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Optimal Placement of Phasor Measurement Units Using Immunity Genetic Algorithm

机译：基于免疫遗传算法的相量测量单元优化配置

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摘要

This paper investigates the application of immunity genetic algorithm (IGA) for the problem of optimal placement of phasor measurement units (PMUs) in an electric power network. The problem is to determine the placement sites of the minimal set of PMUs which makes the system observable. Incorporating immune operator in the canonical genetic algorithm (GA), on the condition of preserving GA's advantages, utilizes some characteristics and knowledge of the problems for restraining the degenerative phenomena during evolution, so as to improve the algorithm efficiency. This type of prior knowledge about some parts of optimal solution exists in the PMU placement problem. So, the IGA is adopted in this paper to solve the problem. Also, a new effect which is preventing from familial reproduction is studied which shows an increase in converging speed. The effectiveness of the proposed method is verified via IEEE standard systems and a realistic large-scale power system.
机译：本文研究了免疫遗传算法（IGA）在电力网络中相量测量单元（PMU）最优布置问题中的应用。问题在于确定使系统可见的最小数量的PMU的放置位置。在保持遗传算法的优势的前提下，将免疫算子纳入规范遗传算法中，利用遗传算法的一些特征和知识来抑制进化过程中的退化现象，从而提高了算法效率。有关PMU放置问题的最佳解决方案某些部分的此类先验知识。因此，本文采用IGA来解决该问题。此外，研究了防止家族繁殖的新效果，该效果显示了收敛速度的提高。通过IEEE标准系统和现实的大规模电力系统验证了所提出方法的有效性。

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