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1、OptimalProductionPlanningunderTime-sensitiveElectricityPricesforContinuousPower-intensiveProcessesSumitMitra,IgnacioE.Grossmanny,JoseM.Pintoz,NikhilAroraxJune16,2011AbstractPower-intensiveprocessescanloweroperatingexpenseswhenad-justingproductionplanningaccordingtotime-depen
2、dentelectricitypricingschemes.Inthispaper,wedescribeadeterministicMILPmodelthatallowsoptimalproductionplanningforcontinuouspower-intensiveprocesses.Weemphasizethesystematicmodelingofopera-tionaltransitions,thatresultfromswitchingtheoperatingmodesoftheplantequipment,withlogicco
3、nstraints.Weprovepropertiesonthetightnessofseverallogicconstraints.Forthetimehorizonofoneweekandhourlychangingelectricityprices,wesolveanindustrialcasestudyonairseparationplants,wheretransitionalmodeshelpuscap-turerampingbehavior.Wealsosolveprobleminstancesoncementplantswherew
4、eshowthattheappropriatechoiceofoperatingmodesallowsustoobtainpracticalschedules,whilelimitingthenumberofchangeovers.DespitethelargesizeoftheMILPs,therequiredsolutiontimesaresmallduetotheexplicitmodelingoftransitions.1IntroductionThepro tabilityofindustrialpower-intensiveproces
5、sesisa ectedbytheavailabilityandpricingofelectricitysupply.Nowadays,twomajortrendsincreasethecomplexityofmanagingpower-intensiveprocesses.First,dereg-ulationinthe1990sintroducedhourlyaswellasseasonalvariations.Sec-ond,theenvironmentalpressuretoreduceCO2emissionsanddiminishingn
6、aturalresourcesleadtoanincreasingshareofrenewableenergies,whichCenterforAdvancedProcessDecision-making,DepartmentofChemicalEngineering,CarnegieMellonUniversity,Pittsburgh,PA15213yCorrespondingauthor.Emailaddress:grossmann@cmu.eduzPraxairInc.,Danbury,CT06810xPraxair,Inc.,Tonaw
7、anda,NY141501intensi estheaforementionedproblem.Thesetrendshaveaddedaconsid-erableamountofuncertaintyandvariabilityinthedailyoperatingexpensesofpower-intensiveindustries,whichinturna ecttheircompetitiveness.OneimportantcomponentofthecurrentandfuturepowersystemistheconceptofDem
8、andSideManagement(DSM),consistingofEnergyEf- ciency(EE)andDem
