Data-Driven Modeling of Wind Turbine Structural Dynamics and Its Application to Wind Speed Estimation

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atmire.migration.oldid4100
dc.contributor.advisorSun, Qiao
dc.contributor.authorSaberi Nasrabad, Vahid
dc.contributor.committeememberWestwick, David
dc.contributor.committeememberWood, David
dc.contributor.committeememberMohamad, Abdulmajeed
dc.date.accessioned2016-01-27T21:25:47Z
dc.date.available2016-01-27T21:25:47Z
dc.date.issued2016-01-27
dc.date.submitted2016en
dc.description.abstractIn wind turbine control systems, the wind speed measurement is used in order to derive the optimal shaft speed for achieving the Maximum Power Point Tracking (MPPT) and to adjust the pitch angle optimally for protecting the turbine from excessive loading. In this thesis, a tower detection based effective wind speed estimation method is proposed. The tower dynamics is identified using subspace system identification method. To estimate the effective wind speed, an online model-based aerodynamic thrust force estimator is designed and implemented using Kalman filter and recursive least square algorithm. The estimated aerodynamic thrust force is used as an input to a neural network estimator to solve the inverse aerodynamic thrust force equation and estimate the effective wind speed. Finally, the simulation results for effective wind speed estimation for a turbulent wind field are presented and an evaluation method based on correlation coefficient is used to validate the results.en_US
dc.identifier.citationSaberi Nasrabad, V. (2016). Data-Driven Modeling of Wind Turbine Structural Dynamics and Its Application to Wind Speed Estimation (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/25518en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/25518
dc.identifier.urihttp://hdl.handle.net/11023/2788
dc.language.isoeng
dc.publisher.facultyGraduate Studies
dc.publisher.institutionUniversity of Calgaryen
dc.publisher.placeCalgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subjectEnergy
dc.subjectEngineering--Mechanical
dc.subject.classificationwind poweren_US
dc.subject.classificationWind Turbineen_US
dc.subject.classificationSystem Identificationen_US
dc.subject.classificationControl Systemsen_US
dc.subject.classificationDynamicsen_US
dc.subject.classificationVibrationen_US
dc.subject.classificationEstimationen_US
dc.subject.classificationWind speed estimationen_US
dc.subject.classificationPitch controlen_US
dc.subject.classificationwind turbine controlen_US
dc.subject.classificationwind turbine modelingen_US
dc.subject.classificationeffective wind speeden_US
dc.subject.classificationTower deflectionen_US
dc.subject.classificationData driven modelingen_US
dc.subject.classificationrecursive least squaresen_US
dc.subject.classificationNeural Networken_US
dc.subject.classificationinverse problemen_US
dc.subject.classificationTurbulenceen_US
dc.subject.classificationsubspace system identificationen_US
dc.subject.classificationvariable speed variable pitch wind turbinesen_US
dc.subject.classificationKalman Filteren_US
dc.subject.classificationBlade element momentum (BEM) theoryen_US
dc.subject.classificationThrust force estimationen_US
dc.subject.classificationfore-aft deflectionen_US
dc.subject.classificationHammerstein Systemen_US
dc.subject.classification4SIDen_US
dc.titleData-Driven Modeling of Wind Turbine Structural Dynamics and Its Application to Wind Speed Estimation
dc.typemaster thesis
thesis.degree.disciplineMechanical and Manufacturing Engineering
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameMaster of Science (MSc)
ucalgary.item.requestcopytrue
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