A multi-criteria GIS based model for wind farm site selection using interval type-2 fuzzy analytic hierarchy process: The case study of Nigeria

T.R. Ayodele, A.S.O. Ogunjuyigbe, O. Odigie and J.L. Munda

Applied Energy, 2018, vol. 228, issue C, 1853-1869

Abstract: The development of wind farm projects requires proper planning and evaluation. Most often, the suitability of locations for siting wind farms is based on the wind resource (i.e. wind speeds) of a location. However, other criteria such as environmental, economic, and social factors are also important during the planning stage at arriving at a robust wind farm siting decision. In this paper, a geographic information system-based model for wind farm site selection using interval type-2 fuzzy analytic hierarchy process is proposed and implemented to determine the suitable wind farm sites in Nigeria. The model focuses on the use of fuzzy sets to represent expert’s linguistic judgement with the aim of addressing the issues of uncertainty, vagueness and inconsistency in wind farm site selection decision making. The model uses two sets of criteria (weighted and constraint) which are either economic, social, or environmental in evaluating the suitable sites for wind farm development. The results of the study revealed that the best sites for wind farm development are basically located in the Northern part of Nigeria with Bauchi, Jigawa, Kaduna, Kano, Katsina, Plateau, and Sokoto states being the most suitable locations for wind farm projects. The suitable area for locating wind farm in the country is evaluated to be approximately 125728.6 km2, out of which about 2650.1 km2 are considered to be extremely suitable for siting a wind farm. This paper could serve as a first-hand scientific information for decision makers and planners in selecting the optimal suitable site for wind farm development. Although, Nigeria is considered as the case study, the methodology can be severally applied to any region in the world.

Keywords: Wind farm; GIS-based model; Site selection; Interval type-2 fuzzy AHP; Spatial analysis; Nigeria (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (65)

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DOI: 10.1016/j.apenergy.2018.07.051

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