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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建模日出太阳能辐射的日常剖面

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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:太阳辐射预测对于多个领域很重要,包括连接到网格的太阳能发电厂。为了满足对太阳辐射的需求,每小时预测本文提出了使用统计和数据挖掘技术,这些技术允许不同的日期使用不同的太阳辐射小时曲线和建立。提出了一种使用日常透明指数预测太阳辐射时曲线的新方法。使用在Malaga中记录的数据检查所提出的方法。所得结果表明,在能量误差约为10%的能量误差可能预测每小时的太阳能全球辐射,这意味着对先前报告的误差有显着改善。

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