Accurate Medium-Term Wind Power Forecasting in a Censored Classification Framework

Christian M. Dahl, Carsten Croonenbroeck

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

We provide a wind power forecasting methodology that exploits many of the actual data's statistical features, in particular both-sided censoring. While other tools ignore many of the important “stylized facts” or provide forecasts for short-term horizons only, our approach focuses on medium-term forecasts, which are especially necessary for practitioners in the forward electricity markets of many power trading places; for example, NASDAQ OMX Commodities (formerly Nord Pool OMX Commodities) in northern Europe. We show that our model produces turbine-specific forecasts that are significantly more accurate in comparison to established benchmark models and present an application that illustrates the financial impact of more accurate forecasts obtained using our methodology.
Original languageEnglish
JournalEnergy
Volume73
Issue number14
Pages (from-to)221-232
Number of pages12
ISSN0360-5442
DOIs
Publication statusPublished - 1. Aug 2014

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Wind power
Turbines
Power markets

Keywords

  • Censored regression
  • Wind energy
  • Forecasting

Cite this

Dahl, Christian M. ; Croonenbroeck, Carsten. / Accurate Medium-Term Wind Power Forecasting in a Censored Classification Framework. In: Energy. 2014 ; Vol. 73, No. 14. pp. 221-232.
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Accurate Medium-Term Wind Power Forecasting in a Censored Classification Framework. / Dahl, Christian M.; Croonenbroeck, Carsten.

In: Energy, Vol. 73, No. 14, 01.08.2014, p. 221-232.

Research output: Contribution to journalJournal articleResearchpeer-review

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