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New solutions on using CO2 emissions as raw material for the chemical Industry
Fraunhofer UMSICHT and Siemens jointly develop solutions in Carbon2Chem project
Release year: 2021
The Carbon2Chem project is working on solutions to use CO2 emissions as raw material for the chemical industry. The project outcome may solve two challenges – to reduce the release of carbon-rich gases to the atmosphere and to substitute fossil raw materials as a carbon source. To achieve these goals, partners from science and industry are developing solutions for the sustainable management of energy and raw materials.  The aim is to use renewable energies to convert carbon-containing gases from steelworks into chemical raw materials such as methanol. The process needs to be designed so as to flexibly manage changes in loads. At the end, the exhaust gas from furnaces serves as input material for fuels, plastics or fertilisers.The challenges of these new processes lies in the fact that exhaust gas flows vary – in terms of both their volume and chemical composition.
The SITRANS TO500 system uses fibre optic methods to determine the temperature profiles in a reactor. It enables many temperature measurements to be captured and evaluated simultaneously. The data collection of temperature and exhaust gas compositions forms the basis for a downstream, multivariable control solution that is being developed by Siemens together with the Fraunhofer Institute UMSICHT, within the framework of Carbon2Chem.  Thanks to its scalable system architecture, SIMATIC PCS 7 enables cost-effective implementation of dedicated automation solutions and economic operation of processes.
In this project, we collect data from multiple temperature measurements and gas analysers and use AI tools to develop a multivariable control system.This leads to a more energy-efficient process, a longer service life for the catalyst as well as improved selectivity and yields. The data also helps to improve existing process-simulations and kinetic models. Both affect the cost-effectiveness and sustainability of the overall process due to model-based predictive control, predictive maintenance or co-simulation to enable far-reaching optimisation
Dr. Andreas Menne, head of Low Carbon Technologiesdepartment at Fraunhofer UMSICHT
  • Higher energy-efficiency and cost effectivenes in the process
  • longer service life of catalyst
  • improved selectivity and yields
  • enabling industrial application that advance defossilisation andmodernisation in line with the EU Commission’s Green Deal
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