Research on Early Warning Algorithm of Active Distribution Network Operational Risk Based on Improved Apriori Association Rules

In order to improve the accuracy and rapidity of risk early warning of active distribution network, this paper adopts the idea of data mining and proposes an improved Apriori algorithm for early warning of risks in the distribution network. This method takes weather, risk equipment and risk reasons as the research objects, and through mathematical analysis, proposes an improved Apriori algorithm based on seasonal classification, which greatly improves the efficiency of the algorithm, thus improving the response speed of the risk early warning system. At the same time, a failure mode library of typical environmental scenarios has been established, and enumerate the algorithm flow. The display interface of the system is designed and developed, so that the matching information is displayed in a separate display interface. Through the example analysis, not only the feasibility of the algorithm is verified, but also the readability of the risk warning data is improved, which has a guiding significance for the actual engineering construction.