The WRF mode was used to investigate the prediction of wind speed ramping events which can have a large impact on renewable energy production.
5 years of forecast data was used for this analysis. 2 sets of deterministic forecasts (10km and 5km resolutions) produced by downscaling GFS 0.5° data and an ensemble forecast produced by downaling the 21 members of the GEFS 1.0° data. The area studied here are 6 coastal stations in northwest Japan. Wind speed ramps are considered changes of greater than or equal to ±5m/s in 6 hours. The ability of the forecast to predict these events as binary occurrences (“yes/no events”) was examined. A variety of skill scores were utilised to measure forecast performance such as Probability Of Detection, Success Rate, Frequency Bias, Probability Of False Detection, Critical Success Index.
The higher resolution deterministic forecasts outperform the coarser resolution forecasts. Ramp ups are also predicted better than ramp down events. The use of probability thresholds from the set of ensemble forecasts offered the ability to predict wind ramp events better.