Worldwide impact of aerosol’s time scale on the predicted long-term concentrating solar power potential

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.

Irradiance Variability Quantification and Small-Scale Averaging in Space and Time: A Short Review

“…The studies covered by this review have unanimously identified clouds as the dominant source of short-term fluctuations in surface irradiance and photovoltaic power. Beyond that, aerosols have been shown to considerably affect irradiance variability as well, albeit on relatively large spatiotemporal scales and with an emphasis on concentrated solar power applications [160][161][162][163][164][165][166][167][168][169][170][171]. In consideration of extreme dust events, such as forest fires or sand storms (which can quickly generate large numbers of aerosols [172]), aerosol-induced small-scale irradiance variability could be non-negligible and further research is necessary in this regard.…”

Dust impact on surface solar irradiance assessed with model simulations, satellite observations and ground-based measurements

“…This underestimation pattern of the peak AOD values is a consequence of imperfect forecasted meteorology and fading impact of the initial assimilation of MODIS AOD information on CAMS performance (MACC, 2015;Allen et al, 2013). Yet, despite this difference, the impact on the energy and SSR simulations is of the order of 10 % (see below description) in most cases (> 90 % of the spatial coverage), which highlights that CAMS 1-day forecasts are of great value and useful for solar energy potential planning and policies (Langerock et al, 2015;Charabi and Gastli, 2015;Kosmopoulos et al, 2015Kosmopoulos et al, , 2017Ruiz-Arias et al, 2016). Since the main inputs to the RTM are the AOD and the SZA, which can both be forecasted (CAMS AOD) and precalculated (SZA), the real time spatial and temporal estimation of the dust events impact on SSR is realistically feasible.…”

Answer to the reviewer #1 comments

“…The MODerate resolution Imaging Spectroradiometer (MODIS) sensors are among the primary instruments on board the polar orbit sun-synchronous NASA satellites Terra and Aqua (Salomonson et al, 1989). MODIS sensors have provided retrievals of AOD at 550 nm since February 2000 and June 2002 for Terra and Aqua satellites respectively.…”