Abstract
Abstract. Renewable energy has less negative impacts on environment than fossil fuels. Iran has many resources for renewable energy exploitation but because of their high price, it has not been developed. Site selection is an important step for utilizing large investments like solar farms and wind turbines. Multi-criteria evaluation methods are commonly used for site selection. The purpose of this paper is to determine suitable sites for solar farm and wind turbine using GIS and AHP in Tehran, in order to generate a distributed network to increase power network stability. The final land suitability index was grouped in four categories as “most suitable”, “suitable”, “moderate” and “low suitable”. As a result 94.61% (789939.63 km2) is low suitable, 4.47% (37337.17 km2) is moderate, 0.59% (4964.22 km2) is suitable and 0.32% (2680.70 km2) is the most suitable for building wind turbine and for solar farm, 44.07% (8116.88 km2) is low suitable, 12.81% (2359.79 km2) is moderate, 35.10% (6464.29 km2) is suitable and 8.02% (1477.28 km2) is the most suitable.
Highlights
Iran is one of the many countries in the world that has the great resources for renewable energy exploitation but because of the low price of fossil fuels, the use of renewable energy has been neglected
MCDM is the method that can be used in these problems (Zoghi, Ehsani et al 2015). (Gorsevski, Cathcart et al 2013) used grouped SDSS for evaluating the suitability for wind farm site selection in northwest Ohio
The factors which are selected for solar site selection are: climatic, location and geomorphology (Zoghi, Ehsani et al 2015) and factors for wind turbine site selection are environmental and economical factors
Summary
Iran is one of the many countries in the world that has the great resources for renewable energy exploitation but because of the low price of fossil fuels, the use of renewable energy has been neglected. (Asakereh, Soleymani et al 2017) used GIS and fuzzyAHP method to prioritize the Khuzestan province in Iran to install PV farms They used fuzzy logic and fuzzy membership functions to create the techno-economic and environmental criteria layer and AHP to weight criteria and create the final map of land suitability for solar farm. (Yushchenko, de Bono et al 2017) used GIS and MCDM method to estimate the solar electricity generation in ECOWAS region in West Africa based on geographical and technical potentials. Their study take both grid connected solar systems and off-grid solar systems into consideration.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
