PhD in AI-driven Fair Energy Curtailment Policies

PhD position in AI-driven control algorithms for distributed energy resources in electrical grids. You will design fairness-aware, AI-integrated distributed optimization methods to manage congestion in electricity distribution networks. Key responsibilities include: reviewing congestion management literature, analyzing distributed optimization methods (consensus-based, ADMM, multi-agent MPC), developing probabilistic curtailment policies grounded in fairness theory, designing fairness-aware distributed controllers, modeling uncertainty in renewable generation, evaluating robustness under forecasting errors and communication delays, implementing multi-agent coordination mechanisms, simulating large-scale distribution networks, collaborating with energy system experts, and validating methods on real-world Dutch DSO data. This is part of the RAICES project at TU/e's Control Systems group, requiring interdisciplinary collaboration across electrical engineering, control, machine learning, and sociotechnical design.