면역알고리즘 기반의 MECs (에너지허브) 시스템

Abstract

Recently,inpowersystem studies,MultipleEnergyCarriers(MECs)suchasEnergyHubhasbeen broadlyutilizedinpowersystem plannersandoperators.Particularly,EnergyHubperformsoneofthemost importantroleastheintermediateinimplementingtheMECs.However,itstillneedstobeputunderexamination inbothmodelingandoperatingconcerns.Forinstance,aprobabilisticoptimizationmodelistreatedbyarobust globaloptimization techniquesuch asmulti-agentgeneticalgorithm (MAGA)which can supporttheonline economicdispatchofMECs.MAGA alsoreducestheinevitableuncertaintycausedbytheintegrationofselected inputenergycarriers.However,MAGA onlyconsiderscurrentstateoftheintegrationofselectedinputenergy carriersinconjunctivewiththeconditionofsmartgridenvironmentsfordecisionmakinginEnergyHub.Thus, inthispaper,weproposeanimmunealgorithm basedMultipleEnergyCarriersSystem whichcanadoptthe learningprocessinordertomakeaselfdecisionmakinginEnergyHub.Inparticular,theproposedimmune algorithm considersthepreviousstate,thecurrentstate,andthefuturestateoftheselectedinputenergycarriers inordertopredictthenextdecisionmakingofEnergyHubbasedontheprobabilisticoptimizationmodel.The below figureshowstheproposedimmunealgorithm basedMultipleEnergyCarriersSystem.Finally,wewill comparetheonlineeconomicdispatchofMECsoftwoalgorithmssuchasMAGA andimmunealgorithm based MECsbyusingRealTimeDigitalSimulator(RTDS).