IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v179y2021icp550-562.html
   My bibliography  Save this article

Estimation of higher heating values (HHVs) of biomass fuels based on ultimate analysis using machine learning techniques and improved equation

Author

Listed:
  • Noushabadi, Abolfazl Sajadi
  • Dashti, Amir
  • Ahmadijokani, Farhad
  • Hu, Jinguang
  • Mohammadi, Amir H.

Abstract

To have a sustainable economy and environment, several countries have widely inclined to the utilization of non-fossil fuels like biomass fuels to produce heat and electricity. The advantage of employing biomass for combustion is emerging as a potential renewable energy, which is regarded as a cheap fuel. Chemical constituents or elements are essential properties in biomass applications, which would be costly and labor-intensive to experimentally estimate them. One of the criteria to evaluate the energy of biomass from an economic perspective is the higher heating value (HHV). In the present work, we have applied multilayer perceptron artificial neural network (MLP-ANN), least-squares support vector machine (LSSVM), ant colony-adaptive neuro-fuzzy inference system (ACO-ANFIS), particle swarm optimization- ANFIS (PSO-ANFIS), genetic algorithm-radial basis function (GA-RBF) and new multivariate nonlinear regression (MNR) as accurate correlation methods to estimate HHVs of biomass fuels based on the ultimate analysis. 535 experimental data were gathered from literature and categorized into eight classes of by-products of fruits, agri-wastes, wood chips/tree species, grasses/leaves/fibrous materials, other waste materials, briquettes/charcoals/pellets, cereal and Industrial wastes. In the term of statistical analysis, average absolute relative deviation (AARD) authenticates that MNR and GA-RBF algorithm with %AARD of 3.5 and 3.4 could be used to estimate HHV. In addition, developed models results were compared to the results of 69 recently previously published empirical correlations and it confirms the reliability of our results. Relevency factor shows the impact of biomass elements on HHV and outlier analysis indicates the unreliable experimental data. The results of this study can be used by researchers to design and optimize biomass combustion systems.

Suggested Citation

  • Noushabadi, Abolfazl Sajadi & Dashti, Amir & Ahmadijokani, Farhad & Hu, Jinguang & Mohammadi, Amir H., 2021. "Estimation of higher heating values (HHVs) of biomass fuels based on ultimate analysis using machine learning techniques and improved equation," Renewable Energy, Elsevier, vol. 179(C), pages 550-562.
    • Handle: RePEc:eee:renene:v:179:y:2021:i:c:p:550-562
    DOI: 10.1016/j.renene.2021.07.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148121010089
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2021.07.003?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. Sharafi, Masoud & ELMekkawy, Tarek Y., 2014. "Multi-objective optimal design of hybrid renewable energy systems using PSO-simulation based approach," Renewable Energy, Elsevier, vol. 68(C), pages 67-79.
    2. Hosseinpour, Soleiman & Aghbashlo, Mortaza & Tabatabaei, Meisam & Mehrpooya, Mehdi, 2017. "Estimation of biomass higher heating value (HHV) based on the proximate analysis by using iterative neural network-adapted partial least squares (INNPLS)," Energy, Elsevier, vol. 138(C), pages 473-479.
    3. Toklu, E., 2017. "Biomass energy potential and utilization in Turkey," Renewable Energy, Elsevier, vol. 107(C), pages 235-244.
    4. Zhou, Hui & Meng, AiHong & Long, YanQiu & Li, QingHai & Zhang, YanGuo, 2014. "An overview of characteristics of municipal solid waste fuel in China: Physical, chemical composition and heating value," Renewable and Sustainable Energy Reviews, Elsevier, vol. 36(C), pages 107-122.
    5. Noushabadi, Abolfazl Sajadi & Dashti, Amir & Raji, Mojtaba & Zarei, Alireza & Mohammadi, Amir H., 2020. "Estimation of cetane numbers of biodiesel and diesel oils using regression and PSO-ANFIS models," Renewable Energy, Elsevier, vol. 158(C), pages 465-473.
    6. Stassen, Ir.H.E.M., 1994. "Biogas and biomass technology: Energy generation from biomass and waste in the Netherlands," Renewable Energy, Elsevier, vol. 5(5), pages 819-823.
    7. Vargas-Moreno, J.M. & Callejón-Ferre, A.J. & Pérez-Alonso, J. & Velázquez-Martí, B., 2012. "A review of the mathematical models for predicting the heating value of biomass materials," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 3065-3083.
    8. Aghbashlo, Mortaza & Hosseinpour, Soleiman & Tabatabaei, Meisam & Dadak, Ali, 2017. "Fuzzy modeling and optimization of the synthesis of biodiesel from waste cooking oil (WCO) by a low power, high frequency piezo-ultrasonic reactor," Energy, Elsevier, vol. 132(C), pages 65-78.
    9. Knoef, H.A.M. & Stassen, H.E.M., 1995. "Energy generation from biomass and waste in the Netherlands: A brief overview and perspective," Renewable Energy, Elsevier, vol. 6(3), pages 329-334.
    10. Aghbashlo, Mortaza & Tabatabaei, Meisam & Mohammadi, Pouya & Mirzajanzadeh, Mehrdad & Ardjmand, Mehdi & Rashidi, Alimorad, 2016. "Effect of an emission-reducing soluble hybrid nanocatalyst in diesel/biodiesel blends on exergetic performance of a DI diesel engine," Renewable Energy, Elsevier, vol. 93(C), pages 353-368.
    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. Ivan Brandić & Lato Pezo & Nikola Bilandžija & Anamarija Peter & Jona Šurić & Neven Voća, 2022. "Artificial Neural Network as a Tool for Estimation of the Higher Heating Value of Miscanthus Based on Ultimate Analysis," Mathematics, MDPI, vol. 10(20), pages 1-12, October.
    2. Leni Maulinda & Husni Husin & Nasrul Arahman & Cut Meurah Rosnelly & Muhammad Syukri & Nurhazanah & Fahrizal Nasution & Ahmadi, 2023. "The Influence of Pyrolysis Time and Temperature on the Composition and Properties of Bio-Oil Prepared from Tanjong Leaves ( Mimusops elengi )," Sustainability, MDPI, vol. 15(18), pages 1-17, September.
    3. Bi, Yingxin & Chen, Chunxiang & Huang, Xiaodong & Wang, Haokun & Wei, Guangsheng, 2023. "Discrimination method of biomass slagging tendency based on particle swarm optimization deep neural network (DNN)," Energy, Elsevier, vol. 262(PA).
    4. Małgorzata Sieradzka & Agata Mlonka-Mędrala & Izabela Kalemba-Rec & Markus Reinmöller & Felix Küster & Wojciech Kalawa & Aneta Magdziarz, 2022. "Evaluation of Physical and Chemical Properties of Residue from Gasification of Biomass Wastes," Energies, MDPI, vol. 15(10), pages 1-19, May.

    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. Alba Mondragón-Valero & Borja Velázquez-Martí & Domingo M. Salazar & Isabel López-Cortés, 2018. "Influence of Fertilization and Rootstocks in the Biomass Energy Characterization of Prunus dulcis (Miller)," Energies, MDPI, vol. 11(5), pages 1-12, May.
    2. Hoang, Anh Tuan & Tabatabaei, Meisam & Aghbashlo, Mortaza & Carlucci, Antonio Paolo & Ölçer, Aykut I. & Le, Anh Tuan & Ghassemi, Abbas, 2021. "Rice bran oil-based biodiesel as a promising renewable fuel alternative to petrodiesel: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    3. Dashti, Amir & Noushabadi, Abolfazl Sajadi & Asadi, Javad & Raji, Mojtaba & Chofreh, Abdoulmohammad Gholamzadeh & Klemeš, Jiří Jaromír & Mohammadi, Amir H., 2021. "Review of higher heating value of municipal solid waste based on analysis and smart modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    4. Aghbashlo, Mortaza & Mandegari, Mohsen & Tabatabaei, Meisam & Farzad, Somayeh & Mojarab Soufiyan, Mohamad & Görgens, Johann F., 2018. "Exergy analysis of a lignocellulosic-based biorefinery annexed to a sugarcane mill for simultaneous lactic acid and electricity production," Energy, Elsevier, vol. 149(C), pages 623-638.
    5. Shirzad, Mohammad & Kazemi Shariat Panahi, Hamed & Dashti, Behrouz B. & Rajaeifar, Mohammad Ali & Aghbashlo, Mortaza & Tabatabaei, Meisam, 2019. "A comprehensive review on electricity generation and GHG emission reduction potentials through anaerobic digestion of agricultural and livestock/slaughterhouse wastes in Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 111(C), pages 571-594.
    6. Babu, D. & Karvembu, R. & Anand, R., 2018. "Impact of split injection strategy on combustion, performance and emissions characteristics of biodiesel fuelled common rail direct injection assisted diesel engine," Energy, Elsevier, vol. 165(PB), pages 577-592.
    7. Fitsum Salehu Kebede & Jean-Christophe Olivier & Salvy Bourguet & Mohamed Machmoum, 2021. "Reliability Evaluation of Renewable Power Systems through Distribution Network Power Outage Modelling," Energies, MDPI, vol. 14(11), pages 1-25, May.
    8. Hu, Mian & Guo, Dabin & Ma, Caifeng & Hu, Zhiquan & Zhang, Beiping & Xiao, Bo & Luo, Siyi & Wang, Jingbo, 2015. "Hydrogen-rich gas production by the gasification of wet MSW (municipal solid waste) coupled with carbon dioxide capture," Energy, Elsevier, vol. 90(P1), pages 857-863.
    9. Juaidi, Adel & Montoya, Francisco G. & Ibrik, Imad H. & Manzano-Agugliaro, Francisco, 2016. "An overview of renewable energy potential in Palestine," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 943-960.
    10. Yanfeng Liu & Yaxing Wang & Xi Luo, 2020. "Design and Operation Optimization of Distributed Solar Energy System Based on Dynamic Operation Strategy," Energies, MDPI, vol. 14(1), pages 1-26, December.
    11. Vasaki E, Madhu & Karri, Rama Rao & Ravindran, Gobinath & Paramasivan, Balasubramanian, 2021. "Predictive capability evaluation and optimization of sustainable biodiesel production from oleaginous biomass grown on pulp and paper industrial wastewater," Renewable Energy, Elsevier, vol. 168(C), pages 204-215.
    12. Patrik Šuhaj & Jakub Husár & Juma Haydary, 2020. "Gasification of RDF and Its Components with Tire Pyrolysis Char as Tar-Cracking Catalyst," Sustainability, MDPI, vol. 12(16), pages 1-14, August.
    13. Mehrabankhomartash, Mahmoud & Rayati, Mohammad & Sheikhi, Aras & Ranjbar, Ali Mohammad, 2017. "Practical battery size optimization of a PV system by considering individual customer damage function," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 36-50.
    14. Lan, Hai & Wen, Shuli & Hong, Ying-Yi & Yu, David C. & Zhang, Lijun, 2015. "Optimal sizing of hybrid PV/diesel/battery in ship power system," Applied Energy, Elsevier, vol. 158(C), pages 26-34.
    15. Wang, Bin & Xu, Jun & Cao, Binggang & Ning, Bo, 2017. "Adaptive mode switch strategy based on simulated annealing optimization of a multi-mode hybrid energy storage system for electric vehicles," Applied Energy, Elsevier, vol. 194(C), pages 596-608.
    16. Maleki, Akbar & Ameri, Mehran & Keynia, Farshid, 2015. "Scrutiny of multifarious particle swarm optimization for finding the optimal size of a PV/wind/battery hybrid system," Renewable Energy, Elsevier, vol. 80(C), pages 552-563.
    17. Abdul, Daud & Wenqi, Jiang & Tanveer, Arsalan, 2022. "Prioritization of renewable energy source for electricity generation through AHP-VIKOR integrated methodology," Renewable Energy, Elsevier, vol. 184(C), pages 1018-1032.
    18. Alkan, Ömer & Albayrak, Özlem Karadağ, 2020. "Ranking of renewable energy sources for regions in Turkey by fuzzy entropy based fuzzy COPRAS and fuzzy MULTIMOORA," Renewable Energy, Elsevier, vol. 162(C), pages 712-726.
    19. Nketiah, Emmanuel & Song, Huaming & Obuobi, Bright & Adu-Gyamfi, Gibbson & Adjei, Mavis & Cudjoe, Dan, 2022. "Citizens' willingness to pay for local anaerobic digestion energy: The influence of altruistic value and knowledge," Energy, Elsevier, vol. 260(C).
    20. Upadhyay, Subho & Sharma, M.P., 2016. "Selection of a suitable energy management strategy for a hybrid energy system in a remote rural area of India," Energy, Elsevier, vol. 94(C), pages 352-366.

    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:179:y:2021:i:c:p:550-562. 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.