Multi-Scale Performance Assessment of Heliosat-4 and LCIM for Solar Irradiance Estimation in Argentina
Abstract
Accurate estimation of solar resources is essential for the development and deployment of large scale photovoltaic (PV) systems. Although in situ measurements are the standard for Surface Solar Irradiance (SSI) data, their limited spatial coverage drives the need for reliable spatio-temporal satellite-based models. This study evaluates the performance of two modelling approaches, Heliosat-4 (physical) and a locally tuned Cloud Index Method (CIM, hybrid), for estimating Global Horizontal Irradiance (GHI) over the Pampa Húmeda region of Argentina. The analysis builds on previous studies by incorporating two additional monitoring sites from the Saver Net network and evaluating the model performance at different temporal resolutions (10 min, 15 min and hourly). The preliminary validation results showed that the CIM based on GOES imagery outperformed the Heliosat 4 based on Meteosat Second Generation (MSG) imagery at all time scales evaluated, with better performance metrics and higher correlation with SSI.
Keywords
GHI, satellite-based models, solar resource estimation performance