Key Parameter Extraction and Condition Assessment for Power Transformer Based on Factor Analysis and D-S Evidence Theory

Abstract

The condition Assessment of transformer is an important basis for its operation, inspection and maintenance. But a transformer has a variety of Assessment parameters, many of which are redundant. How to objectively and reasonably select the Assessment parameters remains a challenge. To solve this problem, this article analyzed thoroughly the requirements and research status of transformer condition Assessment. On this basis, a multi-level fuzzy comprehensive Assessment model based on the key Assessment parameter system and Dempster-Shafer (D-S) evidence theory was constructed. Specifically, the key parameters were scientifically extracted using factor analysis, and an indicator system consisting of key parameters was constructed. Then, in combination with the analytic hierarchy process (AHP), the optimal weights of each sub-indicator in the assessment system were acquired, and the Assessment results of each item layer were obtained based on the respective membership function. At last, based on D-S evidence theory, the Assessment results of each item layer were fused for the decision-making in Assessment. Case analysis results indicate that the proposed model can effectively and reasonably assess the transformer's operating condition.