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A stochastic Markov chain model for simulating wind speed time series at Tangiers, Morocco

机译:摩洛哥丹吉尔风速时间序列的随机马尔可夫链模型

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摘要

Time series of then years of Hourly Average Wind Speed, HAWS, data from Tangiers station are analysed on a statistical basis by applying the Markovian process. The limiting behaviour of the Markov chain is then examined and compared to the histogram of observed wind speed. It was found that a 12 x 12 transition probability matrix was necessary to generate an acceptable synthetic time series. The manner in which the Markovian model can be used to generate wind speed time series are also described. Using the transition probability matrix developed from the real wind data, the synthetic wind speed time series are generated. The comparison between the real wind speed and the synthetic one shows that the statistical characteristics of wind speed are faithfully reproduced. The synthetic HAWS may be utilised as input data for any wind energy system.
机译:通过应用马尔可夫过程,在统计学的基础上分析了丹吉尔站当时每小时平均风速,HAWS的时间序列。然后检查马尔可夫链的极限行为,并将其与观测风速的直方图进行比较。发现要生成可接受的合成时间序列,必须使用12 x 12的转换概率矩阵。还描述了马尔可夫模型可用于生成风速时间序列的方式。使用从实际风数据得出的过渡概率矩阵,可以生成合成风速时间序列。实际风速与合成风速的比较表明,忠实地再现了风速的统计特征。合成的HAWS可以用作任何风能系统的输入数据。

著录项

  • 来源
    《Renewable energy》 |2004年第8期|p.1407-1418|共12页
  • 作者单位

    Departement de Physique, Faculte des Sciences, B.P. 1014, Universite Mohammed. V-Agdal, Rabat, Morocco;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 能源与动力工程;
  • 关键词

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