ESRL/PSD Seminar Series

One of the challenges of integrating large amounts of wind and solar power onto the electric grid is due to the high temporal variability of these power sources. In particular, wind power generation frequently can change by large amounts very rapidly, the occurrence of which is referred to as a wind ramp event. We present a Ramp Tool and Metric developed to identify ramps and quantify model skill at forecasting them. A standard metric (such as mean absolute error or root mean square error) that does not give special consideration to ramp events may not give an adequate representation of model skill or model skill improvement. To test the Ramp Tool and Metric we used the NOAA/ESRL Rapid Refresh Numerical Model (RAP) with13-km horizontal resolution which was used during the Wind Forecast Improvement Project (WFIP) that took place in the Great Plains during 2011-2012. This ramp tool has three components: The first is a process to identify ramp events in the time series of power. Three different ramp identification methods were applied to see if a consistent best method can be identified. The second component is a method for matching in time each forecast ramp event with the most appropriate observed ramp event. The third and last component of the ramp tool is a process through which a skill score of the forecast model is determined. The skill score is calculated from a utility operator’s perspective, incorporates both phase (timing) and amplitude errors, and recognizes that up and down ramps can have significantly different impacts on grid operation. Since no single pair of power and time thresholds defines a ramp, and in fact some utilities may be interested in several different ramp definitions at the same time, the ramp skill metric integrates skill over a range of changes in power over different time windows.