Generating synthetic five-minute solar irradiance values from hourly observations

Abstract

We have developed a method for generating synthetic five-minute pairs of global horizontal irradiance (GHI) and direct normal irradiance (DNI), interpolated from hourly mean values.Our method develops a model based on five-minute pairs of GHI and DNI from a location where real five-minute data is available. Five-minute GHI and DNI clear sky index values are calculated for each five-minute time period, and hourly values are calculated for each hourly period. The hourly values identify a clear sky category into which the twelve five-minute GHI and DNI clear sky index values are placed. The result is clear sky categories each containing five-minute clear sky index values that capture how five-minute GHI and DNI fluctuates for each clear sky category.The process for generating synthetically interpolated five-minute pairs of GHI and DNI from hourly mean values is straightforward. Hourly GHI and DNI clear sky index values are used to identify the clear sky category from which twelve five-minute synthetic pairs of GHI and DNI clear sky index values are bootstrapped. The index values are multiplied by the modelled perfect clear sky GHI and DNI to give synthetically interpolated five-minute pairs of GHI and DNI.Our method performs well. The hourly total Normalised Root Mean Square Deviation (NRMSD) results for our method are 1.4–1.8% for GHI and 2.2–3.0% for DNI. The hourly total Mean Bias Deviation (MBD) results for our method are −0.6% to 0.2% for GHI and −1.5% to −0.2% for DNI. The R2 values between observed and synthetic hourly totals are all greater than 0.99. The monthly Kolmogorov-Smirnov Integral (KSI) values were good for 97% of all months for DNI and for all months for GHI.Our method can be applied to locations where only hourly data is available. For example, it could be applied to the Australian Bureau of Meteorology’s hourly solar irradiance gridded satellite data, to capture the spatial variation in solar irradiance for multiple locations. The result would be particularly useful, from a solar energy perspective, for designing a reliable renewable energy electricity system where its performance could be evaluated for any location in Australia.