Toward Encrypted OPF Across Transmission and Distribution—Prospects and Open Problems of Encrypted Quadratic Programming

The increasing integration of distributed energy resources demands enhanced coordination between transmission system operators (TSOs) and distribution system operators (DSOs) to maintain reliable grid operation. Traditional approaches rely on hierarchical or distributed optimization schemes for power flow management, but these methods either compromise optimality or introduce significant communication overhead and privacy concerns. To address these challenges, privacy‐preserving solution methods have been proposed for optimal power flow (OPF) problems. However, existing methods are typically distributed or require decryption of intermediate results. We propose a novel solution building on the encrypted solution of a centralized problem formulation using the alternating direction method of multipliers (ADMM). Our approach represents a pioneering step toward a practical, encrypted approach for solving large‐scale quadratic programs (QPs) in power systems, offering a framework with applications across systems and control, as well as machine learning.