海上风电系统智能运维的数字孪生技术

ResearchBackground Technology Roadmap Key Innovations Results&Applications ResearchBackground To meet China's carbon goals, we are going green, shifting to clean energy, building apower system onrenewables likewind and solar Chinawill stopincreasingCO,emissionsby2o30andremoveall CO,-XiJP OnSep22,2020.PresidentXiannouncedChina'sgoalsof carbon peaking and carbonneutrality atthe75th UNGeneralAssemblya strategic decisionvital to China'ssustainable development and the sharedfuture ofhumanity. Toreachthisgoal,Chinaisbuilding anewpower systemcentered on renewables expanding the clean energyindustry.andpromotingrenewableenergysubstitution,creating a vast market forgreen development 01 ResearchBackground Developing Offshore Wind Power is a Strategic Choice for Clean Energy According to data released by the National Energy Administration.in 2024, China added 79.82GWof newwindpower capacity,including4GWof offshorewind.Thetotal offshorewindinstalledcapacity hasnow exceeded41 GW.Since2021,China hasmaintained the world's largestoffshorewind capacity China has a Vast sea area, long coastiine,many islands,andhigh wind power density. Advantage: Higher power generationMorestable operationNo land occupationClose to demand centers ResearchBackground Offshorewindpowermonitoringislimited inscopeandmethods,withchallengesindatacollectionandtransmissionInsufficientresearchonmulti-physicscouplinginoffshorewindpowerlacksmethodstosimulatecomplexsvstembehaviorsOffshorewindpower still reliesonreactivemaintenance,lackingintelligent systemsforefficientO&M,leadingtohighcosts. Digital twins are widely used in industries like aerospace, energy, power, and manufacturing,across scenarios suchas design,production,operations,anddecision-making.Theyenabledata-and model-driventransformation,optimizingresourcesmorebroadly,efficiently,andprecisely 02 TechnologyRoadmap Withrapidoffshorewinddeploymentandrelativelylowavailability,traditionalmaintenanceapproachescannomprovingreliabilityand efficiencymarkingthefuture direction ofoffshorewindmanagement DevelopmentBottlenecks: Development Bottlenecks High turbinefailure rates and heavymaintenanceworkloadsLackofexperiencedpersonnel andlowlevelofinformatization Monitoring coverage is limited, data collection isfragmented,andtransmissionisdifficult Insufficientresearchonthecouplingbetweenmultipiephysicaldomainsinoffshorewindfarms ManyfactorsaffecttheO&Mprocess,butthereisalackofacomprehensiveand intelligentsystemtosupportdecision-making Innovations Wedeveloped a flexible,wide-range data collection devicethat gathers all kinds ofkeyinformation-likeoffshorewave conditions,wind farm performance,eguipment statusand safety data--acrossdifferentnetwork zones.Wealsobuilta fast,low-distortionsystem to compressand combinelargeamountsof datafrom different sources.For the first time,we created afull-picture monitoring systemthat connects turbinessites,and the environment-layinga strong data foundation for future digital twin applications. Innovation1.Unit-Site-EnvironmentMoniton 1.1TurbineFull-StateDataAcquisition 1.2OffshoreWindPanoramicDataLink 1.3 Heterogeneous Data Governance 1.1Full-State Wind TurbineMonitoringandDataAcguisitionSystem We developed a multi-channel,wide-band,and scalable dataacquisitionsystemthatcoverskeyturbinecomponentssuchasbladestowers,andnacellesItsupportsintegratedmeasurementofvarioussignaltypes-likeaudiovibration,and laser-enablingfull-statemonitoringoftheturbine Innovations 1.2Offshore Wind Farm Full-Scope DataChainConstruction Weintegrated communicationlinksforSCADA,CMS.AGCIAVC,SVC/SVG,power forecasting,and othermonitoringsystems Wealso broughtinenvironmental data suchasweather, submarine cables,vessel tracking,personnel positioning,andAR-based virtual scenemonitoring Marine radar systemAiS for vessels Video linkage system, which uses radar and Alsdatato sendvessellocation,speed andheadingtothevideo system 03 Innovations 1.3DevelopmentofManagementTechnologies forMassive,Multi-sourceand Heterogeneous Data We've built edge computing tools thatrecognizeequipmentstatusand extractkeyfeatures from different types of data Built an integrateddigital twinmodel forturbine flow,mechanics,and electricity.Mappedkey O&Mfactors(personnel,equipment,materials,methods,environment).Designedaself-correctingmechanismbased on twinperformance.Developedthefirstturbine-site-environment digital twin for offshorepredictivemaintenance Innovation 2:Multi-Level Digital TwinConstruction for Offshore Wind Farms 2.1 Turbine Multi-Physics Modeling 2.2 Full-Process O&M Twin Mapping 2.3 Adaptive Virtual-Physical Mapping 2.1Multi-physicsmodelingof windturbines acrossmultiple scales Wehavebuiltacross-scalemulti-physicsdigitaltwinmodelofoffshorewindturbinesintegrating flowfielddynamicfield,andelectricfield. Bladeaerodynamnic analysis iecincalsimulationofwindturbines Dynamiccharacteristicanalysis Basedonblade elementmomentumtheory, we calculatethe 2D forces andmoments ateach b