2026-04-23T21:10:25Zhttps://uvadoc.uva.es/oai/request
oai:uvadoc.uva.es:10324/659862025-01-31T07:45:41Zcom_10324_1158com_10324_931com_10324_894col_10324_1242
UVaDOC author Hernández Callejo, Luis author Rebollo, Miguel Ángel González author Cardeñoso Payo, Valentín author Alonso Gómez, Víctor author Bello Gutierrez, Hugo José author Moyo, Ranganai Tawanda author Morales Aragones, José Ignacio 2024-02-08T10:59:05Z 2024-02-08T10:59:05Z 2023 Romero, H.F.M.; Hernández-Callejo, L.; Rebollo, M.Á.G.; Cardeñoso-Payo, V.; Gómez, V.A.; Bello, H.J.; Moyo, R.T.; Aragonés, J.I.M. Synthetic Dataset of Electroluminescence Images of Photovoltaic Cells by Deep Convolutional Generative Adversarial Networks. Sustainability 2023, 15, 7175. https://doi.org/10.3390/su15097175 https://uvadoc.uva.es/handle/10324/65986 10.3390/su15097175 7175 9 Sustainability 15 2071-1050 Affordable and clean energy is one of the Sustainable Development Goals (SDG). SDG compliance and economic crises have boosted investment in solar energy as an important source of renewable generation. Nevertheless, the complex maintenance of solar plants is behind the increasing trend to use advanced artificial intelligence techniques, which critically depend on big amounts of data. In this work, a model based on Deep Convolutional Generative Adversarial Neural Networks (DCGANs) was trained in order to generate a synthetic dataset made of 10,000 electroluminescence images of photovoltaic cells, which extends a smaller dataset of experimentally acquired images. The energy output of the virtual cells associated with the synthetic dataset is predicted using a Random Forest regression model trained from real IV curves measured on real cells during the image acquisition process. The assessment of the resulting synthetic dataset gives an Inception Score of 2.3 and a Fréchet Inception Distance of 15.8 to the real original images, which ensures the excellent quality of the generated images. The final dataset can thus be later used to improve machine learning algorithms or to analyze patterns of solar cell defects. spa Synthetic Dataset of Electroluminescence Images of Photovoltaic Cells by Deep Convolutional Generative Adversarial Networks info:eu-repo/semantics/article 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URL https://uvadoc.uva.es/bitstream/10324/65986/1/sustainability-15-07175-v2%20%282%29.pdf File MD5 39b2c16f85ac7428f5e8a4f2d865204c 14334635 application/pdf sustainability-15-07175-v2 (2).pdf