کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
8070764 1521388 2018 28 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Estimation of daily global solar radiation using deep learning model
ترجمه فارسی عنوان
برآورد تابش خورشیدی جهانی روزانه با استفاده از مدل یادگیری عمیق
کلمات کلیدی
تابش خورشیدی جهانی، پارامترهای هواشناسی، یادگیری عمیق، بوقلمون،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی (عمومی)
چکیده انگلیسی
Solar radiation (SR) is an important data for various applications such as climate, energy and engineering. Because of this, determination and estimation of temporal and spatial variability of SR has critical importance in order to make plans and organizations for the present and the future. In this study, a deep learning method is employed for estimating the SR over 30 stations located in Turkey. The astronomical factor, extraterrestrial radiation and climatic variables, sunshine duration, cloud cover, minimum temperature and maximum temperature were used as input attributes and the output was obtained as SR. The datasets of 34 stations, spanning the dates from 2001 to 2007, were used for training and testing the model, respectively, and simulated values were compared with ground-truth values. The overall coefficient of determination, root mean square error and mean absolute error were calculated as 0.980, 0.78 MJm−2day−1 and 0.61 MJm−2day−1, respectively. Consequently, DL model has yielded very precise and comparable results for estimating daily global SR. These results are generally better than or they are comparable to many previous studies reported in literature, so one can conclude that the method can be a good alternative and be successfully applied to similar regions.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy - Volume 162, 1 November 2018, Pages 126-135
نویسندگان
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