Modelling of wind turbine power output by using ANNs and ANFIS techniques

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dc.contributor.authorEkinci, Firat
dc.contributor.authorDemirdelen, Tu?çe
dc.contributor.authorBilgili, Mehmet
dc.date.accessioned2025-01-06T17:29:55Z
dc.date.available2025-01-06T17:29:55Z
dc.date.issued2017
dc.description7th International Conference on Innovative Computing Technology, INTECH 2017 -- 16 August 2017 through 18 August 2017 -- Luton -- 132346
dc.description.abstractIn this study, artificial neural network (ANN) and adaptive neuro fuzzy inference system (ANFIS) were applied to estimate the wind turbine power output of a horizontal axis wind turbine. Hub-height wind speed, atmospheric air temperature and rotational speed values obtained from an operating wind power plant (WPP) were employed as input data in the model. According to the derived results, the mean absolute percentage error (MAPE) and correlation coefficient (R) values for the ANN model were determined as 4.41% and 0.9850, respectively, whereas the corresponding values for the ANFIS model were found as 2.19% and 0.9971, respectively. The obtained results showed that ANN and ANFIS models can be used to predict wind turbine power output in a simple, reliable and accurate way. © 2017 IEEE.
dc.identifier.doi10.1109/INTECH.2017.8102425
dc.identifier.endpage131
dc.identifier.isbn978-150903988-3
dc.identifier.scopus2-s2.0-85040785819
dc.identifier.startpage126
dc.identifier.urihttps://doi.org/10.1109/INTECH.2017.8102425
dc.identifier.urihttps://hdl.handle.net/20.500.14669/1389
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof7th International Conference on Innovative Computing Technology, INTECH 2017
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241211
dc.subjectAdaptive Neuro Fuzzy Inference System
dc.subjectArtificial Neural Network
dc.subjectModelling
dc.subjectWind Power
dc.titleModelling of wind turbine power output by using ANNs and ANFIS techniques
dc.typeConference Object

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