uncompleted observable system for the low data processing and bad astringency.The proposed algorithm is proved to be effective and flexible by tested with IEEE14-bus system and New England 39-bus system.The results of the state estimation show that the precision of the results are improved.It also has good astringency and convergence speed.%限于同步相量测量装置(PMU)在电力系统中应用的局限性以及经济性,分析考虑了基于PMU的系统完全可观条件下电力系统状态估计过分冗余导致数据处理速度慢,收敛性不好等缺点,提出了基于系统不完全可观条件下,采用量子遗传算法对PMU进行合理配置,以期在最少PMU配置的基础上,使系统拥有足够的量测冗余度,得到的状态估计结果具有尽可能高的精度.通过算例仿真研究表明,该算法克服了深度优先算法(DFS)收敛性不好以及模拟退火法(SA)收敛速度慢的缺点,具有很好的收敛性和收敛速度,同时具有很好的精度要求.