Enhancing wind power forecast accuracy using the weather research and forecasting numerical model-based features and artificial neuronal networks

António Couto and Ana Estanqueiro

Renewable Energy, 2022, vol. 201, issue P1, 1076-1085

Abstract: Forecasting with accuracy the quantity of energy produced by wind power plants is crucial to enabling its optimal integration into power systems and electricity markets. Despite the remarkable improvements in the wind forecasting systems in recent years, large errors can still be observed, especially for longer time horizons. This work focuses on identifying new numerical weather prediction (NWP)-based features aiming to improve the overall quality of wind power forecasts.

Keywords: Wind power forecast; Wind power variability; Meteorological parameters; NWP model; Feature selection (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:201:y:2022:i:p1:p:1076-1085

DOI: 10.1016/j.renene.2022.11.022

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