Study of metal oxide arresters health state evaluation based on fuzzy grey theory

With the excellent electric performance, metal oxide arresters (MOA) have been widely used in the electric power system. In order to improve power supply reliability and reduce economic loss, it´s necessary to conduct the health evaluation of electrical equipments. This paper takes metal oxide arrester as a research object. Firstly, condition parameters are selected, which can be gotten through preventive experiments, on-line monitoring and operation maintenance records, constructing the rational state evaluation index system. Secondly, the analytic hierarchy process (AHP) method is adopted to determine the weight for each condition parameter. Thirdly, the health evaluation model of metal oxide arresters is established based on the fuzzy grey clustering theory. Then, metal oxide arresters are taken for example shows that the comprehensive evaluation result is consistent with the actual state of equipment, which proves the proposed model and method´s effectiveness and validity.