|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|89367||2017||16 صفحه PDF||سفارش دهید||10424 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Applied Energy, Volume 206, 15 November 2017, Pages 1225-1240
Site selection for solar power plants is a critical issue for utility-size projects due to the significance of weather factors, proximity to facilities, and the presence of environmental protected areas. The primary goal of this research is to evaluate and select the best location for utility-scale solar PV projects using geographical information systems (GIS) and a multi-criteria decision-making (MCDM) technique. The model considers different aspects, such as economic and technical factors, with the goal of assuring maximum power achievement while minimizing project cost. An analytical hierarchy process (AHP) is applied to weigh the criteria and compute a land suitability index (LSI) to evaluate potential sites. The LSI model groups sites into five categories: âleast suitable,â âmarginally suitable,â âmoderately suitable,â âhighly suitableâ and âmost suitable.â A case study for Saudi Arabia is provided. Real climatology and legislation data, such as roads, mountains, and protected areas, are utilized in the model. The solar analyst tool in ArcGIS software is employed to calculate the solar insolation across the entire study area using actual atmospheric parameters. The air temperature map was created from real dispersed monitoring sensors across Saudi Arabia using interpolation. The overlaid result map showed that 16% (300,000â¯km2) of the study area is promising and suitable for deploying utility-size PV power plants while the most suitable areas to be in the north and northwest of the Saudi Arabia. It has been found that suitable lands are following the pattern of the approximate range of the proximity to main roads, transmission lines, and urban cities. More than 80% of the suitable areas had a moderate to high LSI. The integration of the GIS with MCDM methods has emerged as a highly useful technique to systematically deal with rich geographical information data and vast area as well as manipulate criteria importance towards introducing the best sites for solar power plants.