Thermal Modelling of Power Transformers
Summary
Thermal modelling of power transformers encompasses analytical, numerical and data‐driven approaches to predict temperature distributions arising from electrical losses in windings and cores. Accurate estimation of hotspot temperatures and fluid flow patterns is vital for transformer design, lifetime assessment and safe operation. Traditional network models represent oil channels and thermal resistances in a simplified manner, while computational fluid dynamics (CFD) offers detailed insight into oil flow and heat transfer phenomena. Multiphysics coupling integrates electromagnetic loss calculation with thermal and fluid models to capture feedback between heat generation and cooling performance. Recent trends include the use of machine learning to forecast hotspot temperatures from limited sensor data, the development of advanced thermal networks incorporating radiator nodes for fault diagnosis, and the exploration of novel cooling media such as biodegradable esters and nanofluid suspensions. These efforts aim to support higher loading capacities, extend service life and reduce environmental impact across diverse climate conditions and transformer topologies.
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Thermal Modelling of Power Transformers publication trend
The graph below shows the total number of articles in thermal modelling of power transformers across all publications each year (not limited to Nature Index journals).
Technical terms
Hotspot temperature: The maximum local temperature reached within transformer windings or core due to power losses.
Computational fluid dynamics (CFD): Numerical simulation technique to calculate fluid flow and heat transfer inside transformer cooling media.
Electromagnetic–thermal coupling (EMAG–CFD): Integration of electromagnetic loss computation with CFD‐based thermal analysis to predict temperature distribution.
Electro-thermal resistance model (E-TRM): Analytical framework combining electrical loss data with equivalent thermal resistances to estimate oil and winding temperatures.
Thermography: Infrared imaging method used to map surface temperatures and detect thermal anomalies in transformers.
Nanofluids: Suspensions of nanoparticles within insulating oils to enhance thermal conductivity and improve cooling performance.
Natural ester oil: Biodegradable, vegetable-based insulating fluid with favourable thermo-physical properties used as an alternative to mineral oil.
References
- Thermal analysis of 8.5 MVA disk-type power transformer cooled by biodegradable ester oil working in ONAN mode by using advanced EMAG–CFD–CFD coupling. International Journal of Electrical Power & Energy Systems (2022).
- Prediction of transformer fault in cooling system using combining advanced thermal model and thermography. IET Generation Transmission & Distribution (2021).
- Investigation of Mineral Oil-Based Nanofluids Effect on Oil Temperature Reduction and Loading Capacity Increment of Distribution Transformers. Energy Reports (2021).
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