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首页> 外文期刊>Electric Power Components and Systems >A Novel Topological Genetic Algorithm-Based Phasor Measurement Unit Placement and Scheduling Methodology for Enhanced State Estimation
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A Novel Topological Genetic Algorithm-Based Phasor Measurement Unit Placement and Scheduling Methodology for Enhanced State Estimation

机译：基于新型拓扑遗传算法的相量测量单元布局和调度方法，用于增强状态估计

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摘要

Phasor measurement units are emerging as a potential tool for on-line power system state estimation. Incorporation of phasor measurement units to the existing power system's monitoring system is impeded by various physical and economic constraints. This article proposes a novel topological genetic algorithm for optimal placement of phasor measurement units along with existing conventional measurement units such that state estimation can be achieved with enhanced accuracy and immunity against power grid contingencies. The proposed algorithm optimally places phasor measurement units so that complete observability of the power system is achieved through them and enhanced redundancy in measurement can be accomplished through conventional measurement units. Since practical phasor measurement unit placements are accomplished in multiple horizons, intelligent sorting and phase optimization methodologies have been presented to attain maximum observability during phasing periods. Placement of phasor measurement units with multiple channel limits has also been studied in this article. The efficacy of the proposed topological genetic algorithm for optimizing the number of phasor measurement units and enhancing state estimation under various operating conditions has been validated through extensive simulation studies conducted in IEEE standard bus systems. Practical case studies have been performed in the western and southern region Indian power grids.
机译：相量测量单元正在成为在线电力系统状态估计的潜在工具。相形测量单元与现有电力系统的监视系统的结合受到各种物理和经济约束的阻碍。本文提出了一种新颖的拓扑遗传算法，用于相量测量单元和现有常规测量单元的最佳放置，从而可以以提高的精度和对电网突发事件的抵抗力来实现状态估计。所提出的算法最佳地放置了相量测量单元，从而通过它们可以实现电力系统的完全可观测性，并且可以通过常规的测量单元来实现增强的测量冗余度。由于实际的相量测量单元放置是在多个视野中完成的，因此已经提出了智能的分类和相位优化方法，以在相移期间获得最大的可观察性。本文还研究了具有多个通道限制的相量测量单元的放置。通过在IEEE标准总线系统中进行的广泛仿真研究，已验证了所提出的拓扑遗传算法在各种工作条件下优化相量测量单元的数量并增强状态估计的功效。在印度西部和南部地区的电网中进行了实际案例研究。

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