Understanding wind ramp events through analysis of historical data

As renewable resources start providing an increasingly larger percentage of our energy needs, we need to improve our understanding of these intermittent resources so we can manage them better. In the case of wind resources, large unscheduled changes in the energy output, called ramp events, make it challenging to keep the load and the generation balanced. In this paper, we show that simple statistical analysis of the wind energy generation can provide quantitative insights into these ramp events. In particular, this analysis can help answer questions such as the time period during the day when these events are likely to occur, the relative severity of positive and negative ramps, and the frequency of their occurrence.