Multi-Objective Congestion Management in Low-Voltage Grids: Coordinating End-Users and System Operators for Real-World Implementation

Electrical grids face increasing stress during peak events, leading to congestion and reliability concerns. Although user-based flexibility can mitigate these issues, coordination with Distribution System Operators (DSOs) is often limited by lack of the information exchange. This work introduces the Congestion Management Aggregator (CMA), a central entity with access to both user data and DSO forecasts, including electricity prices. Using a multi-objective optimization approach, the CMA coordinates flexible assets to minimize user costs and support the grid during congestion, based on day-ahead prices and forecast data. The strategy was tested in a real-world low-voltage grid in the Netherlands, solving the congestion up to the available potential. Results highlight the importance of minimizing forecast and hardware response errors to enhance control performance.