Optimized wind power prediction and energy storage scheduling using genetic algorithm and backpropagation neural network

As renewable energy continues to rise in the global energy mix, wind energy is gradually increasing its share in the power system as a clean, renewable form of energy. However, the volatility and uncertainty of wind power bring new challenges to power system operation, making the need for its effici...

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Veröffentlicht in:	International journal of renewable energy development Jg. 14; H. 1; S. 146 - 157
Hauptverfasser:	Wu, Peng, Li, Zongze
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Diponegoro University 01.01.2025
Schlagworte:	backpropagation neural network energy storage scheduling genetic algorithm support vector machine wind power prediction
ISSN:	2252-4940
Online-Zugang:	Volltext
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