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Generation of series of high frequency DNI years consistent with annual and monthly long-term averages using measured DNI data

机译：使用测量的DNI数据一致于年度和每月长期平均值的高频DNI年的一致性

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摘要

In recent years, many researchers are suggesting that statistical approaches are needed to achieve sound estimates of the economic feasibility of commercial Concentrating Solar Thermal Power (CSTP) plants. A key element of such statistical approaches is the capacity of generating large series of high-frequency years which are consistent with the estimated variability of the monthly and annual values of the relevant meteorological variables. This paper presents a method of using high-frequency solar Direct Normal Irradiance (DNI) measurements to generate high frequency DNI series consistent with the variability and distribution of natural series, and also matching monthly and annual long term averages. The method takes advantage of a novel technique for the nondimensionalization of measured high-frequency daily DNI curves. This nondimensionalization technique makes it possible to consistently use measured solar DNI data to generate new daily curves of high-frequency DNI data and the subsequent long series of high-frequency DNI years. The novel technique for the nondimensionalization of measured high-frequency daily DNI curves is based on the nondimensionalization of the temporal scale by dividing the elapsed Universal Time (UT) since sunrise by the total elapsed UT from sunrise to sunset and on the nondimensionalization of the solar DNI scale by dividing each actual solar DNI value by the corresponding DNI value of the clear-day solar DNI envelope curve.
机译：近年来，许多研究人员暗示需要统计方法来实现商业集中太阳能热功率（CSTP）植物的经济可行性的健全估计。这种统计方法的一个关键因素是产生大系列高频率的能力，这与相关气象变量的月度和年度价值的估计变化一致。本文介绍了一种使用高频太阳能直接正常辐照度（DNI）测量的方法，以产生与自然系列的可变性和分布一致的高频DNI系列，也是每月和年度长期平均值的匹配。该方法利用了用于测量的高频日DNI曲线的非潜能的新技术。这种非潜能化技术使得可以一致地使用测量的太阳能DNI数据来产生高频DNI数据的新日常曲线和随后的长系高频DNI岁。用于测量的高频日常DNI曲线的非潜能化的新技术基于分割经过的通用时间（UT），因为从日出到日落的总时间和日出的总时间和太阳能的非潜能化，以来DNI通过将每个实际的太阳能DNI值除以Qual Solar DNI信封曲线的相应DNI值来划分每个实际的太阳能DNI值。

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