基于离群点检测的高压并联电抗器本体电流互感器测量异常故障在线诊断

doi:10.19595/j.cnki.1000-6753.tces.180669

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Abstract In order to increase the accuracy of the overcurrent online monitor of shunt reactor, an online identification method of Measurement Abnormality Fault for Current Transformer (CT) of high voltage shunt reactor based on outlier detection is proposed. Firstly, sigmoid function is utilized to fit the relationship between conditional probability of overcurrent alarms and the RMS of the voltage in the bus. And the center point and uncertain area of the function are chosen as the indexes to generate the key characteristic data point (KCDP). Secondly, isolation forest algorithm is utilized to calculation anomaly score of diagnosis dataset, which includes KCDP under normal condition and that in detection day, in order to detect the outlier point. Finally, supposed the anomaly scores under normal condition meet the Weibull distribution, the judgment of the identification of measurement abnormality fault for CT is proposed. The effectiveness of the method is verified by case study of a practical 500kV high voltage shunt reactor.

Key words： High voltage shunt reactor outlier detection isolation forest algorithm conditional probability Weibull distribution

Received: 23 April 2018 Published: 14 June 2019

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TM45

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	Teng Yufei
	Wu Jie
	Zhang Zhenyuan
	Jiang Zhenchao
	Huang Qi

Cite this article:

Teng Yufei,Wu Jie,Zhang Zhenyuan等. Online Identification of Measurement Abnormality Fault Based on Outlier Detection for Current Transformer in High Voltage Shunt Reactor[J]. Transactions of China Electrotechnical Society, 2019, 34(11): 2405-2416.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.180669 OR https://dgjsxb.ces-transaction.com/EN/Y2019/V34/I11/2405

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