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Enhancing ultra short-term wind power prediction accuracy with feature-based CNN-LSTM models: A comparative study

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Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy

Published online on

Abstract

Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, Ahead of Print.
This study explores the enhancement of ultra-short-term wind power prediction accuracy through a novel integration of Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) models, enriched with an innovative feature-based approach. ...