基于房间空调器使用率与设置温度监控数据的能耗预测模型（英文）-豆柴文库

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基于房间空调器使用率与设置温度监控数据的能耗预测模型（英文）
Title:EnergyPredictionModelBasedonMonitoringDataofRoomAirConditionerUsageandSetTemperature
Abstract:
Airconditionersarewidelyusedinindoorenvironmentstoofferthermalcomfort,buttheirhighenergyconsumptionalsocontributestotheenvironmentproblems.Accurateforecastofairconditionerenergyconsumptionisessentialtoenergy-savingandenvironmentalprotection.Inthispaper,weproposeanenergypredictionmodelbasedonmonitoringdataofroomairconditionerusageandsettemperature.Themodelappliesahybridalgorithm,combiningartificialneuralnetworkandBayesianalgorithm,toforecastenergyconsumption.Theexperimentalresultsshowedthatourmodelachievedanaveragepredictionaccuracyof88%.
Introduction:
Airconditioningsystemsarecommonlyusedinindoorenvironmentstoregulatethetemperatureandcreatecomfortablesurroundings.However,airconditionersconsumeaconsiderableamountofenergy,accountingforasignificantpercentageofbuildings'energyconsumption.Accordingtoresearch,airconditioningaccountedfor10%ofglobalenergyconsumptionin2018(InternationalEnergyAgency,2019).Therefore,itisessentialtodevelopaccurateenergyconsumptionpredictionmodelstoreduceenergyconsumptionandprotecttheenvironment.
Manyvariablesinfluenceenergyconsumptioninairconditioningsystems,suchasoutdoortemperature,roomoccupancy,anduserpreferencefortemperaturesettings.Therefore,accuratepredictionmodelsrequirecomprehensivedatacollectionandanalysisofalltheinfluencingfactors.Inthisstudy,weproposeamodelbasedonmonitoringdataofroomairconditionerusageandthesettemperaturetopredictenergyconsumption.
Methodology:
DataCollection:
Wecollecteddatafromaresidentialbuildinginametropolitanarea,usingthebuildingmanagementsystemthatrecordstheenergyconsumptionandtemperaturesettingsofairconditionersinthebuilding.Thedataincludeddailysettemperature,hourlyenergyconsumption,androomoccupancyinformation.
Preprocessing:
Beforemodeldevelopment,weperformedsomepreprocessingonthedata.Firstly,weusedthez-scorenormalizationmethodtostandardizethedatatothesamerange.Secondly,weeliminat