Algorithms for Optimizing Energy Consumption for Fermentation Processes in Biogas Production

Grzegorz Rybak (), Edward Kozłowski, Krzysztof Król, Tomasz Rymarczyk, Agnieszka Sulimierska, Artur Dmowski and Piotr Bednarczuk
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Grzegorz Rybak: Netrix S.A., Research and Development Center, Związkowa 26, 20-148 Lublin, Poland
Edward Kozłowski: Faculty of Management, Lublin University of Technology, Nadbystrzycka 38, 20-618 Lublin, Poland
Krzysztof Król: Netrix S.A., Research and Development Center, Związkowa 26, 20-148 Lublin, Poland
Tomasz Rymarczyk: Netrix S.A., Research and Development Center, Związkowa 26, 20-148 Lublin, Poland
Agnieszka Sulimierska: Faculty of Management, Lublin University of Technology, Nadbystrzycka 38, 20-618 Lublin, Poland
Artur Dmowski: Faculty of Transport and Computer Science, WSEI University, Projektowa 4, 20-209 Lublin, Poland
Piotr Bednarczuk: Faculty of Transport and Computer Science, WSEI University, Projektowa 4, 20-209 Lublin, Poland

Energies, 2023, vol. 16, issue 24, 1-17

Abstract: Problems related to reducing energy consumption constitute an important basis for scientific research worldwide. A proposal to use various renewable energy sources, including creating a biogas plant, is emphasized in the introduction of this article. However, the indicated solutions require continuous monitoring and control to maximise the installations’ effectiveness. The authors took up the challenge of developing a computer solution to reduce the costs of maintaining technological process monitoring systems. Concept diagrams of a metrological system using multi-sensor techniques containing humidity, temperature and pressure sensors coupled with Electrical Impedance Tomography (EIT) sensors were presented. This approach allows for effective monitoring of the anaerobic fermentation process. The possibility of reducing the energy consumed during installation operation was proposed, which resulted in the development of algorithms for determining alarm states, which are the basis for controlling the frequency of technological process measurements. Implementing the idea required the preparation of measurement infrastructure and an analytical engine based on AI techniques, including an expert system and developed algorithms. Numerous time-consuming studies and experiments have confirmed reduced energy consumption, which can be successfully used in biogas production.

Keywords: biogas; sensors; EIT; energy consumption optimization; expert systems; AI (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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