Abstract：In view of the problem that current fault detection methods exist large error in micro-grid fault detection, this paper presents a model based on Bayesian network and association rule mining. It firstly adopts Hash technology to optimize Apriori algorithm and remove the undesired candidate item set, conducts data mining of original data set, introduces Bayesian network for sample training to reduce detection error, and finally obtains power system detection result. Simulation results show that the proposed fault detection model based on Bayesian network and association rule mining is efficient in power system fault detection with detection error far less than that of traditional algorithm.
2015, Vol. 16 
