On the Correlation Model between Extreme Disaster Weather and Distribution Transformer Fault Types

Nowadays extreme disaster weather have a great impact on the safe operation of distribution transformer. In this paper, an analytic hierarchy process(AHP)-fuzzy comprehensive evaluation method combined with a data mining method based on Apriori algorithm is proposed to build a new disaster weather evaluation system and construct the correlation model between extreme weather conditions and transformer fault types. For the proposed method, the analytic hierarchy process-fuzzy comprehensive evaluation method is firstly used to processed the real data of a certain power grid, and then the disaster weather evaluation system is established to to determine the impact degree of the disaster weather and classify the disaster grade. Lastly the Apriori algorithm is used to mine the real data to obtain the strong association rules and build the correlation model. The proposed model is performed on the field data obtained from a real power grid in South China and the final experimental results prove that the evaluation system and the correlation model are effective and comprehensive.