Research on the method of locating abnormal line loss in substation area based on data mining technology

With the deep integration and rapid development of smart grid and big data analysis technology, the refined management of power line losses in substations has become a key path for energy conservation, emission reduction, and economic efficiency improvement in the power industry. In the complex structure of the power grid, tens of thousands of distribution stations are facing the urgent issue of how to efficiently identify and redNce line losses, achieve continuous optimization and precise control of line loss rates, which is an important problem that power supply enterprises urgently need to solve. This article proposes a detection method for abnormal line loss in substation areas based on data mining technology, combined with K-means⁺⁺clustering algorithm and isolated forest algorithm. It realizes the rapid localization of abnormal line loss in substation areas, provides a new method for the management of substation line loss, and promotes the improvement of management efficiency and power supply service quality of power supply enterprises.