Research on transformer temperature rise detection and optimization method based on multi-physical field coupling

To address the inefficiency of conventional temperature rise tests for dry-type transformers in box substations, this study proposes a closed-loop "Standard-Experiment-Simulation-Optimization" methodology. An electromagnetic‑thermal coupled model was built, calibrated with field test data. The simulation revealed a saturated exponential growth pattern of hotspot temperature rise, verified experimentally. Based on this, additional thermocouples were placed beyond standard positions, enabling earlier and more accurate hotspot measurement. A predictive model using the first‑five‑hour data was derived to estimate steady‑state temperature, rise value, and required test duration. This approach reduces testing time and provides a reusable reference for improving hotspot detection accuracy.

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Publication Details

Journal
Scientific Reports
Published
2026-07-02
DOI
https://doi.org/10.1038/s41598-026-60800-7
Primary Topic
Power Transformer Diagnostics and Insulation
Type
article
Field-Weighted Citation Impact
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article

Research on transformer temperature rise detection and optimization method based on multi-physical field coupling

Hongyun Zhao, Shan Cheng, Yu Zhang
Scientific Reports
Power Transformer Diagnostics and Insulation
article

Research on transformer temperature rise detection and optimization method based on multi-physical field coupling

Hongyun Zhao, Shan Cheng, Yu Zhang
article en

Abstract

To address the inefficiency of conventional temperature rise tests for dry-type transformers in box substations, this study proposes a closed-loop "Standard-Experiment-Simulation-Optimization" methodology. An electromagnetic‑thermal coupled model was built, calibrated with field test data. The simulation revealed a saturated exponential growth pattern of hotspot temperature rise, verified experimentally. Based on this, additional thermocouples were placed beyond standard positions, enabling earlier and more accurate hotspot measurement. A predictive model using the first‑five‑hour data was derived to estimate steady‑state temperature, rise value, and required test duration. This approach reduces testing time and provides a reusable reference for improving hotspot detection accuracy.

Scientific Reports
General Administration of Quality Supervision, Inspection and Quarantine (CN), Xinjiang Uygur Autonomous Region Product Quality Supervision and Inspection Institute (CN), Changzhou Institute of Mechatronic Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 12%
Power Transformer Diagnostics and Insulation
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