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A rolling ARMA method for ultra short term wind power prediction

机译:用于超短期风力预测的滚动ARMA方法

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摘要

Wind power is one of the popular renewable energy in the world. And accurate wind power prediction can improve the quality of wind power integration and help to guarantee the safety of power grid system. In this paper, a Rolling Auto-regressive Moving Average(RARMA) method is proposed to improve the prediction accuracy for ultra short term wind power prediction. And for the purpose of illustrating the feasibility of the RARMA method, numerical experiments are conducted. Simultaneously, the Root Mean Square Error(RMSE), the Maximum Error(MAXE), Average Relative Error(ARE), and Prediction Accuracy Rate(PAR) are selected to compare the effect of prediction methods. The numerical results show that the RARMA method exhibits a promising prediction accuracy.
机译:风力是世界上受欢迎的可再生能源之一。准确的风电预测可以提高风力电力集成的质量,并有助于保证电网系统的安全性。本文提出了一种轧制自动回归移动平均(RARMA)方法以提高超短术语风力预测的预测精度。为说明Rarma方法的可行性,进行数值实验。同时,选择根均方误差(RMSE),最大误差(MAXE),平均相对误差(IS)和预测精度率(PAR)以比较预测方法的效果。数值结果表明,RARMA方法表现出有希望的预测精度。

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