Research

We help building a sustainable energy future by researching new technologies for the intelligent control of renewable energy systems across sectors and industries. Our research focus is the use of novel information technologies, in particular distributed systems, data-driven control algorithms and machine learning.

We are particularly interested in the development and evaluation of new algorithms to control complex energy systems that can take full advantage of energy flexibility while satisfying all relevant constraints. Our use cases cover several levels of granularity, including (1) single devices like batteries, (2) buildings and factories, and (3) electric distribution grids. They comprise all sectors including power, heat, and mobility, as well as sector coupling scenarios.

Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our research process typically involves the following steps: (1) Evaluation of existing systems to understand their limits, (2) extensive model-based analyses to explore the design space, (3) implementation and validation of the most attractive design. To conduct our research, we are continuously developing and expanding our lab infrastructure that enables us to run computationally complex simulations and hardware-in-the-loop experiments.

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