کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6859350 1438701 2018 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Online 3-h forecasting of the power output from a BIPV system using satellite observations and ANN
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Online 3-h forecasting of the power output from a BIPV system using satellite observations and ANN
چکیده انگلیسی
Photovoltaic (PV) systems are the reference technology in the solar-based electricity generation market. Rapid changes in solar radiation can alter PV power output; for this reason, knowledge of future atmospheric scenarios helps system operators to control the PV production in advance, reducing the instabilities that the electrical grid may suffer in electricity integration, and managing the auto consumption power output. With this is mind, we present a model to forecast (up to 3 h ahead) the building integrated photovoltaic (BIPV) system's power output, which is installed on the roof of the Solar Energy Research Center (CIESOL), Almería, Spain. The satellite images have been combined with Artificial Neural Networks (ANN) primarily to predict power output using the lowest number of input variables. The results, which can be considered highly satisfactory, demonstrate the ANN's prediction accuracy with an normalized root mean square error for all sky conditions of less than 26%, and with practically no deviation. We demonstrate how beneficial matching of two already proven techniques can bring about spectacular results in energy generation prediction for the BIPV system.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Electrical Power & Energy Systems - Volume 99, July 2018, Pages 261-272
نویسندگان
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