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An application of a Markov chain noise model to wind generator simulation

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  • Jones, D.I.
  • Lorenz, M.H.

Abstract

A method is presented of using a Markov process model to generate a random time series having similar characteristics, in terms of probability density and autocorrelation function, to a known series. As an extended example, it is shown how the Markov model was used to generate a time series of windspeeds as input to a generalised wind power system simulation. Studies were made of the effects of generator size and battery storage capacity on the average load current capable of being sustained by the wind generator.

Suggested Citation

  • Jones, D.I. & Lorenz, M.H., 1986. "An application of a Markov chain noise model to wind generator simulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 28(5), pages 391-402.
    • Handle: RePEc:eee:matcom:v:28:y:1986:i:5:p:391-402
    DOI: 10.1016/0378-4754(86)90074-1
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    References listed on IDEAS

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    1. McWilliams, B. & Sprevak, D., 1982. "The simulation of hourly wind speed and direction," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 24(1), pages 54-59.
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    Cited by:

    1. Evans, S.P. & Clausen, P.D., 2015. "Modelling of turbulent wind flow using the embedded Markov chain method," Renewable Energy, Elsevier, vol. 81(C), pages 671-678.

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