A novel consensus-based decentralized framework for optimal energy management in cooperative multi-microgrid networks using ADMM

The integration of intermittent renewable energy sources introduces significant operational uncertainties, challenging the economic efficiency and reliability of power systems. Centralized energy management strategies for multi-microgrid (MMG) networks face critical limitations in scalability, data privacy, and resilience to single-point failures. This study presents a scalable, privacy-preserving, and decentralized energy management framework for cooperative MMG networks to enhance operational efficiency and resilience. To achieve this, a novel consensus-based decentralized optimization algorithm is proposed, utilizing the Alternating Direction Method of Multipliers (ADMM), which decomposes the global optimal energy management problem into local subproblems that can be solved independently by each microgrid (MG). The method enables real-time coordination through iterative updates of local variables, consensus on power exchanges, and minimal information sharing—only power flows and dual variables between neighboring MGs. Simulation results on a modified 33-bus system with three interconnected MGs demonstrate that the proposed framework effectively balances supply and demand, optimizes energy storage utilization, and facilitates peer-to-peer energy trading, achieving lower operational costs and faster convergence compared to conventional ADMM, dual decomposition, consensus gradient, and proximal message passing methods. The proposed ADMM-based consensus framework provides a robust, scalable, and economically efficient solution for decentralized energy management in cooperative MMG systems.