Introduction: The growing demand for energy, the depletion of fossil fuel resources, and the increasing environmental impacts associated with conventional energy production, including greenhouse gas emissions, climate change, and air pollution, have intensified the global transition toward renewable energy resources. Among various renewable energy alternatives, solar energy has received considerable attention because of its abundance, environmental compatibility, and long-term sustainability. Iran is recognized as one of the countries with significant solar energy potential due to its favorable geographical location, high annual solar radiation, and extensive areas suitable for photovoltaic development. Nevertheless, the successful implementation of solar power projects depends largely on selecting appropriate locations that satisfy technical, environmental, economic, and infrastructural requirements. Improper site selection may increase construction and operational costs, reduce energy generation efficiency, and create environmental conflicts. Consequently, scientific site selection has become one of the fundamental stages in renewable energy planning. Geographic Information Systems (GIS), combined with Multi-Criteria Decision-Making (MCDM) techniques, have proven to be effective tools for evaluating spatial suitability by integrating numerous criteria simultaneously. Accordingly, the present study aims to identify, evaluate, and map suitable areas for solar power plant development in Bojnord County using GIS-based spatial analysis and multi-criteria evaluation in order to support sustainable energy planning and facilitate optimal utilization of the region's solar energy potential.
Materials and Methods: This study is an applied research conducted using a descriptive–analytical approach based on Geographic Information Systems. Twelve effective criteria representing climatic, environmental, technical, and infrastructural conditions were considered in the site selection process. These criteria included solar radiation, slope, distance from urban population centers, distance from rural settlements, distance from roads, distance from power transmission lines, distance from industrial centers, distance from wells, distance from gas transmission lines, distance from agricultural lands, distance from faults, and distance from rivers. The required spatial data were collected from relevant governmental organizations and reliable spatial databases and were processed to produce thematic GIS layers. Since the selected criteria possessed different measurement scales and units, all layers were standardized using fuzzy membership functions to transform them into a common suitability scale ranging from minimum to maximum suitability. The relative importance of each criterion was determined through the Analytic Hierarchy Process (AHP) based on pairwise comparison matrices completed by seventeen experts with relevant professional experience. The weighted criteria were subsequently integrated using the weighted overlay method within the GIS environment to produce the final land suitability map. This integrated framework enabled simultaneous consideration of multiple influencing factors and provided a comprehensive spatial evaluation for identifying the most appropriate locations for solar power plant construction.
Results and Discussion:
The spatial analysis revealed considerable variation in land suitability across Bojnord County. The final suitability map indicated that the central parts of the county and several areas with appropriate access to technical infrastructure, particularly electricity transmission lines and transportation networks, possess the highest suitability for solar power plant development. These areas benefit from favorable solar radiation conditions, relatively gentle slopes, and appropriate spatial accessibility, making them more suitable for investment in photovoltaic energy projects. The results further demonstrated that solar radiation, distance from power transmission lines, and slope were the most influential criteria affecting the final suitability pattern, highlighting their critical role in determining optimal locations. Conversely, proximity to rivers, faults, agricultural lands, wells, and other environmentally sensitive areas reduced the suitability of several locations because of environmental protection requirements and technical limitations. The findings indicate that high solar radiation alone cannot guarantee the suitability of a site for photovoltaic development. Instead, a balanced consideration of climatic, environmental, technical, and infrastructural factors is necessary to achieve reliable site selection. The integration of GIS, AHP, fuzzy standardization, and weighted overlay analysis provided a systematic and efficient decision-support framework capable of improving the accuracy and reliability of spatial suitability assessment while reducing uncertainty associated with single-criterion evaluations.
Conclusion: The results of this research demonstrate that Bojnord County possesses considerable potential for solar energy development and contains several highly suitable areas for future photovoltaic power plant construction. The integrated GIS-based multi-criteria evaluation framework employed in this study successfully identified priority locations by simultaneously considering environmental, technical, climatic, and infrastructural factors. The generated suitability map can serve as a practical decision-support tool for planners, policymakers, and investors involved in renewable energy development by facilitating more informed site selection, reducing implementation costs, minimizing environmental impacts, and improving investment efficiency. Furthermore, the methodological framework adopted in this research can be applied to other regions with similar geographical and climatic characteristics to support renewable energy planning and sustainable regional development. The findings contribute to expanding the application of spatial decision-support techniques in renewable energy planning and provide a scientific basis for promoting clean energy production, enhancing energy security, and reducing dependence on fossil fuels in accordance with sustainable development objectives.