Arbeitspapier

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

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.

Language
Englisch

Bibliographic citation
Series: Discussion Paper ; No. 355

Classification
Wirtschaft
Multiple or Simultaneous Equation Models: Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
Macroeconomics: Consumption, Saving, Production, Employment, and Investment: Forecasting and Simulation: Models and Applications
Energy Forecasting
Subject
Mycielski algorithm
WPPT
GWPPT
Wind Power
Wind Energy
Forecasting
Prediction

Event
Geistige Schöpfung
(who)
Croonenbroeck, Carsten
Ambach, Daniel
Event
Veröffentlichung
(who)
European University Viadrina, Department of Business Administration and Economics
(where)
Frankfurt (Oder)
(when)
2014

Handle
Last update
10.03.2025, 11:44 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Croonenbroeck, Carsten
  • Ambach, Daniel
  • European University Viadrina, Department of Business Administration and Economics

Time of origin

  • 2014

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