IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v167y2021icp425-432.html
   My bibliography  Save this article

Machine learning application to predict yields of solid products from biomass torrefaction

Author

Listed:
  • Onsree, Thossaporn
  • Tippayawong, Nakorn

Abstract

Machine learning was used to develop a model that had the capability to predict yields of solid products from biomass torrefaction using input features of biomass properties and torrefaction conditions. With ten-fold cross-validation, several machine learning algorithms were evaluated, and their hyper-parameters were optimized by a full-factor grid search. Gradient tree boosting algorithm was found to have the highest prediction accuracy with R2 of about 0.90 and an average error of 0.07 w/w. Six highly important features on making predictions of the model were torrefaction temperature, residence time, and O2 concentration in the reacting gas for torrefaction conditions, as well as volatile matter, carbon content, and oxygen content for biomass properties. Unlike the carbon content, the other features were found to have a negative effect on the yields of torrefied biomass. The biomass property features contributed to the solid yields for about 30%, with approximately one-third accounted by the volatile matter.

Suggested Citation

  • Onsree, Thossaporn & Tippayawong, Nakorn, 2021. "Machine learning application to predict yields of solid products from biomass torrefaction," Renewable Energy, Elsevier, vol. 167(C), pages 425-432.
    • Handle: RePEc:eee:renene:v:167:y:2021:i:c:p:425-432
    DOI: 10.1016/j.renene.2020.11.099
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148120318516
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2020.11.099?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. Álvarez, Ana & Nogueiro, Dositeo & Pizarro, Consuelo & Matos, María & Bueno, Julio L., 2018. "Non-oxidative torrefaction of biomass to enhance its fuel properties," Energy, Elsevier, vol. 158(C), pages 1-8.
    2. Elmaz, Furkan & Yücel, Özgün & Mutlu, Ali Yener, 2020. "Predictive modeling of biomass gasification with machine learning-based regression methods," Energy, Elsevier, vol. 191(C).
    3. Mohd Faizal, Hasan & Shamsuddin, Hielfarith Suffri & M. Heiree, M. Harif & Muhammad Ariff Hanaffi, Mohd Fuad & Abdul Rahman, Mohd Rosdzimin & Rahman, Md. Mizanur & Latiff, Z.A., 2018. "Torrefaction of densified mesocarp fibre and palm kernel shell," Renewable Energy, Elsevier, vol. 122(C), pages 419-428.
    4. Prins, Mark J. & Ptasinski, Krzysztof J. & Janssen, Frans J.J.G., 2006. "More efficient biomass gasification via torrefaction," Energy, Elsevier, vol. 31(15), pages 3458-3470.
    5. Singh, Satyansh & Chakraborty, Jyoti Prasad & Mondal, Monoj Kumar, 2020. "Torrefaction of woody biomass (Acacia nilotica): Investigation of fuel and flow properties to study its suitability as a good quality solid fuel," Renewable Energy, Elsevier, vol. 153(C), pages 711-724.
    6. Barskov, Stan & Zappi, Mark & Buchireddy, Prashanth & Dufreche, Stephen & Guillory, John & Gang, Daniel & Hernandez, Rafael & Bajpai, Rakesh & Baudier, Jeff & Cooper, Robbyn & Sharp, Richard, 2019. "Torrefaction of biomass: A review of production methods for biocoal from cultured and waste lignocellulosic feedstocks," Renewable Energy, Elsevier, vol. 142(C), pages 624-642.
    7. Zhang, Zhiqing & Duan, Hanqi & Zhang, Youjun & Guo, Xiaojuan & Yu, Xi & Zhang, Xingguang & Rahman, Md. Maksudur & Cai, Junmeng, 2020. "Investigation of kinetic compensation effect in lignocellulosic biomass torrefaction: Kinetic and thermodynamic analyses," Energy, Elsevier, vol. 207(C).
    8. Fan, Yuyang & Tippayawong, Nakorn & Wei, Guoqiang & Huang, Zhen & Zhao, Kun & Jiang, Liqun & Zheng, Anqing & Zhao, Zengli & Li, Haibin, 2020. "Minimizing tar formation whilst enhancing syngas production by integrating biomass torrefaction pretreatment with chemical looping gasification," Applied Energy, Elsevier, vol. 260(C).
    9. Singh, Rishikesh Kumar & Chakraborty, Jyoti Prasad & Sarkar, Arnab, 2020. "Optimizing the torrefaction of pigeon pea stalk (cajanus cajan) using response surface methodology (RSM) and characterization of solid, liquid and gaseous products," Renewable Energy, Elsevier, vol. 155(C), pages 677-690.
    10. Bai, Xiaopeng & Wang, Guanghui & Zhu, Zheng & Cai, Chen & Wang, Zhiqin & Wang, Decheng, 2020. "Investigation of improving the yields and qualities of pyrolysis products with combination rod-milled and torrefaction pretreatment," Renewable Energy, Elsevier, vol. 151(C), pages 446-453.
    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. Xiaorui Liu & Haiping Yang & Jiamin Yang & Fang Liu, 2022. "Application of Random Forest Model Integrated with Feature Reduction for Biomass Torrefaction," Sustainability, MDPI, vol. 14(23), pages 1-11, December.
    2. Kartal, Furkan & Özveren, Uğur, 2022. "Prediction of torrefied biomass properties from raw biomass," Renewable Energy, Elsevier, vol. 182(C), pages 578-591.
    3. Rahimi, Mohammad & Abbaspour-Fard, Mohammad Hossein & Rohani, Abbas, 2021. "A multi-data-driven procedure towards a comprehensive understanding of the activated carbon electrodes performance (using for supercapacitor) employing ANN technique," Renewable Energy, Elsevier, vol. 180(C), pages 980-992.
    4. Potnuri, Ramesh & Suriapparao, Dadi V. & Sankar Rao, Chinta & Sridevi, Veluru & Kumar, Abhishankar, 2022. "Effect of dry torrefaction pretreatment of the microwave-assisted catalytic pyrolysis of biomass using the machine learning approach," Renewable Energy, Elsevier, vol. 197(C), pages 798-809.
    5. Zhao, Chenxi & Lu, Xueying & Jiang, Zihao & Ma, Huan & Chen, Juhui & Liu, Xiaogang, 2024. "Prediction of bio-oil yield by machine learning model based on 'enhanced data' training," Renewable Energy, Elsevier, vol. 225(C).
    6. Suvarna, Manu & Jahirul, Mohammad Islam & Aaron-Yeap, Wai Hung & Augustine, Cheryl Valencia & Umesh, Anushri & Rasul, Mohammad Golam & Günay, Mehmet Erdem & Yildirim, Ramazan & Janaun, Jidon, 2022. "Predicting biodiesel properties and its optimal fatty acid profile via explainable machine learning," Renewable Energy, Elsevier, vol. 189(C), pages 245-258.
    7. He, Ke & Ye, Lihong & Li, Fanlue & Chang, Huayi & Wang, Anbang & Luo, Sixuan & Zhang, Junbiao, 2022. "Using cognition and risk to explain the intention-behavior gap on bioenergy production: Based on machine learning logistic regression method," Energy Economics, Elsevier, vol. 108(C).
    8. Xiaorui Liu & Haiping Yang & Jiamin Yang & Fang Liu, 2023. "Prediction of Fuel Properties of Torrefied Biomass Based on Back Propagation Neural Network Hybridized with Genetic Algorithm Optimization," Energies, MDPI, vol. 16(3), pages 1-11, February.
    9. Liu, Shanke & Yang, Yan & Yu, Lijun & Cao, Yu & Liu, Xinyi & Yao, Anqi & Cao, Yaping, 2023. "Self-heating optimization of integrated system of supercritical water gasification of biomass for power generation using artificial neural network combined with process simulation," Energy, Elsevier, vol. 272(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. Onsree, Thossaporn & Tippayawong, Nakorn & Phithakkitnukoon, Santi & Lauterbach, Jochen, 2022. "Interpretable machine-learning model with a collaborative game approach to predict yields and higher heating value of torrefied biomass," Energy, Elsevier, vol. 249(C).
    2. Duan, Hanqi & Zhang, Zhiqing & Rahman, Md Maksudur & Guo, Xiaojuan & Zhang, Xingguang & Cai, Junmeng, 2020. "Insight into torrefaction of woody biomass: Kinetic modeling using pattern search method," Energy, Elsevier, vol. 201(C).
    3. Feng, Yipeng & Qiu, Keying & Zhang, Zhiping & Li, Chong & Rahman, Md. Maksudur & Cai, Junmeng, 2022. "Distributed activation energy model for lignocellulosic biomass torrefaction kinetics with combined heating program," Energy, Elsevier, vol. 239(PC).
    4. Cheng, Wei & Shao, Jing'ai & Zhu, Youjian & Zhang, Wennan & Jiang, Hao & Hu, Junhao & Zhang, Xiong & Yang, Haiping & Chen, Hanping, 2022. "Effect of oxidative torrefaction on particulate matter emission from agricultural biomass pellet combustion in comparison with non-oxidative torrefaction," Renewable Energy, Elsevier, vol. 189(C), pages 39-51.
    5. Sukiran, Mohamad Azri & Wan Daud, Wan Mohd Ashri & Abnisa, Faisal & Nasrin, Abu Bakar & Abdul Aziz, Astimar & Loh, Soh Kheang, 2021. "A comprehensive study on torrefaction of empty fruit bunches: Characterization of solid, liquid and gas products," Energy, Elsevier, vol. 230(C).
    6. Ong, Hwai Chyuan & Yu, Kai Ling & Chen, Wei-Hsin & Pillejera, Ma Katreena & Bi, Xiaotao & Tran, Khanh-Quang & Pétrissans, Anelie & Pétrissans, Mathieu, 2021. "Variation of lignocellulosic biomass structure from torrefaction: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    7. Abdulyekeen, Kabir Abogunde & Umar, Ahmad Abulfathi & Patah, Muhamad Fazly Abdul & Daud, Wan Mohd Ashri Wan, 2021. "Torrefaction of biomass: Production of enhanced solid biofuel from municipal solid waste and other types of biomass," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    8. Sui, Haiqing & Chen, Jianfeng & Cheng, Wei & Zhu, Youjian & Zhang, Wennan & Hu, Junhao & Jiang, Hao & Shao, Jing'ai & Chen, Hanping, 2024. "Effect of oxidative torrefaction on fuel and pelletizing properties of agricultural biomass in comparison with non-oxidative torrefaction," Renewable Energy, Elsevier, vol. 226(C).
    9. Huang, Shengxiong & Lei, Can & Qin, Jie & Yi, Cheng & Chen, Tao & Yao, Lingling & Li, Bo & Wen, Yujiao & Zhou, Zhi & Xia, Mao, 2022. "Properties, kinetics and pyrolysis products distribution of oxidative torrefied camellia shell in different oxygen concentration," Energy, Elsevier, vol. 251(C).
    10. Devaraja, Udya Madhavi Aravindi & Senadheera, Sachini Supunsala & Gunarathne, Duleeka Sandamali, 2022. "Torrefaction severity and performance of Rubberwood and Gliricidia," Renewable Energy, Elsevier, vol. 195(C), pages 1341-1353.
    11. Abdul Waheed & Salman Raza Naqvi & Imtiaz Ali, 2022. "Co-Torrefaction Progress of Biomass Residue/Waste Obtained for High-Value Bio-Solid Products," Energies, MDPI, vol. 15(21), pages 1-20, November.
    12. Singh, Rishikesh Kumar & Sarkar, Arnab & Chakraborty, Jyoti Prasad, 2020. "Effect of torrefaction on the physicochemical properties of eucalyptus derived biofuels: estimation of kinetic parameters and optimizing torrefaction using response surface methodology (RSM)," Energy, Elsevier, vol. 198(C).
    13. Głód, Krzysztof & Lasek, Janusz A. & Supernok, Krzysztof & Pawłowski, Przemysław & Fryza, Rafał & Zuwała, Jarosław, 2023. "Torrefaction as a way to increase the waste energy potential," Energy, Elsevier, vol. 285(C).
    14. Lin, Yi-Li & Zheng, Nai-Yun, 2021. "Torrefaction of fruit waste seed and shells for biofuel production with reduced CO2 emission," Energy, Elsevier, vol. 225(C).
    15. Tsai, Wen-Tien & Lin, Yu-Quan & Tsai, Chi-Hung & Chung, Mei-Hua & Chu, Ming-Hung & Huang, Hung-Ju & Jao, Ya-Hsuan & Yeh, Showin-Ing, 2020. "Conversion of water caltrop husk into torrefied biomass by torrefaction," Energy, Elsevier, vol. 195(C).
    16. Krochmalny, Krystian & Niedzwiecki, Lukasz & Pelińska-Olko, Ewa & Wnukowski, Mateusz & Czajka, Krzysztof & Tkaczuk-Serafin, Monika & Pawlak-Kruczek, Halina, 2020. "Determination of the marker for automation of torrefaction and slow pyrolysis processes – A case study of spherical wood particles," Renewable Energy, Elsevier, vol. 161(C), pages 350-360.
    17. A. Silveira, Edgar & Santanna Chaves, Bruno & Macedo, Lucélia & Ghesti, Grace F. & Evaristo, Rafael B.W. & Cruz Lamas, Giulia & Luz, Sandra M. & Protásio, Thiago de Paula & Rousset, Patrick, 2023. "A hybrid optimization approach towards energy recovery from torrefied waste blends," Renewable Energy, Elsevier, vol. 212(C), pages 151-165.
    18. Chai, Meiyun & Xie, Li & Yu, Xi & Zhang, Xingguang & Yang, Yang & Rahman, Md. Maksudur & Blanco, Paula H. & Liu, Ronghou & Bridgwater, Anthony V. & Cai, Junmeng, 2021. "Poplar wood torrefaction: Kinetics, thermochemistry and implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    19. Oh, Kwang Cheol & Park, Sun Young & Kim, Seok Jun & Choi, Yun Sung & Lee, Chung Geon & Cho, La Hoon & Kim, Dae Hyun, 2019. "Development and validation of mass reduction model to optimize torrefaction for agricultural byproduct biomass," Renewable Energy, Elsevier, vol. 139(C), pages 988-999.
    20. Piotr Piersa & Szymon Szufa & Justyna Czerwińska & Hilal Ünyay & Łukasz Adrian & Grzegorz Wielgosinski & Andrzej Obraniak & Wiktoria Lewandowska & Marta Marczak-Grzesik & Maria Dzikuć & Zdzislawa Roma, 2021. "Pine Wood and Sewage Sludge Torrefaction Process for Production Renewable Solid Biofuels and Biochar as Carbon Carrier for Fertilizers," Energies, MDPI, vol. 14(23), pages 1-27, December.

    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:renene:v:167:y:2021:i:c:p:425-432. 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.journals.elsevier.com/renewable-energy .

    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.