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Experimental evaluation and ANN modeling of a recuperative micro gas turbine burning mixtures of natural gas and biogas

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  • Nikpey, H.
  • Assadi, M.
  • Breuhaus, P.
  • Mørkved, P.T.

Abstract

Previously published studies have addressed modifications to the engines when operating with biogas, i.e. a low heating value fuel. This study focuses on mapping out the possible biogas share in a fuel mixture of biogas and natural gas in micro combined heat and power (CHP) installations without any engine modifications. This contributes to a reduction in CO2 emissions from existing CHP installations and makes it possible to avoid a costly upgrade of biogas to the natural gas quality as well as engine modifications. Moreover, this approach allows the use of natural gas as a “fallback” solution in the case of eventual variations of the biogas composition and or shortage of biogas, providing improved availability.

Suggested Citation

  • Nikpey, H. & Assadi, M. & Breuhaus, P. & Mørkved, P.T., 2014. "Experimental evaluation and ANN modeling of a recuperative micro gas turbine burning mixtures of natural gas and biogas," Applied Energy, Elsevier, vol. 117(C), pages 30-41.
    • Handle: RePEc:eee:appene:v:117:y:2014:i:c:p:30-41
    DOI: 10.1016/j.apenergy.2013.11.074
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    References listed on IDEAS

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    1. Basrawi, Mohamad Firdaus Bin & Yamada, Takanobu & Nakanishi, Kimio & Katsumata, Hideaki, 2012. "Analysis of the performances of biogas-fuelled micro gas turbine cogeneration systems (MGT-CGSs) in middle- and small-scale sewage treatment plants: Comparison of performances and optimization of MGTs," Energy, Elsevier, vol. 38(1), pages 291-304.
    2. Fast, M. & Assadi, M. & De, S., 2009. "Development and multi-utility of an ANN model for an industrial gas turbine," Applied Energy, Elsevier, vol. 86(1), pages 9-17, January.
    3. Bruno, Joan Carles & Ortega-López, Víctor & Coronas, Alberto, 2009. "Integration of absorption cooling systems into micro gas turbine trigeneration systems using biogas: Case study of a sewage treatment plant," Applied Energy, Elsevier, vol. 86(6), pages 837-847, June.
    4. Smrekar, J. & Assadi, M. & Fast, M. & Kuštrin, I. & De, S., 2009. "Development of artificial neural network model for a coal-fired boiler using real plant data," Energy, Elsevier, vol. 34(2), pages 144-152.
    5. Nikpey, H. & Assadi, M. & Breuhaus, P., 2013. "Development of an optimized artificial neural network model for combined heat and power micro gas turbines," Applied Energy, Elsevier, vol. 108(C), pages 137-148.
    6. De, S. & Kaiadi, M. & Fast, M. & Assadi, M., 2007. "Development of an artificial neural network model for the steam process of a coal biomass cofired combined heat and power (CHP) plant in Sweden," Energy, Elsevier, vol. 32(11), pages 2099-2109.
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