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

Abstract

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 12×12 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.