Big Data Correlation Analysis Model of Distribution Network Operation Based on Apriori Correlation Algorithm

With the deepening of enterprise digitalization, data mining technology has become a key tool to extract valuable information from massive data. Among them, association rule extraction, as the core content of data mining, is of great significance for revealing the complex relationship between data. As a common method for association rule mining, the Apriori algorithm provides powerful data analysis and decision support for enterprises. In this paper, the big data correlation analysis model of distribution network operation based on Apriori correlation algorithm and the optimized Apriori algorithm are used to mine the strong correlation law between various influencing factors in the distribution network, and establish a fault environment pattern identification database of distribution network, so as to lay the foundation for the early warning of distribution network operation risk and further improve the stability of power supply.