基于动态易损性评估的相量测量单元概率优化布置方法

M. Priyadharshini, R. Meenakumari, P. Scholar
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引用次数: 4

摘要

本文旨在介绍IEEE-5总线系统相量测量单元(PMU)的最佳配置。本文提出了一种基于电力系统损耗指数的PMU最优配置动态易损性评估的最简单方案,并与多准则决策(MCDM)技术即层次分析法(AHP)、模糊层次分析法(Fuzzy AHP)和理想解相似性排序偏好法(TOPSIS)方法进行了比较。MCDM有助于在基于称重因素的PMU放置的多个替代方案中找到最佳解决方案。但该模型忽略了系统的动态运行。在该方案中,利用网络动力学的概率特性,通过蒙特卡罗仿真,对可能的输入参数变化(如负荷变化、发电变化和可信突发事件列表)迭代评估系统性能,评估系统的脆弱性指数。对每一种突发事件进行牛顿-拉夫森潮流分析,并观察了电网各部分的电力系统损耗。脆弱性指数是基于电力系统总损耗(PSL)计算的。在此基础上,利用数据聚类算法对电力系统网络中的脆弱区域进行识别和聚类。pmu必须位于最脆弱的区域,以防止系统停电并采取纠正控制措施。该方法在IEEE-5总线测试系统上进行了测试。测试结果表明,PSL指数可以有效地识别PMU的最优放置的脆弱区域。PMU位置的发现与MCDM技术进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Probabilistic approach based optimal placement of phasor measurement units via the estimation of dynamic vulnerability assessment
This paper aims in presenting the optimal placement of the Phasor Measurement Unit (PMU) of an IEEE-5 bus system. In this paper a simplest scheme for dynamic vulnerability assessment based on Power System Loss Index has been proposed for Optimal PMU placement and which is compared against the Multi Criteria Decision Making (MCDM) Techniques namely Analytical Hierarchy Process (AHP), Fuzzy AHP approach and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach. MCDM helps in finding the best solution among the multiple alternatives for the placement of PMU which is based on the weighing factor. But this MCDM has neglected the dynamic operation of the system. In the proposed scheme, the probabilistic nature of network dynamics is performed by Monte Carlo Simulation to iteratively evaluate the system performance for probable input parameter variations such as load variation, generation variation and list of credible contingencies to assess the vulnerability index of the system. Newton - Raphson load flow analysis is performed for each contingency and the power system losses in various parts of the networks are observed. The vulnerability Index is calculated based on total Power System Loss (PSL). Based on the index, the vulnerable regions in the power system network are identified and clustered with the help of Data clustering algorithm. The PMUs have to be located in the most vulnerable regions to prevent the system from blackouts and to take corrective control actions. This proposed simple approach is tested on IEEE-5 Bus test systems. The test result shows that PSL index is effective in identifying the vulnerable regions for optimal PMU placement. The findings of the PMU location are compared against MCDM techniques.
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