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Modeling Daily Profiles of Solar Global Radiation Using Statistical and Data Mining Techniques

机译:使用统计和数据挖掘技术对太阳全球辐射的每日概况进行建模

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Solar radiation forecasting is important for multiple fields, including solar energy power plants connected to grid. To address the need for solar radiation hourly forecasts this paper proposes the use of statistical and data mining techniques that allow different solar radiation hourly profiles for different days to be found and established. A new method is proposed for forecasting solar radiation hourly profiles using daily clearness index. The proposed method was checked using data recorded in Malaga. The obtained results show that it is possible to forecast hourly solar global radiation for a day with an energy error around 10% which means a significant improvement on previously reported errors.
机译:太阳辐射预报对于多个领域都很重要,包括与电网连接的太阳能发电厂。为了满足对太阳辐射小时预报的需求,本文提出了使用统计和数据挖掘技术的方法,这些技术可以找到并建立不同日期的不同太阳辐射小时截面。提出了一种利用日清除指数预测太阳辐射小时剖面的新方法。使用马拉加中记录的数据检查了提出的方法。获得的结果表明,可以预测一天中每小时的全球太阳总辐射,其能量误差在10%左右,这意味着对先前报告的误差有很大的改善。

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