Online Identification of Measurement Abnormality Fault Based on Outlier Detection for Current Transformer in High Voltage Shunt Reactor
Teng Yufei1, Wu Jie1, Zhang Zhenyuan2, Jiang Zhenchao1, Huang Qi2
1. State Grid Sichuan Electric Power Research Institute Chengdu 610041 China; 2. School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu 611731 China
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.
滕予非, 吴杰, 张真源, 姜振超, 黄琦. 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[J]. 电工技术学报, 2019, 34(11): 2405-2416.
Teng Yufei, Wu Jie, Zhang Zhenyuan, Jiang Zhenchao, Huang Qi. Online Identification of Measurement Abnormality Fault Based on Outlier Detection for Current Transformer in High Voltage Shunt Reactor. Transactions of China Electrotechnical Society, 2019, 34(11): 2405-2416.
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2019, Vol. 34 
