Spatio-temporal Kriging for spatial irradiance estimation with short-term forecasting in a thermosolar power plant
J. García Martín (TU Delft - Transport Engineering and Logistics, University of Seville)
Jose Ramon D. Frejo (University of Seville)
J. M. Maestre (University of Seville)
Eduardo F. Camacho (University of Seville)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
This article proposes a method to improve the efficiency of solar power plants by estimating and forecasting the spatial distribution of direct normal irradiance (DNI) using a sensor network and anemometer data. For this purpose, the proposed approach employs spatio-temporal kriging with an anisotropic spatio-temporal variogram that depends on wind speed to accurately estimate the distribution of DNI in real-time, making it useful for short-term forecast and nowcast of DNI. Finally, the method is validated using synthetic data from varying sky conditions, outperforming another state-of-the-art technique.
help_outline