Comprehensive Condition Evaluation of Distribution Transformer Considering Internal Operation, External Environment, and Load Operation for Business Expansion

This paper proposes a comprehensive condition evaluation method for distribution transformers considering their internal operation, external environment, and load operation for business expansion. Unlike the existing studies, the proposed method can not only comprehensively consider the impacts of equipment aging, environmental influence, and post-business-expansion load variations on the distribution transformer’s condition but can also effectively simplify the process of determining the comprehensive weight and identifying the condition of the distribution transformer. Firstly, a comprehensive condition evaluation indicator system for distribution transformers is established. Subsequently, the comprehensive weight for each indicator of the distribution transformer is calculated by using the ordering relation analysis–principal component analysis (ORA-PCA) method and the principle of minimum discrimination information. Based on this, an improved golden section method is utilized to construct evaluation criterion clouds. Moreover, a comprehensive condition evaluation model for distribution transformers is developed based on the cloud model and the expectation curve method. Finally, the model effectiveness is validated by the case study, and a sensitivity analysis is conducted for the internal operation, external environment, and load operation of distribution transformers for business expansion, providing theoretical support for condition classification boundaries.

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Publication Details

Journal
Energies
Published
2025-05-10
DOI
https://doi.org/10.3390/en18102456
Citations
4
Primary Topic
Power Transformer Diagnostics and Insulation
Type
article
Field-Weighted Citation Impact
2.92

Funders

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article

Comprehensive Condition Evaluation of Distribution Transformer Considering Internal Operation, External Environment, and Load Operation for Business Expansion

Shengxiang Xie, Yuling He, Dao‐Qing Dai, Dong Wei-feng
4 citations
Energies
Power Transformer Diagnostics and Insulation
2.92
article

Comprehensive Condition Evaluation of Distribution Transformer Considering Internal Operation, External Environment, and Load Operation for Business Expansion

Shengxiang Xie, Yuling He, Dao‐Qing Dai, Dong Wei-feng
article en
4 citations

Abstract

This paper proposes a comprehensive condition evaluation method for distribution transformers considering their internal operation, external environment, and load operation for business expansion. Unlike the existing studies, the proposed method can not only comprehensively consider the impacts of equipment aging, environmental influence, and post-business-expansion load variations on the distribution transformer’s condition but can also effectively simplify the process of determining the comprehensive weight and identifying the condition of the distribution transformer. Firstly, a comprehensive condition evaluation indicator system for distribution transformers is established. Subsequently, the comprehensive weight for each indicator of the distribution transformer is calculated by using the ordering relation analysis–principal component analysis (ORA-PCA) method and the principle of minimum discrimination information. Based on this, an improved golden section method is utilized to construct evaluation criterion clouds. Moreover, a comprehensive condition evaluation model for distribution transformers is developed based on the cloud model and the expectation curve method. Finally, the model effectiveness is validated by the case study, and a sensitivity analysis is conducted for the internal operation, external environment, and load operation of distribution transformers for business expansion, providing theoretical support for condition classification boundaries.

EnergiesVol. 18(10)
North China Electric Power University (CN), China Southern Power Grid (China) (CN)
China Southern Power Grid
Openalex Percentile: Top 9%
Power Transformer Diagnostics and Insulation
2.92
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