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Modelling and prediction of global, direct and diffuse hourly solar irradiance

机译:全球,直接和弥散每小时太阳辐照度的建模和预测

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摘要

In this paper, a model for predicting hourly global, diffuse and direct solar irradiance is described. A dataset of measured air temperature, relative humidity, direct, diffuse and global horizontal irradiance for Madinah site (Saudi Arabia) were used in this study. Several combinations have been proposed, and the best performance is obtained by using sunshine duration, air temperature and relative humidity as inputs of the model. A good agreement between measured and predicted data is obtained. In fact, the correlation coefficient is more than 97% and the mean bias error is less than 0.8%. A comparison between artificial neural network (ANN) and the proposed model is presented in order to demonstrate its performance.
机译:在本文中,描述了一个用于预测小时全球总,漫射和直接太阳辐照度的模型。在这项研究中,使用了麦迪纳站点(沙特阿拉伯)的测得的气温,相对湿度,直接,扩散和整体水平辐照度的数据集。已经提出了几种组合,并且通过使用日照时长,气温和相对湿度作为模型的输入获得最佳性能。在测量数据和预测数据之间取得了良好的一致性。实际上,相关系数大于97%,平均偏差误差小于0.8%。为了证明其性能,将人工神经网络(ANN)与所提出的模型进行了比较。

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