Fully distributed source-load-storage coordination for active distribution networks via multi-agent consensus optimization

Abstract This study proposes a fully distributed coordination optimization strategy for active distribution networks using multi-agent consensus algorithms. To overcome the limitations of centralized control, including computational inefficiency, high infrastructure costs, and reliability vulnerabilities under high renewable energy penetration, generators, flexible loads, and energy storage devices are modeled as autonomous agents. The strategy employs consensus variables derived from incremental generation costs, storage operational costs, and flexible load benefits, which are coordinated through localized communication and first-order discrete-time protocols. Validated through multi-scenario simulations on the IEEE 39-node system, this approach combines centralized scheduling-level performance with convergence, communication robustness, and complex constraint handling capabilities, effectively ensuring power-supply reliability. It eliminates centralized dependencies while significantly enhancing the resilience of distribution networks.