Data-driven analysis of complex systems (DRACOS)

The aim of the research is to solve complex problems of our time, focusing on sustainability and especially the energy transition and the power grid. Methodologically, the group “Data-driven analysis of complex systems (DRACOS)” combines exploratory data analysis, physical modeling and machine learning methods. One focus here is on the interpretability of the models: Instead of “black box” predictions, transparent models will be developed. For example, the algorithm should explain which external factors, such as the feed-in of photovoltaic systems, the current electricity price or the time of day, are relevant for a prediction of the power grid frequency or consumption. This transparency then enables synergies from machine and human models: Where is the machine better than the human? What can we learn from this for our human models and thus make them better?