As part of the GameOpSys research project, people were asked to document their own energy consumption with a study app. Researchers at TU Graz use this data for modelling and optimising future energy systems.
As part of the GameOpSys research project, people were asked to document their own energy consumption with a study app. Researchers at TU Graz use this data for modelling and optimising future energy systems. Lunghammer - TU Graz By Christoph Pelzl Researchers at TU Graz are linking energy consumption data and user feedback with AI applications to optimize energy consumption in households, buildings and higher-level energy systems. Additional Images for download at the end of the text Wind farms and solar plants play a central role in the success of the energy transition and thus in climate protection. However, these renewable energies also cause disruptive fluctuations in the energy grid because they do not always produce energy when we consume it. This problem can be countered by a combination of interconnected systems and innovative artificial intelligence (AI)-based energy services - such as predictive control or demand side management. The Intelligent energy systems and cyber-physical systems research group at the Institute of Software Technology at Graz University of Technology (TU Graz) is working on methods to increase the efficiency and intelligence of energy system, while also taking into account the interaction between humans and technology.
TO READ THIS ARTICLE, CREATE YOUR ACCOUNT
And extend your reading, free of charge and with no commitment.
Your Benefits
- Access to all content
- Receive newsmails for news and jobs
- Post ads
