A fuzzy information axiom based method to determine the optimal location for a biomass power plant: A case study in Aegean Region of Turkey. (1st December 2016)

• Record Type: Journal Article
• Authors: Cebi, Selcuk; Ilbahar, Esra; Atasoy, Aylin
• Is Part Of: Energy. Volume 116:Part 1(2016)
• Page Start: 894
• Page End: 907
• Publication Date: 2016-12-01
• Subjects: Biomass energy -- Facility location selection -- Multiple criteria decision making -- Fuzzy logic -- Opinion aggregation -- Information axiom; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2016.10.024
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Biomass energy is one of the fundamental renewable energy sources. It decreases fossil fuel combustion and consequently net greenhouse gas emissions since no new carbons aren't released to the atmosphere. Generally, agricultural, forest, animal and urban wastes are considered as potential sources for biomass energy. Among these sources, agricultural wastes are the most suitable type to generate biomass energy in Turkey. Aegean Region has a great potential with respect to its lands and its diversity of agricultural products. In this paper, the most appropriate location for a biomass power plant has been investigated among the eight alternative locations in Aegean Region by examining both quantitative and qualitative criteria. It is the first time, an integrated model including fuzzy sets, analytic hierarchy process, opinion aggregation method, and information axiom method has been proposed to obtain a solution for such a problem. According to the results, Aydin is determined as the most appropriate location for a biomass power plant at Aegean Region. Furthermore, a sensitivity analysis has been performed to present the reliability of the obtained results. Highlights: Biomass energy facility locations are evaluated for Aegean Region of Turkey. An integrated method for the evaluation of biomass facility locations is proposed. An original methodology is proposed to deal with the location selection problem.