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Gueymard C.A.,Solar Consulting Services
Journal of Solar Energy Engineering, Transactions of the ASME | Year: 2011

The design, energy output, and cost effectiveness of solar projects using concentrators critically depend on the resource in direct normal irradiance (DNI). Many modeled DNI datasets now exist, and a recent preliminary study has shown some areas of serious disagreement in Europe. So far, no rigorous performance assessment has been undertaken for other parts of the world. The present contribution focuses on North Africa and bordering regions, which have great solar potential for power plants based on thermal or photovoltaic concentration systems. The mean monthly and annual performance of eight different modeled datasets providing DNI is analyzed here, with respect to measured radiation data at 14 sites, which are used as "ground-truth". Relatively good results are generally obtained for sites in southern Europe. Serious problems, however, are found at various sites in North Africa or the Middle East. Most of these problems appear linked to inadequate aerosol optical depth data used by the models, and to the dust storms from the Sahara that regularly, and strongly, modify the aerosol regime. A method that can potentially correct these problems, or allow for model benchmarking based on a reference aerosol database, is proposed. The bankability of current datasets is questioned. © 2011 American Society of Mechanical Engineers.


Gueymard C.A.,Solar Consulting Services | Ruiz-Arias J.A.,University of Jaen | Ruiz-Arias J.A.,University of Malaga
Renewable and Sustainable Energy Reviews | Year: 2015

In this study, a detailed review of the performance of 24 radiative models from the literature is presented. These models are used to predict the clear-sky surface direct normal irradiance (DNI) at a 1-min time resolution. Coincident radiometric and sunphotometric databases of the highest possible quality, and recorded at seven stations located in arid environments, are used for this analysis. At most sites, an extremely large range of aerosol loading conditions and high variability in their characteristics are noticed. At one site (Solar Village), DNI was measured routinely with an active cavity radiometer with very low uncertainty compared to field pyrheliometers, which makes its dataset exceptional. The reviewed models are categorized into 5 classes, depending on the number of aerosol-related inputs they require. One of the models (RRTMG) is considerably more sophisticated (and thus less computationally efficient) than the other models-which are all of the parametric type currently in use in solar applications, and specifically devised for cloudless conditions. RRTMG is more versatile and is selected here for benchmarking purposes. The results show good consistency between the different stations, with generally higher prediction uncertainties at sites experiencing larger mean aerosol optical depth (AOD). Disaggregation of the performance results as a function of two aerosol optical characteristics (AOD at 1 j.im, ft, and Angstrom exponent, a) shows that the simplest parametric models' performance decreases when subjected to turbidity conditions outside of what is "normal" or "typical" under temperate climates. Only a few parametric models perform well under all conditions and at all stations: REST2, CPCR2, MMAC, and METSTAT, in decreasing order of performance. The Ineichen and Hoyt models perform adequately at low AODs, but diverge beyond a specific limit. REST2 is the only parametric model that performs similarly to the RRTMG benchmark under all AOD regimes observed here-and even sometimes better. The inspection of the models' performance when considering the simultaneous effects of both ft and a reveals a clear pattern in the models' error, which is influenced by the frequency distribution of a values. This suggests most models may have difficulty in correctly capturing the effect of a, and/or that observational and instrumental issues at high AOD values may also enhance the apparent model prediction errors. A study of the specific sensitivity of DNI on AOD confirmed previous findings. It is concluded that, assuming a "perfect" model, DNI can be modeled within 5% accuracy only if ft is known to within =t 0.02. © 2015 Elsevier Ltd. All rights reserved.


In the context of the current rapid development of large-scale solar power projects, the accuracy of the modeled radiation datasets regularly used by many different interest groups is of the utmost importance. This process requires careful validation, normally against high-quality measurements. Some guidelines for a successful validation are reviewed here, not just from the standpoint of solar scientists but also of non-experts with limited knowledge of radiometry or solar radiation modeling. Hence, validation results and performance metrics are reported as comprehensively as possible. The relationship between a desirable lower uncertainty in solar radiation data, lower financial risks, and ultimately better bankability of large-scale solar projects is discussed. A description and discussion of the performance indicators that can or should be used in the radiation model validation studies are developed here. Whereas most indicators are summary statistics that attempt to synthesize the overall performance of a model with only one number, the practical interest of more elaborate metrics, particularly those derived from the Kolmogorov-Smirnov test, is discussed. Moreover, the important potential of visual indicators is also demonstrated. An example of application provides a complete performance analysis of the predictions of clear-sky direct normal irradiance obtained with six models of the literature at Tamanrasset, Algeria, where high-turbidity conditions are frequent. © 2014 Elsevier Ltd.


Various types of precipitable water (PW) measurement are compared for different sites around Tucson, Arizona, where arid conditions prevail, and the sensitivity of irradiance to PW variations is largest. The accuracy of some determinations of this quantity is assessed by comparison with routine GPS meteorology data. Large scatter is obtained with all types of empirical functions relating PW to surface temperature and humidity data, but the climate sensitivity of this kind of determination is found lowest when relating PW to the surface specific humidity, rather than the more usual vapor pressure or dew point temperature. The impact on the accuracy of predicted direct normal irradiance (DNI) and global horizontal irradiance (GHI) of various sources of PW data, at either low or high temporal resolution, is assessed using predictions from the REST2 radiative model, in combination with co-located sunphotometric and radiometric data at Tucson during a 7-month period. Results suggest that the accuracy of the predicted DNI and GHI is only lightly sensitive to the uncertainty in the input PW data. In case PW is not measured locally, a convenient source of data is provided by reanalysis, such as from the MERRA model. © 2013 Elsevier Ltd.


Leloux J.,Technical University of Madrid | Lorenzo E.,Technical University of Madrid | Garcia-Domingo B.,University of Jaen | Aguilera J.,University of Jaen | Gueymard C.A.,Solar Consulting Services
Applied Energy | Year: 2014

Concentrating Photovoltaics (CPV) is an alternative to flat-plate module photovoltaic (PV) technology. The bankability of CPV projects is an important issue to pave the way toward a swift and sustained growth in this technology. The bankability of a PV plant is generally addressed through the modeling of its energy yield under a baseline loss scenario, followed by an on-site measurement campaign aimed at verifying its energy performance. This paper proposes a procedure for assessing the performance of a CPV project, articulated around four main successive steps: Solar Resource Assessment, Yield Assessment, Certificate of Provisional Acceptance, and Certificate of Final Acceptance. This methodology allows the long-term energy production of a CPV project to be estimated with an associated uncertainty of ≈5%. To our knowledge, no such method has been proposed to the CPV industry yet, and this critical situation has hindered or made impossible the completion of several important CPV projects undertaken in the world. The main motive for this proposed method is to bring a practical solution to this urgent problem. This procedure can be operated under a wide range of climatic conditions, and makes it possible to assess the bankability of a CPV plant whose design uses any of the technologies currently available on the market. The method is also compliant with both international standards and local regulations. In consequence, its applicability is both general and international. © 2013 Elsevier Ltd.

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