A new power transformer risk modelling considering cumulative surge effects in insulation coordination studies

Accurate insulation risk assessment plays a critical role in ensuring the reliability of power transformers, given the significant technical complexities involved in their design. Back flashover failure (BF) caused by lightning overvoltages on incoming substation lines must be considered as an effective stress component in transformer insulation design. These transient surges impose electrical stress on the paper-based insulation system of the transformer. Since such insulation materials are non-self-restoring, the analysis of the voltage–time (V-T) withstand characteristic is essential for insulation risk evaluation. These characteristics are typically derived from laboratory tests on power transformers; however, insulation aging occurring during the testing process may influence the accuracy of the extracted data. In real operating conditions, neglecting aging effects can lead to inconsistencies in insulation coordination. This paper proposes a novel model for correcting aging- deviations in voltage-time (V-T) characteristic curve, enabling a more accurate evaluation of insulation risk. Furthermore, the proposed framework incorporates the cumulative impact of aging in order to estimate the overall insulation risk of the transformer throughout its service life. The findings of this study contribute to safer and more optimized design of power transformers and support improved insulation coordination under realistic operating conditions.

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Publication Details

Journal
Electric Power Systems Research
Published
2026-09-18
DOI
https://doi.org/10.1016/j.epsr.2026.114227
Primary Topic
Power Transformer Diagnostics and Insulation
Type
article
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A new power transformer risk modelling considering cumulative surge effects in insulation coordination studies

Reza Shariatinasab, Mohsen Akafi-Mobarakeh, Behrooz Vahidi
Electric Power Systems Research
Power Transformer Diagnostics and Insulation
article

A new power transformer risk modelling considering cumulative surge effects in insulation coordination studies

Reza Shariatinasab, Mohsen Akafi-Mobarakeh, Behrooz Vahidi
article en

Abstract

Accurate insulation risk assessment plays a critical role in ensuring the reliability of power transformers, given the significant technical complexities involved in their design. Back flashover failure (BF) caused by lightning overvoltages on incoming substation lines must be considered as an effective stress component in transformer insulation design. These transient surges impose electrical stress on the paper-based insulation system of the transformer. Since such insulation materials are non-self-restoring, the analysis of the voltage–time (V-T) withstand characteristic is essential for insulation risk evaluation. These characteristics are typically derived from laboratory tests on power transformers; however, insulation aging occurring during the testing process may influence the accuracy of the extracted data. In real operating conditions, neglecting aging effects can lead to inconsistencies in insulation coordination. This paper proposes a novel model for correcting aging- deviations in voltage-time (V-T) characteristic curve, enabling a more accurate evaluation of insulation risk. Furthermore, the proposed framework incorporates the cumulative impact of aging in order to estimate the overall insulation risk of the transformer throughout its service life. The findings of this study contribute to safer and more optimized design of power transformers and support improved insulation coordination under realistic operating conditions.

Electric Power Systems ResearchVol. 265
Amirkabir University of Technology (IR), University of Birjand (IR)
Affordable and clean energy
Openalex Percentile: Top 20%
Power Transformer Diagnostics and Insulation
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A new power transformer risk modelling considering cumulative surge effects in insulation coordination studies — Reza Shariatinasab, Mohsen Akafi-Mobarakeh, et al. · Electric Power Systems Research (2026) | TGRS Research Map | TGRS