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

Eryılmaz, Serkan
Bulanık, İrem
Devrim, Yılser
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Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability
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.
Open Access; Article first published online: November 11, 2022, Issue published: February 2024; Published by Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability;; Serkan Eryilmaz, İrem Bulanik, Atilim University, Department of Industrial Engineering, Ankara, Turkey; Yilser Devrim, Atilim University Department of Energy Systems Engineering, Ankara, Turkey.
Expected energy not supplied; Loss of Load Probability; Hybrid system; Reliability; Renewable energy; Wind speed