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Accurate prediction of wind ramp events is critical for ensuring thereliability and stability of the power systems with high penetration of windenergy. This paper proposes a classification based approach for estimating thefuture class of wind ramp event based on certain thresholds. A parallelizedgradient boosted regression tree based technique has been proposed toaccurately classify the normal as well as rare extreme wind power ramp events.The model has been validated using wind power data obtained from the NationalRenewable Energy Laboratory database. Performance comparison with severalbenchmark techniques indicates the superiority of the proposed technique interms of superior classification accuracy.

Wind ramp event prediction with parallelized Gradient Boosted Regression Trees