First And Second Order Markov Chain Models For Synthetic Generation Of Wind Speed Time Series.

Abstract

Hourly wind speed time series data of two meteorological stations in Malaysia have been used for stochastic generation of wind speed data using transition matrix approach of the Markov chain process. The transition probability matrices have been formed using two different approaches; the first approach involves the use of the first order transition probability matrix of a Markov chain, and the second involves the use of a second order transition probability matrix that uses the current and preceding values to describe probabilistically the next wind s peed value.