The prediction of photovoltaic module temperature with artificial neural networks
Küçük Resim Yok
Tarih
2014
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier Ltd
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
In this study, photovoltaic module temperature has been predicted according to outlet air temperature and solar radiation. For this investigation, photovoltaic module temperatures have been determined in the experimental system for 10, 20, 30, and 40 °C ambient air temperature and different solar radiations. This experimental study was made in open air and solar radiation was measured and then this measured data was used for the training of ANN. Photovoltaic module temperatures have been predicted according to solar radiation and outside air temperature for the Aegean region in Turkey. Electrical efficiency and power was also calculated depending on the predicted module temperature. Kutahya, U§ak and Afyon are the most suitable cities in terms of electrical efficiency and power product in the Aegean region in Turkey.
Açıklama
Anahtar Kelimeler
ANN, Electrical efficiency, Photovoltaic power
Kaynak
Case Studies in Thermal Engineering
WoS Q Değeri
Scopus Q Değeri
Q1
Cilt
3
