Validity Evaluation of Transformer DGA Online Monitoring Data in Grid Edge Systems

Jun Jia; Fengbo Tao; Guojiang Zhang; Jin Shao; Xinghui Zhang; Bo Wang

doi:10.1109/ACCESS.2020.2982674

Validity Evaluation of Transformer DGA Online Monitoring Data in Grid Edge Systems

Jun Jia
, Fengbo Tao
, Guojiang Zhang
, Jin Shao
, Xinghui Zhang
, Bo Wang^*

^*Corresponding author for this work

State Grid Corporation of China
Southeast University, Nanjing
Wuhan University

Research output: Contribution to journal › Article › peer-review

18 Scopus citations

Abstract

Dissolved gas analysis (DGA) is an important method of predicting transformer faults, and the accuracy of DGA measurements is of great significance to the evaluation of the transformer state in grid edge systems. In actual situations, it is difficult to regularly calibrate online DGA monitoring devices in a uniform way. Therefore, this paper proposes a method based on B-EMD and DBN to evaluate the validity of online DGA monitoring data and optimize the corresponding calibration plan. An analysis of actual DGA signals shows that the method proposed in this paper can effectively diagnose faults and improve the reliability of DGA online monitoring devices.

Original language	English
Article number	9044814
Pages (from-to)	60759-60768
Number of pages	10
Journal	IEEE Access
Volume	8
DOIs	https://doi.org/10.1109/ACCESS.2020.2982674
State	Published - 2020
Externally published	Yes

Keywords

Dissolved gas analysis
deep belief network
empirical mode decomposition
power transformer
validity evaluation

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10.1109/ACCESS.2020.2982674

Cite this

@article{9f579a0445714b16b116968fdb092983,

title = "Validity Evaluation of Transformer DGA Online Monitoring Data in Grid Edge Systems",

abstract = "Dissolved gas analysis (DGA) is an important method of predicting transformer faults, and the accuracy of DGA measurements is of great significance to the evaluation of the transformer state in grid edge systems. In actual situations, it is difficult to regularly calibrate online DGA monitoring devices in a uniform way. Therefore, this paper proposes a method based on B-EMD and DBN to evaluate the validity of online DGA monitoring data and optimize the corresponding calibration plan. An analysis of actual DGA signals shows that the method proposed in this paper can effectively diagnose faults and improve the reliability of DGA online monitoring devices.",

keywords = "Dissolved gas analysis, deep belief network, empirical mode decomposition, power transformer, validity evaluation",

author = "Jun Jia and Fengbo Tao and Guojiang Zhang and Jin Shao and Xinghui Zhang and Bo Wang",

note = "Publisher Copyright: {\textcopyright} 2013 IEEE.",

year = "2020",

doi = "10.1109/ACCESS.2020.2982674",

language = "英语",

volume = "8",

pages = "60759--60768",

journal = "IEEE Access",

issn = "2169-3536",

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TY - JOUR

T1 - Validity Evaluation of Transformer DGA Online Monitoring Data in Grid Edge Systems

AU - Jia, Jun

AU - Tao, Fengbo

AU - Zhang, Guojiang

AU - Shao, Jin

AU - Zhang, Xinghui

AU - Wang, Bo

PY - 2020

Y1 - 2020

N2 - Dissolved gas analysis (DGA) is an important method of predicting transformer faults, and the accuracy of DGA measurements is of great significance to the evaluation of the transformer state in grid edge systems. In actual situations, it is difficult to regularly calibrate online DGA monitoring devices in a uniform way. Therefore, this paper proposes a method based on B-EMD and DBN to evaluate the validity of online DGA monitoring data and optimize the corresponding calibration plan. An analysis of actual DGA signals shows that the method proposed in this paper can effectively diagnose faults and improve the reliability of DGA online monitoring devices.

AB - Dissolved gas analysis (DGA) is an important method of predicting transformer faults, and the accuracy of DGA measurements is of great significance to the evaluation of the transformer state in grid edge systems. In actual situations, it is difficult to regularly calibrate online DGA monitoring devices in a uniform way. Therefore, this paper proposes a method based on B-EMD and DBN to evaluate the validity of online DGA monitoring data and optimize the corresponding calibration plan. An analysis of actual DGA signals shows that the method proposed in this paper can effectively diagnose faults and improve the reliability of DGA online monitoring devices.

KW - Dissolved gas analysis

KW - deep belief network

KW - empirical mode decomposition

KW - power transformer

KW - validity evaluation

UR - https://www.scopus.com/pages/publications/85083378238

U2 - 10.1109/ACCESS.2020.2982674

DO - 10.1109/ACCESS.2020.2982674

M3 - 文章

AN - SCOPUS:85083378238

SN - 2169-3536

VL - 8

SP - 60759

EP - 60768

JO - IEEE Access

JF - IEEE Access

M1 - 9044814

ER -

Validity Evaluation of Transformer DGA Online Monitoring Data in Grid Edge Systems

Abstract

Keywords

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