IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v131y2014icp189-200.html
   My bibliography  Save this article

Model predictive control utilizing fuel and moisture soft-sensors for the BioPower 5 combined heat and power (CHP) plant

Author

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

Abstract

This paper presents a model predictive control (MPC) strategy for efficient energy production in BioGrate boiler. In addition to compensating for the main disturbances caused by variations in fuel quality such as fuel moisture content, and variations in fuel feed, this strategy models water evaporation, and models and controls the fuel bed height of the grate. Usually, combustion power in a furnace have been estimated by utilizing oxygen consumption. There is however a need for more accurate prediction and control of combustion power, which is greatly affected by the fuel bed height and fuel moisture content. It is shown that water evaporation and thermal decomposition of dry fuel can be estimated by utilizing fuel moisture soft-sensor and oxygen consumption calculations respectively. As a result, the primary air can be adjusted to produce the necessary combustion power, and the power output of the boiler can be accurately predicted. This enables efficient stabilization of plant operations. To verify the model, experiments were performed at a BioPower 5 CHP plant, which utilizes BioGrate combustion technology to enable the use of wet biomass fuels with a moisture content as high as 65%. Then the MPC strategy was compared with the currently used control strategy. Finally, the results are presented, analyzed, and discussed.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:131:y:2014:i:c:p:189-200
    DOI: 10.1016/j.apenergy.2014.06.014
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261914005960
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2014.06.014?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ström, Henrik & Thunman, Henrik, 2013. "A computationally efficient particle submodel for CFD-simulations of fixed-bed conversion," Applied Energy, Elsevier, vol. 112(C), pages 808-817.
    2. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yang, Dan & Peng, Xin & Ye, Zhencheng & Lu, Yusheng & Zhong, Weimin, 2021. "Domain adaptation network with uncertainty modeling and its application to the online energy consumption prediction of ethylene distillation processes," Applied Energy, Elsevier, vol. 303(C).
    2. Alexandre Boriouchkine & Sirkka-Liisa Jämsä-Jounela, 2016. "Simplification of a Mechanistic Model of Biomass Combustion for On-Line Computations," Energies, MDPI, vol. 9(9), pages 1-25, September.
    3. Palash Sarkar & Jukka Kortela & Alexandre Boriouchkine & Elena Zattoni & Sirkka-Liisa Jämsä-Jounela, 2017. "Data-Reconciliation Based Fault-Tolerant Model Predictive Control for a Biomass Boiler," Energies, MDPI, vol. 10(2), pages 1-14, February.
    4. Ferrari, Mario L., 2015. "Advanced control approach for hybrid systems based on solid oxide fuel cells," Applied Energy, Elsevier, vol. 145(C), pages 364-373.
    5. Liang Tian & Xinping Liu & Huanhuan Luo & Tuoyu Deng & Jizhen Liu & Guiping Zhou & Tianting Zhang, 2021. "Soft Sensor of Heating Extraction Steam Flow Rate Based on Frequency Complementary Information Fusion for CHP Plant," Energies, MDPI, vol. 14(12), pages 1-17, June.
    6. Böhler, Lukas & Fallmann, Markus & Görtler, Gregor & Krail, Jürgen & Schittl, Florian & Kozek, Martin, 2021. "Emission limited model predictive control of a small-scale biomass furnace," Applied Energy, Elsevier, vol. 285(C).
    7. Böhler, Lukas & Görtler, Gregor & Krail, Jürgen & Kozek, Martin, 2019. "Carbon monoxide emission models for small-scale biomass combustion of wooden pellets," Applied Energy, Elsevier, vol. 254(C).
    8. Böhler, Lukas & Krail, Jürgen & Görtler, Gregor & Kozek, Martin, 2020. "Fuzzy model predictive control for small-scale biomass combustion furnaces," Applied Energy, Elsevier, vol. 276(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Linzheng & Zhang, Ruizhi & Deng, Ruiqu & Liu, Zeqing & Luo, Yonghao, 2023. "Comprehensive parametric study of fixed-bed co-gasification process through Multiple Thermally Thick Particle (MTTP) model," Applied Energy, Elsevier, vol. 348(C).
    2. Meng, Xiaoxiao & Sun, Rui & Ismail, Tamer M. & El-Salam, M. Abd & Zhou, Wei & Zhang, Ruihan & Ren, Xiaohan, 2018. "Assessment of primary air on corn straw in a fixed bed combustion using Eulerian-Eulerian approach," Energy, Elsevier, vol. 151(C), pages 501-519.
    3. 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.
    4. Caposciutti, Gianluca & Barontini, Federica & Antonelli, Marco & Tognotti, Leonardo & Desideri, Umberto, 2018. "Experimental investigation on the air excess and air displacement influence on early stage and complete combustion gaseous emissions of a small scale fixed bed biomass boiler," Applied Energy, Elsevier, vol. 216(C), pages 576-587.
    5. Mikulčić, Hrvoje & von Berg, Eberhard & Vujanović, Milan & Wang, Xuebin & Tan, Houzhang & Duić, Neven, 2016. "Numerical evaluation of different pulverized coal and solid recovered fuel co-firing modes inside a large-scale cement calciner," Applied Energy, Elsevier, vol. 184(C), pages 1292-1305.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:131:y:2014:i:c:p:189-200. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.