Novel wind turbine reliability model-implementation to estimate wind farms capacity credit

The expanded integration of wind energy imposes technical challenges to maintain system reliability. In order to tackle these challenges, comprehensive reliability models for wind turbines and related factors are essential. Proposed algorithm classifies Wind Turbine Generator (WTG) components based on their impact on WTG output. There upon, the WTG has a composite three-state reliability model which aggregates WTG foremost components. The chronological operation conditions of each component is obtained using state duration sampling method. Precise Wind Farms (WFs) reliability assessment requires accurate Wind Speed (WS) forecasting methods which acknowledge WSs propagation through WFs terrains. Thus, WS variations are developed based on Weibull distribution. Offered algorithms are integrated to estimate the capacity factor of some WFs using Monte Carlo simulation method. The implied WS data are recorded in certain locations in Egypt which are candidates to host WFs. The utilized simulation environments are MATLAB and Simulink.