Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/9523
Title: | Applications of ANNs in the field of the HCPV technology | Authors: | Almonacid, Florencia Mellit, Adel Kalogirou, Soteris A. |
Major Field of Science: | Engineering and Technology | Field Category: | Environmental Engineering | Keywords: | High-concentrator photovoltaics;Artificial neural networks | Issue Date: | 5-Aug-2015 | Source: | High Concentrator Photovoltaics, 2015, pp. 333-351 | 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: | https://hdl.handle.net/20.500.14279/9523 | ISBN: | 978-3-319-15039-0 | DOI: | 10.1007/978-3-319-15039-0_12 | Rights: | © Springer International Publishing Switzerland 2015 | Type: | Book Chapter | Affiliation : | University of Jaen Jijel University Cyprus University of Technology |
Publication Type: | Peer Reviewed |
Appears in Collections: | Κεφάλαια βιβλίων/Book chapters |
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