Abstract
As the urban power grids gradually enter the high reliability level, the distribution network risk early warning becomes the key to further improve the reliability level. Distribution network faults have the characteristics of strong randomness and weak causality, and conventional methods are difficult to find their laws. The idea of data mining is introduced in this paper. Based on the analysis of various types of fault data, the improved Apriori algorithm is used to mine the strong correlation rules of various influencing factors in the distribution network, and the fault-environment pattern recognition library of distribution network is established to lay the foundation for the early warning of distribution network operation risk.
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