GA Optimized Fractional Controller for a Wind Turbine Ride Through Pitch Malfunction

dc.contributor.authorPandiyan, Surya
dc.contributor.authorValério, Duarte
dc.contributor.authorMelício, Rui
dc.contributor.authorMendes, Victor
dc.date.accessioned2021-01-25T13:36:12Z
dc.date.available2021-01-25T13:36:12Z
dc.date.issued2020-11
dc.description.abstractThis paper is about better integration of wind energy into an electric grid, avoiding wind turbine pitch malfunction to become a failure. A fractional-order controller is used in the two-level converters of the wind turbine to reduce the voltage drops during the malfunction. The reduction is attained by an optimization problem for selection of the parameters of the fractional-order control. The optimization problem is a nonconvex one, solved by a genetic algorithm together with a model of the wind turbine pitch malfunction. Kriging metamodeling is used to assist in output prediction due its lower computational requirements and its ability to provide a value for the uncertainty of the estimate. A comparison between the Kriging metamodeling and the complete model is presented and conclusions are stated to show the advantage of the Kriging metamodeling.por
dc.identifier.authoremailnd
dc.identifier.authoremailnd
dc.identifier.authoremailruimelicio@gmail.com
dc.identifier.authoremailnd
dc.identifier.doi10.1109/CoDIT49905.2020.9263799por
dc.identifier.scientificarea482por
dc.identifier.urihttps://ieeexplore.ieee.org/document/9263799
dc.identifier.urihttp://hdl.handle.net/10174/28840
dc.identifier.withinvitedoralpresentationnaopor
dc.identifier.withoralpresentationsimpor
dc.identifier.withposternaopor
dc.language.isoengpor
dc.rightsrestrictedAccesspor
dc.subjectGenetic algorithmpor
dc.subjectOptimized Fractional Controllerpor
dc.subjectwind turbinepor
dc.subjectRide Through Pitch Malfunctionpor
dc.subjectKriging metamodelingpor
dc.titleGA Optimized Fractional Controller for a Wind Turbine Ride Through Pitch Malfunctionpor
dc.typelecturepor

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