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This paper presents a grey-box model for predicting hot-spot temperatures of oil-immersed transformers in power distribution networks, addressing the need for dynamic transformer ratings due to increasing electricity demand. The model utilizes non-intrusive measurements and offers high accuracy in temperature forecasting, with a mean average error of 0.4–0.6 °C over a six-hour prediction horizon. By enabling real-time temperature predictions, the model helps distribution system operators optimize transforme

Author

Zineb Khodja

Language

EN