Smart Energy Testbed

Demonstrating Digitization and AI for a successful energy transition!

The energy system is in the process of a radical transition: To achieve the climate goals and a sustainable energy supply, the traditional, fossil fuel-based, centrally organized supply is increasingly being replaced by volatile renewable sources such as wind and solar. At the DAI Laboratory, we are researching how digitization and artificial intelligence can counteract the challenges posed by the energy transition and enable new potentials.

In the context of the energy transition, an increasingly decentralized structure of the energy system is emerging. Local optimization of decentralized energy management in neighborhoods, buildings and households is becoming increasingly important.

In the Smart Energy Testbed, we are testing and demonstrating how this optimal interaction of producers, consumers, and storage facilities can be implemented in an intelligent decentralized energy management. Machine learning is used to create forecasts and increase energy efficiency, reduce CO2 emissions, or cut costs through optimization. If required, the electric vehicle’s mobile storage, a stationary battery, and a supercapacitor can also be used to stabilize the power grid. We also show how the user and the algorithms can interact better together, for example, by visualizing energy and grid data through Augmented- and Mixed-Reality.