太阳辐照度与光伏电站发电功率密切相关,其预报的准确性直接影响发电功率预报的准确性。根据光伏电站太阳辐照度实况、气象站实况、WRF(Weather Research and Forecast Model)模式辐照度预报、EC细网格数值预报以及太阳理论辐照度,利用...太阳辐照度与光伏电站发电功率密切相关,其预报的准确性直接影响发电功率预报的准确性。根据光伏电站太阳辐照度实况、气象站实况、WRF(Weather Research and Forecast Model)模式辐照度预报、EC细网格数值预报以及太阳理论辐照度,利用逐步回归法开展太阳辐照度预报订正研究,得到以下结论:①太阳辐照度实况与太阳理论辐照度的比值与EC细网格数值预报中气象要素的相关性优于太阳辐照度实况与气象要素的相关性;②不同时刻影响太阳辐照度的气象因子存在差异,通过逐步回归法建立不同时刻太阳辐照度预报模型;③在非晴天情况下,回归预报辐照度相对均方根误差比WRF模式预报辐照度降低10%左右,减小了辐照度预报误差。该研究成果在光伏电站的新能源数值预报服务中有一定的应用价值。展开更多
In this works, artificial neural network is com-bined with wavelet analysis for the forecast of solar irradiance. This method is characteristic of the preprocessing of sample data using wavelet transformation for the ...In this works, artificial neural network is com-bined with wavelet analysis for the forecast of solar irradiance. This method is characteristic of the preprocessing of sample data using wavelet transformation for the forecast, i.e., the data se-quence of solar irradiance as the sample is first mapped into several time-frequency domains, and then a chaos optimization neural network is established for each domain. The forecasted so-lar irradiance is exactly the algebraic sum of all the forecasted components obtained by the re-spective networks, which correspond respec-tively the time-frequency domains. On the basis of combination of chaos optimization neural network and wavelet analysis, a model is devel-oped for more accurate forecasts of solar irradi-ance. An example of the forecast of daily solar irradiance is presented in the paper, the historical daily records of solar irradiance in Shanghai constituting the data sample. The results of the example show that the accuracy of the method is more展开更多
文摘太阳辐照度与光伏电站发电功率密切相关,其预报的准确性直接影响发电功率预报的准确性。根据光伏电站太阳辐照度实况、气象站实况、WRF(Weather Research and Forecast Model)模式辐照度预报、EC细网格数值预报以及太阳理论辐照度,利用逐步回归法开展太阳辐照度预报订正研究,得到以下结论:①太阳辐照度实况与太阳理论辐照度的比值与EC细网格数值预报中气象要素的相关性优于太阳辐照度实况与气象要素的相关性;②不同时刻影响太阳辐照度的气象因子存在差异,通过逐步回归法建立不同时刻太阳辐照度预报模型;③在非晴天情况下,回归预报辐照度相对均方根误差比WRF模式预报辐照度降低10%左右,减小了辐照度预报误差。该研究成果在光伏电站的新能源数值预报服务中有一定的应用价值。
文摘In this works, artificial neural network is com-bined with wavelet analysis for the forecast of solar irradiance. This method is characteristic of the preprocessing of sample data using wavelet transformation for the forecast, i.e., the data se-quence of solar irradiance as the sample is first mapped into several time-frequency domains, and then a chaos optimization neural network is established for each domain. The forecasted so-lar irradiance is exactly the algebraic sum of all the forecasted components obtained by the re-spective networks, which correspond respec-tively the time-frequency domains. On the basis of combination of chaos optimization neural network and wavelet analysis, a model is devel-oped for more accurate forecasts of solar irradi-ance. An example of the forecast of daily solar irradiance is presented in the paper, the historical daily records of solar irradiance in Shanghai constituting the data sample. The results of the example show that the accuracy of the method is more
