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UV-A Estimation in Atacama Desert from GHI Measurements by Using Artificial Neural Network

机译:利用人工神经网络从GHI测量值估算阿塔卡马沙漠中的UV-A

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The Atacama Desert presents ideal conditions for the proliferation of solar projects due to the high solar resource present in the area. However, Atacama Desert is also known to have a large amount of ultraviolet radiation due to the scarcity of ozone and aerosols in its atmosphere. Ultraviolet radiation is harmful to the people who work under its influence and affects the durability of the materials used in PV facilities. Two useful models for the estimation of solar irradiance and daily solar irradiation in the ultraviolet A spectral range in the Atacama Desert are shown in this paper. The models were generated by using artificial neural networks and use global horizontal irradiance measurements and astronomical calculations as inputs. Results show relative errors of 6% and 3% for the estimations of UV-A irradiance and UV-A daily irradiation, respectively. Therefore, these models show that they are reliable for the estimation of solar radiation in the UV-A range in the Atacama Desert, being able to provide information in those places where it is needed.
机译:阿塔卡马沙漠为该地区太阳能项目的发展提供了理想的条件,这是因为该地区拥有大量的太阳能资源。但是,由于大气中臭氧和气溶胶的稀缺性,阿塔卡马沙漠也有大量的紫外线辐射。紫外线辐射对在其影响下工作的人员有害,并影响光伏设施中使用的材料的耐用性。本文介绍了两个有用的模型,用于估算阿塔卡马沙漠中紫外线A光谱范围内的太阳辐照度和日太阳辐照度。这些模型是使用人工神经网络生成的,并使用整体水平辐照度测量和天文计算作为输入。结果表明,估计UV-A辐照度和每日UV-A辐照度的相对误差分别为6%和3%。因此,这些模型表明,它们对于估算阿塔卡马沙漠中UV-A范围内的太阳辐射是可靠的,能够在需要的地方提供信息。

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