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电力系统运行状态云平台建设研究
Title:ResearchontheConstructionofCloudPlatformforMonitoringtheOperationalStateofPowerSystems
Abstract:
Withtherapiddevelopmentofurbanizationandindustrialization,thedemandforelectricityisincreasing,whichbringschallengestothestableoperationandmanagementofpowersystems.Inordertoeffectivelymonitorandevaluatetheoperationalstateofpowersystems,itisnecessarytoestablishacloudplatformthatintegratesvariousdatasourcesandprovidesreal-timeanalysisanddecisionsupport.Thispaperexplorestheconstructionofacloudplatformformonitoringtheoperationalstateofpowersystemsanddiscussesitspotentialbenefitsinenhancingsystemreliability,optimizingenergymanagement,andimprovingoverallperformance.
1.Introduction
Electricityisanessentialcomponentofmodernsociety,andthereliableandsecureoperationofpowersystemsisofparamountimportance.Aspowersystemsbecomemorecomplexandinterconnected,itbecomesincreasinglydifficulttomonitorandmanagetheiroperationalstate.Acloudplatformthatleveragesthepowerofbigdataanalyticsandartificialintelligencecanprovidereal-timeinsightsintotheperformanceofpowersystemsandenableproactivedecision-making.
2.TheNeedforaCloudPlatforminPowerSystems
2.1IntegrationofDataSources
Powersystemsgenerateavastamountofoperationaldatafromvarioussourcessuchassensors,smartmeters,andcontroldevices.Acloudplatformcanintegratethesedatasourcesintoaunifieddatabase,enablingcomprehensiveandholisticanalysisofthesystem'soperationalstate.
2.2Real-timeMonitoringandAnalysis
Byleveragingreal-timedatastreamingandadvancedanalytics,acloudplatformcanprovidecontinuousmonitoringofpowersystemparameterssuchasvoltage,frequency,andload.Thisenablesoperatorstoquicklyidentifyabnormalconditions,anticipatepotentialissues,andtakeproactivemeasurestoensuresystemstability.
2.3DecisionSupportandPredictiveMaintenance
Thecloudplatformcanalsoprovidedecisionsupporttoolsthatincorporatehistoricaldata,algorithms,andmachinelearningtechniquestooptimizesystemperformance.Bypredictingpotentialfailuresorfaults,operatorscanschedulepreventive