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used in this project. The overall goal of the project is to use AI to optimize combustion in real time and select which combustion mode is the best at each instance. The AI controlled engine will rely
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, optimization, control, game theory, and machine learning. Interdisciplinary by design: Work at the intersection of energy systems and markets, privacy and cybersecurity, forecasting, optimization, control, game
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challenges. This PhD project aims to advance the efficient, controllable, and optimized use of renewable energy by integration of advanced TES technologies (latent heat and thermochemical storage) in
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with PV generation. The research will contribute to developing management and real-time operation tools to coordinate and optimize charging with PV production, while also enabling grid services
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-enhanced exact methods, particularly focusing on Column Generation (and Branch-and-Price), to improve scalability and convergence in solving complex optimization problems. In collaboration with your