Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/98735
Authors: 
Croonenbroeck, Carsten
Ambach, Daniel
Year of Publication: 
2014
Series/Report no.: 
Discussion Paper, European University Viadrina, Department of Business Administration and Economics 355
Abstract: 
In the wind power industry, wind speed forecasts are obtained and transformed into wind power forecasts. The Mycielski algorithm has proven to be an accurate predictor for wind speed in short-term scenarios. Moreover, Mycielski has the capability of forecasting wind power directly, instead of wind speed. This article compares wind power forecasts calculated by the Mycielski algorithm to state-of-the-art forecasters. As such, we use the Wind Power Prediction Tool (WPPT) and the recently developed generalization of it, GWPPT (Generalized WPPT). Furthermore, we evaluate statistical time series models such as autoregressive and vector autoregressive models. As an additional benchmark we use the persistence model, which is often used to assess forecasting accuracy. Each model is evaluated and we give a recommendation for the best forecasting model.
Subjects: 
Mycielski algorithm
WPPT
GWPPT
Wind Power
Wind Energy
Forecasting
Prediction
JEL: 
C35
E27
Q47
Document Type: 
Working Paper

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