Seasonal Analysis and Prediction of Wind Energy Using Random Forests and ARX Model Structures

To effectively utilize wind energy, many learning-based autoregressive models have been proposed in the literature. Improving their short-term prediction accuracy, however, is difficult, which mainly result from the stochastic nature of wind. Moreover, the incorporation of seasonal effects to improv...
Ausführliche Beschreibung

Gespeichert in:
Autor*in:

Lin, Yujie [verfasserIn]

Kruger, Uwe

Zhang, Junping

Wang, Qi

Lamont, Lisa

Chaar, Lana El

Format:

Artikel

Sprache:

Englisch

Erschienen:

2015

Schlagwörter:

Wind speed

Autoregressive (AR) data structure

Predictive models

meteorological models

Mathematical model

Accuracy

wind direction

renewable energy

Analytical models

Wind forecasting

Data models

Meteorology

Übergeordnetes Werk:

Enthalten in: IEEE transactions on control systems technology - New York, NY : IEEE, 1993, 23(2015), 5, Seite 1994-2002

Übergeordnetes Werk:

volume:23 ; year:2015 ; number:5 ; pages:1994-2002

Links:

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DOI / URN:

10.1109/TCST.2015.2389031

Katalog-ID:

OLC1959561340

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