Research on Ferroresonance and Lightning Overvoltage Identification Method Based on Multi-Level Support Vector Machine

doi:10.3969/j.issn.1008-0198.2022.01.004

Abstract

Abstract: Aiming at the frequent occurrence of overvoltage in power system, which seriously threatens the safety of equipment and personnel, a pattern recognition method based on support vector machine is proposed. Based on the overvoltage waveforms collected by Chongqing 110 kV substation, the characteristic differences of different overvoltage waveforms are analyzed, and then six kinds of characteristic quantities that can effectively reflect the difference between ferroresonance and lightning overvoltage are extracted by time domain analysis and frequency domain analysis. Finally, the extracted characteristic quantities are applied to overvoltage pattern recognition. The theoretical basis of support vector machine used in this recognition method is simple and intuitive. The simulation results show that this method can correctly identify ferroresonance and lightning overvoltage, and has the advantage of fast recognition speed.

Key words: ferroresonance overvoltage, lightning overvoltage, feature extraction, support vector machine, overvoltage identification

CLC Number:

TM862

ZHAO Hongbin, LUO Qingliang, LI Xin, XIANG Yingzhu, HE Zhiqiang, DENG Hualong. Research on Ferroresonance and Lightning Overvoltage Identification Method Based on Multi-Level Support Vector Machine[J]. Hunan Electric Power, 2022, 42(1): 17-22.

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