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Journal Articles Renewable and Sustainable Energy Reviews Year : 2021

Overview of electrical power models for concentrated photovoltaic systems and development of a new operational model with easily accessible inputs

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Abstract

The utilization of multi-junction solar cells with high efficiency is still not widespread for terrestrial power applications. These solar cells, composed by several material layers, reach high efficiencies but its cost is expensive, more of 100 higher than classical silicon solar cells. Thus, one solution consists to use reduced sizing solar cells associated with optics mounted on solar tracker to concentrate the solar beam. Numerous meteoro-logical parameters such as beam solar irradiance, ambient temperature and air mass and especially spectral characteristics of sun radiation are involved in the conversion process and are generally used as inputs in power models. Several models from literature, different by their form and by the number and type of input variables, are presented; based on this state-of-art, some similar models are selected and tested on two experimental CPV systems located on two different sites, Ajaccio and Le Bourget du Lac. Then, an operational model of electrical power using inputs easily measured and available for a solar CPV plant operator is developed. It could be used as a decision-aided tool for investors in providing an estimation of the energy production capacity of the CPV systems on the future implantation site. This established model based on data measured on the CPV system in Ajaccio estimates the produced power with a root mean square error of about 5% on the two sites using only a reduced number of inputs.
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cea-03776106 , version 1 (13-09-2022)

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Mousaab Benhammane, Gilles Notton, Gregoire Pichenot, Philippe Voarino, David Ouvrard. Overview of electrical power models for concentrated photovoltaic systems and development of a new operational model with easily accessible inputs. Renewable and Sustainable Energy Reviews, 2021, 135, pp.110221. ⟨10.1016/j.rser.2020.110221⟩. ⟨cea-03776106⟩
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