Please use this identifier to cite or link to this item: http://ktisis.cut.ac.cy/handle/10488/9523
Title: Applications of ANNs in the field of the HCPV technology
Authors: Almonacid, Florencia 
Mellit, Adel 
Kalogirou, Soteris A. 
Keywords: High-concentrator photovoltaics;Artificial neural networks
Category: Environmental Engineering
Field: Engineering and Technology
Issue Date: 5-Aug-2015
Publisher: Springer Verlag
Source: High Concentrator Photovoltaics, 2015, Pages 333-351
metadata.dc.doi: 10.1007/978-3-319-15039-0_12
Abstract: High-concentrator photovoltaic (HCPV) devices are based on the use of multijunctions solar cells and optical devices. Therefore, the electrical modelling of an HCPV device presents a great level of complexity. Several artificial neural network (ANN)-based models have been developed to try to address this issue. In this chapter, a review of the developed ANN-based models developed to try to address some issues related with the field of high concentrator PV technology is reported. In addition, the results obtained from the application of some of these models to estimate the electrical parameters of an HCPV module-such as maximum power, short-circuit current, and open-circuit voltage-are presented. The results show that the ANNs are a useful tool for modelling HCPV applications.
URI: http://ktisis.cut.ac.cy/handle/10488/9523
ISBN: 978-3-319-15039-0
Rights: © Springer International Publishing Switzerland 2015
Appears in Collections:Κεφάλαια βιβλίων/Book chapters

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