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New method for assessing the performance of agricultural biogas plants

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  • Djatkov, Djordje
  • Effenberger, Mathias
  • Lehner, Andreas
  • Martinov, Milan
  • Tesic, Milos
  • Gronauer, Andreas

Abstract

Around 5000 agricultural biogas plants were operating in Germany by the end of 2009. There is a recognized need for their assessment, comparison and performance improvement. Prerequisites for their reliable assessment include: 1) detailed and reliable performance data, 2) defined criteria for the assessment, and 3) comprehensive method. The limitations of existing assessment methods have been reviewed. The new method developed for assessing the overall performance of biogas plants is focused on four assessment aspects: biogas production, biogas utilization, environmental impact and socio-economic efficiency. Each assessment aspect was determined by two performance criteria. The method is based on fuzzy set theory and fuzzy mathematics, which enables use of imprecise and uncertain data. Incorporation of enough expertise from the field of biogas technology was enabled in this method as well. Pre-assessment of future biogas plants in their planning phase is possible, contributing to their effective development. The reliability of the method was tested using data from ten monitored biogas plants. The assessment of the ten biogas plants showed that biogas utilization is the aspect with the largest potential for performance improvement, by increasing the external heat utilization. The method developed is adjustable to accommodate new developments related to biogas technology and biogas plants in any geographical region. Future research should be focused on definition and inclusion of more assessment criteria and on developing the methods that are capable to handle compensation between individual criteria.

Suggested Citation

  • Djatkov, Djordje & Effenberger, Mathias & Lehner, Andreas & Martinov, Milan & Tesic, Milos & Gronauer, Andreas, 2012. "New method for assessing the performance of agricultural biogas plants," Renewable Energy, Elsevier, vol. 40(1), pages 104-112.
    • Handle: RePEc:eee:renene:v:40:y:2012:i:1:p:104-112
    DOI: 10.1016/j.renene.2011.09.026
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    References listed on IDEAS

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    1. Taleghani, Giti & Shabani Kia, Akbar, 2005. "Technical–economical analysis of the Saveh biogas power plant," Renewable Energy, Elsevier, vol. 30(3), pages 441-446.
    2. Madlener, Reinhard & Antunes, Carlos Henggeler & Dias, Luis C., 2009. "Assessing the performance of biogas plants with multi-criteria and data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 197(3), pages 1084-1094, September.
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    1. Rácz, Viktor J. & Vestergaard, Niels, 2016. "Productivity and efficiency measurement of the Danish centralized biogas power sector," Renewable Energy, Elsevier, vol. 92(C), pages 397-404.
    2. Herbes, Carsten & Halbherr, Verena & Braun, Lorenz, 2018. "Factors influencing prices for heat from biogas plants," Applied Energy, Elsevier, vol. 221(C), pages 308-318.
    3. Hans-Joachim Naegele & Andreas Lemmer & Hans Oechsner & Thomas Jungbluth, 2012. "Electric Energy Consumption of the Full Scale Research Biogas Plant “Unterer Lindenhof”: Results of Longterm and Full Detail Measurements," Energies, MDPI, vol. 5(12), pages 1-17, December.
    4. Andreas Eder & Bernhard Mahlberg, 2018. "Size, Subsidies and Technical Efficiency in Renewable Energy Production: The Case of Austrian Biogas Plants," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    5. Emma Lindkvist & Maria T. Johansson & Jakob Rosenqvist, 2017. "Methodology for Analysing Energy Demand in Biogas Production Plants—A Comparative Study of Two Biogas Plants," Energies, MDPI, vol. 10(11), pages 1-20, November.
    6. Djatkov, Djordje & Effenberger, Mathias & Martinov, Milan, 2014. "Method for assessing and improving the efficiency of agricultural biogas plants based on fuzzy logic and expert systems," Applied Energy, Elsevier, vol. 134(C), pages 163-175.
    7. Batas-Bjelic, Ilija & Rajakovic, Nikola & Duic, Neven, 2017. "Smart municipal energy grid within electricity market," Energy, Elsevier, vol. 137(C), pages 1277-1285.
    8. Brudermann, Thomas & Mitterhuber, Corinna & Posch, Alfred, 2015. "Agricultural biogas plants – A systematic analysis of strengths, weaknesses, opportunities and threats," Energy Policy, Elsevier, vol. 76(C), pages 107-111.
    9. Havukainen, J. & Uusitalo, V. & Niskanen, A. & Kapustina, V. & Horttanainen, M., 2014. "Evaluation of methods for estimating energy performance of biogas production," Renewable Energy, Elsevier, vol. 66(C), pages 232-240.
    10. Suganthi, L. & Iniyan, S. & Samuel, Anand A., 2015. "Applications of fuzzy logic in renewable energy systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 585-607.
    11. De Clercq, Djavan & Wen, Zongguo & Caicedo, Luis & Cao, Xin & Fan, Fei & Xu, Ruifei, 2017. "Application of DEA and statistical inference to model the determinants of biomethane production efficiency: A case study in south China," Applied Energy, Elsevier, vol. 205(C), pages 1231-1243.
    12. Parisa Kazemiani-Najafabadi & Ehsan Amiri Rad, 2020. "Optimizing the bio/natural gas ratio in a dual-fuel gas turbine (DFGT) through energy-economic, environmental, and renewability analyses," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(6), pages 5371-5386, August.

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