Research Papers

Uncertainties in Modeled Direct Irradiance Around the Sahara as Affected by Aerosols: Are Current Datasets of Bankable Quality?

[+] Author and Article Information
Christian A. Gueymard

 Solar Consulting Services, P.O. Box 392, Colebrook, NH 03576Chris@SolarConsultingServices.com

http://eosweb.larc.nasa.gov/sse; http://www.pa.op.dlr.de/ISIS







J. Sol. Energy Eng 133(3), 031024 (Aug 17, 2011) (13 pages) doi:10.1115/1.4004386 History: Received January 11, 2011; Revised June 08, 2011; Published August 17, 2011; Online August 17, 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.

Copyright © 2011 by American Society of Mechanical Engineers
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Figure 1

Direct normal irradiance as a function of turbidity, air mass and precipitable water for background desert aerosols (top), and dust storm aerosols (bottom)

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Figure 2

Map showing the 14 measurement stations used in this study

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Figure 3

Monthly average Ångström turbidity coefficient measured by a sunphotometer at five ground sites. The long-term average (climatology) is indicated by the continuous line.

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Figure 4

Measured long-term average direct horizontal irradiance and monthly bias of various modeled datasets at Caceres (top) and Granada (bottom)

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Figure 5

Measured long-term average direct normal irradiance and monthly bias of various modeled datasets at Aswan

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Figure 6

Measured long-term average direct normal or horizontal irradiance and monthly bias of various modeled datasets at Cairo, Ilorin, Sede Boker, and Tamanrasset

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Figure 7

Measured monthly mean direct normal irradiance and bias of various modeled datasets at Sede Boker and TEI Crete

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Figure 8

Measured monthly mean direct normal irradiance and bias of various modeled datasets at Tamanrasset, Solar Village and Izana

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Figure 9

Measured monthly mean direct horizontal irradiance and bias of the 3Tier modeled datasets at Santa Cruz




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