Almost 50 % of annual global greenhouse gas emissions are attributable to the energy supply and industry sectors. In addition to the use of energy from renewable sources, increasing the efficiency of industrial energy systems offers great potential for moving a step closer to the climate targets defined in the Paris Agreement. The aim here is to exploit all energy-saving potentials - including those that have so far been too costly or uneconomical to tap. At the Institute of Energy Systems and Thermodynamics, the team led by Professor René Hofmann is conducting research into the innovative application of digital technologies that make it possible to operate industrial processes more efficiently and at the same time more profitable.
In the 5DIndustrialTwin research project, an interdisciplinary team from the fields of energy systems, computer science and automation are working on the development of a digital twin for use in a steel production process. In this process, a large amount of waste heat is available that could be used in other processes to reduce overall energy consumption. Utilization of the waste heat is challenging for two reasons: first, the steelmaking process is intermittent, which requires the use of a buffer tank. Secondly, the hot exhaust gas carries a lot of metal dust, which would significantly damage most storage tanks and heat exchangers. For several years, the Institute of Energy Systems and Thermodynamics has been researching technologies for thermal energy storage that can also be used under these difficult conditions. In the 5DIndustrialTwin project, a so-called packed bed regenerator, which buffers the heat from the hot and dusty exhaust gas and makes it usable at a later time, is used. The digital twin developed for this storage technology should now make it possible to design this heat recovery process efficiently and economically.
To tackle these issues, Professor Hofmann's team is developing physical and data-driven simulation models that are continuously adapted to the current state of the plant. In this way, the accumulation of dust from the hot exhaust gas in the regenerator can be taken into account and its effect on the thermal behavior of the storage tank can be compensated. Another function of the digital twin is to continuously monitor the operation of the regenerator, for example to detect clogging of the apparatus due to fouling at an early stage and to initiate the necessary maintenance steps. For this purpose, Professor Hofmann's team is developing new methods that combine simulation models, artificial intelligence, and expert knowledge.
Although the digital twin in the 5DIndustrialTwin project is being developed for a specific process, many of the newly developed concepts can also be transferred to other industrial energy systems. Through the symbiosis of state-of-the-art technologies and digital methods, the digital twin enables processes in industrial energy systems to be designed more efficiently and to significantly reduce their greenhouse gas emissions.
- Kasper, L.; Birkelbach, F.; Schwarzmayr, P.; Steindl, G.; Ramsauer, D.; Hofmann, R. Toward a Practical Digital Twin Platform Tailored to the Requirements of Industrial Energy Systems. Appl. Sci. 2022, 12, 6981.
- Schwarzmayr, P.; Birkelbach, F.; Kasper, L.; Hofmann, R. Development of a digital twin platform for industrial energy systems. Applied Energy Symposium: MIT A+B. 2022. Cambridge, USA.
- Schwarzmayr, P., Birkelbach, F., Walter, H., & Hofmann, R. (2023). Standby efficiency and thermocline degradation of a packed bed thermal energy storage: An experimental study. Applied Energy, 337, Article 120917
- Kasper, L.; Schwarzmayr, P.; Birkelbach, F.; Javernik, F.; Schwaiger, M.; Hofmann, R. (2024) A digital twin-based adaptive optimization approach applied to waste heat recovery in green steel production: Development and experimental investigation. Applied Energy, 353, Article 122192
- Schwarzmayr, P.; Birkelbach, F.; Walter, H.; Hofmann, R. (2023) Study on the Standby Characteristics of a Packed Bed Thermal Energy Storage: Experimental Results and Model Based Parameter Optimization. Proceedings of the ASME Power Applied R&D 2023, POWER2023-108578
- Schwarzmayr, P.; Birkelbach, F.; Walter, H.; Javernik, F.; Schwaiger, M.; Hofmann, R. (2024) Packed bed thermal energy storage for waste heat recovery in the iron and steel industry: A cold model study on powder hold-up and pressure drop. Journal of Energy Storage, 75, Article 109735