Parameterization of the direct and diffuse surface solar radiation components in the Global Solar Energy Estimator (GSEE) and related uncertainties in the energy production simulations

Solar energy will play key role in the effort for the decoupling from fossil fuels in the forthcoming decades. Minimizing the cost to energy production ratio for photovoltaics (PV) installations is key for the maximization of the potential benefits from their use. For this purpose, solar energy production models can be exploited for nowcasting, forecasting, and for climatological studies. PV panels are usually installed with tilt angles optimized for maximum energy production, and thus the energy production is usually not proportional to the global horizontal irradiance (GHI), which is the variable that is commonly measured at the surface. Both, the direct and the diffuse solar irradiances reaching the PV panels are necessary (to be used as inputs to the solar energy models) for the accurate quantification of the produced energy when the PV efficiency is known. Nevertheless, ground-based measurements of the diffuse irradiance are scarce, and estimates of the surface solar radiation (SSR) components (direct and diffuse), relied on Earth observations are usually more uncertain than ground-based measurements. The Global Solar Energy Estimator (GSEE) is a widely used open access solar energy simulation library which takes as input either the GHI or both, the GHI and the diffuse horizontal irradiance (DHI).  It simulates the produced energy for various types of PV panels at the tilt angles specified by the user, or for panels that are rotating at one or two dimensions. GSEE can estimate the solar energy production for specific locations taking as inputs the SSR parameters at timescales ranging from instantaneous to monthly integrals. When only the GHI is provided as input, multi-parametric equations are applied to estimate the DHI, and subsequently the produced energy (after applying further parameterizations to estimate the DHI fraction that reaches the panels). To quantify the uncertainty in the estimates of the energy production when only GHI is utilized as input with respect to aerosol and cloudiness conditions we use high quality measurements of the GHI and DHI at three stations of the Baseline Surface Radiation Network (BSRN) (Lindenberg, Carpentras, and Tamanraset) for one year (2017). In parallel, we perform the same analysis using the satellite GHI and DHI estimates from the Copernicus Atmospheric Monitoring Service (CAMS) for the aforementioned stations aiming to quantify the uncertainties in the energy production estimates when they are used instead of ground-based measurements.

Acknowledgements

This work has been supported by the action titled “Support for upgrading the operation of the National Network for Climate Change (CLIMPACT II)”, funded by the Public Investment Program of Greece, General Secretary of Research and Technology/Ministry of Development and Investments. The authors would also like to acknowledge the Action Harmonia CA21119 supported by COST (European Cooperation in Science and Technology).