Research on the Construction of Sensitive Energy Data Identification Model and Technologies for Active Distribution Network

With the direct impact on the smooth operation of active distribution networks of distributed power sources, power grid enterprises urgently need to build sensitive energy data identification technology. This study proposes a sensitive energy data identification model and technologies for structured datasets based on theoretical knowledge such as information theory and clustering analysis. Firstly, energy data sensitivity quantification technology based on information entropy is constructed, which calculates the sensitivity of each data attribute using the data attribute entropy, maximum discrete entropy, and sensitivity definition formula. Secondly, sensitivity clustering algorithm technology based on k-means to aggregate is constructed, which analyzes energy big data center datasets and perform sensitive data desensitization operations. Thirdly, sensitive attribute recognition technology based on association rule is constructed, which optimizes the recognition effect of sensitive information attributes in energy big data centers at the dataset level.