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A through analysis of solar irradiation measurements in the region of Arica Parinacota, Chile

机译:智利Arica Parinacota地区太阳辐射测量的直通分析

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This paper presents radiometric and meteorological data measured at three ground stations (University of Tarapaca, Quiborax and Las Rejas) in the region of Arica-Parinacota (Chile). Global horizontal irradiance, diffuse horizontal irradiance, direct normal irradiance, surface temperature, wind speed and wind direction and relative humidity were measured and analysed for more than one complete year at each station. The data is filtered to guarantee its consistency and quality, following a particular set of filters selected and adapted for the radiometric conditions of Arica. Daily, monthly and yearly averages of solar irradiation and meteorological values are processed from the 10-min averages registered at the stations. The data collected indicates that there is a strong relationship between altitude and proximity to the coast, which influences the annual levels of solar energy. These results also show that the region of Arica-Parinacota has among the highest yearly values of solar radiation in the World and consequently a strong potential for capturing solar energy using photovoltaic (PV), concentrated photovoltaic (CPV) and concentrated solar power (CSP) technologies. The ground radiometric data has been compared with long-term satellite-derived data from NASA, NREL, CIEMAT, INPE BRASIL-SR and numerical model WRF. Overall, the model with the lowest error for GHI is CIEMAT and WRF models and for DNI is CIEMAT model. (C) 2017 Elsevier Ltd. All rights reserved.
机译:本文介绍了在Arica-Parinacota(智利)地区的三个地面站(塔拉帕卡大学,基波拉克斯大学和拉斯里哈斯大学)测量的辐射度和气象数据。在每个站点进行了一年以上的测量,并分析了整体水平辐照度,弥散水平辐照度,直接法向辐照度,表面温度,风速和风向以及相对湿度。遵循为Arica的辐射条件选择和调整的一组特定过滤器,对数据进行过滤以确保其一致性和质量。每天,每月和每年的太阳辐射和气象值的平均值是根据气象站记录的10分钟平均值得出的。收集到的数据表明,海拔高度与靠近海岸之间存在很强的关系,这会影响每年的太阳能水平。这些结果还表明,阿里卡-帕里纳科塔州地区是世界上年度太阳辐射值最高的地区之一,因此具有利用光伏(PV),聚光光伏(CPV)和聚光太阳能(CSP)捕获太阳能的强大潜力。技术。已将地面辐射数据与来自NASA,NREL,CIEMAT,INPE BRASIL-SR和数值模型WRF的长期卫星衍生数据进行了比较。总体而言,GHI的误差最小的模型是CIEMAT和WRF模型,而DNI的误差是CIEMAT模型。 (C)2017 Elsevier Ltd.保留所有权利。

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