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A fuzzy approach to a multiple criteria and Geographical Information System for decision support on suitable locations for biogas plants

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  • Franco, Camilo
  • Bojesen, Mikkel
  • Hougaard, Jens Leth
  • Nielsen, Kurt

Abstract

The purpose of this paper is to model the multi-criteria decision problem of identifying the most suitable facility locations for biogas plants under an integrated decision support methodology. Here the Geographical Information System (GIS) is used for measuring the attributes of the alternatives according to a given set of criteria. Measurements are taken in interval form, expressing the natural imprecision of common data, and the Fuzzy Weighted Overlap Dominance (FWOD) procedure is applied for aggregating and exploiting this kind of data, obtaining suitability degrees for every alternative. The estimation of criteria weights, which is necessary for applying the FWOD procedure, is done by means of the Analytical Hierarchy Process (AHP), used jointly with the LLSM-AHP for the estimation of upper and lower bounds for the weights. Then, a combined AHP-FWOD methodology allows identifying the more suitable sites for building biogas plants. We show that the FWOD relevance-ranking procedure can also be successfully applied over the outcomes of different decision makers, in case a unique social solution is required to exist.

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  • Franco, Camilo & Bojesen, Mikkel & Hougaard, Jens Leth & Nielsen, Kurt, 2015. "A fuzzy approach to a multiple criteria and Geographical Information System for decision support on suitable locations for biogas plants," Applied Energy, Elsevier, vol. 140(C), pages 304-315.
    • Handle: RePEc:eee:appene:v:140:y:2015:i:c:p:304-315
    DOI: 10.1016/j.apenergy.2014.11.060
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    15. Francesco Latterini & Walter Stefanoni & Alessandro Suardi & Vincenzo Alfano & Simone Bergonzoli & Nadia Palmieri & Luigi Pari, 2020. "A GIS Approach to Locate a Small Size Biomass Plant Powered by Olive Pruning and to Estimate Supply Chain Costs," Energies, MDPI, vol. 13(13), pages 1-17, July.
    16. Grzegorz Ginda & Marta Szyba, 2023. "Identification of Key Factors for the Development of Agricultural Biogas Plants in Poland," Energies, MDPI, vol. 16(23), pages 1-19, November.
    17. Patrizio, P. & Leduc, S. & Chinese, D. & Dotzauer, E. & Kraxner, F., 2015. "Biomethane as transport fuel – A comparison with other biogas utilization pathways in northern Italy," Applied Energy, Elsevier, vol. 157(C), pages 25-34.
    18. 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.
    19. Valenti, Francesca & Porto, Simona M.C. & Dale, Bruce E. & Liao, Wei, 2018. "Spatial analysis of feedstock supply and logistics to establish regional biogas power generation: A case study in the region of Sicily," Renewable and Sustainable Energy Reviews, Elsevier, vol. 97(C), pages 50-63.
    20. Kheybari, Siamak & Kazemi, Mostafa & Rezaei, Jafar, 2019. "Bioethanol facility location selection using best-worst method," Applied Energy, Elsevier, vol. 242(C), pages 612-623.
    21. Xiang Zhao & Xiaoya Ma & Kun Wang & Yuqing Long & Dongjie Zhang & Zhanchun Xiao, 2017. "A Spatially Explicit Optimization Model for Agricultural Straw-Based Power Plant Site Selection: A Case Study in Hubei Province, China," Sustainability, MDPI, vol. 9(5), pages 1-19, May.
    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.
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    24. Danijel Topić & Marinko Barukčić & Dražen Mandžukić & Cecilia Mezei, 2020. "Optimization Model for Biogas Power Plant Feedstock Mixture Considering Feedstock and Transportation Costs Using a Differential Evolution Algorithm," Energies, MDPI, vol. 13(7), pages 1-22, April.
    25. Baležentis, Tomas & Streimikiene, Dalia, 2017. "Multi-criteria ranking of energy generation scenarios with Monte Carlo simulation," Applied Energy, Elsevier, vol. 185(P1), pages 862-871.

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