What we did
- Collect data from 320 publicly available ground stations measuring GHI.
- Collect data from 235 publicly available ground stations measuring DNI.
- Compare measurements with the same periods from our satellite-based irradiance model.
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The received irradiance represents the first step in the energy conversion process, as it defines the maximum theoretical amount of solar energy available before further losses are considered.
Ensuring the accuracy of solar radiation modeling is therefore crucial for reliable energy yield predictions.
We calculated the bias of modeled vs measured data and RMSD for all available stations, for both GHI and DNI series:
Bias follows expected probability for irradiance models for all climates.
RMSD for monthly, daily and hourly data showing consistent values.
A set of complete performance metrics was calculated, including bias, RMSD, KSI, and other indicators to show the relative frequency of exceedance situations and a combined performance index.
Environmental conditions define the operating environment in which the system functions. Therefore, accurate validation of temperature, wind, humidity, and other meteorological parameters is essential for assessing efficiency losses' accuracy and estimating long-term degradation effects.
For RH, the calculated mean bias is 0% (24 h) and standard deviation of 7% reflect solid agreement with ground measurements.
Accurate simulation algorithms are essential for optimizing PV system performance during the design process. Critical factors include the quality of the input data used to model energy conversion—from solar radiation to DC in PV modules, from DC to AC in inverters—and the estimation of energy losses during subsequent transmission and distribution.