Distributionally Robust Chance-Constrained Optimal Load Shedding Model for Active Distribution Networks Based on KDE
With the high penetration of distributed energy resources in active distribution networks(ADNs), forecast errors from renewables and loads pose significant risks of bilateral violations, including overvoltage/undervoltage and line overloads. To address this challenge, this paper proposes a KDE-DRCCO model that integrates kernel density estimation (KDE) with distributionally robust chance-constrained optimization (DRCCO). Leveraging the radial topology … Read more