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Algorithms for Optimizing Energy Consumption for Fermentation Processes in Biogas Production

Author

Listed:
  • 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
    Faculty of Transport and Computer Science, WSEI University, Projektowa 4, 20-209 Lublin, Poland)

  • Tomasz Rymarczyk

    (Netrix S.A., Research and Development Center, Związkowa 26, 20-148 Lublin, Poland
    Faculty of Transport and Computer Science, WSEI University, Projektowa 4, 20-209 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)

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.

Suggested Citation

  • Grzegorz Rybak & Edward Kozłowski & Krzysztof Król & Tomasz Rymarczyk & Agnieszka Sulimierska & Artur Dmowski & Piotr Bednarczuk, 2023. "Algorithms for Optimizing Energy Consumption for Fermentation Processes in Biogas Production," Energies, MDPI, vol. 16(24), pages 1-17, December.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:24:p:7972-:d:1296763
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    References listed on IDEAS

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    2. Godfrey, Leslie G, 1978. "Testing against General Autoregressive and Moving Average Error Models When the Regressors Include Lagged Dependent Variables," Econometrica, Econometric Society, vol. 46(6), pages 1293-1301, November.
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