A comparison of different wind power forecasting models to the Mycielski approach

Carsten Croonenbroeck and Daniel Ambach

No 355, Discussion Papers from European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics

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.

Keywords: Mycielski algorithm; WPPT; GWPPT; Wind Power; Wind Energy; Forecasting; Prediction (search for similar items in EconPapers)
JEL-codes: C35 E27 Q47 (search for similar items in EconPapers)
Date: 2014
New Economics Papers: this item is included in nep-for and nep-mac
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:euvwdp:355

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