• Patil Bhushan Prataprao
• Dr. Shah Paresh Jaychand

Conventional transformer protection methods have limited information about the transformer's condition based on terminal data, making it challenging to distinguish between magnetizing inrush current and internal faults. This study presents a method to identify transients caused by magnetization and internal faults, providing additional information to improve protection algorithms. The Discrete Wavelet Transform (DWT) technique is used to extract features and discriminate between transformer magnetization and internal fault current. MATLAB Simulink software package is used to model a power transformer and simulation conducted under various operating conditions shows that the proposed approach provides reliable discrimination between magnetizing inrush current and internal faults, leading to an improved transformer protection algorithm. The outcomes can help in developing advanced protection schemes that predict faults ahead of time and minimize downtime.

Inrush current, internal fault, transients, second harmonic component in transformer, wavelet transform.

"Discrete Wavelet Transform based Classification of Transients and Fault Diagnosis in Power Transformer", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 4, page no.1-9, April-2021, Available :http://www.jetir.org/papers/JETIR2104428.pdf

"Discrete Wavelet Transform based Classification of Transients and Fault Diagnosis in Power Transformer", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 4, page no. pp1-9, April-2021, Available at : http://www.jetir.org/papers/JETIR2104428.pdf