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1、华北电力大学硕士学位论文AbstractMicrogridwhichisaneworganizationofdistributedenergyisanimportantpartofthesmartgrid.MicrogridEnergyManagementSystem(MEMS)isthekeyofreal-timeschedulingandloadforecasting.InmicrogridEMS,subsystemsofReal-timeoptimizationschedulingrequirethedatabaseofmi
2、crogridEMStoprovidestablereal-timedata,inaddition,subsystemsofloadforecastingrequirethedatabaseofmicrogridEMStoprovidereliablehistoricaldata,therefore,theperformanceofdatabaseinMicrogridEMSisputtedforwardhigherrequirement.Meanwhile,thenumberofdatabecomeshugerandhugera
3、sthesmartgriddeveloping,whichbringbigchallengesforoperationalprecisionandoperationalefficiency.Inthiscase,abilityofsinglecomputationbecomestheconstraintoftheapplicationlayer.Inordertosolvetheaboveproblemstobreakthroughthebottleneck,distributeddatastorageandcomputingof
4、cloudcomputingareintroducedintoMEMS.ThetechnologyofcloudcomputingappliedinMEMSisresearched,andcompletedworkisfollowing:Firstly,throughintroductionofarchitectureofHadoop2.2.0,hierarchyarchitectureofmicrogridenergymanagementsystemisdesigned.Then,throughthedesignoflogica
5、lstructureofHBase,theimplementationofdatareal-timestoragecorrespondingtoCIMisfinished.AndthroughdatasynchronizationtechnologyofHBaseandHive,theimplementationofstorageofhistorydatabasedondatawarehouseofHiveisfinished.Secondly,Onthebasisofstorageandmanagementofdataconst
6、ructedbythispaper,aleastsquaressupportvectormachinemodelforshort-termloadforecastingoptimizedbyimprovedparallelparticleswarmisproposed.UncertainparametersareoptimizedbyintroducingtheSparkonYarnmemorycomputingplatformonwhichimprovedparallelparticleswarmalgorithmisdeplo
7、yed.Thepredictionaccuracyofthealgorithmandthecapabilityofprocessofmassivehigh-dimensionaldataareimprovedbyintroducingtheideasofparallelanddistribution.Atlast,Inordertoverifythevalidityofmethodofdatastorageandmanagementandaccuracyandefficiencyofthealgorithmofloadforeca
8、sting,cloudII华北电力大学硕士学位论文platformofHadoopisbuiltinenvironmentofmylaboratory,andthedatabaseofHBase,thedatawarehouseofHiveandm
