Probabilistic ramp detection and forecasting for wind power prediction

Abstract

This paper presents a new approach to the critical problem of detecting or forecasting ramping events in the context of wind power prediction. The novelty of the model relies on departing from the probability density function estimated for the wind power and building a probabilistic representation of encountering, at each time step, a ramp event according to some definition. The model allows the assignment of a probability value to each possible magnitude of a predicted ramp and its worth is assessed by several metrics including ROC curves.