Quantitative analysis of high-frequency radiometric databases. Application to the case of Seville

The short-term variability of solar resource is one of the main challenges faced by the large-scale implementation of photovoltaic (PV) systems today; this will increase as the installed power of solar PV increases. To evaluate its influence on electrical grid operation, it is essential to analyse the variability of solar resource based on high-frequency data, 30 s and shorter. In this study, the high-frequency measurements of Global Horizontal Irradiation (GHI) and Direct Normal Irradiation (DNI) recorded every 5 s at the radiometric station of the University of Seville for 20 years are analysed and characterised. For this purpose, a corrected database for GHI and DNI was obtained from the application of a correction methodology. To understand the reliability of this database it is required to know its uncertainty. This work proposes a methodology to quantify the uncertainty of high-frequency radiometric databases whose wrong data have been corrected. Applying it, the daily uncertainty is 2.69% for GHI and 4.07% for DNI. To characterize the distribution of the database, the distribution of high frequency k t and k b indices are modelled providing the fitting parameters. To characterize the variability of high-frequency measurements, transition matrices are proposed, which allow identifying both the magnitude and frequency of jumps. The results obtained show that jumps of up to 800 W/m 2 occur in both GHI and DNI. In the case of GHI, the percentage of jumps equal to or greater than 500 W/m 2 is 1.36%, about 43,000 jumps in a year in measurements every 5 s.