Can Targeted Off-Site Observations of Boundary Layer Wind Profiles Improve Ramp Forecasting?

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Wednesday, 5 February 2014
Hall C3 (The Georgia World Congress Center )
Eric P. Grimit, 3TIER, Inc., Seattle, WA; and C. Maalouf, J. Lerner, and P. Storck

A multi-month field study funded by the US-Israel Binational Industrial Research and Development (BIRD) Foundation was conducted in 2013 in two prominent regions of Southern California with large installed wind power generation. The experiment was designed to test the impact that a small network of elastic lidars measuring boundary layer wind profiles and deployed in key areas near a target wind facility could have on wind power forecast skill in complex terrain. The Israeli company, Pentalum, supplied six direct-detection elastic lidars to the study and deployed three within each target area as the proof of concept. 3TIER determined the lidar siting locations using an iterative partial correlation approach based on an in-house 1-km WRF regional reanalysis filtered by up and down ramp events over a 2-year period. After the lidar wind data was collected and quality controlled, 3TIER conducted retrospective forecasts of the wind speed and power output at the target facilities for 2-3 hour lead times. The lidar wind data influenced the re-forecasts via both statistical and physical models. In addition to being used directly as predictors in a statistical forecast, the lidar wind profiles were assimilated into a nested 5-km WRF domain using a 48-member EnKF with 3-hourly cycling to improve the local, mesoscale initial conditions for subsequent forecast runs. These forecasts were compared to an identical statistical-physical forecast system that did not use the lidar wind data as a control. Verification of the forecasts focused mainly on the ability to identify large wind speed changes and power ramping events, with a particular focus on down ramps, since those are deemed more costly. An estimate of the economic value of the improved forecasts was made in order to approximate the cost-benefit ratio of the additional instrumentation.