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Assessment of spatial and temporal variability in the US solar resource from radiometric measurements and predictions from models using ground-based or satellite data

机译:根据地基或卫星数据的辐射测量和模型预测,评估美国太阳能资源的时空变异性

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The US National Renewable Energy Laboratory (NREL) is responding to a growing demand for high-accuracy solar resource data with uncertainties significantly lower than those of existing solar resource datasets, such as the National Solar Radiation Database (NSRDB). Measurements for long-term solar resource characterizations require years to complete, which is an unacceptable timeline for the rapidly emerging needs of renewable energy applications. This contribution seeks methods of reducing the uncertainty of existing long-term solar resource datasets by incorporating lower-uncertainty site-specific ground measurements of a limited period of record. In particular, various techniques are being explored to make full use of the existing high-resolution radiation data available in the NSRDB and other sources, and extrapolate them over time using locally measured data and other supportive information. The interannual variability in global and direct radiation is studied here using long-term data at various sites. NSRDB's modeled data for the 1998-2005 period are compared to quality-controlled measurements to assess the performance of the model, which is found to vary greatly depending on climatic condition. The reported results are encouraging for applications involving concentrators at very sunny sites. Large seasonal biases are found at some cloudy sites. Various improvements are proposed to enhance the quality of the existing model and modeled data. The measurement of solar radiation to characterize the solar climate for renewable energy and other applications is a time consuming and expensive operation. Full climate characterization may require several decades of measurements—a prospect that is not practical for an industry intent on rapid deployment of solar technologies. This study demonstrates that the consistency of the solar resource in both time and space varies widely across the United States. The mapped results here illustrate regions with high and low variability and provide readers with quick visual information to help them decide where and how long measurements should be taken for a particular application. The underlying data that form these maps are also available from NREL to provide users the opportunity for more detailed analysis.
机译:美国国家可再生能源实验室(NREL)对高精度太阳能资源数据的需求不断增长,其不确定性大大低于现有的太阳能资源数据集,例如国家太阳辐射数据库(NSRDB)。长期太阳能资源表征的测量需要数年才能完成,对于可再生能源应用迅速出现的需求来说,这是不可接受的时间表。该贡献力图寻求方法,通过结合有限记录期间的不确定性较低的特定地点的地面测量,来减少现有长期太阳能资源数据集的不确定性。尤其是,正在探索各种技术,以充分利用NSRDB和其他来源中现有的高分辨率辐射数据,并使用本地测量的数据和其他支持信息随时间推断它们。在这里使用不同地点的长期数据来研究全球辐射和直接辐射的年际变化。将NSRDB 1998-2005年的建模数据与质量控制的测量值进行比较,以评估该模型的性能,发现该模型的变化取决于气候条件。对于在阳光充足的地点使用选矿厂的应用,所报告的结果令人鼓舞。在一些多云的地点发现较大的季节性偏差。为提高现有模型和建模数据的质量,提出了各种改进措施。测量太阳辐射以表征可再生能源和其他应用的太阳气候是一项耗时且昂贵的操作。全面的气候特征描述可能需要数十年的测量时间-对于希望快速部署太阳能技术的行业而言,这种前景不切实际。这项研究表明,在整个美国,太阳能在时间和空间上的一致性差异很大。此处的映射结果说明了变化率高低的区域,并为读者提供了快速的视觉信息,以帮助他们确定针对特定应用应在何处以及多长时间进行测量。 NREL也可以提供构成这些图的基础数据,从而为用户提供进行更详细分析的机会。

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