Energy is an unavoidable requirement for humans. However, due to population expansion, the energy source is expected to become limited in the next years. As a result, consumers favor renewable, clean, and cost-effective energy sources. Unfortunately, there is no one source of energy that can fulfill these needs. Within the framework of a long-term and strategic process, determining the right energy policy problem with interactive criteria and alternatives can be seen as a multiple criteria decision making (MCDM) problem. One of the features of Iran's energy system is its reliance on imports. Different sets of decision-makers are engaged in the process of picking one of several Renewable Energy investment projects. Because of the increasingly complicated social, economic, technical, and environmental elements at play, decision-making must take multiple competing agendas into account. Traditional single-criterion decision-making is no longer capable of dealing with these issues. The VIKOR technique, also known as the Compromise Ranking method, introduces the Multi-criteria ranking index based on a specific measure of "closeness" to the "ideal" answer. The approach is used with the Analytical Hierarchy Process method to weight the relevance of the various criteria, allowing decision-makers to give these values depending on their preferences. The integration of renewable energy supply systems into energy supply networks is a critical lever for addressing the issues of sustainable development and climate protection. The synthesis issue, on the other hand, is an intrinsically complex process for which three hierarchically dependent layers must be considered. The configuration level is where equipment selection is made, the sizing level is where equipment capacity is calculated, and the operational level is where real load dispatch is specified. While these levels must be considered for any energy system, dealing with the complexity resulting from the temporal and spatial interdependencies associated with renewable resources, which usually necessitates the installation of storage systems, is a key challenge in the synthesis of renewable energy systems. Furthermore, the diversity of available technologies and conceivable combinations adds to the complexity. Furthermore, because the adoption of renewables is still often motivated by environmental concerns, both the economic and ecological consequences must be addressed. Thus, complicated linkages and trade-offs between technological, economic, and ecological implications must be weighed in order to identify the optimum solution for a specific synthesis challenge.
This study presents a synthesis approach for determining optimal solar and geothermal sites of the output layers of the Surface Energy Balance Algorithm for Land (SEBAL) algorithm, as well as a multi-criteria analysis of various environmental, socioeconomic, remote sensing data, and spatial information system. Identifying both prospective solar and geothermal locations together or adjacent to each other can not only provide a complementary output, but by combining these two energies, it addresses the deficiencies in each of their separate performance. The designation of such regions necessitates a thorough understanding of their efficacy elements and criteria. To that aim, fifteen distinct data layers, as well as Landsat 8 satellite imaging, were used in northern Iran over two periods of cold season for ground energy and warm season for solar energy, digital elevation model and its derivatives. First, multiple types of study data are quantified, weighted, and then merged. Following that, for economic evaluation of the results, the two main factors, demographic-industrial centers and development of these centers, are experimenters and analyzed, and become a more suitable construction of power plants were classified into five classes: poor, medium, appropriate, and very appropriate. Separate analyses for solar and geothermal energy show that about 51% and 30% of solar and geothermal energy, respectively, are found in acceptable and extremely suitable regions. Furthermore, when economic considerations and population-industrial hubs are taken into account, the combined findings of these two energies show that almost 59% of the territories represent areas prone to solar energy and geothermal. These locations in the province's south, southeast, and central regions, as well as the province's north and northwest, have high potential for geothermal and solar energy.