Adaptive Bandwidth Hybrid Density Estimation and Correlation‐Aware Risk Assessment in <scp>PV</scp> ‐Integrated <scp>MV</scp> – <scp>LV</scp> Distribution Networks

Abstract This study proposes a comprehensive approach that combines accurate marginal distribution modeling with correlation‐driven risk assessment for evaluating the operational risks of medium and low voltage distribution networks with high‐penetration distributed photovoltaic (PV) integration. First, an adaptive bandwidth partitioned hybrid density model (ABP‐HDM) is developed to improve the fitting accuracy of local probability distributions of solar irradiance. The marginal distribution model is then embedded into a Gaussian Copula‐based joint probability modeling framework to precisely fit and characterize the correlations among solar irradiance, residential load, and commercial load, thereby generating physically consistent joint output scenarios. Finally, based on a modified IEEE 33‐bus distribution network model, voltage violation and power flow overload indices are employed to analyze the risk distribution across network locations (nodes/branches) while accounting for PV‐load correlations. The results demonstrate that the proposed method provides effective risk assessment support for the planning and operation of distribution networks with high PV penetration. © 2026 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.