Wind Energy

Within the KAUST-funded project entitled “Space-time Statistical Models for Wind Field Forecasting with High Performance Computing” we are quantifying energy potential and relative uncertainty from wind in Saudi Arabia to enhance its renewable energy portfolio.

Windmills in a windfarm

Relevant Publications:

  1. Giani P., Tagle F., Genton M.G., Castruccio C. and Crippa, P. (2020): Closing the gap between wind energy targets and implementation for emerging countries, Applied Energy, 269, 115085,
  2. Chen, W., Castruccio, S., Genton, M.G., Crippa, P. (2018): Current and Future Estimates of Wind Energy Potential over Saudi Arabia, Journal of Geophysical Research-Atmospheres,123, doi:10.1029/2017JD028212. Link
  3. Tagle, F., Castruccio, S., Crippa, P., and Genton, M.G., (2018, in press): A Non-Gaussian Spatio-Temporal Model for Daily Wind Speeds Based on a Multivariate Skew-t Distribution, Journal of Time Series Analysis.
  4. Jeong, J., Castruccio S., Crippa, P., and Genton, M.G. (2018), Reducing storage of global wind ensembles with stochastic generators, Annals of Applied Statistics ,12, 1, 490-509.
  5. Wang, H., Barthelmie, R.J., Crippa, P., Doubrawa, P., Pryor, S.C. (2014), Profiles of Wind and Turbulence in the Coastal Atmospheric Boundary Layer of Lake Erie, Journal of Physics: Conference Series 524 012117, Lyngby. Link
  6. Barthelmie, R.J., Crippa, P., Wang, H., Smith, C. M., Krishnamurthy, R., Calhoun, R., Valyou, D., Marzocca, P., Matthiesen, D., Brown, G., and Pryor, S. C. (2014), 3D wind and turbulence characteristics or the atmospheric boundary-layer, Bulletin of the American Meteorological Society, 95, 743-756. Link