کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
8115504 1522330 2016 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Assessment of solar energy potential over the United Arab Emirates using remote sensing and weather forecast data
ترجمه فارسی عنوان
ارزیابی پتانسیل انرژی خورشیدی در امارات متحده عربی با استفاده از داده های سنجش از دور و پیش بینی هوا
کلمات کلیدی
انرژی تجدید پذیر، تابش خورشیدی، شرایط آب و هوایی، محدودیت های زمین، مناطق مناسب
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
چکیده انگلیسی
This research proposes innovative maps to describe the land relative suitability indices for the implementation of solar energy systems (PV and CSP) over the United Arab Emirates. These maps have been developed by combining the solar irradiances maps (global horizontal irradiance and direct normal irradiance) with the effects of the land constraints (land slope, land use and land accessibility to the transportation infrastructure) and weather conditions (airborne dust properties, wind speed, relative humidity, air temperature). Remote sensing, weather forecast models and geospatial information system (GIS) offer excellent tools for estimating and monitoring the aforementioned data at high temporal and spatial resolutions. Indeed, these data have acceptable accuracy to provide a good understanding of the degree of exposure to these data over each location. Our results highlight the potential for using the considered tools to estimate the UAE land capability map, dust/relative-humidity/air-temperature risk map and finally the land relative suitability index for both PV and CSP power plants setting. The obtained results confirm that PV power plants are more appropriate for the UAE context than CSP power plants. In fact, the most suitable areas for PV power plants are located in the eastern side of the country, an area which represents 9.7% of the UAE's total land area. As for the CSP power plants, their most suitable areas are located on the coast nearby Abu-Dhabi and the extreme south of the UAE, with an area that represents 1%.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Renewable and Sustainable Energy Reviews - Volume 55, March 2016, Pages 1210-1224
نویسندگان
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