A decision support system for the selection of sustainable biomass resources for bioenergy production

R. N. Ossei-Bremang and F. Kemausuor ()
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R. N. Ossei-Bremang: Kwame Nkrumah University of Science and Technology (KNUST)
F. Kemausuor: KNUST

Environment Systems and Decisions, 2021, vol. 41, issue 3, 437-454

Abstract: Abstract Bioenergy production from biomass is a multicriteria decision-making (MCDM) problem involving multidimensional criteria due to the vast range of resources available for consideration. In this paper, we propose a hybrid fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) and analytical hierarchy process (AHP) that is able to tackle vagueness and ambiguity in data and produce weights for all criteria in the MCDM problem. By utilizing this methodology, different aspects of experts’ data evaluation including fuzzy values can be converted into crisp values. Accuracy in each decision matrix is ensured by determining the weights of the subcriteria. We then apply the model to sustainable biomass resource selection in Ghana. Specifically, we comprehensively review the sustainable criteria within the bioenergy domain namely social, environmental, and economic aspects together with thirteen subcriteria. The proposed model was applied to biomass resource alternatives including crop residue, animal manure, forest residue, energy crops, and municipal solid waste. Results show the weights of thirteen subcriteria to be within the range of 0.10340 and 0.05263. The FTOPSIS shows that animal manure may be the most desirable resource for bioenergy production in Ghana, followed by energy crop, municipal solid waste, forest residue, and crop residue, respectively. Engineering and energy planning problems with conflicting multicriteria data can be easily solved by using this proposed hybrid AHP/FTOPSIS framework.

Keywords: Multicriteria decision-making; Analytical hierarchy process; Fuzzy logic; Technique for order preference by similarity to ideal solution; Biomass resources (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s10669-021-09810-6

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