Research on Comprehensive Optimization Method for Line Loss Prediction of Distribution Network Considering Distributed Photovoltaic Access

With the introduction of the “double carbon” goal, the integration of distributed power sources into the grid has significantly altered the operational dynamics of distribution networks. However, existing line loss prediction methods often overlook the seasonal variations of distributed power sources, leading to reduced prediction accuracy and limited emergency response capabilities. To address this issue, this paper proposes a comprehensive optimization method for line loss prediction in distribution networks, incorporating distributed photovoltaic (PV) access. The method employs the Maximum Information Coefficient (MIC) to screen characteristic parameters of the distribution network. The Multivariate Variational Mode Decomposition (MVMD) algorithm is then used to decompose aperiodic feature parameters and historical line loss data, forming a matrix with distribution network line loss characteristics. Finally, the line loss feature matrix is input into a prediction model based on the Stacking algorithm. Experimental results on a 10kV distribution network demonstrate that the proposed method significantly improves prediction accuracy compared to existing approaches.