کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1549381 1513086 2016 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Preliminary survey on site-adaptation techniques for satellite-derived and reanalysis solar radiation datasets
ترجمه فارسی عنوان
نظرسنجی اولیه در مورد تکنیک های انطباق سایت برای مجموعه داده های تابش خورشیدی حاصل از ماهواره و مجددا تجزیه و تحلیل شده است
کلمات کلیدی
تابش خورشیدی تابشی ماهواره ای، سازگاری با سایت قابلیت اطمینان داده ها برای پروژه های خورشیدی، داده های حاصل از مدل تابش خورشیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
چکیده انگلیسی


• Model-derived solar irradiance data usually has systematic errors and bias.
• Site adaptation refers to techniques for improving long-term solar data using measurements.
• Uncertainty of improved dataset is needed for bankable solar resource assessments.

At any site, the bankability of a projected solar power plant largely depends on the accuracy and general quality of the solar radiation data generated during the solar resource assessment phase. The term “site adaptation” has recently started to be used in the framework of solar energy projects to refer to the improvement that can be achieved in satellite-derived solar irradiance and model data when short-term local ground measurements are used to correct systematic errors and bias in the original dataset. This contribution presents a preliminary survey of different possible techniques that can improve long-term satellite-derived and model-derived solar radiation data through the use of short-term on-site ground measurements. The possible approaches that are reported here may be applied in different ways, depending on the origin and characteristics of the uncertainties in the modeled data. This work, which is the first step of a forthcoming in-depth assessment of methodologies for site adaptation, has been done within the framework of the International Energy Agency Solar Heating and Cooling Programme Task 46 “Solar Resource Assessment and Forecasting”.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Solar Energy - Volume 132, July 2016, Pages 25–37
نویسندگان
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