Institute of Climate and Energy Systems (ICE)

Energy Systems Engineering (ICE-1)

ICE-1 develops models and algorithms for the simulation, optimization and control of energy systems, which are characterized by a high spatial and temporal variability of energy supply and demand, an increasing degree of intersectoral dependencies as well as an increasing digitalization. The focus is on multi-physical energy grids, industrial energy systems, and buildings and districts. A major goal of the research is to provide scalable and faster-than-real-time capable methods and tools that enable energy-optimal, cost-efficient and safe design and operation of these future energy systems. For this purpose, physical-technical system descriptions are combined with machine learning methods and customized simulation and optimization methods are developed especially for multicore, cluster and high-performance computers, which enable the handling of large-scale problems. With the help of the Reallabor "Living Lab Energy Campus" as well as a "Hardware-in-the-loop" laboratory, these innovative solution approaches for future energy systems are tested and validated under almost realistic conditions.

ICE-1 offers many opportunities for engineers and mathematicans to work in an interdisciplinary environment. We supervise Bachelor, Master and doctoral theses.

research groups

Energy Grids

Develops and applies models for the simulation and optimization of multi-physical energy infrastructures.

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Buildings and Districts

Develops and demonstrates innovative low-carbon and energy efficient solutions for buildings and (city) districts

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Industrial Energy Systems

Focuses on economic and low-CO2 solutions for industrial sites integrating electricity, heat, cooling, and chemical energy carriers.

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Develops and applies models for the simulation and optimization of multi-physical energy infrastructures.

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High Performance Computing

The High-Performance Computing department pursues the goal of further developing the simulation and optimization-based methods used for the planning and operation of energy systems with regard to numerical mathematics and high-performance computing.

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Control Solutions

The Control Solutions department focuses on the development of methods and algorithms for the control of power systems and their components. The focus is on application-oriented methods that can operate in real time, are scalable and are suitable for the operation of decentralized systems.

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Optimization and Machine Learning

In the Optimization and Machine Learning department, we apply and develop numerical optimization methods and algorithms for the design and operation of complex energy systems.

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Networks and Complex Systems

The department networks and complex systems develops mathematical methods and tools for a stable operation of the electric power grids. One focus of our work is the stability and robustness against outages and equipment failures.

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The High-Performance Computing department pursues the goal of further developing the simulation and optimization-based methods used for the planning and operation of energy systems with regard to numerical mathematics and high-performance computing.

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