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Industrial Energy Management with Visual MESA at BP Lingen refinery Availability Department – BP Lingen refinery Soteica ERTC Annual Meeting – Vienna 2012
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Bp Lingen Refinery Industrial Energy Management With Visualmesa

Nov 25, 2015

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  • IndustrialEnergyManagementwithVisualMESAatBPLingenrefinery

    AvailabilityDepartment BPLingen refinery

    Soteica

    ERTCAnnual Meeting Vienna 2012

  • Outline

    Introduction BPLingenrefinery VisualMESA

    Energysystemdescription Projectobjectives Projectscheduleandmodelsummary Benefits Conclusions

  • Introduction(I)

    BPLingenrefinery Oneofthemostcomplexrefineriesintheworld LocatedinNorthWestGermany ConsideredoneofEurope'sleadingconversionrefineries Inkeepingwitheffortstoprotecttheenvironment,allofthegasoline

    anddieselfuelproductsareessentiallyfreeofsulphur Refiningcapacityof93thousandbarrelsperdayofcrudeoil

    VisualMESAenergymanagementsystemimplemented

  • Introduction(II)

    HydrogenFuelSteamWaterElectricityUtilitiesSystems

    ExternalUtilitiesContracts

    EmissionsRegulations

    ProcessIndustrialSite

    RealTimeandWhatifPlanningOptimizerthatfindstheoptimalwaytooperateutilitiessubjecttocontractual,environmentalandoperationalconstraints

    OptimumUtilitiesOperationsReport

    Measurements OptimumSetPoints

    KPIMonitoringandAccountingReports

  • Introduction(III) VisualMESAisa1st PrinciplesModelingandOptimization(SQP

    MINLP)programforfuels,steam,BFW,condensate,hydrogenandelectricalsystems,includingemissions

    Fieldsofapplication: RealTimeOptimization Monitoring,AuditingandAccounting Engineering Planning RealTimeValidatedEnergyandEmissionsKPICalculationServer

    Currentlyinuseinmorethan70refineriesandpetrochemicalsites

  • Energysystemdescription

    Setoffiredboilersandprocessfurnacesburningfuelgas Steamnetworkwiththreesteampressurelevels Setofsteamturbogenerators Twocogenerationunits

    Productionof50MWofelectricityfromtwonaturalgaspoweredgasturbines,foruseonsiteandforsaleoftheexcessenergy

    Thegasturbineshavesteaminjectionandheatrecoverysteamgeneratorwithpostcombustion

    Differenteconomictradeoffs(amongelectricity,steamandfuelnetworks)

    Manychallengestooperatetheenergysystematminimumcost,withintheconstraints(e.g.emissions)

  • ProjectObjectives

    Monitoringandreductionoftherefinery'stotalenergycosts

    Monitoringequipmentperformance Balancingthevariousenergycosts Developing"Whatif"studies

  • ProjectSchedule

    Datacollection Softwareinstallation(August2010) FunctionalDesignSpecifications Modelbuildingandoptimizationconfiguration Training(January2011) Modelreview Burningperiod Projectandmodeldocumentation(July2011)

  • Modelscope

    Steam,fuels,emissions,boilerfeedwater,condensatesandelectricitysystem

    OptimizationObjectivefunction:TotalEnergycosts=Fuels+Electricity+Othercosts

    (FuelOil/NaturalGas/LPG(Propane/Butane)/Electricity/Water)

  • VisualMESAGUI(mainview)

  • Powerplantmodelview

  • Optimizationvariables Cogeneration

    GTsloads SteaminjectiontoGTs FuelGastopostcombustion

    Steamproductionatboilers FuelGas/FuelOiltoafiredboiler FuelGastotheotherfiredboilers

    Turbogeneratorsmanagement TGsloads

    Pumpswaps(steamturbines/electricalmotorsswitches) 6possibleswitchesfor401.5barsteamturbines) 36switches111.5barsteamturbines CondensingTurbines

    Electricityexportation(orimportation) NaturalGas/Butane/PropanemakeuptoFGsystem Steamletdownandvents

  • Constraints

    Equipmentrelated(i.e.burnerscapacity) Operationalconstraints Utilitiesprocessplantsdemand Contractual Environmental

    NOxandSO2emissionslimits CO2emissions(monitoring)

    85Optimizationvariables(54discretevariables)29Constraints

  • Benefits

  • DaytoDayOptimization Steamproductionbalance GasTurbinesloadsandsteaminjection Turbogeneratorsloads NaturalGas/Butane/PropanemakeuptoFGnetwork

    Pumpswaps Theremainingvariables(forexample,steamletdownflow

    rates)areconsequencesofthechangesmentionedbefore,beingmanipulatedautomaticallybythecontrolsystem

  • Energycostsreductionexamples

    NaturalGas/Butane/PropaneadditiontoFGnetwork

    GasTurbineloads Pumpswaps

  • Example1:MinimizationofbutaneadditiontoFGnetwork

    Butane reduction

  • Example1(cont):MinimizationofbutaneadditiontoFGnetwork

    Energy cost reductionaround 5% on total energy cost

    Butane reductionto FG networkaround 3 t/h

    Delta Cost (Current minus Optimized)

  • Example1(cont):Effectonheaters(furnaces)

    FG flow increase at a furnace(around 0.15 t/h)

    Burners FG pressure(around 0.25 bar increase)

    below the constraint of 1.5 bar

  • Example2:OptimizationofGasTurbinesloads

    Although electricity exportation penalty increase

    Gas turbine load increase operating at higher efficiency

  • Example3:OptimizationofPumpswaps

    Steam vent eliminated

  • Example3:OptimizationofPumpswaps

    Several pump swapsA maximum pump swaps constraint required

    Economic impact of 1.4% cost reduction on total energy cost

  • Performancemonitoring(equipmentefficiency)

    Gas turbine heat rate

    Deviation

    Gas turbine theoretical heat rate

  • Performancemonitoring(equipmentefficiency)

    Fired boiler efficiency

    Turbogenerator efficiency

  • Systemauditing(steamimbalances)

    Steam imbalance 1,5 bar header

  • Casestudies

    GasTurbineOfflinewashingevaluation Effectofstart/stopofequipment:

    Firedboilers Turbogenerators Largesteamcondensingturbines

    UseofNGlinesinfiredboilers

  • Differentmodeluses

    Clientservermodel Shiftsupervisors,Operators,Engineers Optimizationonshiftbasis

    Standalonemodeluse Engineeringandplanningstudies

    Sustainabilityoftheuptodatemodel KeyPerformanceIndicatorsserver Instrumentationreview

  • Conclusions

    VisualMESAimplementedatBPLingenrefinery Asaresultoftheproject,abetterknowledgeofutilities

    systeminteractionshasbeenacquired,understandingalldecisionvariablesandtheassociatedconstraintswhichsometimesarehidden

    Abilitytoreactonlinetocapturebusinessopportunitiestoreduceenergycostsandimproveemissionsmanagement,gettingsignificantenergysavings