Digitally control and improve fluctuating energy processes

how the application of digital capabilities can push the energy and resource transition.

By Martina Walzer September 29, 2021
Courtesy: Siemens, New Products for Engineers Database

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 carbon source. To achieve these goals partners from science and industry are developing solutions for the sustainable management of energy and raw materials.

The Kyoto Protocol pinpoints carbon dioxide as a greenhouse gas, which heavily influences global warming. This odorless and colorless gas emerges, for example, while burning fossil energy carriers as coal, oil, or natural gas and it is the main contributor to the human-intensified greenhouse effect (anthropogenic carbon dioxide). Various estimates assume a residence time (i.e. the time until natural processes finally remove the CO2 molecule from the atmosphere) of over 100 years. It is, therefore, essential to lower emissions in the coming years.

Recycling of carbon to support the circular economy is the subject of the Carbon2Chem project. Partners from science and industry are collaborating to develop solutions, funded by the Germany Ministry of Education and Research. 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 fertilizers.

The challenges of these new processes lies in the fact that exhaust gas flows vary – in terms of both their volume and chemical composition. What is more, renewable energies – and the hydrogen they are used to produce – are not uniformly available. However, the process automation system must deliver safe, optimal control of these fluctuating processes.

Reliable basis for AI

“In this project, we collect data from multiple temperature measurements and gas analyzers 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,” said Dr. Andreas Menne, head of Low Carbon Technologies department at Fraunhofer UMSICHT. “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 enable far-reaching optimization.”

Instrumentation and control systems are effectively supporting the progress of developing the methanol synthesis out of gas streams, which fluctuate in terms of quantity and composition.

Accurate temperature profiles

Fiber-optic methods are used to determine the temperature profiles in a reactor. It enables many temperature measurements to be captured and evaluated simultaneously. Several sensors (Fiber Bragg grating (FBG)) are arranged on a very slim fiber-optic measuring lance.

A FBG is a microstructure typically of a few millimeters in length that is inscribed in the core of a standard single-mode fibre. It acts as a resonance structure for the selective reflection of wave lengths: it is a narrow-band filter. Changes in temperature and pressure cause a change in wavelength. To eliminate the influence of pressure, the FBG must not be subjected to strain when used as a temperature sensor. For this reason, the individual optical fibers, which are referred to as lances, are installed in protective tubes (metal capillaries). Due to the measured value transmission (reflection of light) in the same fibre, no additional cables are necessary. This means the cross-section of the protective tubes for the measurement setup can be substantially reduced.

The transmitter emits light in a range of 1500 to 1600 nm. Based on the reflections of the individual FBG sensors, the system calculates the temperature profile and provides the values via a Profibus interface for evaluation in the control system. This information forms the basis for implementation and optimization of the processes control as well as for management of the installed assets.

Reliable information is vital for realizing innovative processes to meet the goals of the Paris climate agreement without jeopardizing the competitiveness of energy-intensive sectors such as the chemical, steel or cement industries in Europe. Precise data evaluation in dedicated applications and implementation of the results into improved control algorithms enable economical and sustainable process control. The digitalized plant thus enables industrial applications that advance de-fossilization and modernization in line with the EU Commission’s Green Deal.

This article originally appeared on Control Engineering Europe’s website. Edited by Chris Vavra, web content manager, Control Engineering, CFE Media,

Original content can be found at

Author Bio: Martina Walzer is manager technical concepts at Siemens Digital Industries.