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A Honey Bee Foraging approach for optimal location of a biomass power plant

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  • Vera, David
  • Carabias, Julio
  • Jurado, Francisco
  • Ruiz-Reyes, Nicolás

Abstract

Over eight million hectares of olive trees are cultivated worldwide, especially in Mediterranean countries, where more than 97% of the world's olive oil is produced. The three major olive oil producers worldwide are Spain, Italy, and Greece. Olive tree pruning residues are an autochthonous and important renewable source that, in most of cases, farmers burn through an uncontrolled manner. Besides, industrial uses have not yet been developed. The aim of this paper consists of a new calculation tool based on particles swarm (Binary Honey Bee Foraging, BHBF). Effectively, this approach will make possible to determine the optimal location, biomass supply area and power plant size that offer the best profitability for investor. Moreover, it prevents the accurate method (not feasible from computational viewpoint). In this work, Profitability Index (PI) is set as the fitness function for the BHBF approach. Results are compared with other evolutionary optimization algorithms such as Binary Particle Swarm Optimization (BPSO), and Genetic Algorithms (GA). All the experiments have shown that the optimal plant size is 2 MW, PI = 3.3122, the best location corresponds to coordinate: X = 49, Y = 97 and biomass supply area is 161.33 km2. The simulation times have been reduced to the ninth of time than the greedy (accurate) solution. Matlab® is used to run all simulations.

Suggested Citation

  • Vera, David & Carabias, Julio & Jurado, Francisco & Ruiz-Reyes, Nicolás, 2010. "A Honey Bee Foraging approach for optimal location of a biomass power plant," Applied Energy, Elsevier, vol. 87(7), pages 2119-2127, July.
    • Handle: RePEc:eee:appene:v:87:y:2010:i:7:p:2119-2127
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    2. Jin Su Jeong, 2018. "Biomass Feedstock and Climate Change in Agroforestry Systems: Participatory Location and Integration Scenario Analysis of Biomass Power Facilities," Energies, MDPI, vol. 11(6), pages 1-16, May.
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    5. De Meyer, Annelies & Cattrysse, Dirk & Rasinmäki, Jussi & Van Orshoven, Jos, 2014. "Methods to optimise the design and management of biomass-for-bioenergy supply chains: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 657-670.
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    7. Janmenjoy Nayak & Bighnaraj Naik, 2018. "A Novel Honey-Bees Mating Optimization Approach with Higher order Neural Network for Classification," Journal of Classification, Springer;The Classification Society, vol. 35(3), pages 511-548, October.
    8. Nunes, L.J.R. & Causer, T.P. & Ciolkosz, D., 2020. "Biomass for energy: A review on supply chain management models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    9. Najafi, Fatemeh & Sedaghat, Ahmad & Mostafaeipour, Ali & Issakhov, Alibek, 2021. "Location assessment for producing biodiesel fuel from Jatropha Curcas in Iran," Energy, Elsevier, vol. 236(C).
    10. Francisco J. Ruiz-Rodríguez & Jesús C. Hernández & Francisco Jurado, 2017. "Probabilistic Load-Flow Analysis of Biomass-Fuelled Gas Engines with Electrical Vehicles in Distribution Systems," Energies, MDPI, vol. 10(10), pages 1-23, October.
    11. Wu, Juanjuan & Zhang, Jian & Yi, Weiming & Cai, Hongzhen & Li, Yang & Su, Zhanpeng, 2022. "Agri-biomass supply chain optimization in north China: Model development and application," Energy, Elsevier, vol. 239(PD).
    12. Lim, Chun Hsion & Lam, Hon Loong & Ng, Wendy Pei Qin, 2018. "A novel HAZOP approach for literature review on biomass supply chain optimisation model," Energy, Elsevier, vol. 146(C), pages 13-25.
    13. 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.
    14. Jin Su Jeong & Álvaro Ramírez-Gómez, 2017. "A Multicriteria GIS-Based Assessment to Optimize Biomass Facility Sites with Parallel Environment—A Case Study in Spain," Energies, MDPI, vol. 10(12), pages 1-14, December.
    15. Mobini, Mahdi & Sowlati, Taraneh & Sokhansanj, Shahab, 2011. "Forest biomass supply logistics for a power plant using the discrete-event simulation approach," Applied Energy, Elsevier, vol. 88(4), pages 1241-1250, April.
    16. Wu, Bingqing & Sarker, Bhaba R. & Paudel, Krishna P., 2015. "Sustainable energy from biomass: Biomethane manufacturing plant location and distribution problem," Applied Energy, Elsevier, vol. 158(C), pages 597-608.
    17. Steubing, Bernhard & Ballmer, Isabel & Gassner, Martin & Gerber, Léda & Pampuri, Luca & Bischof, Sandro & Thees, Oliver & Zah, Rainer, 2014. "Identifying environmentally and economically optimal bioenergy plant sizes and locations: A spatial model of wood-based SNG value chains," Renewable Energy, Elsevier, vol. 61(C), pages 57-68.
    18. 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.
    19. Shabani, Nazanin & Akhtari, Shaghaygh & Sowlati, Taraneh, 2013. "Value chain optimization of forest biomass for bioenergy production: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 299-311.
    20. Cebi, Selcuk & Ilbahar, Esra & Atasoy, Aylin, 2016. "A fuzzy information axiom based method to determine the optimal location for a biomass power plant: A case study in Aegean Region of Turkey," Energy, Elsevier, vol. 116(P1), pages 894-907.
    21. Shabani, Nazanin & Sowlati, Taraneh, 2013. "A mixed integer non-linear programming model for tactical value chain optimization of a wood biomass power plant," Applied Energy, Elsevier, vol. 104(C), pages 353-361.
    22. Durusut, Emrah & Tahir, Foaad & Foster, Sam & Dineen, Denis & Clancy, Matthew, 2018. "BioHEAT: A policy decision support tool in Ireland’s bioenergy and heat sectors," Applied Energy, Elsevier, vol. 213(C), pages 306-321.
    23. Vera, D. & Jurado, F. & de Mena, B. & Schories, G., 2011. "Comparison between externally fired gas turbine and gasifier-gas turbine system for the olive oil industry," Energy, Elsevier, vol. 36(12), pages 6720-6730.

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