Title :
Generation of Statistical Scenarios of Short-term Wind Power Production
Author :
Pinson, Pierre ; Papaefthymiou, George ; Klockl, B. ; Nielsen, Henrik Aa
Author_Institution :
Inf. & Math. Modeling Dept., Tech. Univ. of Denmark, Lyngby
Abstract :
Short-term (up to 2-3 days ahead) probabilistic forecasts of wind power provide forecast users with a paramount information on the uncertainty of expected wind generation. Whatever the type of these probabilistic forecasts, they are produced on a per horizon basis, and hence do not inform on the development of the forecast uncertainty through forecast series. This issue is addressed here by describing a method that permits to generate statistical scenarios of wind generation that accounts for the interdependence structure of prediction errors, in plus of respecting predictive distributions of wind generation. The approach is evaluated on the test case of a multi-MW wind farm over a period of more than two years. Its interest for a large range of applications is discussed.
Keywords :
load forecasting; statistical analysis; wind power plants; predictive distributions; short-term wind power production; statistical scenarios; wind farm; wind generation; wind power forecasting; Economic forecasting; Least squares approximation; Power generation; Power system modeling; Production; Random variables; Uncertainty; Wind energy; Wind energy generation; Wind forecasting; multivariate Normal variable; probabilistic forecasting; scenarios; transformation; uncertainty; wind power;
Conference_Titel :
Power Tech, 2007 IEEE Lausanne
Conference_Location :
Lausanne
Print_ISBN :
978-1-4244-2189-3
Electronic_ISBN :
978-1-4244-2190-9
DOI :
10.1109/PCT.2007.4538366