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Framework for Optimized Analysis of Waste Bioenergy Projects

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  • Eliana M. A. Guerreiro

    (Sustainable Production Systems Laboratory (LESP), Graduate Program in Industrial Engineering (PPGEP), Universidade Tecnológica Federal do Parana (UTFPR), Rua Doutor Washington Subtil Chueire, 330, Ponta Grossa 84017-220, Brazil)

  • Maicon Silva

    (Sustainable Production Systems Laboratory (LESP), Graduate Program in Urban Environmental Sustainbility (PPGSAU), Universidade Tecnologica Federal do Parana (UTFPR), Rua Deputado Heitor Alencar Furtado, 500, Curitiba 81280-340, Brazil)

  • Marcio Guerreiro

    (Computational Intelligence and Advanced Control Laboratory (LICON), Graduate Program in Industrial Engineering (PPGEP), Universidade Tecnologica Federal do Parana (UTFPR), Rua Doutor Washington Subtil Chueire, 330, Ponta Grossa 84017-220, Brazil)

  • Taís Carvalho

    (Sustainable Production Systems Laboratory (LESP), Graduate Program in Industrial Engineering (PPGEP), Universidade Tecnológica Federal do Parana (UTFPR), Rua Doutor Washington Subtil Chueire, 330, Ponta Grossa 84017-220, Brazil)

  • Attilio Converti

    (Department of Civil, Chemical and Environmental Engineering, University of Genoa, Pole of Chemical Engineering, Via Opera Pia 15, 16145 Genoa, Italy)

  • Hugo Valadares Siqueira

    (Computational Intelligence and Advanced Control Laboratory (LICON), Graduate Program in Industrial Engineering (PPGEP), Universidade Tecnologica Federal do Parana (UTFPR), Rua Doutor Washington Subtil Chueire, 330, Ponta Grossa 84017-220, Brazil)

  • Cassiano Moro Piekarski

    (Sustainable Production Systems Laboratory (LESP), Graduate Program in Industrial Engineering (PPGEP), Universidade Tecnológica Federal do Parana (UTFPR), Rua Doutor Washington Subtil Chueire, 330, Ponta Grossa 84017-220, Brazil)

Abstract

Over the years, cities have undergone transformations that, invariably, overload and even compromise the functioning of an energy matrix dependent on increasingly scarce resources. The high demand for energy has challenged stakeholders to invest in more sustainable alternatives, such as bioenergy, which, in addition, helps to reduce the pressure for finite resources, enable the energy recovery of waste and contribute to the mitigation of carbon emissions. For these improvements to be successful, stakeholders need specific technological strategies, requiring tools, methods and solutions that support the decision-making process. In this perspective, the current work aimed to develop a framework optimizing the evaluation of waste bioenergy projects through the application of algorithms. Therefore, a literature review was carried out to select the algorithms and identify the sectors/areas and stages in which they are applied. These algorithms were then grouped into two sequential phases. The first targeted the evaluation of region, based on the type and supply of biomass, while the second sought to optimize aspects related to infrastructure and logistics. Both phases were concluded with the application of multi-criteria methods, thus, identifying the areas/regions with the greatest potential for implementing bioenergy projects. In general, it was observed that there are different algorithms and multi-criteria analysis methods that can be suitable in bioenergy projects. They were used to identify and select the regions with the greatest potential for bioenergy plant implementation, focusing on the type, quantity and perpetuity of biomass supply, to assess the operational efficiency of machines, equipment, processes and to optimize the logistics chain, especially the collection and transport of biomass. Thus, the joint work between the use of algorithms and multi-criteria decision methods provides greater assertiveness in choices, helping to identify the most viable projects and mitigating risks and uncertainties for decision-makers.

Suggested Citation

  • Eliana M. A. Guerreiro & Maicon Silva & Marcio Guerreiro & Taís Carvalho & Attilio Converti & Hugo Valadares Siqueira & Cassiano Moro Piekarski, 2022. "Framework for Optimized Analysis of Waste Bioenergy Projects," Energies, MDPI, vol. 15(17), pages 1-15, August.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:17:p:6136-:d:896069
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    References listed on IDEAS

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    1. Chen, Chien-Wei & Fan, Yueyue, 2012. "Bioethanol supply chain system planning under supply and demand uncertainties," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 150-164.
    2. Mirkouei, Amin & Haapala, Karl R. & Sessions, John & Murthy, Ganti S., 2017. "A mixed biomass-based energy supply chain for enhancing economic and environmental sustainability benefits: A multi-criteria decision making framework," Applied Energy, Elsevier, vol. 206(C), pages 1088-1101.
    3. Shen, Yafei & Zhao, Peitao & Shao, Qinfu & Takahashi, Fumitake & Yoshikawa, Kunio, 2015. "In situ catalytic conversion of tar using rice husk char/ash supported nickel–iron catalysts for biomass pyrolytic gasification combined with the mixing-simulation in fluidized-bed gasifier," Applied Energy, Elsevier, vol. 160(C), pages 808-819.
    4. Mulliner, Emma & Malys, Naglis & Maliene, Vida, 2016. "Comparative analysis of MCDM methods for the assessment of sustainable housing affordability," Omega, Elsevier, vol. 59(PB), pages 146-156.
    5. Kaundinya, Deepak Paramashivan & Balachandra, P. & Ravindranath, N.H. & Ashok, Veilumuthu, 2013. "A GIS (geographical information system)-based spatial data mining approach for optimal location and capacity planning of distributed biomass power generation facilities: A case study of Tumkur distric," Energy, Elsevier, vol. 52(C), pages 77-88.
    6. Sarker, Bhaba R. & Wu, Bingqing & Paudel, Krishna P., 2019. "Modeling and optimization of a supply chain of renewable biomass and biogas: Processing plant location," Applied Energy, Elsevier, vol. 239(C), pages 343-355.
    7. Regina Negri Pagani & João Luiz Kovaleski & Luis Mauricio Resende, 2015. "Methodi Ordinatio: a proposed methodology to select and rank relevant scientific papers encompassing the impact factor, number of citation, and year of publication," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 2109-2135, December.
    8. Krystel K. Castillo-Villar, 2014. "Metaheuristic Algorithms Applied to Bioenergy Supply Chain Problems: Theory, Review, Challenges, and Future," Energies, MDPI, vol. 7(11), pages 1-33, November.
    9. Zhao, Ning & You, Fengqi, 2019. "Dairy waste-to-energy incentive policy design using Stackelberg-game-based modeling and optimization," Applied Energy, Elsevier, vol. 254(C).
    10. Omid Abrishambaf & Pedro Faria & Zita Vale & Juan M. Corchado, 2019. "Energy Scheduling Using Decision Trees and Emulation: Agriculture Irrigation with Run-of-the-River Hydroelectricity and a PV Case Study," Energies, MDPI, vol. 12(20), pages 1-21, October.
    11. Zamar, David S. & Gopaluni, Bhushan & Sokhansanj, Shahab, 2017. "Optimization of sawmill residues collection for bioenergy production," Applied Energy, Elsevier, vol. 202(C), pages 487-495.
    12. Scott, James A. & Ho, William & Dey, Prasanta K., 2012. "A review of multi-criteria decision-making methods for bioenergy systems," Energy, Elsevier, vol. 42(1), pages 146-156.
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