Modelling site selection for solar power establishment by fuzzy logic and ordered weighted averaging methods in arid and semi-arid regions (Case study Yazd province-IRAN)

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Research Paper 01/05/2017
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Modelling site selection for solar power establishment by fuzzy logic and ordered weighted averaging methods in arid and semi-arid regions (Case study Yazd province-IRAN)

Saeedeh Nasehi, Sakineh Shadkam Birak Olia, Saeed Karimi, Sousan Heydari
J. Bio. Env. Sci.10( 5), 177-192, May 2017.
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Solar energy as one of the cleanest, cheapest and available energies in the arid and semi- arid regions is receiving lots of scientific attention. Two thirds of Iran’s country having more than 300 sunny days in the year with average solar radiation of 4.5-5.5 Kw/hr/m2/day. The aim of this study is to provide a conceptual model for solar power site selection by considering spatial and climatologically information using Fuzzy Logic (FL), Analytic Network Process (ANP) and Ordered Weighted Averaging (OWA) methods. The database including climatic, geomorphologic, environmental, spatial and constrain parameters is prepared for analysis in the Geographic Information System (GIS). In the next step each layer was standardized and weighted through the fuzzy logic approach and overlaid by ANP and OWA methods Finaly, the best power solar site map with four classes of suitable, moderately suitable, relatively unsuitable and unsuitable is produced. The results showed that a conceptual model based on the combining FL, MCDM, OWA and ANP methods could provide the best solar power site with high accuracy in the arid and semi-arid regions. The cities of this province were inspected in terms of land suitability for solar power plant establishment. Many areas in the study area are placed in the appropriate category. Clearer Results showed Counties of Khatam and Sadugh have the best Suitability for the establishing of solar power plant, while cities of Marvast, Harat, Abarkooh, Ashkezar and Bafg in are among the suitable regions for development of the solar power plant.


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