Online 24-h solar power forecasting based on weather type classification using artificial neural network

► The RBFN model can forecast PV power output accurately in sunny days and cloudy days. ► The RBFN model makes a direct forecast of the power output of the PV system. ► A self-organized map is applied to classify the local weather type. ► The main factors are identified to forecast the power output...

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Veröffentlicht in:	Solar energy 2011-11, Vol.85 (11), p.2856-2870
Hauptverfasser:	Chen, Changsong, Duan, Shanxu, Cai, Tao, Liu, Bangyin
Format:	Artikel
Sprache:	eng
Schlagworte:	Applied sciences Artificial intelligence Classification Climatology Direct energy conversion and energy accumulation Electric power generation Electrical engineering. Electrical power engineering Electrical power engineering Energy Equipments, installations and applications Exact sciences and technology Forecasting Miscellaneous Natural energy Neural network Neural networks Operators Photoelectric conversion Photovoltaic cells Photovoltaic conversion Photovoltaic power system Power forecasting Power networks and lines Solar cells Solar energy Solar power Solar power generation Solar radiation Weather Weather type
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