Our research contributes to the energy transition by leading to the cross-sector development of new technologies for the intelligent control of future energy systems. Our research focus is the use of the latest information technologies, in particular distributed systems, data-driven control algorithms, and machine learning.
The research areas of the professorship can be divided into (1) data and models, (2) data-driven control algorithms, and (3) prototypical software systems for energy management. Areas of application cover all sectors including electricity, heat, and mobility. We are interested in both small-scale applications such as energy management in buildings and large-scale applications such as transmission grids and electricity markets.
Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our research process typically involves the following steps: (1) assessment of existing systems to understand their limitations, (2) extensive model-based analysis to explore the solution space, (3) implementation and validation of the most attractive solution. To carry out our research, we continuously develop and expand our laboratory infrastructure, which enables us to perform computationally intensive simulations and hardware-in-the-loop experiments.