基于等效磁化曲线智能识别的变压器保护原理

doi:10.19595/j.cnki.1000-6753.tces.190511

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Abstract This paper proposed an equivalent magnetization curve-based transformer protection. The transformer operation states are essentially affected by iron core and intuitively demonstrated by magnetization hysteresis loop. Firstly, based on the analysis of magnetization hysteresis loop, the correspondence between equivalent magnetization curves and operation states was shown in this paper. Secondly, several extracted geometric characteristics were used as input to BP neural network, which was trained with a small amount of training data to identify transformer operation states. Finally, digital simulation and dynamic-model experiments were conducted to verify the proposed scheme. The results of 100% showed that the classification model with a small amount of training data could accurately identify transformer operation states. Moreover, this classification model had higher generalization ability, not affected by CT saturation and over-excitation. The proposed scheme solves effectively the poor performance of AI technique in power system, which has a great application value.

Key words： Transformer protection equivalent magnetization curve BP neural network data fusion generalization ability

Received: 30 April 2019 Published: 07 April 2020

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TM40

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	Li Zongbo
	Jiao Zaibin
	He Anyang

Cite this article:

Li Zongbo,Jiao Zaibin,He Anyang. Equivalent Magnetization Curve Intelligent Recognition Based Transformer Protection[J]. Transactions of China Electrotechnical Society, 2020, 35(7): 1464-1475.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.190511 OR https://dgjsxb.ces-transaction.com/EN/Y2020/V35/I7/1464

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