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Short-Term Wind Power Ensemble Prediction Based on Gaussian Processes and Neural Networks

contributor authorDuehee Lee
contributor authorBaldick, Ross
date accessioned2020-03-12T18:28:38Z
date available2020-03-12T18:28:38Z
date issued2014
identifier issn1949-3053
identifier other6606922.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/959805?show=full
formatgeneral
languageEnglish
publisherIEEE
titleShort-Term Wind Power Ensemble Prediction Based on Gaussian Processes and Neural Networks
typeJournal Paper
contenttypeMetadata Only
identifier padid7992412
subject keywordsGaussian processes
subject keywordsload forecasting
subject keywordsneural nets
subject keywordspower system simulation
subject keywordswind power plants
subject keywordsGP submodel
subject keywordsGaussian process submodel
subject keywordsNN submodel
subject keywordsPES
subject keywordsPower and Energy Society
subject keywordsdecision process
subject keywordsneural network submodel
subject keywordsshort-term wind power ensemble prediction
subject keywordsshort-term wind power forecasting model
subject keywordstime 48 h
subject keywordstime 5 hour
subject keywordswind farm
subject keywordsArtificial neural networks
subject keywordsData models
subject keywordsForecasting
subject keywordsPredictive models
subject keywordsWind forecasting
subject keywordsWind power generation
subject keywordsWind speed
subject keywordsEnsemble forecasting
subject keywordsGaussian pr
identifier doi10.1109/TSG.2013.2280649
journal titleSmart Grid, IEEE Transactions on
journal volume5
journal issue1
filesize1382589
citations2


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