HDS-LEE

Goals:

Addressing the challenge of developing renewable energy systems by focusing on the design and control of decentralized, integrated energy networks through data science. This requires collecting and processing large volumes of operational data, which are analyzed using high-performance simulations, optimization algorithms, and data-driven models.

Contribution from ICE-1:

- Applying explainable Artificial Intelligence (XAI) to both real-world and simulated data to identify key factors for resilient low-carbon power systems.

- Using reinforcement learning and Koopman theory to learn task-optimal dynamic surrogate models for real-time capable operational optimization of complex energy systems components.

- Leveraging semi-infinite programming to identify sustainable and robust designs for isolated energy systems