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

Author:
Duehee Lee
,
Baldick, Ross
Publisher:
IEEE
Year
: 2014
DOI: 10.1109/TSG.2013.2280649
URI: https://libsearch.um.ac.ir:443/fum/handle/fum/959805
Keyword(s): Gaussian processes,load forecasting,neural nets,power system simulation,wind power plants,GP submodel,Gaussian process submodel,NN submodel,PES,Power and Energy Society,decision process,neural network submodel,short-term wind power ensemble prediction,short-term wind power forecasting model,time 48 h,time 5 hour,wind farm,Artificial neural networks,Data models,Forecasting,Predictive models,Wind forecasting,Wind power generation,Wind speed,Ensemble forecasting,Gaussian pr
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    Short-Term Wind Power Ensemble Prediction Based on Gaussian Processes and Neural Networks

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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
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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