Abstract
Concentrating solar technologies, which are fuelled by the direct normal component of solar irradiance (DNI), are among the most promising solar technologies. Currently, the state-of the-art methods for DNI evaluation use datasets of aerosol optical depth (AOD) with only coarse (typically monthly) temporal resolution. Using daily AOD data from both site-specific observations at ground stations as well as gridded model estimates, a methodology is developed to evaluate how the calculated long-term DNI resource is affected by using AOD data averaged over periods from 1 to 30 days. It is demonstrated here that the use of monthly representations of AOD leads to systematic underestimations of the predicted long-term DNI up to 10% in some areas with high solar resource, which may result in detrimental consequences for the bankability of concentrating solar power projects. Recommendations for the use of either daily or monthly AOD data are provided on a geographical basis.
Highlights
IntroductionThe current state-of-the-art approach for the assessment of the long-term solar resource over wide areas relies on relatively accurate algorithms to evaluate cloud extinction based on the cloud reflectance sensed from spaceborne spectrometers[23,24,25,26,27,28]
The bias describing the difference between the DNI resource calculated from multi-day average aerosol optical depth (AOD) data as opposed to daily AOD data is always found negative
In the current context of advanced concentrating solar applications that require unbiased determinations of the long term DNI resource, long time series of accurate AOD data are required as inputs to the radiation models to provide DNI at the desirable high spatio-temporal resolution
Summary
The current state-of-the-art approach for the assessment of the long-term solar resource over wide areas relies on relatively accurate algorithms to evaluate cloud extinction based on the cloud reflectance sensed from spaceborne spectrometers[23,24,25,26,27,28] This is further combined with clear-sky irradiance evaluations based, most importantly, on aerosol optical depth (AOD) data. Most of these models are still in early development stages and the AOD datasets based on their simulations are scarce, available only for limited historical periods, or with only limited accuracy They have started to be used for solar radiation evaluation in combination with satellite-based retrievals of cloud reflectance[39,40,41], they are not expected to replace the traditional approach based on AOD observations
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