Transformer health status evaluation model based on multi-feature factors

Abstract

During the entire period of transformer's service, the internal parts get ageing gradually. But the aging degree of each part cannot be observed directly. To correctly master the condition of the transformer contributes to the prediction of the risk and reliability of the transformer, and also, this is the foundation of making effective repairing strategies or replacement, ensuring the safe and reliable operation of transformers. However, the exact assessment result has not been acquired according to traditional assessments that based on only one of the state parameter. A new assessment model based on the multi-feature factors is proposed to overcome the disadvantage of traditional condition assessments. Firstly, in order to find out the rule that the characteristic of transformer changes, the factors that influence the state of the transformer health are researched with the method of the correlation analysis of Mathematical Statistics. These factors include DGA, breakdown voltage, dielectric loss, micro-water content, acid value, furfural content and so on. Secondly, determine the state information of the power transformer; establish the index system for health evaluation. Combining with qualitative analysis, the analytic hierarchy process method is adopted to determine the weight of each index, and the health status evaluation model of power transformer is established. As for a transformer that is in operation, as long as the corresponding experimental data is got, the health condition of the transformer can be obtained with the help of the health status evaluation model. Take transformers of a substation for instance. Using the proposed model, the corresponding experimental data is analyzed. The investigations results show that the new health status evaluation mode is effective.