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Computing reliability indices of a wind power system via Markov chain modelling of wind speed

Author

Listed:
  • Serkan Eryilmaz
  • Ä°rem Bulanik
  • Yilser Devrim

Abstract

Statistical modelling of wind speed is of great importance in the evaluation of wind farm performance and power production. Various models have been proposed in the literature depending on the corresponding time scale. For hourly observed wind speed data, the dependence among successive wind speed values is inevitable. Such a dependence has been well modelled by Markov chains. In this paper, the use of Markov chains for modelling wind speed data is discussed in the context of the previously proposed likelihood ratio test. The main steps for Markov chain based modelling methodology of wind speed are presented and the limiting distribution of the Markov chain is utilized to compute wind speed probabilities. The computational formulas for reliability indices of a wind farm consisting of a specified number of wind turbines are presented through the limiting distribution of a Markov chain. A case study that is based on real data set is also presented.

Suggested Citation

  • Serkan Eryilmaz & Ä°rem Bulanik & Yilser Devrim, 2024. "Computing reliability indices of a wind power system via Markov chain modelling of wind speed," Journal of Risk and Reliability, , vol. 238(1), pages 71-78, February.
    • Handle: RePEc:sae:risrel:v:238:y:2024:i:1:p:71-78
    DOI: 10.1177/1748006X221133601
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    References listed on IDEAS

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    1. 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.
    2. 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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