基于样本协方差矩阵特征特性的电网多重扰动定位方法

doi:10.19595/j.cnki.1000-6753.tces.200013

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摘要为提升随机矩阵理论在电网扰动定位应用中的计算效率和适应性,基于样本协方差矩阵的最大特征值及最小特征向量（即特征特性）,提出一种适用于多重扰动场景的电网扰动定位方法。首先,针对考虑负荷随机波动及噪声干扰工况的电网数据源矩阵,通过构建其窗口矩阵和标准矩阵,进而形成其样本协方差矩阵。其次,获取当前时刻最大特征值并计算基于Spiked模型的最大特征值阈值。最后,当最大特征值越过其动态阈值时,说明电网中有扰动事件发生,通过最小特征向量中异常元素的位置与受扰节点编号之间的对应关系,依据特征向量的“相变”现象可实现电网多重扰动定位。借助DIgSILENT和Matlab R2014a软件,案例分析在IEEE 118节点标准系统中展开,涉及两处同时扰动事件、相继扰动事件和同时故障事件,计算结果表明了所提方法的有效性和高效性。

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	李洪乾
	韩松
	周忠强

关键词 ：样本协方差矩阵, 特征特性, 多重扰动, Spiked模型, “相变”现象, 扰动定位

Abstract：A random matrix theory based multiple disturbance positioning method employing maximum eigenvalue of sample covariance matrix (Max-ESCM) and its corresponding Minimum Eigenvector (Min-ESCM) is proposed for improving the efficiency of disturbance positioning and the adaptability in multi-disturbance condition. A group of data source matrices should be firstly constructed considering random load fluctuation and noise interference for simulating the working conditions in the real world. Then the standard matrices can be obtained using a moving window matrix. The sample covariance matrices would be formed as a consequence. Furthermore, the Max-ESCM may be acquired. Meanwhile, the Spiked model based dynamic threshold for Max-ESCM might be used for detecting the abnormal disturbance in power system. Consequently, the abnormal elements involving the Min-ESCM will be found according to the phase-transition phenomenon if the dynamic threshold for Max-ESCM is violated, which might be helpful for identifying the disturbed buses with anomalous variation. The case studies have been carried on an IEEE 118-bus system utilizing DIgSILENT and Matlab® software, involving three kinds of working conditions such as simultaneous disturbance events, successive disturbance events and simultaneous fault events. The results show that the proposed methodology is valid and efficient.

Key words： Sample covariance matrix eigen characteristic multi-disturbance Spiked model phase-transition phenomenon disturbance positioning

收稿日期: 2020-01-07

PACS:

TM744

基金资助:国家自然科学基金（51567006）、贵州省普通高等学校科技拔尖人才支持计划（2018036）和贵州省科学技术基金（黔科合基础[2019]1100）资助

通讯作者: 韩松男,1978年生,教授,研究方向为交直流电力系统动态分析、新型电力电子装备以及配电网规划等。E-mail：shan@gzu.edu.cn

作者简介: 李洪乾男,1994年生,硕士研究生,研究方向为电力系统大数据分析与应用。E-mail：1067920874@qq.com

引用本文:

李洪乾, 韩松, 周忠强. 基于样本协方差矩阵特征特性的电网多重扰动定位方法[J]. 电工技术学报, 2021, 36(3): 646-655. Li Hongqian, Han Song, Zhou Zhongqiang. Eigen Characteristic of Sample Covariance Matrix Based Multi-Disturbance Positioning Method of Power System. Transactions of China Electrotechnical Society, 2021, 36(3): 646-655.

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