Application of Line Loss Correlation Analysis and Calculation of Power Distribution Network Based on Improved KNN Algorithm

The high resistance ratio of distribution network lines is an important cause of line losses. In order to reduce line losses, it is of great significance to carry out the relevant analysis of distribution network line losses. Based on the massive historical data on line losses, this first uses K-means clustering algorithm to construct a statistical model of line loss distribution. Subsequently, a balanced K-nearest neighbor (KNN) algorithm is adopted to increase the scenario division accuracy in face of unbalanced data. In addition, the inverse entropy method is proposed to calculate the significance of various scenarios in causing losses. Finally, through practical examples, this paper shows that our method not only helps to identify weak links in the operation of distribution networks, but also provides strong decision support for reducing losses.