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Power Transformers Cooling Design: A Comprehensive Review

Sandra Sorte, André Ferreira Monteiro, Diogo Ventura, Alexandre Salgado, Mónica S. A. Oliveira and Nelson Martins ()
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Sandra Sorte: TEMA-Centre for Mechanical Technology and Automation, Department of Mechanical Engineering, University of Aveiro (UA), Campus Universitário de Santiago, 3810-193 Aveiro, Portugal
André Ferreira Monteiro: TEMA-Centre for Mechanical Technology and Automation, Department of Mechanical Engineering, University of Aveiro (UA), Campus Universitário de Santiago, 3810-193 Aveiro, Portugal
Diogo Ventura: TEMA-Centre for Mechanical Technology and Automation, Department of Mechanical Engineering, University of Aveiro (UA), Campus Universitário de Santiago, 3810-193 Aveiro, Portugal
Alexandre Salgado: TEMA-Centre for Mechanical Technology and Automation, Department of Mechanical Engineering, University of Aveiro (UA), Campus Universitário de Santiago, 3810-193 Aveiro, Portugal
Mónica S. A. Oliveira: TEMA-Centre for Mechanical Technology and Automation, Department of Mechanical Engineering, University of Aveiro (UA), Campus Universitário de Santiago, 3810-193 Aveiro, Portugal
Nelson Martins: TEMA-Centre for Mechanical Technology and Automation, Department of Mechanical Engineering, University of Aveiro (UA), Campus Universitário de Santiago, 3810-193 Aveiro, Portugal

Energies, 2025, vol. 18, issue 5, 1-42

Abstract: Efficient cooling technologies for power transformers are critical to modern power systems, ensuring reliability, performance, and AN extended lifespan. This review systematically analyses advancements, challenges, and opportunities in cooling systems for power transformers. Oil-immersed transformers, widely used due to their superior insulation and effective cooling, require efficient thermal management to prevent overheating and ensure operational stability. This review evaluates key cooling strategies across oil-natural air-natural (ONAN), oil-natural air-forced (ONAF), oil-directed air-forced (ODAF), and oil-forced air-forced (OFAF) systems. It highlights innovations in radiator design, such as top-mounted radiators and chimney caps, and explores sustainable alternatives, including biodegradable esters, nanofluids, and hybrid ventilation methods. Advanced computational tools like Computational Fluid Dynamics (CFD) and artificial intelligence (AI), particularly neural networks, are identified as transformative for optimising cooling performance, predicting thermal behaviour, and enabling real-time monitoring. Despite progresses, challenges persist in radiator optimisation, airflow dynamics, and scalability of innovative cooling methods. By offering a comprehensive review and identifying critical areas for improvement, this study provides a foundation for developing cost-effective, reliable, and environmentally sustainable cooling systems, aligning with the growing demand for efficient energy infrastructure.

Keywords: thermal modelling; biodegradable fluids; power transformers; radiator optimization; CFD simulation; heat management (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: 2025
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