Geo-spatial site selection for solar power plants using Geographic Information System (GIS) in Kermanshah Province, Iran

Volume 20 , Issue 3 , December 2019 , Pages 719-730

Authors

Hazhir Karimi 1 ; Hadi Ramin 2 ; Hawkar Bapeer Bakir 3

1 Department of Geography, Faculty of Education, Koya University

2 Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, Canada

3 Petroleum Engineering Department, Faculty of Engineering, Koya University, Koya Koy45, Kurdistan Region, Iraq

DOI logo 10.17656/jzsb.10936

Keywords

Abstract

In this study, integration of multi-criteria decision analysis and geographical information system (GIS) are used together to select the best solar farm sites in Kermanshah Province, Iran. For this aim, first, different criteria were identified, and maps were built in a GIS environment. Since the criteria have different scales and nature, theprepared maps were divided into layers. After that, the relative weights of these layers were determined, and weighted information layers were combined using the overlay method. The final index maps were grouped into four categories ranging from “no suitability” to “high suitability” with an equal interval classification method. The results reveal that 23 % of the area has high suitability for solar farms, mostly found in the southern parts, while the unsuitable sites represent 5%.

In conclusion, considering different criteria and technical requirements to select the appropriate solar farm site, is an effective approach which leads to a more efficient solar farm with minimum social and environmental issues. This approach can be replicated in any location providing availability of information and geographical data. The results of this study are particularly useful for investors and governments in developing countries such as Iran, Iraq and Saudi Arabia who are planning to build renewable energy sites. It is also recommended that in the future studies other decision criteria such as population growth, heritage sites, proximity to line power, and proximity to the location of the main power generation station would be considered to enhance the precision of the optimal sites and enrich proposed model.

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  • Published at26 December 2019

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