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Optimization of biodiesel production from Nahar oil using Box-Behnken design, ANOVA and grey wolf optimizer

1Institute of Engineering, HUTECH University, Ho Chi Minh City, Viet Nam

2Department of Mechanical Engineering, Delhi Skill and Entrepreneurship University, Delhi, India

3School of Mechanical Engineering, Hanoi University of Science and Technology, Hanoi, Viet Nam

4 Institute of Maritime, Ho Chi Minh City University of Transport, Ho Chi Minh City, Viet Nam

5 PATET Research Group, Ho Chi Minh City University of Transport, Ho Chi Minh City, Viet Nam

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Received: 2 May 2023; Revised: 5 Jun 2023; Accepted: 19 Jun 2023; Available online: 25 Jun 2023; Published: 15 Jul 2023.
Editor(s): H Hadiyanto
Open Access Copyright (c) 2023 The Author(s). Published by Centre of Biomass and Renewable Energy (CBIORE)
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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Abstract

Biodiesel manufacturing from renewable feedstocks has received a lot of attention as a viable alternative to fossil fuels. The Box-Behnken design, analysis of variance (ANOVA), and the Grey Wolf Optimizer (GWO) algorithm were used in this work to optimise biodiesel production from Nahar oil. The goal was to determine the best operating parameters for maximising biodiesel yield. The Box-Behnken design is used, with four essential parameters taken into account: molar ratio, reaction duration and temperature, and catalyst weight percentage. The response surface is studied in this design, and the key factors influencing biodiesel yield are discovered. The gathered data is given to ANOVA analysis to determine the statistical significance. ANOVA analysis is performed on the acquired data to determine the statistical significance of the components and their interactions. The GWO algorithm is used to better optimise the biodiesel production process. Based on the data provided, the GWO algorithm obtains an optimised yield of 91.6484% by running the reaction for 200 minutes, using a molar ratio of 7, and a catalyst weight percentage of 1.2. As indicated by the lower boundaries, the reaction temperature ranges from 50 °C. The results show that the Box-Behnken design, ANOVA, and GWO algorithm were successfully integrated for optimising biodiesel production from Nahar oil. This method offers useful insights into process optimisation and indicates the possibilities for increasing the efficiency and sustainability of biodiesel production. Further study can broaden the use of these strategies to various biodiesel production processes and feedstocks, advancing sustainable energy technology.

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Keywords: GWO; ANOVA; Optimization; Nahar oil; Alternative fuels

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  1. Abdullah, B., Syed Muhammad, S.A.F., Shokravi, Z., Ismail, S., Kassim, K.A., Mahmood, A.N., Aziz, M.M.A., 2019. Fourth generation biofuel: A review on risks and mitigation strategies. Renew. Sustain. Energy Rev. 107, 37–50. https://doi.org/10.1016/j.rser.2019.02.018
  2. Abualigah, L., Shehab, M., Alshinwan, M., Alabool, H., Abuaddous, H.Y., Khasawneh, A.M., Diabat, M. Al, 2020. TS-GWO: IoT Tasks Scheduling in Cloud Computing Using Grey Wolf Optimizer, in: Swarm Intelligence for Cloud Computing. Chapman and Hall/CRC, pp. 127–152. https://doi.org/10.1201/9780429020582-5
  3. Ahmad, K., Saini, P., 2022. Effect of butanol additive with mango seed biodiesel and diesel ternary blends on performance and emission characteristics of diesel engine. Energy Sources, Part A Recover. Util. Environ. Eff. 44, 9988–10005. https://doi.org/10.1080/15567036.2022.2143954
  4. Babadi, A.A., Rahmati, S., Fakhlaei, R., Barati, B., Wang, S., Doherty, W., Ostrikov, K. (Ken), 2022. Emerging technologies for biodiesel production: Processes, challenges, and opportunities. Biomass and Bioenergy 163, 106521. https://doi.org/10.1016/j.biombioe.2022.106521
  5. Bakır, H., Ağbulut, Ü., Gürel, A.E., Yıldız, G., Güvenç, U., Soudagar, M.E.M., Hoang, A.T., Deepanraj, B., Saini, G., Afzal, A., 2022. Forecasting of future greenhouse gas emission trajectory for India using energy and economic indexes with various metaheuristic algorithms. J. Clean. Prod. 360, 131946. https://doi.org/10.1016/j.jclepro.2022.131946
  6. Barik, D., Vijayaraghavan, R., 2020. Effects of waste chicken fat derived biodiesel on the performance and emission characteristics of a compression ignition engine. Int. J. Ambient Energy 41, 88–97. https://doi.org/10.1080/01430750.2018.1451370
  7. da Silva Neto, J.V., Gallo, W.L.R., Nour, E.A.A., 2020. Production and use of biogas from vinasse: Implications for the energy balance and GHG emissions of sugar cane ethanol in the brazilian context. Environ. Prog. Sustain. Energy 39, 13226. https://doi.org/10.1002/ep.13226
  8. Dey, S., Reang, N.M., Deb, M., Das, P.K., 2020. Study on performance-emission trade-off and multi-objective optimization of diesel-ethanol-palm biodiesel in a single cylinder CI engine: a Taguchi-fuzzy approach. Energy Sources, Part A Recover. Util. Environ. Eff. https://doi.org/10.1080/15567036.2020.1767234
  9. Domachowski, Z., 2021. Minimizing Greenhouse Gas Emissions From Ships Using a Pareto Multi-Objective Optimization Approach. Polish Marit. Res. 28, 96–101. https://doi.org/10.2478/pomr-2021-0026
  10. Elkelawy, M., El Shenawy, E.A., Alm-Eldin Bastawissi, H., Shams, M.M., Panchal, H., 2022. A comprehensive review on the effects of diesel/biofuel blends with nanofluid additives on compression ignition engine by response surface methodology. Energy Convers. Manag. X 14, 100177. https://doi.org/10.1016/j.ecmx.2021.100177
  11. Gasparatos, A., Mudombi, S., Balde, B.S., von Maltitz, G.P., Johnson, F.X., Romeu-Dalmau, C., Jumbe, C., Ochieng, C., Luhanga, D., Nyambane, A., Rossignoli, C., Jarzebski, M.P., Dam Lam, R., Dompreh, E.B., Willis, K.J., 2022. Local food security impacts of biofuel crop production in southern Africa. Renew. Sustain. Energy Rev. 154, 111875. https://doi.org/10.1016/j.rser.2021.111875
  12. Geng, P., Cao, E., Tan, Q., Wei, L., 2017. Effects of alternative fuels on the combustion characteristics and emission products from diesel engines: A review. Renew. Sustain. Energy Rev. https://doi.org/10.1016/j.rser.2016.12.080
  13. Gul, M., Shah, A.N., Aziz, U., Husnain, N., Abbas, M., Kousar, T., Ahmad, R., Hanif, M.F., 2019. Grey-Taguchi and ANN based optimization of a better performing low-emission diesel engine fueled with biodiesel. Energy Sources, Part A Recover. Util. Environ. Eff. 0, 1–14. https://doi.org/10.1080/15567036.2019.1638995
  14. Hoang, A.T., 2021a. Combustion behavior, performance and emission characteristics of diesel engine fuelled with biodiesel containing cerium oxide nanoparticles: A review. Fuel Process. Technol. 218, 106840. https://doi.org/10.1016/j.fuproc.2021.106840
  15. Hoang, A.T., 2021b. Prediction of the density and viscosity of biodiesel and the influence of biodiesel properties on a diesel engine fuel supply system. J. Mar. Eng. Technol. 20, 299–311. https://doi.org/10.1080/20464177.2018.1532734
  16. Hoang, A.T., Sirohi, R., Pandey, A., Nižetić, S., Lam, S.S., Chen, W.-H., Luque, R., Thomas, S., Arıcı, M., Pham, V.V., 2022. Biofuel production from microalgae: challenges and chances. Phytochem. Rev. https://doi.org/10.1007/s11101-022-09819-y
  17. Hoang, A.T., Tabatabaei, M., Aghbashlo, M., Carlucci, A.P., Ölçer, A.I., Le, A.T., Ghassemi, A., 2021. Rice bran oil-based biodiesel as a promising renewable fuel alternative to petrodiesel: A review. Renew. Sustain. Energy Rev. 135, 110204. https://doi.org/10.1016/j.rser.2020.110204
  18. Jin, C., Wei, J., 2023. The combined effect of water and nanoparticles on diesel engine powered by biodiesel and its blends with diesel: A review. Fuel 343, 127940. https://doi.org/10.1016/j.fuel.2023.127940
  19. Kalyani, T., Prasad, L.S.V., Kolakoti, A., 2023. Biodiesel Production from a Naturally Grown Green Algae Spirogyra Using Heterogeneous Catalyst: An Approach to RSM Optimization Technique. Int. J. Renew. Energy Dev. 12, 300–312. https://doi.org/10.14710/ijred.2023.50065
  20. Kolakoti, A., Setiyo, M., Rochman, M.L., 2022. A green heterogeneous catalyst production and characterization for biodiesel production using RSM and ANN approach. Int. J. Renew. Energy Dev. 11, 703–712. https://doi.org/10.14710/ijred.2022.43627
  21. Lamas, M.I., C.G., R., J., T., J.D., R., 2015. Numerical Analysis of Emissions from Marine Engines Using Alternative Fuels. Polish Marit. Res. 22, 48–52. https://doi.org/10.1515/pomr-2015-0070
  22. Leung, D.Y.C., Wu, X., Leung, M.K.H., 2010. A review on biodiesel production using catalyzed transesterification. Appl. Energy 87, 1083–1095. https://doi.org/10.1016/j.apenergy.2009.10.006
  23. Makhadmeh, S.N., Alomari, O.A., Mirjalili, S., Al-Betar, M.A., Elnagar, A., 2022. Recent advances in multi-objective grey wolf optimizer, its versions and applications. Neural Comput. Appl. 34, 19723–19749. https://doi.org/10.1007/s00521-022-07704-5
  24. Malla, F.A., Mushtaq, A., Bandh, S.A., Qayoom, I., Hoang, A.T., Shahid-e-Murtaza, 2022. Understanding Climate Change: Scientific Opinion and Public Perspective, in: Climate Change. Springer International Publishing, Cham, pp. 1–20. https://doi.org/10.1007/978-3-030-86290-9_1
  25. Manojkumar, N., Muthukumaran, C., Sharmila, G., 2022. A comprehensive review on the application of response surface methodology for optimization of biodiesel production using different oil sources. J. King Saud Univ. - Eng. Sci. 34, 198–208. https://doi.org/10.1016/j.jksues.2020.09.012
  26. Mayer, F.D., Brondani, M., Vasquez Carrillo, M.C., Hoffmann, R., Silva Lora, E.E., 2020. Revisiting energy efficiency, renewability, and sustainability indicators in biofuels life cycle: Analysis and standardization proposal. J. Clean. Prod. 252, 119850. https://doi.org/10.1016/j.jclepro.2019.119850
  27. Mohapatra, P., Swain, A.K., Mishra, J., 2022. Temporal variations of NDVI with responses to climate change in Mayurbhanj district of Odisha from 2015-2020. J. Technol. Innov. 2, 11–15. https://doi.org/10.26480/jtin.01.2022.11.15
  28. Molino, A., Larocca, V., Chianese, S., Musmarra, D., 2018. Biofuels Production by Biomass Gasification: A Review. Energies 11, 811. https://doi.org/10.3390/en11040811
  29. Murugapoopathi, S., Vasudevan, D., 2021. Experimental and numerical findings on VCR engine performance analysis on high FFA RSO biodiesel as fuel using RSM approach. Heat Mass Transf. 57, 495–513. https://doi.org/10.1007/s00231-020-02961-3
  30. Nagarajan, J., Balasubramanian, D., Khalife, E., Usman, K.M., 2022. Optimization of compression ignition engine fuelled with Cotton seed biodiesel using Diglyme and injection pressure. J. Technol. Innov. 2, 52–61. https://doi.org/10.26480/jtin.02.2022.52.61
  31. Nguyen, X.P., Hoang, A.T., Ölçer, A.I., Huynh, T.T., 2021. Record decline in global CO 2 emissions prompted by COVID-19 pandemic and its implications on future climate change policies. Energy Sources, Part A Recover. Util. Environ. Eff. 1–4. https://doi.org/10.1080/15567036.2021.1879969
  32. Patel, A., Hrůzová, K., Rova, U., Christakopoulos, P., Matsakas, L., 2019. Sustainable biorefinery concept for biofuel production through holistic volarization of food waste. Bioresour. Technol. 294, 122247
  33. Pimentel, D., Marklein, A., Toth, M.A., Karpoff, M.N., Paul, G.S., McCormack, R., Kyriazis, J., Krueger, T., 2009. Food Versus Biofuels: Environmental and Economic Costs. Hum. Ecol. 37, 1–12. https://doi.org/10.1007/s10745-009-9215-8
  34. Porwal, O., 2022. Box-Behnken Design-based formulation optimization and characterization of spray dried rutin loaded nanosuspension: State of the art. South African J. Bot. 149, 807–815. https://doi.org/10.1016/j.sajb.2022.04.028
  35. Ruiz, J.A., Ríos, A., Cáceres, E., 2021. Theoretical Estimation of the Production Potential of Biodiesel from Microalgae at the Talara Refinery. Int. J. Renew. Energy Res. 11, 1760–1775. https://doi.org/10.20508/ijrer.v11i4.12498.g8328
  36. Rulli, M.C., Bellomi, D., Cazzoli, A., De Carolis, G., D’Odorico, P., 2016. The water-land-food nexus of first-generation biofuels. Sci. Rep. 6, 22521. https://doi.org/10.1038/srep22521
  37. Serbin, S., Diasamidze, B., Gorbov, V., Kowalski, J., 2021. Investigations of the Emission Characteristics of a Dual-Fuel Gas Turbine Combustion Chamber Operating Simultaneously on Liquid and Gaseous Fuels. Polish Marit. Res. 28, 85–95. https://doi.org/10.2478/pomr-2021-0025
  38. Sharma, P., Sahoo, B.B., 2022. An ANFIS-RSM based modeling and multi-objective optimization of syngas powered dual-fuel engine. Int. J. Hydrogen Energy. https://doi.org/10.1016/J.IJHYDENE.2022.04.093
  39. Sharma, P., Sharma, A.K., 2022. Statistical and Continuous Wavelet Transformation-Based Analysis of Combustion Instabilities in a Biodiesel-Fueled Compression Ignition Engine. J. Energy Resour. Technol. 144. https://doi.org/10.1115/1.4051340
  40. Sharma, P., Sharma, A.K., 2021. AI-Based Prognostic Modeling and Performance Optimization of CI Engine Using Biodiesel-Diesel Blends. Int. J. Renew. Energy Resour. 11, 701–708
  41. Silviana, S., Anggoro, D.D., Hadiyanto, H., Salsabila, C.A., Aprilio, K., Utami, A.W., Sa’adah, A.N., Dalanta, F., 2022. A Review on the Recent Breakthrough Methods and Influential Parameters in the Biodiesel Synthesis and Purification. Int. J. Renew. Energy Dev. 11, 1012–1036. https://doi.org/10.14710/ijred.2022.43147
  42. Skea, J., Shukla, P., Kılkış, Ş., 2022. Climate change 2022: mitigation of climate change
  43. Soulayman, S., Dayoub, O., 2019. Optimal Parameters Synthesis of Biodiesel From Frying Oils Wastes. Int. J. Renew. Energy Dev. 8, 33–39. https://doi.org/10.14710/ijred.8.1.33-39
  44. Stelmasiak, Z., Larisch, J., Pielecha, J., Pietras, D., 2017. Particulate Matter Emission from Dual Fuel Diesel Engine Fuelled with Natural Gas. Polish Marit. Res. 24, 96–104. https://doi.org/10.1515/pomr-2017-0055
  45. Thirunavukkarasu, M., Sawle, Y., Lala, H., 2023. A comprehensive review on optimization of hybrid renewable energy systems using various optimization techniques. Renew. Sustain. Energy Rev. 176, 113192. https://doi.org/10.1016/j.rser.2023.113192
  46. Tuan Hoang, A., Nižetić, S., Chyuan Ong, H., Tarelko, W., Viet Pham, V., Hieu Le, T., Quang Chau, M., Phuong Nguyen, X., 2021. A review on application of artificial neural network (ANN) for performance and emission characteristics of diesel engine fueled with biodiesel-based fuels. Sustain. Energy Technol. Assessments 47, 101416. https://doi.org/10.1016/j.seta.2021.101416
  47. Veza, I., Karaoglan, A.D., Ileri, E., Kaulani, S.A., Tamaldin, N., Latiff, Z.A., Muhamad Said, M.F., Hoang, A.T., Yatish, K.V., Idris, M., 2022. Grasshopper optimization algorithm for diesel engine fuelled with ethanol-biodiesel-diesel blends. Case Stud. Therm. Eng. 31, 101817. https://doi.org/10.1016/j.csite.2022.101817
  48. Wang, S., Zhang, Z., Hou, X., Lv, J., Lan, G., Yang, G., Hu, J., 2023. The environmental potential of hydrogen addition as complementation for diesel and biodiesel: A comprehensive review and perspectives. Fuel 342, 127794. https://doi.org/10.1016/j.fuel.2023.127794
  49. Yaashikaa, P.R., Kumar, P.S., Karishma, S., 2022. Bio-derived catalysts for production of biodiesel: A review on feedstock, oil extraction methodologies, reactors and lifecycle assessment of biodiesel. Fuel 316, 123379. https://doi.org/10.1016/j.fuel.2022.123379
  50. Yang, Z., Tan, Q., Geng, P., 2019. Combustion and Emissions Investigation on Low-Speed Two-Stroke Marine Diesel Engine with Low Sulfur Diesel Fuel. Polish Marit. Res. 26, 153–161. https://doi.org/10.2478/pomr-2019-0017
  51. Zhang, Y., Wang, Z., Li, R., Liu, S., 2022. Study on physicochemical properties of biodiesel and Fischer–Tropsch diesel exhaust particle. Energy Sources, Part A Recover. Util. Environ. Eff. 44, 139–152
  52. Zullaikah, S., Putra, A.K., Fachrudin, F.H., Naulina, R.Y., Utami, S., Herminanto, R.P., Rachmaniah, O., Ju, Y.H., 2021. Experimental Investigation and Optimization of Non-Catalytic In-Situ Biodiesel Production from Rice Bran Using Response Surface Methodology Historical Data Design. Int. J. Renew. Energy Dev. 10, 803–810. https://doi.org/10.14710/ijred.2021.34138

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