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Markov chain modeling for very-short-term wind power forecasting

机译:马尔可夫链模型用于极短期风能预测

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摘要

A Wind power forecasting method based on the use of discrete time Markov chain models is developed starting from real wind power time series data. It allows to directly obtain in an easy way an estimate of the wind power distributions on a very short-term horizon, without requiring restrictive assumptions on wind power probability distribution. First and Second Order Markov Chain Model are analytically described. Finally, the application of the proposed method is illustrated with reference to a set of real data. (C) 2015 The Authors. Published by Elsevier B.V.
机译:从实际风电时间序列数据出发,开发了基于离散时间马尔可夫链模型的风电预测方法。它允许以简便的方式直接获得非常短期的风电分布估计,而无需对风电概率分布进行限制性假设。一阶和二阶马尔可夫链模型进行了分析描述。最后,参考一组实际数据说明了所提出方法的应用。 (C)2015作者。由Elsevier B.V.发布

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