Sources of uncertainty in annual global horizontal irradiance data

Abstract

The major sources of uncertainty in short-term assessment of global horizontal radiation (G) are the pyranometer type and their operation conditions for measurements, whereas the modeling approach and the geographic location are critical for estimations. The influence of all these factors in the uncertainty of the data has rarely been compared. Conversely, solar radiation data users are increasingly demanding more accurate uncertainty estimations. Here we compare the annual bias and uncertainty of all the mentioned factors using 732 weather stations located in Spain, two satellite-based products and three reanalyses. The largest uncertainties were associated to operational errors such as shading (bias =-8.0%) or soiling (bias =-9.4%), which occurred frequently in low-quality monitoring networks but are rarely detected because they pass conventional QC tests. Uncertainty in estimations greatly changed from reanalysis to satellite-based products, ranging from the gross accuracy of ERA-Interim (+6.1 +18.8 6.7 %) to the high quality and spatial homogeneity of SARAH-1 (+1.4 +5.6 5.3 %). Finally, photodiodes from the Spanish agricultural network SIAR showed an uncertainty of +6.9 5.4 %, which is far greater than that of secondary standards (±1.5%) and similar to SARAH-1. This is probably caused by the presence of undetectable operational errors and the use of uncorrected photodiodes. Photodiode measurements from low-quality monitoring networks such as SIAR should be used with caution, because the chances of adding extra uncertainties due to poor maintenance or inadequate calibration considerably increase.

Global Climate Data Processing and Mapping of Degradation Mechanisms and Degradation Rates of PV Modules

“…The studies over large geographical regions can be made by processing GIS data estimated from Numerical Weather Predictions (NWP) including satellite or reanalysis models [20]. Even though satellite-based estimations can be more accurate than the reanalysis-based ones, the advantage of the second is the possibility to extract all the essential variables together in the same dataset, without gaps and identical timestamps.…”

“…In comparison with previous datasets (e.g., ERA-Interim), ERA5 provides a spatial resolution of 31 km and temporal resolution of hourly data from 1979 [16]. Also in the literature, the improvement on the accuracy of the global horizontal irradiance (GHI) is reported [20].…”

Quantifying the amplified bias of PV system simulations due to uncertainties in solar radiation estimates

“…The three radiation databases selected are implemented in PVGIS and provide at least two out of the three horizontal irradiance variables (Table 1). An extensive validation of these databases can be found in Urraca et al (2018aUrraca et al ( , 2017bUrraca et al ( , 2018b.…”

“…Ground measurements are the most accurate source of radiation data for PV simulations (Urraca et al, 2018b). However, ground sensors are sparsely distributed and rarely close to the PV system location.…”

“…They have global coverage and estimate other climatic variables required for PV simulations such as wind speed and temperature. But even with the recent progress made in reanalysis, they generally have coarser spatial resolutions and larger uncertainties than satellite-based models (Urraca et al, 2018b(Urraca et al, , 2017c.…”