Insulation condition evaluation of oil-immersed transformer based on entropy weight hierarchy method

In order to evaluate the insulation condition of oil-immersed transformers effectively, a weight allocation method considering expert experience and degradation state is proposed in this paper. Firstly, a hierarchical structure for insulation condition evaluation is built based on dissolved gas in oil, ambient temperature and defect information, and subjective weights is assigned to each index based on expert experience. Then, the method of combined weight is adopted to introduce entropy weight into the weight allocation of index layer, thus weights of the index layer are dynamically adjusted to reflect the differences in the individual operation process while retaining expert experience for the criterion layer. Furthermore, the transformer insulation state is subdivided into five states from common four to realize more accurate perception of insulation state. Finally, case study of four 500 kV transformers shows that the method proposed can effectively identify normal transformers and discriminate abnormal transformers compared with the method based only on objective or subjective weight, which verifies the rationality of the method.