Fully Distributed and Fast Optimization Approaches for AC-DC Radial Distribution Networks with Dynamic Load and DER Response

This paper addresses the computational challenges posed by integrating massive distributed energy resources (DERs) into evolving AC-DC distribution networks. As conventional centralized optimization approaches struggle to handle the increased complexity at the grid edge, we propose an Alternating Direction Method of Multipliers (ADMM)-based consensus approach for a fully distributed active power loss minimization strategy based on second-order conic programming (SOCP). Then, we extended the approach to another distributed approach based on block-coordinated descent to improve the convergence time by reducing the number of macro-iterations compared to ADMM for extensive networks. The original centralized problem is partitioned into multiple sub-problems, each further divided into three distinct areas corresponding to the AC, DC, and voltage source converter. Our approach efficiently determines optimal operating conditions by enabling parallel solutions of these sub-problems and facilitating the sharing of global information among different agents. Simulation results on 33-bus, 132-bus, 123-bus, and an extensive 8500-bus AC-DC radial test systems, under dynamic load and DER output scenarios, demonstrate that the proposed distributed strategy achieves optimal decisions significantly faster than centralized and state-of-the-art ADMM methods.