Skill forecasting from different wind power ensemble prediction methods

Pierre Pinson (1) , Henrik A. Nielsen (1) , Henrik Madsen (1) , Georges Kariniotakis (2)

1 Risø DTU - Risø National Laboratory for Sustainable Energy
2 CEP/Sophia

This paper presents an investigation on alternative approaches to the providing of uncertainty estimates associated to point predictions of wind generation. Focus is given to skill forecasts in the form of prediction risk indices, aiming at giving a comprehensive signal on the expected level of forecast uncertainty. Ensemble predictions of wind generation are used as input. A proposal for the definition of prediction risk indices is given. Such skill forecasts are based on the dispersion of ensemble members for a single prediction horizon, or over a set of successive look-ahead times. It is shown on the test case of a Danish offshore wind farm how prediction risk indices may be related to several levels of forecast uncertainty (and energy imbalances). Wind power ensemble predictions are derived from the transformation of ECMWF and NCEP ensembles of meteorological variables to power, as well as by a lagged average approach alternative. The ability of risk indices calculated from the various types of ensembles forecasts to resolve among situations with different levels of uncertainty is discussed.

Mots clés: Computational physics; Instrumentation and measurement; Environmental and Earth science

Domaines: Développement durable

Pierre Pinson, Henrik A. Nielsen, Henrik Madsen, Georges Kariniotakis. Skill forecasting from different wind power ensemble prediction methods. The Science of Making Torque from Wind, Aug 2007, Kongens Lyngby, Denmark. pp.012046, ⟨10.1088/1742-6596/75/1/012046⟩. ⟨hal-00837982⟩