Machine Learning Applied to Anomaly Diagnosis in Transformers and Reactors Using Gas Chromatography

Rafael Ferreira¹, Thiago Sanchez¹, Tatiana Escovedo², Marcos Kalinowski²

¹Eletrobras CGT Eletrosul, Brazil; ²PUC-RJ, Brazil

Advances in Data-Driven Models for Digital Twins of Power Transformers

Sruti Chakraborty¹, Mauricio Soto², Alexander Alber³, Brian Sparling⁴, Patrick Picher⁵, Federica Bragone⁶

¹OMICRON Electronics, Austria; ²Hitachi Energy, United-States; ³Hitachi Energy, Germany; ⁴Kinectrics, Canada; ⁵Hydro Quebec, Canada; ⁶KTH University, Sweden

Application of Machine Learning on Prediction of Power Transformer No-Load Losses

Bruno Bosnjak, Walter Lee

GE Vernova

Approach, experiences and lessons learned in a fault developing HV transformer:Case Study perspective

Parag Chatterjee, Sushil Kumar

NTPC Limited, India

Application of Machine Learning Interpretability and Explainability Metrics in FRA of Transformers

Gabriel Lopes

Siemens Energy, Germany

Digital Transformation (DX) in Power Transformer Manufacturing: Enhancing Efficiency and Precision

Shigeyoshi Yoshida, Daisuke Ueno, Atsushi Yamatake, Yoshinobu Kitagawa, Kenichi Mino, Mitsugu Ueda, Tadao Minagawa, Hirotaka Muto

Mitsubishi Electric Corp, Japan

A Novel Hybrid Multilayer Model for Diagnosing Faults in Power Transformers Through Dissolved Gas Analysis (DGA)

Mouloud Bouzar¹, issouf Fofana¹, Patrick Picher²

¹Canada Research Chair Tier 1 in the Aging of Oil-Filled Equipment on High Voltage Lines (ViAHT), Université du Québec à Chicoutimi (UQAC), Chicoutimi, QC G7H 2B1, Canada; ²Hydro-Québec's Research Institute

Advancing Power Transformer Monitoring: Machine Learning-Based Temperature Monitoring

Hoda Jalali, Avinash Jain

VIE Technologies, United States of America