Digital integration of multi-energy flexibility assets in Regional Energy Systems (DigiRES)

Our new CETP project DigiRES is aiming for demonstrations of semi/self-learning AI models for prediction and optimization of multi-energy systems in a living lab, residential households, industrial parks, and campus buildings in three countries.

DigiRES aims to enable the concept of Flexibility-as-a-Service (FaaS), which can integrate a wide range of multi-energy flexibility assets, mapping optimally to available market products, to support the resilient and secure energy transition. An Internet-of-Energy (IoE) platform will be developed to connect to assets on the local and regional energy layers.

DigiRES will explore potential uses of semi/self-learning AI models that can deliver results comparable with cloud-based fully supervised AI models in prediction and optimisation tasks. This novel approach addresses privacy-preserving and cyber-security needs of the developed IoE platform, thus increasing engagement of end-users and stakeholders in using FaaS. The FaaS model is not a one-size-fits-all solution but is inherently adaptable and can be tailored to meet specific requirements of regional contexts, ensuring its relevance and applicability across diverse energy ecosystems.

The project will offer demonstrations in a living lab, residential households, industrial parks, and campus buildings in three member countries. 

Facts
Our new project is financed by CETP through Energimyndigheten and project partners are: Eindhoven University of Technology, Chalmers University of Technology, Ericsson AB, Catholic University of Leuven, SB-InnovaEnergie, Centrica Business Solution Belgium, Befo Almelo BV, PLS Energy Systems, Gislaved Energy park, Akademiska Hus.