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Decomposed Threshold ARMAX Models for short- to medium-term wind power forecasting

机译:分解阈值ARMAX模型用于中短期风电预测

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The integration of wind energy into the electrical grid is complex due to the high variability of wind fields when electricity should be available all time. In this context, accurate wind power forecasts have to be given 48 h before. However, the major difficulty is that wind power is highly nonlinear and non-stationary. This paper proposes a methodology to cope with these two issues by a two folded model. First, the time-series are decomposed into a low and high frequency components to deal with non stationarity. Second, the nonlinearities are accounted by regimes defined by wind direction. The model called D-TARX is compared with other models with only regimes, only decomposition, and none. Results show that our model outperforms other models according to statistical criteria. The methodology is straightforward while more work could be performed to continue towards accurate wind power forecasts.
机译:由于风场的高度可变性(应始终有电可用),将风能集成到电网中非常复杂。在这种情况下,必须在48小时之前给出准确的风能预测。然而,主要的困难是风力是高度非线性且不稳定的。本文提出了一种通过两个折叠模型来应对这两个问题的方法。首先,将时间序列分解为低频和高频分量,以处理非平稳性。第二,非线性是由风向定义的。将称为D-TARX的模型与仅具有方案,仅具有分解且没有任何约束的其他模型进行比较。结果表明,根据统计标准,我们的模型优于其他模型。该方法简单易行,同时可以进行更多工作以继续进行准确的风能预测。

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