| Título | UV-A Estimation in Atacama Desert from GHI Measurements by Using Artificial Neural Network |
|---|---|
| Autores | Mondaca, Gino , Trigo-Gonzalez, Mauricio , Marzo, Aitor , Alonso-Montesinos, Joaquin , Barbero, Javier , Salazar, German , Olivares, Douglas , FERRADA MARTINEZ, PABLO DANIEL, Cardemil, JM , Guthrie, K , Ruther, R |
| Publicación externa | No |
| Medio | Proceedings Of The Ises Solar World Conference 2019 And The Iea Shc Solar Heating And Cooling Conference For Buildings And Industry 2019 |
| Alcance | Proceedings Paper |
| Naturaleza | Científica |
| Fecha de publicacion | 01/01/2019 |
| ISI | 000604438100037 |
| DOI | 10.18086/swc.2019.08.08 |
| Abstract | The Atacama Desert presents ideal conditions for the proliferation of solar projects due to the high solar resource present in the area. However, Atacama Desert is also known to have a large amount of ultraviolet radiation due to the scarcity of ozone and aerosols in its atmosphere. Ultraviolet radiation is harmful to the people who work under its influence and affects the durability of the materials used in PV facilities. Two useful models for the estimation of solar irradiance and daily solar irradiation in the ultraviolet A spectral range in the Atacama Desert are shown in this paper. The models were generated by using artificial neural networks and use global horizontal irradiance measurements and astronomical calculations as inputs. Results show relative errors of 6% and 3% for the estimations of UV-A irradiance and UV-A daily irradiation, respectively. Therefore, these models show that they are reliable for the estimation of solar radiation in the UV-A range in the Atacama Desert, being able to provide information in those places where it is needed. |
| Palabras clave | UV-A irradiance; artificial neural network; Atacama Desert; Resource solar |
| Miembros de la Universidad Loyola |