Investigating Land Suitability for PV Farm and Existing Sites Using a Multi-Criteria Decision Approach in Gaziantep, Türkiye
Source abstract
Abstract
Nowadays, renewable energy facilities are coming to the forefront in order to protect nature and prevent climate change. In this context, location-based analyses are carried out for the most optimal use of renewable energy resources. This study aims to identify suitable locations for photovoltaic (PV) farms in Gaziantep using the Analytical Hierarchy Process (AHP) and Geographic Information System (GIS) technologies. The research incorporates various criteria, including solar radiation, land use, slope, aspect, distance to road, fault line proximity, distance to powerlines, and wind speed to evaluate potential sites for solar energy production. The AHP method is applied to prioritize these criteria through a pairwise comparison matrix and to calculate the weight values for each factor. The analysis reveals that approximately 80% of Gaziantep’s land is suitable for PV farm installation, with the southern region being the most favorable. Furthermore, the comparison between existing PV installations and the identified suitable areas highlights a high degree of alignment, with most of the current PV farms located in areas classified as suitable or highly suitable. Additionally, it was determined that 92% of the existing PV farms have been established within suitable areas. This indicates a high alignment between the identified suitable zones and the locations of the current PV installations, reflecting an effective site selection process based on the applied criteria. The study concludes that GIS-based AHP is an effective tool for rapid and reliable decision-making in renewable energy site selection, offering a valuable approach for future solar energy projects in Gaziantep and similar regions.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Multi-Criteria Decision Making · Solar Radiation and Photovoltaics · Soil and Land Suitability Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Map and Cadastre, Istanbul Topkapi University, 34020 Istanbul, Turkey
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