Optimal sites selection for solar farms development using Fuzzy-AHP method in Southern Khorasan province

In recent years, there has been a growing demand for solar energy, as one of the cleanest and most innovative energy sources in the world. South Khorasan province is one of the less developed regions of Iran that the transfer of energy carriers to this province is costly. On the other hand, the development of agricultural farms in South Khorasan province is facing a serious challenge due to the lack of water resources in arid and desert climate. Therefore, the development of solar farms can be a good alternative for the development of agricultural farms, especially irrigated and non-strategic crops. The purpose of this study is to identify the optimal locations for the development of solar farms in South Khorasan province. The different stages of this research have been done in six steps. First, the criteria affecting the location of solar farms were identified by the Delphi method. In the second step, with the help of experts and environmentalists, the criteria were coded and screened. In the third step, the spatial database of effective criteria was established. In the fourth step, the weight of the effective criteria was calculated through the Analytic Hierarchy Process (AHP). In the fifth step, the layers of effective criteria were classified and coded. In the final step, the weighted fuzzy layers with gamma fuzzy operator was overlapped. The results showed that in South Khorasan province, the cities of Tabas (387.4 km2), Nehbandan (120.4 km2) and Sarayan (119.6 km2) are sites with very high optimality for the development of solar farms in the province, respectively. The optimal area by the cities of the province at the average, desirable and very desirable level for operation in different conditions was presented. The current results and even changing the existing conditions by re-implementing the proposed approach can consciously lead managers' decisions towards the wise development of the region, the use of environmental capacities and new energies.