Decentralized agent-based optimization for congestion management in low-voltage grids incorporating legally mandated and voluntary flexibility

The increasing electrification of transport and heating sectors through electric vehicles and heat pumps presents significant challenges for low-voltage distribution grids, leading to potential congestion situations. We present a decentralized agent-based optimization approach for congestion management that leverages both legally mandated consumer flexibility and voluntary battery flexibility. This multi-agent system enables individual households to participate in grid congestion management through autonomous decision-making while aiming to preserve household data sovereignty and to achieve privacy-preserving coordination via minimal information exchange. Our approach incorporates the German Energy Industry Act (§ 14a EnWG) framework and utilises the Alternating Direction Method of Multipliers (ADMM) for decentralized optimization. Evaluation results using the IEEE-33 test system demonstrate significant peak load reduction, complete elimination of thermal constraint violations, and real-time feasibility. These findings demonstrate that decentralized coordination can effectively manage grid congestion while maintaining privacy and regulatory compliance, offering a scalable alternative to traditional centralized approaches for future smart grid implementations.