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This paper addresses the problem of predicting a wind farm's power generationwhen no or few statistical data is available. The study is based on atime-series wind speed model and on a simple dynamic model of a DFIG windturbine including cut-off and cut-in behaviours. The wind turbine is modeled asa stochastic hybrid system with three operation modes. Numerical results,obtained using Monte-Carlo simulations, provide the annual distribution of awind farm's active power generation. For different numbers of wind turbines, wecompare the numerical results obtained using the dynamic model with thoseobtained considering the wind turbine's steady-state power curve. Simulationsshow that the wind turbine's dynamics do not need to be considered foranalyzing the annual distribution of a wind farm generation.

Probabilistic computation of wind farm power generation based on wind turbine dynamic modeling