Page - 102 - in Short-Term Load Forecasting by Artificial Intelligent Technologies

Energies2018,11, 3442 agriculture, domestic, commercial, traction railways and other sectors of India for the year 2030; using linearprogramming,multiple linearprogramming,correlation,exponential smoothing,Holt’s, Brown’sandexpertmodelusingthe independentvariablesviz.,population,GDPandGDP/capita. GDPandpopulationare twovital independentvariableswhichareproventobeplayingan important role inenergy load forecasting in the literatureamongvarious countries. Bothof thevariables are closely,positivelyandcomparativelyhighlycorrelatedwithenergyconsumption. Thepredictedvalue ofTECiscomparedto thatof theactualvalueofEnergyStatisticsdataof2017. This study is also attempted to get back to the basics and reliablemethodologieswhich are sometimesmuchbetterthantheadvancedmethodswhicharebasicallybuiltuponthesemethodologies forsomeof thesimplekeyresearchproblemssuchas forecasting theenergyconsumptionofRepublic India. Nevertheless severalotheradvancedandmultifaceted techniquesarealso inplace. Thekey featuresare (a) itprovidesapoint forecast for theenergyconsumptionvalues for theupcomingyears withdemonstrated errors and (b) the gapbetween the forecasted andactual data are analysed in close intervals. Thedataused for the analyses is consideredonly from the early 1960s and1970s. With the interventionofnewmethods, thereareareas forprobablepotential enhancement innear future.Anaddedregionforprogresswouldbetooptimize the forecast further. For India theenergy consumption is forecastedfor theyear2030andthis shallbedoneevenforyearsdownthe lane from thenon that is, long time forecasting. The softwareused in the analyses is SPSSwhich stands for ‘StatisticalPackagefortheSocialSciences’whichwasdevelopedbyIBM.Thevariouscurveestimations andotheranalysesusedforforecastingiscarriedoutbyIBMSPSSStatistics20. TheLinear,Compound, LogarithmicandPowercurvesarealsofittedusingthis tool.MicrosoftExcel isalsousedforvarious otheranalyses. Thedeviceonwhichtheanalysis iscarriedoutconfigures2.00GHzIntelCore2Duo Processor,withamemoryof4096MBandaharddriveof320GB. Total EnergyConsumption for theperiod1960–2013 for sectors suchas industry, agriculture, commercial, domestic, traction railways and otherswere obtained fromvarious energy statistics reportsofMinistryofStatisticsandProgrammeImplementation (MOSPI),GoI.Theyearwisedata for thepopulation,GDPpercapitaandGDPwerealsoobtained fromvariousother sourcesandother differentdepartmentsof theGoI [34]. After the independence of the country, that is, in 1947 theTEC is observed to be 4182GwH. At that timethedomestic sectorconsumedaround10%of theoverallandindustrial sectorconsumed almost71%, these twowere themajorplayers till theendof the3rdplan.Duringthe1968–1969 that is, duringthe3rdAnnualplanthedomestic sectorexperiencedadipcomparedto thatof theagriculture sectorandtheIndustrialandagriculturesectorwere foundtobethemajorconsumers till theendof the9thplanthat is, 2001–2002.Duringthatpointof time industrial sectorconsumedaround43%and theagriculturesectorengulfed21.8%which is just shortofdomesticsector21.27%.Againfromthe endof the19thplan till theendof the12thplan that is, from2001–2002 to2016–2017 thedomestic sectoragainstartedconsumingmorecomparedto theagriculturesectorwhichwasfoundtobe24.11% comparedtoagriculture’s18.01%.Nevertheless the Industrieshavealwaysbeenthemajorconsumer since independence tilldateeventhoughadecreasingtrendisnoticedoverall. Thetractionsector in Indiahasalways followedadecreasingtrendapart fromafewperiodswhichhasalsoshownonlya feeble increase. TheMiscellaneoussector (others)has increasedlately to6.45%since independence compared to its5.24%eventhough it isnotakeyconsumer. This isanoverviewof thesectorwise totalenergyconsumptionfor Indiasince1947asdemonstrated inFigure1. 102