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Markov chain model for turbulent wind speed data

Author

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  • Kantz, Holger
  • Holstein, Detlef
  • Ragwitz, Mario
  • K. Vitanov, Nikolay

Abstract

A continuous state Markov chain of suitable order is employed to approximate the dynamics of surface wind speeds recorded at a single site. Using past observations, the model yields probabilistic forecasts of the future. We employ it for the prediction of turbulent gusts.

Suggested Citation

  • Kantz, Holger & Holstein, Detlef & Ragwitz, Mario & K. Vitanov, Nikolay, 2004. "Markov chain model for turbulent wind speed data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 342(1), pages 315-321.
    • Handle: RePEc:eee:phsmap:v:342:y:2004:i:1:p:315-321
    DOI: 10.1016/j.physa.2004.01.070
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    References listed on IDEAS

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    1. Ettoumi, F.Youcef & Sauvageot, H & Adane, A.-E.-H, 2003. "Statistical bivariate modelling of wind using first-order Markov chain and Weibull distribution," Renewable Energy, Elsevier, vol. 28(11), pages 1787-1802.
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    Cited by:

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    3. Wang, Jianzhou & Qin, Shanshan & Zhou, Qingping & Jiang, Haiyan, 2015. "Medium-term wind speeds forecasting utilizing hybrid models for three different sites in Xinjiang, China," Renewable Energy, Elsevier, vol. 76(C), pages 91-101.
    4. Tang, Jie & Brouste, Alexandre & Tsui, Kwok Leung, 2015. "Some improvements of wind speed Markov chain modeling," Renewable Energy, Elsevier, vol. 81(C), pages 52-56.
    5. D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2013. "First and second order semi-Markov chains for wind speed modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(5), pages 1194-1201.
    6. Kalantar, M. & Mousavi G., S.M., 2010. "Dynamic behavior of a stand-alone hybrid power generation system of wind turbine, microturbine, solar array and battery storage," Applied Energy, Elsevier, vol. 87(10), pages 3051-3064, October.
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