Buildings are responsible for 40% of the primary energy demand in the EU and for a high share of peak electricity use; the bulk of it for heating and cooling. Thanks to their high thermal inertia, buildings also have a large potential for energy flexibility.
Until now, it has proven difficult to activate this latent flexibility. While digitalization is thought to be a key enabler, a major bottleneck is the fact that in most existing buildings the main energy meter data are the only data available, while the development of data services for buildings would depend on the availability of additional information, such as the split of energy use for heating and cooling.
ADRENALIN aims to develop machine learning and smart control algorithms that will enable or improve new data services such as flexible control of heating and cooling, with the ability to automatically schedule and adjust the demand in response to price signals from the energy system while safeguarding the users' comfort.
By collecting a large and varied pool of measurement data from real buildings (data sandbox), ADRENALIN will organize competitions to crowdsource solutions to specific data challenges. The best-performing solutions will be implemented in real-life conditions on the digital platforms of the partner companies to test their general validity and replicability, and to demonstrate real-life performance.
SDU Center for Energy Informatics, Denmark
External advisory group:
The project is funded by the Joint Call 2020 (MICall20) for transnational projects on digital transformation for green energy transition. The funding partners participating in the Joint Call are from ERA-Net Smart Energy Systems (ERA-Net SES) and the Mission Innovation (MI) Initiative.
Project duration: 2022-2025