Sensitivity of artificial neural network based model for photovoltaic system actual performance

Conference Proceeding - 2014 IEEE International Conference on Power and Energy, PECon 2014

Volumn , Issue , 2014, Pages 241-244

  Ameen, Ammar Mohammed ^a,b   Pasupuleti, Jagadeesh ^b   Khatib, Tamer ^c  

^a General Company of Electricity Production Middle Region   (Iraq)

^b Universiti Tenaga Nasional   (Malaysia)

^c UNIVERSITY OF KLAGENFURT   (Austria)

Author keywords

CFNN; field performance; Modeling of PV system; PV system

Indexed keywords

BACKPROPAGATION; NEURAL NETWORKS; PHOTOVOLTAIC CELLS; SUN;

ARTIFICIAL NEURAL-NETWORK BASED MODELING; BACK PROPAGATION ARTIFICIAL NEURAL NETWORK (BPANN); CFNN; FIELD PERFORMANCE; MEAN ABSOLUTE PERCENTAGE ERROR; MODELING OF PV SYSTEMS; PV SYSTEM; ROOT MEAN SQUARE ERRORS;

MEAN SQUARE ERROR;

EID: 84946691724     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/PECON.2014.7062449     Document Type: Conference Paper

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