Phase angle-free line active power anomaly detection method

Abstract

The invention provides a line active power anomaly detection method not involving a phase angle. According to the method, pre-calibration or a reference mutual inductor with high precision is not needed, online detection can be achieved, and therefore the accuracy of protection setting and state estimation of the electric power system is guaranteed. Firstly, a line active loss model which does not involve a phase angle is deduced, and an active loss theoretical value during operation of a power transmission line can be determined; secondly, determining a PMU / SCADA positive sequence data measurement error limit and an operation parameter deviation limit of the line based on the accuracy grade of a line mutual inductor and the actual operation condition of the line; then, determining an active loss reasonable deviation value under a set data error limit and a line parameter deviation limit in combination with an error propagation law; and finally, comparing a difference value between an active loss measured value and a theoretical value, judging whether the difference value is within a reasonable deviation value, and outputting a line abnormal condition.

Description

technical field [0001] The invention relates to the field of power system operation control and protection, in particular to a line active power abnormality detection method that does not involve phase angle. Background technique [0002] At present, PMU data has become one of the important data sources of smart grid. A series of advanced applications have been developed based on PMU / WAMS, such as parameter identification, state estimation, power system monitoring and control. The characteristic of PMU is that it can provide phasor measurement data with consistent time scale, which can reflect the dynamic response and has a small delay; due to the precise time scale, even if there is a delay in channel transmission, the consistency of the time profile can be guaranteed. Therefore, the accuracy of PMU data is the basis for various advanced applications. However, the field measured PMU data shows that some PMU phase angle measurement data has quality problems. At the same ti...

AI Technical Summary

Problems solved by technology

However, most of the current methods essentially detect the mutation of the data, and it is difficult to detect the long-term, continuous, and non-mutation measurement error, and many methods require a machine that has been calibrated or has a low precision. high transformer

In addition, there are few detection methods for PMU / SCADA measured power abnormal data

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