Wind ramps present a significant challenge to the wind energy industry and are a source of inefficiency for wind farm owners and power grid operators. One approach to investigating wind ramp predictability is ensemble sensitivity analysis (ESA), which relates a scalar response function to an atmospheric variable at an earlier time. Applying ESA to wind ramps is challenging because the transient nature of the events makes it difficult to capture the ramp with a traditional response function that is fixed in space and time. This study introduces four response functions that are allowed to vary in space and time in order to identify key features of the wind ramp, such as the timing of the ramp and the largest horizontal extent of the ramp. Comparing these event-based response functions to a traditional response function reveals key differences in the sensitivity, which indicates that different aspects of the wind ramp event are sensitive to different atmospheric features. The use of multiple response functions is shown to provide a more complete understanding of the ramp event when compared to using only a traditional response function. Observation targeting is addressed by manipulating the ESA fields of six synoptically driven wind ramp events, with results showing that the horizontal location of the optimal target region varies widely between cases and a single observation location likely would not provide benefit to each case. These results indicate that a dynamic observing system would be preferable to a fixed observation for improving wind ramp forecasts.
- Data assimilation
- Mesoscale models
- Numerical weather prediction/forecasting