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Development of a Comprehensive Model for Drying Optimization and Moisture Management in Power Transformer Manufacturing

Author

Listed:
  • Youssouf Brahami

    (Aging of Oil-Filled Equipment on High Voltage Lines (ViAHT), Department of Applied Sciences (DSA), University of Quebec at Chicoutimi (UQAC), Saguenay, QC G7H 2B1, Canada)

  • Amidou Betie

    (Institute National Polytechnique Houphouet Boigny, Department of Electrical Engineering, Yamoussoukro BP 1093, Côte d’Ivoire)

  • Fethi Meghnefi

    (Aging of Oil-Filled Equipment on High Voltage Lines (ViAHT), Department of Applied Sciences (DSA), University of Quebec at Chicoutimi (UQAC), Saguenay, QC G7H 2B1, Canada)

  • Issouf Fofana

    (Aging of Oil-Filled Equipment on High Voltage Lines (ViAHT), Department of Applied Sciences (DSA), University of Quebec at Chicoutimi (UQAC), Saguenay, QC G7H 2B1, Canada)

  • Zié Yeo

    (Institute National Polytechnique Houphouet Boigny, Department of Electrical Engineering, Yamoussoukro BP 1093, Côte d’Ivoire)

Abstract

The presence of moisture in the insulation of power transformers accelerates the degradation of both paper and oil, thereby increasing the risk of unexpected failures. Due to the hygroscopic nature of cellulose, the insulation can retain up to 8% moisture after the transformer manufacturing process. Reducing this moisture content is crucial in extending the operational lifespan of transformers. The drying cycle of paper insulation is a critical step in power transformer manufacturing, directly influencing the insulation’s longevity and overall performance. This paper introduces a nomogram that combines degradation and drying models, enabling the precise optimization of the drying process based on various parameters such as the temperature, paper mass, and extraction rate. The results of this study demonstrate that for a given extraction rate threshold, the required drying time can be determined based on the mass of paper to be dried, the drying temperature, and the degree of paper degradation (degree of polymerization). These predictive tools are essential for engineers and researchers aiming to enhance transformer reliability.

Suggested Citation

  • Youssouf Brahami & Amidou Betie & Fethi Meghnefi & Issouf Fofana & Zié Yeo, 2025. "Development of a Comprehensive Model for Drying Optimization and Moisture Management in Power Transformer Manufacturing," Energies, MDPI, vol. 18(4), pages 1-18, February.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:4:p:789-:d:1586451
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