A model based on artificial neuronal network for the prediction of the maximum power of a low concentration photovoltaic module for building integration

Solar Energy

Volumn 100, Issue , 2014, Pages 148-158

  Fernández, Eduardo F ^a   Almonacid, F ^a   Sarmah, N ^b   Rodrigo, P ^a   Mallick, T K ^b   Perez Higueras P ^a  

^a UNIVERSITY OF JAÉN   (Spain)

^b UNIVERSITY OF EXETER   (United Kingdom)

Author keywords

Artificial neural networks; Building integration; Low concentrator photovoltaics; Maximum power prediction

Indexed keywords

ARTIFICIAL NEURONAL NETWORK; BUILDING INTEGRATION; CONCENTRATOR PHOTOVOLTAICS; DIFFUSE IRRADIANCE; LOW CONCENTRATIONS; MAXIMUM POWER; MODULE TEMPERATURE; PHOTOVOLTAIC TECHNOLOGY;

INCIDENT SOLAR RADIATION; NEURAL NETWORKS; NEURONS; PHOTOVOLTAIC CELLS;

INTEGRATION;

ARTIFICIAL NEURAL NETWORK; ERROR ANALYSIS; IRRADIANCE; NUMERICAL MODEL; PHOTOVOLTAIC SYSTEM; PREDICTION; RENEWABLE RESOURCE; SOLAR POWER; TECHNOLOGICAL DEVELOPMENT;

EID: 84891053883     PISSN: 0038092X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.solener.2013.11.036     Document Type: Article

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