IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v239y2022ipbs0360544221023203.html
   My bibliography  Save this article

Optimal operating parameter determination based on fuzzy logic modeling and marine predators algorithm approaches to improve the methane production via biomass gasification

Author

Listed:
  • Rezk, Hegazy
  • Inayat, Abrar
  • Abdelkareem, Mohammad A.
  • Olabi, Abdul G.
  • Nassef, Ahmed M.

Abstract

The current study is related to optimizing methane production from steam gasification of palm kernel shell (PKS) utilizing coal bottom ash as a catalyst. Based on the experimental dataset, the fuzzy logic technique, represented by the Adaptive Network-based Fuzzy Inference System (ANFIS) structure, is used to create a robust model to simulate methane production via biomass gasification. Then, a Marine Predator Algorithm (MPA) is used to determine the optimal operating parameter of the gasification process. The temperature, particle size, CaO/PKS ratio, and coal bottom ash are used as the decision variables, whereas methane production is used as the objective function. The main findings confirmed that the yield of methane gasification reached 52.82 vol% when the associated temperature, particle size, CaO/PKS Ratio, and coal bottom ash are at 678 °C, 0.42 mm, 3.03, and 0.037 wt%, respectively. Accordingly, the proposed strategy provides a better result than the Analysis of Variance (ANOVA) methodology reported in the literature. Furthermore, the proposed strategy's output exceeds both the results obtained experimentally and ANOVA methods by 20.26% and 29.69%, respectively.

Suggested Citation

  • Rezk, Hegazy & Inayat, Abrar & Abdelkareem, Mohammad A. & Olabi, Abdul G. & Nassef, Ahmed M., 2022. "Optimal operating parameter determination based on fuzzy logic modeling and marine predators algorithm approaches to improve the methane production via biomass gasification," Energy, Elsevier, vol. 239(PB).
    • Handle: RePEc:eee:energy:v:239:y:2022:i:pb:s0360544221023203
    DOI: 10.1016/j.energy.2021.122072
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544221023203
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2021.122072?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. Inayat, Abrar & Inayat, Muddasser & Shahbaz, Muhammad & Sulaiman, Shaharin A. & Raza, Mohsin & Yusup, Suzana, 2020. "Parametric analysis and optimization for the catalytic air gasification of palm kernel shell using coal bottom ash as catalyst," Renewable Energy, Elsevier, vol. 145(C), pages 671-681.
    2. Chan, Fan Liang & Tanksale, Akshat, 2014. "Review of recent developments in Ni-based catalysts for biomass gasification," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 428-438.
    3. Nassef, Ahmed M. & Olabi, A.G. & Rodriguez, Cristina & Abdelkareem, Mohammad Ali & Rezk, Hegazy, 2021. "Optimal operating parameter determination and modeling to enhance methane production from macroalgae," Renewable Energy, Elsevier, vol. 163(C), pages 2190-2197.
    4. Shahbaz, Muhammad & yusup, Suzana & Inayat, Abrar & Patrick, David Onoja & Ammar, Muhammad, 2017. "The influence of catalysts in biomass steam gasification and catalytic potential of coal bottom ash in biomass steam gasification: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 468-476.
    5. Tanveer, Waqas Hassan & Rezk, Hegazy & Nassef, Ahmed & Abdelkareem, Mohammad Ali & Kolosz, Ben & Karuppasamy, K. & Aslam, Jawad & Gilani, Syed Omer, 2020. "Improving fuel cell performance via optimal parameters identification through fuzzy logic based-modeling and optimization," Energy, Elsevier, vol. 204(C).
    6. Kumar, Sunil & Jain, Siddharth & Kumar, Harmesh, 2021. "Application of adaptive neuro-fuzzy inference system and response surface methodology in biodiesel synthesis from jatropha–algae oil and its performance and emission analysis on diesel engine coupled ," Energy, Elsevier, vol. 226(C).
    7. Singh, Anoop & Olsen, Stig Irving, 2011. "A critical review of biochemical conversion, sustainability and life cycle assessment of algal biofuels," Applied Energy, Elsevier, vol. 88(10), pages 3548-3555.
    8. Nassef, Ahmed M. & Sayed, Enas T. & Rezk, Hegazy & Inayat, Abrar & Yousef, Bashria A.A. & Abdelkareem, Mohammad A. & Olabi, A.G., 2020. "Developing a fuzzy-model with particle swarm optimization-based for improving the conversion and gasification rate of palm kernel shell," Renewable Energy, Elsevier, vol. 166(C), pages 125-135.
    9. Raheem, Abdul & Wan Azlina, W.A.K.G. & Taufiq Yap, Y.H. & Danquah, Michael K. & Harun, Razif, 2015. "Thermochemical conversion of microalgal biomass for biofuel production," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 990-999.
    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. Nassef, Ahmed M. & Houssein, Essam H. & Helmy, Bahaa El-din & Rezk, Hegazy, 2022. "Modified honey badger algorithm based global MPPT for triple-junction solar photovoltaic system under partial shading condition and global optimization," Energy, Elsevier, vol. 254(PA).
    2. Alharbi, Abdullah G. & Fathy, Ahmed & Rezk, Hegazy & Abdelkareem, Mohammad Ali & Olabi, A.G., 2023. "An efficient war strategy optimization reconfiguration method for improving the PV array generated power," Energy, Elsevier, vol. 283(C).
    3. Kijo-Kleczkowska, Agnieszka & Gnatowski, Adam & Krzywanski, Jaroslaw & Gajek, Marcin & Szumera, Magdalena & Tora, Barbara & Kogut, Krzysztof & Knaś, Krzysztof, 2024. "Experimental research and prediction of heat generation during plastics, coal and biomass waste combustion using thermal analysis methods," Energy, Elsevier, vol. 290(C).
    4. Hou, Guolian & Fan, Yuzhen & Wang, Junjie, 2024. "Application of a novel dynamic recurrent fuzzy neural network with rule self-adaptation based on chaotic quantum pigeon-inspired optimization in modeling for gas turbine," Energy, Elsevier, vol. 290(C).
    5. Du, Yanxiang & Liang, Jin & Yang, Shiliang & Hu, Jianhang & Bao, Guirong & Wang, Hua, 2022. "Numerical investigation of the Ni-based catalytic methanation process in a bubbling fluidized bed reactor," Energy, Elsevier, vol. 257(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. Shahbaz, Muhammad & Al-Ansari, Tareq & Inayat, Muddasser & Sulaiman, Shaharin A. & Parthasarathy, Prakash & McKay, Gordon, 2020. "A critical review on the influence of process parameters in catalytic co-gasification: Current performance and challenges for a future prospectus," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    2. Nassef, Ahmed M. & Sayed, Enas T. & Rezk, Hegazy & Inayat, Abrar & Yousef, Bashria A.A. & Abdelkareem, Mohammad A. & Olabi, A.G., 2020. "Developing a fuzzy-model with particle swarm optimization-based for improving the conversion and gasification rate of palm kernel shell," Renewable Energy, Elsevier, vol. 166(C), pages 125-135.
    3. Li, Jie & Chang, Guozhang & Song, Ke & Hao, Bolun & Wang, Cuiping & Zhang, Jian & Yue, Guangxi & Hu, Shugang, 2023. "Influence of coal bottom ash additives on catalytic reforming of biomass pyrolysis gaseous tar and biochar/steam gasification reactivity," Renewable Energy, Elsevier, vol. 203(C), pages 434-444.
    4. Jambo, Siti Azmah & Abdulla, Rahmath & Mohd Azhar, Siti Hajar & Marbawi, Hartinie & Gansau, Jualang Azlan & Ravindra, Pogaku, 2016. "A review on third generation bioethanol feedstock," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 756-769.
    5. David, E. & Kopač, J., 2021. "Efficient removal of tar from gas fraction resulting from thermo-chemical conversion of biomass using coal fly ash–based catalysts," Renewable Energy, Elsevier, vol. 171(C), pages 1290-1302.
    6. Giwa, Adewale & Adeyemi, Idowu & Dindi, Abdallah & Lopez, Celia García-Baños & Lopresto, Catia Giovanna & Curcio, Stefano & Chakraborty, Sudip, 2018. "Techno-economic assessment of the sustainability of an integrated biorefinery from microalgae and Jatropha: A review and case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 239-257.
    7. Ahmed, Gaffer & Kishore, Nanda, 2024. "Synergistic effects on properties of biofuel and biochar produced through co-feed pyrolysis of Erythrina indica and Azadirachta indica biomass," Renewable Energy, Elsevier, vol. 227(C).
    8. Feng, Huan & Zhang, Bo & He, Zhixia & Wang, Shuang & Salih, Osman & Wang, Qian, 2018. "Study on co-liquefaction of Spirulina and Spartina alterniflora in ethanol-water co-solvent for bio-oil," Energy, Elsevier, vol. 155(C), pages 1093-1101.
    9. Łukajtis, Rafał & Hołowacz, Iwona & Kucharska, Karolina & Glinka, Marta & Rybarczyk, Piotr & Przyjazny, Andrzej & Kamiński, Marian, 2018. "Hydrogen production from biomass using dark fermentation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 665-694.
    10. Kasivisvanathan, Harresh & Barilea, Ivan Dale U. & Ng, Denny K.S. & Tan, Raymond R., 2013. "Optimal operational adjustment in multi-functional energy systems in response to process inoperability," Applied Energy, Elsevier, vol. 102(C), pages 492-500.
    11. Hu, Mian & Laghari, Mahmood & Cui, Baihui & Xiao, Bo & Zhang, Beiping & Guo, Dabin, 2018. "Catalytic cracking of biomass tar over char supported nickel catalyst," Energy, Elsevier, vol. 145(C), pages 228-237.
    12. Prajapati, Sanjeev Kumar & Malik, Anushree & Vijay, Virendra Kumar, 2014. "Comparative evaluation of biomass production and bioenergy generation potential of Chlorella spp. through anaerobic digestion," Applied Energy, Elsevier, vol. 114(C), pages 790-797.
    13. Ruivo, Luís & Silva, Tiago & Neves, Daniel & Tarelho, Luís & Frade, Jorge, 2023. "Thermodynamic guidelines for improved operation of iron-based catalysts in gasification of biomass," Energy, Elsevier, vol. 268(C).
    14. Olabi, A.G. & Wilberforce, Tabbi & Abdelkareem, Mohammad Ali, 2021. "Fuel cell application in the automotive industry and future perspective," Energy, Elsevier, vol. 214(C).
    15. Muhammad Asif Qureshi & Jawaid Ahmed Qureshi & Ammar Ahmed & Shahzad Qaiser & Ramsha Ali & Arshian Sharif, 2020. "The Dynamic Relationship Between Technology Innovation and Human Development in Technologically Advanced Countries: Fresh Insights from Quantiles-on-Quantile Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 152(2), pages 555-580, November.
    16. Fathy, Ahmed & Ferahtia, Seydali & Rezk, Hegazy & Yousri, Dalia & Abdelkareem, Mohammad Ali & Olabi, A.G., 2022. "Optimal adaptive fuzzy management strategy for fuel cell-based DC microgrid," Energy, Elsevier, vol. 247(C).
    17. Söyler, Nejmi & Goldfarb, Jillian L. & Ceylan, Selim & Saçan, Melek Türker, 2017. "Renewable fuels from pyrolysis of Dunaliella tertiolecta: An alternative approach to biochemical conversions of microalgae," Energy, Elsevier, vol. 120(C), pages 907-914.
    18. Shahnazari, Mahdi & Bahri, Parisa A. & Parlevliet, David & Minakshi, Manickam & Moheimani, Navid R., 2017. "Sustainable conversion of light to algal biomass and electricity: A net energy return analysis," Energy, Elsevier, vol. 131(C), pages 218-229.
    19. Enagi, Ibrahim I. & Al-attab, K.A. & Zainal, Z.A., 2018. "Liquid biofuels utilization for gas turbines: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 43-55.
    20. Milano, Jassinnee & Ong, Hwai Chyuan & Masjuki, H.H. & Chong, W.T. & Lam, Man Kee & Loh, Ping Kwan & Vellayan, Viknes, 2016. "Microalgae biofuels as an alternative to fossil fuel for power generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 180-197.

    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:energy:v:239:y:2022:i:pb:s0360544221023203. 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/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.