Multifactorial condition assessment for power transformers

Accurately assessing the health condition of the power transformer is critical to improving the operational reliability of power systems. Although great efforts to improve the accuracy of transformer fault diagnosis, accurate detection of multiple latent faults is still a difficult problem. Therefore, a multifactorial condition assessment method based on fuzzy sets and factor space is proposed. Different from the previous diagnosis methods that only provide a single-valued result, the proposed method can display the influence degree of various variables on the condition assessment result, which indirectly indicates the cause and location of faults that occur in a transformer. In the proposed method, the type-2 fuzzy set is used to describe the evaluation of various test values and the multifactorial condition assessment model based on factor space is applied to integrate the condition information. A modified analytic hierarchy process method is developed to estimate the relative importance of attributes. This method can distinctly indicate multiple probable latent faults of the transformer and help engineers quickly determine the cause and location of faults, which is helpful to improve the accuracy of diagnosis and the efficiency of transformer maintenance. The effectiveness of this method is verified with case studies.