Document Type : Research Paper


Faculty member at ShahidBahonar University of Kerman, Iran


Extended Abstract
Most of the energy consumed in the world comes from fossil fuels. Combustion of fossil fuels enters a huge amount of sulfur and nitrogen oxides, carbon monoxide and carbon dioxide in the atmosphere. Continuous increases in greenhouse gas emissions and rising fuel prices are key drivers behind more effective efforts to use renewable energy sources. Renewable energies include diverse sources of natural and accessible energy. Given that these energies are not ideal, their use reduces the consumption of oil products and creates jobs and reduces the amount of environmental pollution. The prospect of using this energy in Iran, as well as other developed countries, has become significant in the way that the government has made the necessary planning in the fifth development plan. Therefore, considering the global policies of developing these energies in our country, in order to solve problems and create employment, will be inevitable. Studies in this regard suggest that the development of the use of new energy can play a significant role in increasing the security of the country's energy system. Due to low latitudes, Iran has more capability to receive this energy. To exploit this energy, there is a need to build solar power plants. Solar panels used in solar power plants are converters of solar radiation into electrical energy. One of the most important issues in using solar energy is determining where to use it, which has a great impact on the efficiency of solar power equipment. Therefore, taking advantage of the potential of the climate can have a positive effect on the conservation of energy resources. In this regard, it is important to identify appropriate and prone areas where solar energy is sufficient and able to replace current energies.
Materials & Methods
The required data in this study was collected from the ‘Iran’s Meteorological Organization’ for 30 years and was entered into the Excel environment and analyzed. In the Arc GIS software environment, the locations of the stations, according to their geographical coordinates, were added to the digital map of the area and the database was formed. To prepare the map of the climatic parameters, the layer for each parameter was first prepared using the IDW interpolation method in the Geo-statistical Analyst field in the ARCGIS software environment, and then, using the AHP method, an intra-layer weight was defined. By using the ‘Reclassify’ command in the ARCGIS software, each layer was classified into several classes and each class was classified according to its importance and mapped to it. Then, to obtain a final map representing potential regions, the interlayer weight was applied according to the importance and effectiveness of each layer. Then, by overlapping the weighted layers, using the ‘Fuzzy overlay’ command in the ‘Spatial Analyst’ section, a map of all-potential regions that represents the areas with high potential for the construction of the power plant was obtained.
Discussion and Results
In order to quantitatively evaluate the climate of solar power plants in the study area, the layers obtained from the sunshine, cloudy, dust, relative humidity, altitude and precipitation have been weighted. For this purpose, the weight of the effective indices has been obtained using the AHP model. Then, using the ‘Raster calculator’ command in the ARCGIS software, weighted difference maps were obtained, and finally, using the ‘Fuzzy overlay’ command in the same software, the final map which is a combination of overlapping of the harmonious layers, has been obtained. At last, the final map was made up of a combination of overlapping harmonious layers and the selection of the regions with the highest capacity for the construction of solar power plants.
The method used in this study is important in determining the effective indices in locating solar stations as overlapping of the harmonious layers. This method is achieved by taking into account the relative importance of all the effective indices in the final layer, which can be more credible than other methods, because this algorithm, using degree weights, gives the power to decision- makers to place more important factors which in his view affect the problem more, in the problem with the same importance and due to this superiority, the results of this method has a better resolution.. Accordingly, the results show that Fars province has a high potential in terms of solar electrical energy which in the study area, the cities of Neyriz, Estahban and Fasa are more indicative in this regard and have higher potential. It can also be concluded that the total relative weight of all indices has a greater effect on locating and cannot be determined only by one or more of the indices.


1- اﺳﻔﻨﺪﯾﺎری، علی، 1390، ﭘﺘﺎﻧﺴﯿﻞ‌ﺳﻨﺠﯽ ﻧﯿﺮوﮔﺎه‌ﻫﺎی ﺧﻮرﺷﯿﺪی ﺑﺎ ﺑﺮرﺳﯽ ﭘﺎراﻣﺘﺮﻫﺎی اﻗﻠﯿﻤﯽ در اﺳﺘﺎن ﺧﻮزﺳﺘﺎن ﺑﺎ اﺳﺘﻔﺎده از GIS، ﻫﻤﺎﯾﺶ ﻣﻠﯽ ژﺋﻮﻣﺎﺗﯿﮏ، ﺗﻬﺮان
2- ﺳﺎﻟﻨﺎﻣﻪ‌ﻫﺎی آﻣﺎری  ﺳﺎزﻣﺎن ﻫﻮاﺷﻨﺎﺳﯽ ﮐﺸﻮر،  1394.
3- ﺧﻮش‌اﺧﻼق، روﺷﻦ، ﺑﺮﻧﺎ؛ فرامرز، غلامرضا، رﺿﺎ؛ 1386، ﻣﮑﺎﻧﯿﺎﺑﯽ ﻧﯿﺮوﮔﺎه ﺧﻮرﺷﯿﺪی ﺑﺎ ﺗﻮﺟﻪ ﺑﻪ ﭘﺎراﻣﺘﺮﻫﺎی اﻗﻠﯿﻤﯽ، ﻧﺸﺮﯾﻪ ﺳﭙﻬﺮ، ﺷﻤﺎره 67.
4- ﻋﻠﯿﺠﺎﻧﯽ، ﮐﺎوﯾﺎﻧﯽ؛ بهلول، ﻣﺤﻤﺪ رضا؛ 1383، ﻣﺒﺎﻧﯽ آب و ﻫﻮاﺷﻨﺎﺳﯽ،اﻧﺘﺸﺎرات ﺳﻤﺖ،تهران
5- ﻋﻠﯿﺠﺎﻧﯽ، ﺑﻬﻠﻮل، 1383، آب و ﻫﻮای اﯾﺮان .اﻧﺘﺸﺎرات داﻧﺸﮕﺎه ﭘﯿﺎم ﻧﻮر.
6- ﻋﻠﯿﺰاده، ﮐﻤﺎﻟﯽ، ﻣﻮﺳﻮی، ﻣﻮﺳﻮی ﺑﺎﯾﮕﯽ؛ امین، غلامعلی، فرهاد، ﻣﺤﻤﺪ؛ 1379، ﻫﻮا و اﻗﻠﯿﻢ ﺷﻨﺎﺳﯽ، اﻧﺘﺸﺎرات داﻧﺸﮕﺎه ﻓﺮدوﺳﯽ ﻣﺸﻬﺪ.
7- ﻋﻠﯿﺰاده، اﻣﯿﻦ، 1386، اﺻﻮل ﻫﯿﺪروﻟﻮژی ﮐﺎرﺑﺮدی .اﻧﺘﺸﺎرات داﻧﺸﮕﺎه اﻣﺎم رﺿﺎ.
8- ﺣﯿﺪری، ﻣﺼﻄﻔﯽ، 1388، ﻣﮑﺎﻧﯿﺎﺑﯽ نیروگاه‌های ﺧﻮرﺷﯿﺪی در اﯾﺮان .ﻧﺸﺮﯾﻪ ﻣﺒﺪل ﮔﺮﻣﺎﯾﯽ
9- ﻣﻘﺼﻮدی، ا،1385، ﻣﻜﺎن ﻳﺎﺑﻲ ﻧﻴﺮوﮔﺎه ﺧﻮرﺷﻴﺪی ﺑﺎ اﺳﺘﻔﺎده از روش ﻫﺎی ﺗﺤﻠﻴﻞ ﭼﻨﺪﮔﺎﻧﻪ، ﭘﺎﻳﺎن ﻧﺎﻣﺔ ﻛﺎرﺷﻨﺎﺳﻲ ارﺷﺪ، ﺑﻪ راﻫﻨﻤﺎﻳﻲ  دﻛﺘﺮ ﺳﻴﺪ ﻓﺮﻳـﺪ ﻗﺎدری، رﺷﺘﺔ  ﻣﻬﻨﺪﺳﻲ ﺻﻨﺎﻳﻊ، داﻧﺸﮕﺎه ﺗﻬﺮان
10- Bahrami, M.; Abbaszadeh, P.; (2013), “An overview of renewable energies in Iran”, Renewable and Sustainable Energy Reviews, Vol. 24, p.p. 198-208,
11- Djurdjevic , D. Z.,( 2011), Perspectives and Assessments of Solar PV Power Engineering in the Republic of Serbia, Renewable and Sustainable Energy Reviews, Vol. 15, No. 5, PP. 2431–2446. 
12-Janke, J. R.,( 2010), Multi criteria GIS Modeling of Wind and Solar Farms in Colorado, Renewable Energy, Vol. 35, No. 10, PP. 2228-2234.
13- Ghastly A. and Y. Chalabi, (2010), solar electricity prospects in Oman using GIS-based solar radiation maps. Renewable and Sustainable Energy Reviews, 14, pp: 790-797.
14-Kenisarin, M. (2007), Solar Energy Storage Using Phase Change Materials, PP. 1913-1965.
15-Miller, A. L. (2012), Utility Scale Solar Power Plants, New Delhi: IFC.
16-Sánchez-Lozano J.M., J. Terrell -Solano, P.L. Soto-Elvira and M. Socorro Garcia Cascades, (2013): Geographical Information Systems (GIS) and Multi-Criteria Decision Making (MCDM) methods for the evaluation of solar farms locations: Case study in south-eastern Spain. Renewable and Sustainable Energy Reviews, 24, pp: 544-556.
17-Solangi K.H., M.R. Islam, R. Saidpur, N.A. Rahim and H. Fayez, (2011): A review on global solar energy policy. Renewable and Sustainable Energy Reviews, 15, pp: 2149-2163.
18-Zohoori M., (2012): Exploiting Renewable Energy Sources in Iran. Interdisciplinary J. of Contemporary Research in Business, 4, pp: 849-862.