Transformer Winding Parameter Identification based on Frequency Response Analysis using Hybrid Wavelet Transform (WT) and Simulated Annealing Algorithm (SA) and Compare with Genetic Algorithm (GA)

Sajad Bagheri; Reza Effatnejad   and Abolfazl Salami

doi:10.17485/ijst/2014/v7i5.2

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Transformer Winding Parameter Identification based on Frequency Response Analysis using Hybrid Wavelet Transform (WT) and Simulated Annealing Algorithm (SA) and Compare with Genetic Algorithm (GA)

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2014/v7i5.2

Year: 2014, Volume: 7, Issue: 5, Pages: 614–621

Original Article

Transformer Winding Parameter Identification based on Frequency Response Analysis using Hybrid Wavelet Transform (WT) and Simulated Annealing Algorithm (SA) and Compare with Genetic Algorithm (GA)

Sajad Bagheri¹ , Reza Effatnejad^2* and Abolfazl Salami³

¹Department of Electrical Engineering, Science and Research Branch, Islamic Azad University, Arak-Iran; bagheri_ieee@yahoo.com
²Electrical Engineering Department, Karaj Branch, Islamic Azad University, Karaj, Iran; Reza.efatnejad@kiau.ac.ir
³Faculty of Electrical Engineering, Arak Technology University, Arak, Iran; a_salami@iust.ac.ir

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Frequency response analysis method is used for certain evaluating and monitoring of the winding displacement and deformation of transformer core to detect incipient faults. Frequency response analysis is based on the graphical analysis and comparison of the current measured transfer function with a base current. In this paper we use compound of haar wavelet transform and intelligent Simulated Anealing Algorithms (SA) and finally we compare the achieved parameters with Genetic Algorithm (GA).

Keywords: Frequency Response Analysis, Haar Wavelet Transform, Genetic Algorithm, Simulated Annealing, Transformers Winding Parameter Identification, Traveling Wave Model