Hybrid Models for Efficient Control, Optimization, and Monitoring of Thermo-Chemical Processes and Plants

This paper describes a procedure and an IT product that combine numerical models, expert knowledge, and data-based models through artificial intelligence (AI)-based hybrid models to enable the integrated control, optimization, and monitoring of processes and plants. The working principle of the hybr...

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Bibliographic Details
Published inProcesses Vol. 9; no. 3; p. 515
Main Authors Freudenmann, Thomas, Gehrmann, Hans-Joachim, Aleksandrov, Krasimir, El-Haji, Mohanad, Stapf, Dieter
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.03.2021
Subjects
Algorithms
Artificial intelligence
Calibration
Chemical reactions
Data mining
Emissions control
Hybrid systems
Integrated control
Internet of Things
Knowledge
Maintenance costs
Monitoring
Numerical models
Optimization
Pulverized fuels
Social factors
Solid fuels
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Summary:This paper describes a procedure and an IT product that combine numerical models, expert knowledge, and data-based models through artificial intelligence (AI)-based hybrid models to enable the integrated control, optimization, and monitoring of processes and plants. The working principle of the hybrid model is demonstrated by NOx reduction through guided oscillating combustion at the pulverized fuel boiler pilot incineration plant at the Institute for Technical Chemistry, Karlsruhe Institute of Technology. The presented example refers to coal firing, but the approach can be easily applied to any other type of nitrogen-containing solid fuel. The need for a reduction in operation and maintenance costs for biomass-fired plants is huge, especially in the frame of emission reductions and, in the case of Germany, the potential loss of funding as a result of the Renewable Energy Law (Erneuerbare-Energien-Gesetz) for plants older than 20 years. Other social aspects, such as the departure of experienced personnel may be another reason for the increasing demand for data mining and the use of artificial intelligence (AI).
ISSN:2227-9717
2227-9717
DOI:10.3390/pr9030515