FH Bielefeld
University of
Applied Sciences


Autonomous AI for cellular energy systems increasing flexibilities
provided by sector coupling and distributed storage

The cellular approach addresses decentralized, self-governed energy cells on all hierarchical grid levels. Every cell can encompass electric, gas and district heating grids achieving high efficiency and flexibility due to sector coupling and energy storage solutions such as batteries and Power-to-X systems. Compared to conventional grid operation, each cell optimizes its renewable power generation, energy consumption and storing on a much finer granularity level and a much higher level of complexity of the optimisation due to a high number of participants. In order to address this challenge, an autonomous AI-based cell optimizer will be developed for the efficient energy management of a multitude of energy storage devices from the perspective of an energy cell. The AI-based control is integrated and demonstrated under real-world conditions by means of a Digital Twin of the energy system serving as a coherent information and interaction layer for all market participants.

Fachhochschule Bielefeld, Technische Universität Kaiserslautern, Graz University of Technology, Stadtwerke Bielefeld GmbH, Voltaris GmbH, Omnetric, Wiener Netze

ERA-Net Smart Energy Systems