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Application of Parity Mismatches on Detection of Bad Data in Power System State Estimation

机译:奇偶校验中的应用在电力系统状态估计中检测不良数据的应用

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Measurement residuals have been conventionally used in the detection and identification of gross errors in power system state estimation. Other types of mismatches have been employed in failure detection of complex plants, though their application to power systems has not yet been reported. Parameters in power systems can be used for the purpose of generating such mismatches called parity mismatches in this paper. Parameters calculated from measurements containing erroneous ones differ from their true values resulting in parity mismatches. In this paper, parity mismatches are employed for identification of gross errors in given measurements. A relation between parity mismatches and measurement residuals has been derived. Similar to the method of residuals, normalization can be effected on parity mismatches. Physical appeal of the parity mismatches enables one to adopt normalization which improves the detectability of bad data in short lines. A segregated treatment for real, reactive power flows and also the injections can be applied unlike the method of residuals.
机译:测量残差通常用于检测和识别电力系统状态估计中的总误差。虽然尚未报道它们对电力系统的应用,但是在复杂植物的故障检测中采用了其他类型的错配。电力系统中的参数可以用于产生本文中称为奇偶校验不匹配的这种不匹配的目的。从包含错误的测量计算的参数与其真正的值不同,导致奇偶校验不匹配。在本文中,采用奇偶校验不匹配来识别给定测量中的总误差。阶段不匹配与测量残差之间的关系已经推导出来。类似于残差的方法,可以在奇偶校验不匹配上实现归一化。奇偶频道不匹配的物理吸引力使一个人采用正常化,这提高了短线中不良数据的可检测性。与残留方法不同,可以应用用于实际,无功功率流量的隔离处理。

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