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Energies 2018, 11(11), 3041; https://doi.org/10.3390/en11113041

A Novel Integrated Method to Diagnose Faults in Power Transformers

1,* , 1
,
1
and
2
1
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
2
China Electric Power Research Institute, Beijing 100192, China
*
Author to whom correspondence should be addressed.
Received: 10 September 2018 / Revised: 6 October 2018 / Accepted: 15 October 2018 / Published: 5 November 2018
(This article belongs to the Special Issue Optimization Methods Applied to Power Systems)
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Abstract

In a smart grid, many transformers are equipped for both power transmission and conversion. Because a stable operation of transformers is essential to maintain grid security, studying the fault diagnosis method of transformers can improve both fault detection and fault prevention. In this paper, a data-driven method, which uses a combination of Principal Component Analysis (PCA), Particle Swarm Optimization (PSO), and Support Vector Machines (SVM) to enable a better fault diagnosis of transformers, is proposed and investigated. PCA is used to reduce the dimension of transformer fault state data, and an improved PSO algorithm is used to obtain the optimal parameters for the SVM model. SVM, which is optimized using PSO, is used for the transformer-fault diagnosis. The diagnostic-results of the actual transformers confirm that the new method is effective. We also verified the importance of data richness with respect to the accuracy of the transformer-fault diagnosis. View Full-Text
Keywords: smart grid; transformer-fault diagnosis; principal component analysis; particle swarm optimization; support vector machine smart grid; transformer-fault diagnosis; principal component analysis; particle swarm optimization; support vector machine
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Wu, J.; Li, K.; Sun, J.; Xie, L. A Novel Integrated Method to Diagnose Faults in Power Transformers. Energies 2018, 11, 3041.

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