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Experimental-data-based, easy-to-use product gas composition prediction of a commercial open-top gasifier based on commercially used properties of softwood chips

Author

Listed:
  • Zachl, Angelika
  • Buchmayr, Markus
  • Gruber, Johann
  • Anca-Couce, Andrés
  • Scharler, Robert
  • Hochenauer, Christoph

Abstract

The high fuel requirements for downdraft gasifiers prevent the technology's breakthrough. To identify the limitations for the woodchips fines content (FC), bark content (BC) and water content (WC), this work developed novel and easy-to-use functions to predict the gas composition based on these fuel properties. While previous prediction tools require the elemental fuel composition, the presented tool uses only typical commercial fuel properties. Multivariate polynomial regression is performed using 24 different operating points of an 85-kW open-top gasifier. The evaluations revealed three novel findings: (1) The polynomial functions of first order were the most suitable to describe the effects of the fuel properties on the gas composition. (2) According to the developed approach, the optimum fuel leading to the highest product gas lower heating value and a total hydrocarbon content below 8000 ppm contains 0 m% FC, 6.1 m% BC and 7.2 m% WC. (3) The achieved average deviation of the predicted gas composition compared to the measured one was in the same range as the typical variations between experiments. Therefore, a satisfying accuracy was achieved. The developed functions can be applied in academia and industry to identify suitable woodchips and to predict the gas quality when buying woodchips.

Suggested Citation

  • Zachl, Angelika & Buchmayr, Markus & Gruber, Johann & Anca-Couce, Andrés & Scharler, Robert & Hochenauer, Christoph, 2024. "Experimental-data-based, easy-to-use product gas composition prediction of a commercial open-top gasifier based on commercially used properties of softwood chips," Renewable Energy, Elsevier, vol. 226(C).
    • Handle: RePEc:eee:renene:v:226:y:2024:i:c:s0960148124004725
    DOI: 10.1016/j.renene.2024.120407
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    References listed on IDEAS

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    1. Maximilian Robert Heinrich & André Herrmann & Andy Gradel & Marco Klemm & Tobias Plessing, 2023. "Extensive Experimental Characterization with Kinetic Data for the Gasification Simulation of Solid Biofuels," Energies, MDPI, vol. 16(6), pages 1-31, March.
    2. Zachl, A. & Buchmayr, M. & Gruber, J. & Anca-Couce, A. & Scharler, R. & Hochenauer, C., 2022. "Evaluation and extension of the load and fuel flexibility limits of a stratified downdraft gasifier," Energy, Elsevier, vol. 239(PD).
    3. Benedikt, Florian & Kuba, Matthias & Schmid, Johannes Christian & Müller, Stefan & Hofbauer, Hermann, 2019. "Assessment of correlations between tar and product gas composition in dual fluidized bed steam gasification for online tar prediction," Applied Energy, Elsevier, vol. 238(C), pages 1138-1149.
    4. Giulio Allesina & Simone Pedrazzi, 2021. "Barriers to Success: A Technical Review on the Limits and Possible Future Roles of Small Scale Gasifiers," Energies, MDPI, vol. 14(20), pages 1-23, October.
    5. Situmorang, Yohanes Andre & Zhao, Zhongkai & Yoshida, Akihiro & Abudula, Abuliti & Guan, Guoqing, 2020. "Small-scale biomass gasification systems for power generation (<200 kW class): A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 117(C).
    6. Martínez, Laura V. & Rubiano, Jairo E. & Figueredo, Manuel & Gómez, María F., 2020. "Experimental study on the performance of gasification of corncobs in a downdraft fixed bed gasifier at various conditions," Renewable Energy, Elsevier, vol. 148(C), pages 1216-1226.
    7. Elmaz, Furkan & Yücel, Özgün & Mutlu, Ali Yener, 2020. "Predictive modeling of biomass gasification with machine learning-based regression methods," Energy, Elsevier, vol. 191(C).
    8. Anca-Couce, A. & Hochenauer, C. & Scharler, R., 2021. "Bioenergy technologies, uses, market and future trends with Austria as a case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    9. Gendek, Arkadiusz & Piętka, Jacek & Aniszewska, Monika & Malaťák, Jan & Velebil, Jan & Tamelová, Barbora & Krilek, Jozef & Moskalik, Tadeusz, 2023. "Energy value of silver fir (Abies alba) and Norway spruce (Picea abies) wood depending on the degree of its decomposition by selected fungal species," Renewable Energy, Elsevier, vol. 215(C).
    10. Huchon, Valentin & Pinta, François & Commandré, Jean-Michel & Van De Steene, Laurent, 2020. "How electrical engine power load and feedstock moisture content affect the performance of a fixed bed gasification genset," Energy, Elsevier, vol. 197(C).
    11. HajiHashemi, MohammadSina & Mazhkoo, Shahin & Dadfar, Hossein & Livani, Ehsan & Naseri Varnosefaderani, Aliakbar & Pourali, Omid & Najafi Nobar, Shima & Dutta, Animesh, 2023. "Combined heat and power production in a pilot-scale biomass gasification system: Experimental study and kinetic simulation using ASPEN Plus," Energy, Elsevier, vol. 276(C).
    12. Vikram, Shruti & Deore, Sujeetkumar P. & De Blasio, Cataldo & Mahajani, Sanjay M. & Kumar, Sandeep, 2023. "Air gasification of high-ash solid waste in a pilot-scale downdraft gasifier: Experimental and numerical analysis," Energy, Elsevier, vol. 270(C).
    13. Zachl, A. & Soria-Verdugo, A. & Buchmayr, M. & Gruber, J. & Anca-Couce, A. & Scharler, R. & Hochenauer, C., 2022. "Stratified downdraft gasification of wood chips with a significant bark content," Energy, Elsevier, vol. 261(PB).
    14. Rajat Kumar Sharma & Mohammad Ali Nazari & Juma Haydary & Triveni Prasad Singh & Sandip Mandal, 2023. "A Review on Advanced Processes of Biohydrogen Generation from Lignocellulosic Biomass with Special Emphasis on Thermochemical Conversion," Energies, MDPI, vol. 16(17), pages 1-27, September.
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