Project objective

The design of future energy systems that can cope well with fluctuating feed-in and flexible demand serves the provision of public services and corresponding research is therefore essential. One fundamental aspect is the energy consumption of complex systems, such as industrial plants or IT infrastructures. Important factors include making them more flexible so that more sustainable and locally generated energy is used, the resilience of the supply (robustness) and the efficiency of new energy systems. A prerequisite for all of this is the structured recording and evaluation of energy status data. This data describes energy supply, storage, transmission and use in the form of measured values, derived variables such as the degree of battery wear and influencing factors such as electricity prices. The collection, analysis and use of this data is the subject of this RTG. An interdisciplinary approach (computer science, engineering, economics, law) is essential. It enables us to look at new scientific challenges that we will confront doctoral students with as part of their training. One example is that reduced supply quality manifests itself in high-resolution voltage history data, but conventional query languages for time series are not ideal for searching for it. Computer scientists need help from engineers to evaluate the suitability and generality of proposed solutions. Another example is the search in market transaction data for potentially conspicuous behavior of energy market participants who exploit their market power but do not act illegally. This requires the interaction of economics and IT. In the second funding period, we want to pay more attention to 'capture' than before, ensure even more that data analysis methods are tailored to the needs of experts in the energy systems domain and, orthogonally, pay more attention to 'robustness'.

• Training of new resources that can work in data management in the energy networks domain in the future.