A Novel Implementation of Quality Checks of Spectral Direct Normal Irradiance Measurements

This study develops a robust quality control (QC) method for spectral irradiance measurements to improve solar resource assessment accuracy. It combines QC techniques for spectral and broadband irradiance data to detect systematic and random errors. Using EKO MS-711 spectroradiometers at two research sites, the method applies logical checks for physically plausible values and compares measurements with SMARTS2 clear-sky simulations (using AERONET/MERRA2 atmospheric data). A Python interface simplifies data comparison, aiming to boost spectral modeling adoption in photovoltaic research. Preliminary results confirm the method’s effectiveness and potential for future advancements.