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Feed control of anaerobic digestion processes for renewable energy production: A review

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  • Gaida, Daniel
  • Wolf, Christian
  • Bongards, Michael

Abstract

Over the last 40 years many different control methodologies for substrate feed control of anaerobic digestion processes have been proposed in order to increase plant efficiency and sustainable long-term energy production. This review shows that although sophisticated controllers exist, full-scale biogas plants are mostly still operated without a closed-loop feed control. No matter which application, such control always has to find a compromise between maximizing economic yield, minimizing the ecological footprint and minimizing the risk of process failure. For anaerobic wastewater treatment, control systems which come close to this ideal, exist, but for agricultural as well as industrial biogas plants such control has not yet been developed and neither been successfully implemented and validated at full-scale. Main challenges are a lack of robust and reliable process monitoring using online instrumentation as well as a conservative industry which is reluctant towards the implementation of fully automated process control strategies.

Suggested Citation

  • Gaida, Daniel & Wolf, Christian & Bongards, Michael, 2017. "Feed control of anaerobic digestion processes for renewable energy production: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P2), pages 869-875.
  • Handle: RePEc:eee:rensus:v:68:y:2017:i:p2:p:869-875
    DOI: 10.1016/j.rser.2016.06.096
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    References listed on IDEAS

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    1. Appels, Lise & Lauwers, Joost & Degrève, Jan & Helsen, Lieve & Lievens, Bart & Willems, Kris & Van Impe, Jan & Dewil, Raf, 2011. "Anaerobic digestion in global bio-energy production: Potential and research challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4295-4301.
    2. Madsen, Michael & Holm-Nielsen, Jens Bo & Esbensen, Kim H., 2011. "Monitoring of anaerobic digestion processes: A review perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(6), pages 3141-3155, August.
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    3. Sakiewicz, P. & Piotrowski, K. & Ober, J. & Karwot, J., 2020. "Innovative artificial neural network approach for integrated biogas – wastewater treatment system modelling: Effect of plant operating parameters on process intensification," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
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    7. Francesco Calise & Mário Costa & Qiuwang Wang & Xiliang Zhang & Neven Duić, 2018. "Recent Advances in the Analysis of Sustainable Energy Systems," Energies, MDPI, vol. 11(10), pages 1-30, September.

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