"Estimation of Global Solar Radiation Potential using Hybrid Models : A Case Study of Nepal”
Date
2021-09
Authors
Journal Title
Journal ISSN
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Publisher
Pulchowk Campus
Abstract
Solarenergyhasimmensepromiseasasourceofrenewableenergy.Itisabundantthroughout
theyear,althoughitissubjecttouncertaintyduetovariousparameters.Sunenergysources’
affectivityandproductivitycanbeimprovedbyaccurateforecastingofsolarradiation.Fore-
castingGlobalSolarRadiation(GSR)inthefieldofresearchhasattractedwidespreadattention
fromtheresearchcommunityinmanypracticalfieldsincludingenergy.Differentmodelsfor
predictingGSRpotentialhavebeenusedintheliterature.Oneofthemostprominentlinear
modelsfortimeseriesforecastingistheAutoregressiveIntegratedMovingAverage(ARIMA).
Therearealsodifferentmachinelearningmodelswhichshowpromisingforecastingresults.To
takeadvantageoftheuniquebenefitsofARIMAandmachinelearningmodelsinlinearand
nonlinearmodelingthedataofsolarradiationpotential,weproposeahybridmethodcombining
ARIMAandmachinelearningmodelsANN(ArtificialNeuralNetwork)andLSTM(LongShort
TermMemory)modelsinthisstudy.ThedatasetwasobtainedforthelocationofKushma,
Parbatfordurationbetween1990to2014.Forthesupplieddatasets,theARIMAplusANN
hybridmodelwasseentobethebestmethodforpredictingsolarradiationpotential.Thecor-
relationcoefficient(Rsquare)iscalculated0.847.Theerrorvaluesforthismodelareaccessed
asRMSE,MAPEandMAEof1.719,6.456and1.330respectively.Theexperimentalresults
ofrealdatasetsshowthatthecombinedmodelcaneffectivelyimprovethepredictionaccuracy
achievedbyanymodelusedalone.TTheacquiredresultsalsodemonstratedthatthecreated
modelcouldbeutilizedtocalculatethesolarradiationpotentialofanygeographicregionwith
knownclimaticparameters.
Description
Solar energy has immense promise as a source of renewable energy. Itisabundantthroughout
theyear,althoughitissubjecttouncertaintyduetovariousparameters.Sunenergysources’
Keywords
Citation
MASTERS OF SCIENCE IN CLIMATE CHANGE AND SUSTAINABLE DEVELOPMENT PROGRAMME