Exploiting Deep Learning for Wind Power Forecasting Based on Big Data Analytics

Recently, power systems are facing the challenges of growing power demand, depleting fossil fuel and aggravating environmental pollution (caused by carbon emission from fossil fuel based power generation). The incorporation of alternative low carbon energy generation, i.e., Renewable Energy Sources...

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Veröffentlicht in:	Applied sciences Jg. 9; H. 20; S. 4417
Hauptverfasser:	Mujeeb, Sana, Alghamdi, Turki Ali, Ullah, Sameeh, Fatima, Aisha, Javaid, Nadeem, Saba, Tanzila
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.10.2019
Schlagworte:	Accuracy Alternative energy sources Big Data convolution neural network Data analysis data analytics Decomposition Deep learning demand side management energy management Energy resources Forecasting Forecasting techniques Industrial plant emissions Neural networks Optimization techniques Power supply Random variables Renewable resources Teaching methods Time series Wavelet transforms Wind power
ISSN:	2076-3417, 2076-3417
Online-Zugang:	Volltext
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