Understanding Diurnal Patterns in Wind Power Generation Data
Integrating wind energy on the power grid is a challenging task given the intermittent nature of these resources. When the percentage of wind energy was small, control room operators did not have a major problem in scheduling wind resources. However, as this percentage has increased, it is clear that the operators will need more accurate forecasts, as well as any additional information they can exploit, to make better-informed scheduling decisions. In this paper, we investigate diurnal patterns observed in wind-power time series data. Using actual wind generation data from two sites, we try to identify these patterns, understand them better, and determine if it is possible to use weather conditions in the vicinity of the wind farms to predict the pattern for a day. Such analysis could provide insights useful in scheduling wind resources on days with inaccurate forecasts.