最大归一化残差检验和b -检验对粗误差的脆弱性

J. Massignan, J. London, C. S. Vieira, Vladimiro Miranda
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引用次数: 3

摘要

电力系统依靠广泛的信息和传感器来维持可靠和安全的运行。对这些信息进行适当的处理,以保证电力系统数据的完整性,是任何现代控制中心的要求,通常通过与不良数据处理算法相关的状态估计来完成。本文表明,与通常假设的关于不良数据处理的主张相反,在某些情况下,单粗误差(GE)污染的非关键测量并不呈现最大的归一化残差。通过对剩余灵敏度矩阵元素的分析,正式证明了这种说法并不总是成立的。除了演示之外,还通过Undetectability Index (UI)映射了传统的坏数据处理可能存在的漏洞。在IEEE 14和IEEE 118测试系统上进行的计算模拟提供了对论文命题的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vulnerability of Largest Normalized Residual Test and b̂-Test to Gross Errors
Power systems rely on a broad set of information and sensors to maintain reliable and secure operation. Proper processing of such information, to guarantee the integrity of power system data, is a requirement in any modern control centre, typically performed by state estimation associated with bad data processing algorithms. This paper shows that contrarily to a commonly assumed claim regarding bad data processing, in some cases of single gross error (GE) the noncritical measurement contaminated with GE does not present the largest normalized residual. Based on the analysis of the elements of the residual sensitivity matrix, the paper formally demonstrates that such claim does not always hold. Besides this demonstration, possible vulnerabilities for traditional bad data processing are mapped through the Undetectability Index (UI). Computational simulations carried out on IEEE 14 and IEEE 118 test systems provide insight into the paper proposition.
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