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Rapid Determination of Wood and Rice Husk Pellets’ Proximate Analysis and Heating Value

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  • Xiaodan Liu

    (College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China
    Key Laboratory of Spectroscopy Sensing, Ministry of Agriculture, Hangzhou 310058, China)

  • Xuping Feng

    (College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China
    Key Laboratory of Spectroscopy Sensing, Ministry of Agriculture, Hangzhou 310058, China)

  • Lingxia Huang

    (The Rural Development Academy, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China)

  • Yong He

    (College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China
    Key Laboratory of Spectroscopy Sensing, Ministry of Agriculture, Hangzhou 310058, China
    State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China)

Abstract

Biomass pellets are a potential renewable and clean energy source. With the advantages of perfect combustion performance and easy storage and transport, biomass pellets have gradually replaced fossil fuels and become widely used. Rapid and accurate determination of biomass pellets’ quality is critical to efficient energy use. Laser-induced breakdown spectroscopy (LIBS) combined with chemometric methods were utilized. The gross calorific value (CV) and ash content (Ash), volatile matter (VM) and fixed carbon (FC) were firstly measured and analyzed. LIBS spectra and their corresponding elements of biomass pellet samples were analyzed. Three quantitative analysis models for quality indexes including partial least-squares regression (PLSR), least squares-support vector machines (LS-SVM), extreme learning machines (ELM) were further built. All models performed well, especially the LS-SVM model which obtained the best determination results, with all R 2 values over 0.95. Concurrently, the modeling performance of ash was slightly better than that of the other three quality indexes, which further confirmed the feasibility of using relevant elements to predict biomass quality indexes. The overall results indicated that LIBS coupled with suitable chemometrics could be an alternative promising method to determine quality indexes of biomass pellets and further improve energy utilization by using biomass materials with better quality.

Suggested Citation

  • Xiaodan Liu & Xuping Feng & Lingxia Huang & Yong He, 2020. "Rapid Determination of Wood and Rice Husk Pellets’ Proximate Analysis and Heating Value," Energies, MDPI, vol. 13(14), pages 1-13, July.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:14:p:3741-:d:387224
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    References listed on IDEAS

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    Cited by:

    1. Erlina Yustanti & Endarto Yudo Wardhono & Anggoro Tri Mursito & Ali Alhamidi, 2021. "Types and Composition of Biomass in Biocoke Synthesis with the Coal Blending Method," Energies, MDPI, vol. 14(20), pages 1-18, October.
    2. Wentao Li & Mingfeng Wang & Fanbin Meng & Yifei Zhang & Bo Zhang, 2022. "A Review on the Effects of Pretreatment and Process Parameters on Properties of Pellets," Energies, MDPI, vol. 15(19), pages 1-23, October.
    3. Mohammad Hosseini Rahdar & Fuzhan Nasiri, 2020. "Operation Adaptation of Moving Bed Biomass Combustors under Various Waste Fuel Conditions," Energies, MDPI, vol. 13(23), pages 1-18, December.

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