Partial Discharge Data Matching Method for GIS Case-Based Reasoning

Jiejie Dai, Yingbing Teng, Zhaoqi Zhang, Zhongmin Yu, Gehao Sheng and Xiuchen Jiang
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Jiejie Dai: State Grid Shanghai Shinan Electric Power Supply Company, Xinbei Road No.268, Shanghai 201199, China
Yingbing Teng: State Grid Shanghai Shinan Electric Power Supply Company, Xinbei Road No.268, Shanghai 201199, China
Zhaoqi Zhang: Department of Electrical Engineering, Shanghai Jiao Tong University, Dongchuan Road No.800, Shanghai 200240, China
Zhongmin Yu: State Grid Shanghai Electric Power Company, Yuanshen Road No.1122, Shanghai 200120, China
Gehao Sheng: Department of Electrical Engineering, Shanghai Jiao Tong University, Dongchuan Road No.800, Shanghai 200240, China
Xiuchen Jiang: Department of Electrical Engineering, Shanghai Jiao Tong University, Dongchuan Road No.800, Shanghai 200240, China

Energies, 2019, vol. 12, issue 19, 1-15

Abstract: With the accumulation of partial discharge (PD) detection data from substation, case-based reasoning (CBR), which computes the match degree between detected PD data and historical case data provides new ideas for the interpretation and evaluation of partial discharge data. Aiming at the problem of partial discharge data matching, this paper proposes a data matching method based on a variational autoencoder (VAE). A VAE network model for partial discharge data is constructed to extract the deep eigenvalues. Cosine distance is then used to calculate the match degree between different partial discharge data. To verify the advantages of the proposed method, a partial discharge dataset was established through a partial discharge experiment and live detections on substation site. The proposed method was compared with other feature extraction methods and matching methods including statistical features, deep belief networks (DBN), deep convolutional neural networks (CNN), Euclidean distances, and correlation coefficients. The experimental results show that the cosine distance match degree based on the VAE feature vector can effectively detect similar partial discharge data compared with other data matching methods.

Keywords: partial discharge; gas insulated switchgear; case-based reasoning; data matching; variational autoencoder (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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