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Method for Predicting Outputs of Photovoltaic Devices Based on Two-Dimensional Fourier Analysis and Seasonal Auto-Regression
Method for Predicting Outputs of Photovoltaic Devices Based on Two-Dimensional Fourier Analysis and Seasonal Auto-Regression
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机译:二维傅里叶分析和季节自回归的光伏装置输出量预测方法
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摘要
An output of a photovoltaic (PV) device is predicted by applying Fourier analysis to historical data to obtain frequencies and a mean of the frequencies in the data. Regression analysis is applied to the data to obtain a regression coefficient. Then, the prediction is a sum of the mean at the time step and a deviation from the mean at a previous time step, wherein the means are represented and approximated by selected frequencies, and the deviation for the previous time step is weighted by the regression coefficient.
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