Title :
Stochastic modeling of future wind generation scenarios
Author :
MacCormack, J.R. ; Westwick, D. ; Zareipour, H. ; Rosehart, W.D.
Author_Institution :
Schulich Sch. of Eng., Univ. of Calgary, Calgary, AB, Canada
Abstract :
This work uses historical data from existing wind generation facilities as a sample of a larger future population of wind generation to create realistic long term time series of future wind generation scenarios. Models are created that reasonably capture both the deterministic and random characteristics of wind generation that are locally unique. Observed correlations in outputs between existing wind generators are used to create scenarios of future wind generation that can estimate the impact of greater diversity of wind generation on overall wind generation variability. Publically available historical data for ten wind generation facilities in Alberta are used to illustrate the methods proposed.
Keywords :
stochastic processes; wind power plants; stochastic modeling; wind generation scenarios; wind generation variability; Autocorrelation; Character generation; Data engineering; Modeling; Power generation; Stochastic processes; Wind energy generation; Wind forecasting; Wind power generation; Wind speed; Planning; Power System Modeling; Wind Power Generation;
Conference_Titel :
Power Symposium, 2008. NAPS '08. 40th North American
Conference_Location :
Calgary, AB
Print_ISBN :
978-1-4244-4283-6
DOI :
10.1109/NAPS.2008.5307311