Mengying Li

Solar irradiance forecasts from numerical weather prediction (NWP) models are indispensable data sources in photovoltaic (PV) power forecasting, especially over long time horizons. It is well accepted that post-processing NWP forecasts is beneficial for the irradiance-to-power conversion process. However, this is primarily focused on the global horizontal irradiance (GHI), as GHI separation has been extensively used to generate the direct normal irradiance (DNI) and diffuse horizontal irradiance (DHI). Considering that there are some accumulated uncertainties in the GHI-separated DNI and DHI, and these irradiance components are available as NWP forecasts, this work directly incorporates all three post-processed NWP irradiance forecasts for improved PV power forecasting with the physical model chain. Compared with GHI separation, PV forecasts converted from all irradiance components are found to have better performance. Post-processing NWP irradiance forecasts generally reduces errors in the irradiance-to-power conversion process, the use of all post-processed irradiance components shows more benefits than GHI separation for PV power forecasting. Furthermore, an in-depth sensitivity analysis is performed to quantify the impact of each irradiance component on PV power forecasting with the physical model chain. It is found that DNI generally has a higher influence on the PV power output, while DNI also poses greater challenges for the post-processing step. Unexpectedly, DHI exhibits a considerably stronger impact on PV power forecasting than GHI when all irradiance components are used in the physical model chain. Given the increasing demand for accurate PV power forecasts, this work highlights the practical value of post-processed NWP irradiance forecasts for all three components. Such post-processing is essential for the efficient integration of solar energy systems.