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Project | EnFoSaar

Duration:
EnFoSaar Energy Research for the Saarland - Transformation to tackle climate change and structural change

EnFoSaar Energy Research for the Saarland - Transformation to tackle climate change and structural change

Application fields

The core idea behind the EnergieForschungSaar (EnFoSaar) research project is to develop a scientifically sound yet application-oriented methodology to drive forward the transformation of the Saarland’s energy sector and the research landscape required to keep pace with the speed and momentum of the impacts of climate change and the (inter)national energy transition. An efficient, climate-friendly energy supply makes a decisive contribution to shaping structural change in the Saarland's industry. The DFKI is working in the field of multi-energy systems. Multi-energy systems consider electricity, heat and hydrogen, as well as sector coupling, in their entirety. The aim is to develop models (digital twins) and AI methods to design multi-energy systems and to develop, investigate and evaluate optimal control algorithms over the entire lifetime under any boundary conditions (e.g., changing legal frameworks). The focus of this area of expertise lies in the standardization of methods, the integration of digitalization processes in the energy sector (e.g., measurement data acquisition and storage), and the development and application of AI methods (e.g., in measurement data processing). Digitalization and AI enable better integration of renewable energies, help meet rising energy demand and ensure grid stability in an increasingly decentralized and volatile energy landscape. This involves an intermodal/intersectoral systems approach, such as

  • (Decentralized) generation: (waste) heat, electricity, hydrogen
  • Sector coupling: Power2X, Vehicle2X, CO22X, CO2 pipelines
  • Storage: electricity, H2, heat
  • Flexibility: heat pumps, BEVs (battery electric vehicles)

Also important are the monitoring of energy grids, the forecasting and management of feed-in and consumption, extensive automation of multi-energy systems, anomaly detection and fault prevention, increasing the resilience of the electricity grid, the identification, forecasting and utilization of flexibility options, and the integration across different sectors (electricity, heat, mobility) and areas of use (households, commerce, industry).

Partners

  • Hochschule für Technik und Wirtschaft des Saarlandes (htw saar)
  • Universität des Saarlandes (UdS)
  • Institut für Zukunftsenergie- und Stoffstromsysteme (IZES)

Publications

  1. Chronological Inference with Latent Gaussian Distributions

    Thomas Achim Schmeyer; Remi Oguni; Julia Bayer; Boris Brandherm; Ichiro Kobayashi

    In: 2026 Joint 14th International Conference on Soft Computing and Intelligent Systems and 26th International Symposium on Advanced Intelligent Systems (SCIS&ISIS). Joint International Conference on Soft Computing and Intelligent Systems and International Symposium on Advanced Intelligent Systems (SCIS&ISIS-2026), November 2-5, Tokyo, Japan, IEEE, 2027.

Funding Authorities

Ministerium der Finanzen und für Wissenschaft