Enhanced Distributed Parallel Firefly Algorithm Based on the Taguchi Method for Transformer Fault Diagnosis

Zhi-Jun Li, Wei-Gen Chen, Jie Shan, Zhi-Yong Yang and Ling-Yan Cao
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Zhi-Jun Li: State Key Laboratory of Power Transmission Equipment and System Security and New Technology, Chongqing University, Chongqing 400044, China
Wei-Gen Chen: State Key Laboratory of Power Transmission Equipment and System Security and New Technology, Chongqing University, Chongqing 400044, China
Jie Shan: School of Electric Power Engineering, Shanghai University of Electric Power, Shanghai 200090, China
Zhi-Yong Yang: Guodian Nanjing Automation Co., Ltd., Nanjing 210032, China
Ling-Yan Cao: Guodian Nanjing Automation Co., Ltd., Nanjing 210032, China

Energies, 2022, vol. 15, issue 9, 1-22

Abstract: To improve the reliability and accuracy of a transformer fault diagnosis model based on a backpropagation (BP) neural network, this study proposed an enhanced distributed parallel firefly algorithm based on the Taguchi method (EDPFA). First, a distributed parallel firefly algorithm (DPFA) was implemented and then the Taguchi method was used to enhance the original communication strategies in the DPFA. Second, to verify the performance of the EDPFA, this study compared the EDPFA with the firefly algorithm (FA) and DPFA under the test suite of Congress on Evolutionary Computation 2013 (CEC2013). Finally, the proposed EDPFA was applied to a transformer fault diagnosis model by training the initial parameters of the BP neural network. The experimental results showed that: (1) The Taguchi method effectively enhanced the performance of EDPFA. Compared with FA and DPFA, the proposed EDPFA had a faster convergence speed and better solution quality. (2) The proposed EDPFA improved the accuracy of transformer fault diagnosis based on the BP neural network (up to 11.11%).

Keywords: firefly algorithm; the Taguchi method; communication strategy; transformer fault diagnosis; BP neural network (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: 2022
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