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Reinforcement Learning improves the energy efficiency of battery storage systems
The KI-M-Bat project has developed a reinforcement learning-based control strategy and successfully deployed it on a real-world battery storage…
The research professorship in “Smart Energy Systems” was instated at Kempten University of Applied Sciences in autumn 2022. The aim of the research group is to use modern optimisation processes and machine learning methods to enable the optimal design and operational management of battery storage systems in energy systems. With regard to the sustainability of our energy system, existing technical solutions are optimised in terms of functionality, efficiency and flexibility. Professor Holger Hesse – previously a research group leader at the Technical University of Munich – has been working for some time on the design and operation of stationary battery storage systems in applications within the energy industry.
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The KI-M-Bat project has developed a reinforcement learning-based control strategy and successfully deployed it on a real-world battery storage…

Test facilities on campus and at industry partners
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The installation of Fenecon battery systems in the KATEK and Fahrzeugtechniklabor is revolutionizing energy management. Optimum power split, advanced…

Kempten University of Applied Sciences hosted the SMA workshop, at which leading experts from industry and research discussed the latest approaches…
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