Estimating Ultraviolet Radiation From Global Horizontal Irradiance
Terrestrial ultraviolet radiation (UV) radiation is a primary factor contributing to the degradation of photovoltaic (PV) modules' efficiency and reliability over time. Therefore, accurate knowledge of terrestrial UV incident on the surface of the PV materials is essential to understand the deg...
Gespeichert in:
Veröffentlicht in: | IEEE journal of photovoltaics 2019-01, Vol.9 (1), p.139-146 |
---|---|
Hauptverfasser: | , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Terrestrial ultraviolet radiation (UV) radiation is a primary factor contributing to the degradation of photovoltaic (PV) modules' efficiency and reliability over time. Therefore, accurate knowledge of terrestrial UV incident on the surface of the PV materials is essential to understand the degradation of PV modules and provide reliable assessment of their service life. As PV is deployed in various climate zones, it is crucial that terrestrial UV information is available at various locations. However, the availability of terrestrial UV data-measured or modeled-is extremely limited. On the other hand, total solar irradiance (TS) datasets are relatively abundant. In this study, the National Renewable Energy Laboratory, its industry partners, and ASTM's International Subcommittee on Radiometry and Service Life Prediction are developing a simple method to estimate the clear-sky terrestrial UV irradiance (280-400 nm, 295-400 nm, 285-385 nm, or 295-385 nm) from total irradiance data (280-4000 nm). The goal is to provide reliable estimates of the UV received by samples as a function of location, orientation, tilt, and airmass, thus encompassing a variety of conditions. The Simple Model of the Atmospheric Radiative Transfer of Sunshine (SMARTS) model is used to estimate the UV:TS ratio under various scenarios, and examines the influences of atmospheric constituents, such as aerosols, precipitable water vapor or ozone, and of the local surface characteristics (albedo), on the predicted UV. |
---|---|
ISSN: | 2156-3381 2156-3403 |
DOI: | 10.1109/JPHOTOV.2018.2871780 |