Quality-Controlled Spectral Irradiance Data Processing for Photovoltaic Performance Modeling

Accurate spectral factor (SF) modeling for photovoltaic (PV) applications requires careful integration and analysis of spectral irradiance and broadband reference data. This study presents a robust methodology for preparing high-quality datasets suitable for developing spectral correction models. Specifically, the methodology encompasses (1) procedures for spectroradiometric extrapolation to reconstruct full-range solar irradiance from 280 to 4000 nm, and (2) protocols for validating the integrated spectroradiometer data against calibrated pyranometer measurements. The comparison between these measurement modalities is further examined as a function of the clearness index (Kt) to assess the sensitivity of the spectral-broadband relationship under varying sky conditions, including overcast events. The approach is demonstrated using one year of high-frequency spectral and broadband irradiance data from the Lindenberg Meteorological Observatory in Germany (52.209275 °N, 14.120870 °E). The resulting quality-controlled dataset provides new insights into the influence of spectral variability on PV performance prediction. This reproducible framework enables systematic assessment of spectral-mismatch effects, supporting more accurate and reliable PV energy-yield modeling.Spectral Irradiance, Photovoltaic Performance, PV Modeling, Spectral Effects, Spectral Factor, Spectral Correction.