基于二元粒子群算法的相量测量单元优化配置

S. Kumari, Pratima Walde, Asif Iqbal, A. Tyagi
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引用次数: 4

摘要

本文提出了一种以尽可能少的相量测量单元(pmu)数量实现完全电网可观测性的最佳相量测量单元(pmu)布置技术。由于pmu的安装成本高,有必要在最小的pmu下使系统完全可观测。在IEEE标准系统和Puducherry 17总线系统上实现了二粒子群优化方法(BPSO)。因此,PMU最优放置的BPSO方法可以应用于任何电力系统,使系统在电力系统的不同方面完全可观察。将得到的结果与其他方法进行比较,发现自适应遗传算法、GILP、SA、TS、BSA和所提出的BPSO方法效果更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal phasor measuring unit placement by binary particle swarm optimization
This work presents a technique for the optimal Phasor Measurement Units (PMUs) placement for complete power network observability with number of PMUs as minimum as possible. Due to the high installation cost of PMUs it is necessary to make the system fully observable with minimum PMUs. A binary particle swarm optimization method (BPSO) is implemented on IEEE standard system and Puducherry 17 bus system. The BPSO method of Optimum PMU Placement can therefore be applied to any power system to make the system fully observable with different aspects of the power system. The obtained results are compared with other techniques and it is found that Adaptive GA, GILP, SA, TS, BSA and the proposed BPSO method was found better.
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