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Atmospheric extinction in solar tower plants - A review

Journal

SOLAR ENERGY
Volume 152, Issue -, Pages 193-207

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.solener.2017.01.013

Keywords

Atmospheric extinction; Attenuation loss; Central receiver; Solar resource assessment; CSP

Categories

Funding

  1. Helmholtz Association within Helmholtz NREL Solar Energy Initiative (HNSEI) [SO-075]
  2. project on Impact of Desert Environment on Solar Energy Systems (DESERGY) [PD-205]

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In solar tower plants, radiation losses between the heliostat field and the receiver occur due to atmospheric extinction which varies with site and time. Currently, atmospheric extinction is usually approximated using a few constant standard atmospheric conditions in ray-tracing and plant optimization tools. Some tools allow the input of time dependent extinction data, but such site specific data sets are generally not available for prospective concentrated solar power (CSP) sites. In this paper, the most applied model equations which are implemented in different ray-tracing tools are summarized and compared. Several developed approaches to determine atmospheric extinction are presented. Furthermore, different studies about the effect of atmospheric extinction on the tower plant yield are summarized. It can be concluded that project developers should consider atmospheric extinction and its temporal variation as site specific data sets in power plant optimization, plant yield forecast and plant operation. The effect of atmospheric extinction can account for a reduction of the annual plant yield of up to several percent points and is dependent on the heliostat field size, the operation strategy and the on-site atmospheric conditions. Different approaches to determine atmospheric extinction for solar tower plants at a future CSP site have been developed and validated in the past and can be applied dependent on the prevailing atmospheric conditions. The costs of a power plant can be lowered by reducing the simulation uncertainty since it implies in turn a reduction of risk margins in plant yield forecasts. (C) 2017 Elsevier Ltd. All rights reserved.

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