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Fuel moisture soft-sensor and its validation for the industrial BioPower 5 CHP plant

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  • Kortela, J.
  • Jämsä-Jounela, S-L.

Abstract

This paper presents a soft-sensor for on-line monitoring of fuel moisture in a furnace. The method utilizes combustion power estimation and a dynamic model of the secondary superheater. In addition, the time delays in detecting changes in moisture content of the fuel are small enough for the method to be used for controlling air and fuel feed and preventing steam and pressure oscillations. To verify the fuel moisture soft-sensor, experiments were performed at a BioPower 5 CHP plant, which utilizes BioGrate combustion technology for very wet biomass fuels with a moisture content as high as 65%. Finally, the results are analyzed and discussed.

Suggested Citation

  • Kortela, J. & Jämsä-Jounela, S-L., 2013. "Fuel moisture soft-sensor and its validation for the industrial BioPower 5 CHP plant," Applied Energy, Elsevier, vol. 105(C), pages 66-74.
    • Handle: RePEc:eee:appene:v:105:y:2013:i:c:p:66-74
    DOI: 10.1016/j.apenergy.2012.12.049
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    1. Siitonen, Sari & Tuomaala, Mari & Suominen, Markku & Ahtila, Pekka, 2010. "Implications of process energy efficiency improvements for primary energy consumption and CO2 emissions at the national level," Applied Energy, Elsevier, vol. 87(9), pages 2928-2937, September.
    2. Lian, Z.T. & Chua, K.J. & Chou, S.K., 2010. "A thermoeconomic analysis of biomass energy for trigeneration," Applied Energy, Elsevier, vol. 87(1), pages 84-95, January.
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    Cited by:

    1. Zeng, De-Liang & Hu, Yong & Gao, Shan & Liu, Ji-Zhen, 2015. "Modelling and control of pulverizing system considering coal moisture," Energy, Elsevier, vol. 80(C), pages 55-63.
    2. Kortela, J. & Jämsä-Jounela, S.-L., 2014. "Model predictive control utilizing fuel and moisture soft-sensors for the BioPower 5 combined heat and power (CHP) plant," Applied Energy, Elsevier, vol. 131(C), pages 189-200.

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