Generation of synthetic solar datasets for risk analysis

Abstract

In this paper, we present a method for the synthetic generation of long-term time series of coupled 1-min global horizontal solar irradiance (GHI) and direct normal solar irradiance (DNI). This method requires an input of 10–15 annual time series of hourly DNI and GHI values that can be retrieved from satellite-based irradiance databases, and produces 100 years of 1-min solar radiation values that can be used for risk analysis or as input for solar plants performance simulation in a wide range of scenarios. The method consists of the conjunction of three steps. The first one, based on a stochastic procedure, is used to generate 100 years of monthly DNI and GHI values. The second step consists of the subsequent generation of daily irradiation values. To that end we have used a bootstrapping technique. The synthetic daily sequences have the same serial correlation structure as the observed data. The last step consists of the generation of 100 years of 1-min solar irradiance data out of the daily values based on the non-dimensionalization of the daily profiles by the clear sky envelope approach. The method has been applied for the location of Seville showing satisfactory results in terms of cumulative distribution functions (CDFs) of the synthetic data. We obtain an average monthly KSI (Kolmogorov-Smirnov test integral) index of 0.11 kWh/m2 for GHI and 0.26 kWh/m2 for DNI. The minimum KSI value is 0.07 kWh/m2 for GHI and 0.15 kWh/m2 for DNI obtained in January. The maximum KSI value is 0.19 kWh/m2 for GHI and 0.34 kWh/m2 for DNI obtained in June and August respectively.