RT Journal Article
T1 Estimation of visibility from spectral irradiance using artificial neural networks
A1 López Rodríguez, Gabriel
A1 Gueymard, Christian A.
A1 Bosch Saldaña, Juan Luis
A1 Alonso Montesinos, Joaquín
A1 Rapp Arrarás, Ígor
A1 Polo, Jesús
A1 Ballestrín, Jesús
A1 Barbero, Javier
A1 Caro Parrado, Manuel J.
A1 Batlles, Francisco J.
AB Visibility has become a key input to determine the transmission losses of solar radiation propagating between heliostats and the receiver of solar tower power (STP) plants. Recent studies suggest that haze can reduce visibility and increase these losses up to 25% compared to clear conditions. Monitoring visibility would thus be needed for proper design and operation of STPs, but this is usually not done at all potential sites. In this work, the dependence of visibility's magnitude on relative humidity (RH) and aerosol optical depth (AOD) at three different wavelengths is analyzed. To that effect, 1-min observations from a visibilimeter located in Huelva (southwestern Spain) are analyzed during the winter season. RH is linearly correlated with visibility and explains 46% of its variability. A complex non-linear relationship between visibility and AOD is observed with also dependence on RH. Artificial neural networks (ANN) are thus investigated here for mapping the complex and non-linear relationships between visibility, RH and AOD at multiple wavelengths. This improves results significantly, increasing the explained visibility variability up to 68% and reducing RMSD from 30% to 22% with almost zero bias. The ANN analysis shows that the visibility-AOD relationship is not sensitive to the specific wavelength at which AOD is measured. These findings show that, using ANN, visibility can be estimated from local observations of RH and AOD at only a single wavelength.
PB American Institute of Physics
SN 0094-243X
SN 1551-7616 (electrónico)
YR 2018
FD 2018-11
LK https://hdl.handle.net/10272/23183
UL https://hdl.handle.net/10272/23183
LA eng
NO López, G., Gueymard, C. A., Bosch, J. L., Alonso-Montesinos, J., Rapp-Arrarás, I., Polo, J., Ballestrín, J., Barbero, J., Caro-Parrado, M. J., & Batlles, F. J. (2018). Estimation of visibility from spectral irradiance using artificial neural networks. In AIP Conference Proceedings. SolarPACES 2017: International Conference on Concentrating Solar Power and Chemical Energy Systems. Author(s). https://doi.org/10.1063/1.5067059
NO The authors are grateful for the financial support provided by Spanish Project PRESOL (Forecast of Solar Radiation at the Receiver of a Solar Power Tower) with references ENE2014-59454-C3-2-R, ENE2014-59454-C3-1R1 and ENE2014-59454-C3-3-R which is funded by the Ministerio de Economıa y Competitividad and co-financed by the European Regional Development Fund (FEDER). The authors thank INTA-ESAt team for their assistance and for allowing the equipment to be installed in their facilities. The authors also thank the principal investigators of the El Arenosillo AERONET site: Dr. Victoria E. Cachorro and Dr. Margarita Yela.
DS Repositorio Institucional de la Universidad de Huelva
RD 30 may 2026