Abstract
The production of wind energy often involves uncertainties due to the stochastic nature of wind speeds and the variation of the power curve. In this study, a method for modeling wind power plant in power systems reliability evaluation is proposed. This method is a combination of analytical and simulation methods. Initially, the mechanical behavior of each wind turbine generator (WTG) is modeled through sequential Monte Carlo method. Then, considering the wind speed of the area, the Markov model is used for modeling the power output of wind farm. The combination method is compared with the Auto Regressive Moving Average (ARMA) time series method and some other techniques such as Weibull and normal distribution methods in wind speed modeling. Also in this study, the effects of different parameters, such as failure, repair rate and number of output power levels of WTG on the system reliability are analyzed.
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