Wind turbine power output prediction using a new hybrid neuro-evolutionary method

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dc.contributor.authorNeshat, M.
dc.contributor.authorNezhad, M.M.
dc.contributor.authorAbbasnejad, E.
dc.contributor.authorMirjalili, S.
dc.contributor.authorGroppi, D.
dc.contributor.authorHeydari, A.
dc.contributor.authorTjernberg, L.B.
dc.contributor.authorAstiaso Garcia, D.
dc.contributor.authorAlexander, B.
dc.contributor.authorShi, Q.
dc.contributor.authorWagner, M.
dc.date.issued2021
dc.descriptionAvailable online 18 April 2021
dc.description.abstractAbstract not available
dc.description.statementofresponsibilityMehdi Neshat, Meysam Majidi Nezhad, Ehsan Abbasnejad, Seyedali Mirjalili, Daniele Groppi, Azim Heydari, Lina Bertling Tjernberg, Davide Astiaso Garcia, Bradley Alexander, Qinfeng Shi, Markus Wagner
dc.identifier.citationEnergy, 2021; 229:120617-1-120617-24
dc.identifier.doi10.1016/j.energy.2021.120617
dc.identifier.issn0360-5442
dc.identifier.issn1873-6785
dc.identifier.orcidNeshat, M. [0000-0002-9537-9513]
dc.identifier.orcidAlexander, B. [0000-0003-4118-2798]
dc.identifier.orcidShi, Q. [0000-0002-9126-2107]
dc.identifier.orcidWagner, M. [0000-0002-3124-0061]
dc.identifier.urihttps://hdl.handle.net/2440/139925
dc.language.isoen
dc.publisherElsevier
dc.rights© 2021 Elsevier Ltd. All rights reserved.
dc.source.urihttps://doi.org/10.1016/j.energy.2021.120617
dc.subjectNeuro-evolutionary algorithms; Alternating optimisation algorithm; Recurrent deep learning; Long short-term memory neural network; Adaptive variational mode decomposition; Power prediction model; Wind turbin; Power curve
dc.titleWind turbine power output prediction using a new hybrid neuro-evolutionary method
dc.typeJournal article
pubs.publication-statusPublished

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