Andrew Scholbrock - Wake Steering for Improved Wind Plant Performance
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Transcript of Andrew Scholbrock - Wake Steering for Improved Wind Plant Performance
WakeSteeringforImprovedWindPlantPerformanceAndrewScholbrock,NREL
2016WindTurbineBladeWorkshopAlbuquerque, NM,USAAugust31,2016
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Problem
Photoby:ChristianSteiness
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ResearchMethodology
CFDModeling ofAtmosphere/WindPlant
SimplifiedEngineering
ModelsofWakes
WindPlantOptimizationSimulations
FieldTestingValidationofWakeModels
FieldTestingTurbine
InteractionsCoordinatedWind
PlantControl
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• SOWFA:SimulatorfOrWindFarmApplicationso Usedtoinvestigatewindturbineandwindplantperformanceundervariousatmosphericconditions
o LESmodelofatmosphericboundarylayer(ABL)basedonOpenFOAMCFDtoolbox
o FASTturbinemodelusingrotatingactuatorlinestomodelrotor
CFDModeling
AdaptedFrom:J.Annoni et.al.“Analysisofaxial-induction-basedwindplantcontrolusinganengineeringandahigh-orderwindplantmodel”WindEnergy.Vol.19.pp.1135-1150.DOI:10.1002/we.1891.2016.More information: nwtc.nrel.gov/SOWFA
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WakeEngineeringModel
• FLORIS(FLOw RedirectionandInductioninSteady-state):o Steady-stateengineeringmodelbasedonJensenandJimenezmodelswithextensions
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Methodsforwakemanipulation
o Axial-basedcontrolo WakeSteering:
– Repositioning(layoutoptimization)– Tilt-basedwake-steering– Yaw-based
AdaptedFrom:J.Annoni et.al.“Analysisofaxial-induction-basedwindplantcontrolusinganengineeringandahigh-orderwindplantmodel”WindEnergy.Vol.19.pp.1135-1150.DOI:10.1002/we.1891.2016.
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AxialBasedMethod– SimulationResults
AdaptedFrom:J.Annoni et.al.“Analysisofaxial-induction-basedwindplantcontrolusinganengineeringandahigh-orderwindplantmodel”WindEnergy.Vol.19.pp.1135-1150.DOI:10.1002/we.1891.2016.
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WakeSteering– InitialCFDInvestigations
AdaptedFrom:P.Fleming,et.al.“Simulationcomparisonofwakemitigationcontrolstrategiesforatwo-turbinecase”WindEnergy.Vol.18.pp.2135-2143DOI:10.1002/we.1810.2014.
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WindPlantOptimizationSimulationResults
AdaptedFrom:Gebraad,P.M.O.;Teeuwisse, F.W.;vanWingerden,J.W.;Fleming,P.A.;Ruben,S.D.;Marden,J.R.;Pao,L. Y. (2014).“Data-DrivenModelforWindPlantPowerOptimizationbyYawControl.”Proceedingsofthe2014AmericanControlConference(ACC);June4-6,2014,Portland,Oregon.NREL/CP-5000-61405.Piscataway,NJ:InstituteofElectricalandElectronicsEngineers;pp.3128-3134.
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FieldTesting
MoreinformationonSWiFT:energy.sandia.gov/energy/renewable-energy/wind-power/wind_plant_opt/More informationonNWTC:nwtc.nrel.govMoreinformationonDTULidar:www.windscanner.dk/MoreinformationonSWELidar:www.ifb.uni-stuttgart.de/windenergie/index.en.html
ScaledWindFarmTechnology Facility(SWiFT),Lubbock,Texas
PhotobyThomasHerges,SandiaNationalLaboratory PhotobyDennisSchroeder,NREL
NationalWindTechnologyCenter(NWTC),Boulder,Colorado
• WindTurbine:Vestas V27• Lidar:DanishTechnicalUniversity(DTU)modified
ZephIR
• WindTurbine:GE1.5 MW• Lidar:UniversityofStuttgart (SWE)modified
Leosphere
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LidarpatternsampledCFDdata
SimulatedLidarSamplingofYawedWakeforSWiFT(CourtesyMattChurchfield–NREL)
q =30°
winddirection
g =-20°b =-10°
PureCFDdata
Datareconstructed fromlidarsampling
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Lidarsamplingatdifferentranges
ImagecourtesyofTommyHerges,SandiaNationalLaboratory
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SimulatedLidarSamplingofWakeforGE1.5(CourtesyMattChurchfield–NREL)
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GE1.5FieldTestWakeSteering
WakebehindGE1.5AlignedwithWindDirection
WakebehindGE1.5+25ᵒYawMisalignment
ImagescourtesyofJenniferAnnoni, NREL
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SWiFT Fieldtestresults– StableABLWakebehindSWiFTwindturbineStableAtmosphericBoundaryLayer
VideocourtesyofTommyHerges,SandiaNationalLaboratory
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SWiFT Fieldtestresults– UnstableABL
WakebehindSWiFTwindturbineUnstableAtmosphericBoundaryLayer
VideocourtesyofTommyHerges,SandiaNationalLaboratory
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• CFDsimulationshelpedimmenselyinguidingthedesignoffieldexperiments
• Intentionalwakesteeringisfeasiblefromfieldexperiments
• Atmosphericstabilityplaysalargeroleinwakemeanderingandneedstobetakenintoaccountforcoordinatedwindfarmcontrol
• Needtoquantify“steered”wakefromfieldtestsandcomparetosimulationmodelsforvalidation
• Needtoquantifyturbinetoturbineinteractions
Conclusions
Thankyouforyourtime!
Photoby:DennisSchroeder,NREL