Integrated Modeling of CarbonIntegrated Modeling of CarbonManagement Technologies forManagement Technologies for

Electric Power SystemsElectric Power Systems

Edward S. Rubin and Anand B. RaoDepartment of Engineering & Public Policy

Carnegie Mellon University

Aspen Global Change InstituteJuly 24, 2000

Some Questions to be AddressedSome Questions to be Addressed

What carbon management technologies may be used ina particular application (e.g., existing vs. new plants)?

What are the key parameters that affect theperformance, emissions, and cost of a given option?

How do the alternative options compare in terms ofperformance, reliability, and cost?

What are the uncertainties and technological risks ofdifferent carbon management options?

What are the priorities and benefits of R&D to reducekey uncertainties in new process designs?

Scope and ObjectivesScope and Objectives Identify potential options for power generation with carbon

capture and sequestration, suitable for, (a) existing plants,and (b) new plants

Develop a model to quantify performance, emissions, andcost of alternative options, and their dependency on keyplant and technology design parameters, operatingparameters, and carbon management methods

Characterize uncertainty in key parameters of the carbonmanagement system

Integrate carbon management technologies with other plantenvironmental control systems

Conduct case studies to illustrate model applications

Current ApplicationsCurrent Applications

Enhanced oil recovery (EOR) Dow MEA (Some plants in TX

and NM, now shut down) Common in 1970s and 1980s

(100-1200 tons CO2/d) Fertilizer industry

H2 and CO2 separation ⇒ Ureaproduction

Dow MEA (Indo GulfFertilizer Co.) - 150 tons CO2/d

Carbonation of brine (soda ash) Kerr-McGee MEA (North

American Chemical Co.,operational since 1978) - 800tons CO2/d

Food-grade Fluor Daniel / Dow MEA

(Northeast Energy Associates,MA) - 320 tons CO2/d

Commercial CO2 capture andsequestration facility Injection into deep saline

aquifer (Sleipner West gasfield, Norway, installed in1996) - ~3000 tons CO2/d

Power Generation Options UsingPower Generation Options UsingFossil FuelsFossil Fuels

Combustion-basedGasification-based

Coal

Direct CombustionGas Reforming

Gas

Fuel

Air

Pure Oxygen

Oxidant

Pulverized CoalGas Turbines

Simple Cycle

Gas TurbinesCoal GasificationFuel CellsOther

Combined Cycle

Technology

Power Generation Technologies

COCO22 Capture Technologies Capture Technologies

MEACausticOther

Chemical

SelexolRectisolOther

Physical

Absorption

AluminaZeoliteActivated C

Adsorber Beds

Pressure SwingTemperature SwingWashing

Regeneration Method

Adsorption Cryogenics

PolyphenyleneoxidePolydimethylsiloxane

Gas Separation

Polypropelene

Gas Absorption

Ceramic BasedSystems

Membranes Microbial/AlgalSystems

CO2 Separation and Capture

COCO22 Sequestration Options Sequestration Options

Deep SalineReservoirs

ExhaustedOil and Gas Wells

AbandonedCoal Seams

GeologicalSequestration

Very Deep OceanInjection

Unconfined Release(@ ~ 1000 m)

Dense Plume Formation(shallow)

Dry Ice Injection

OceanSequestration

Forests andTerrestrial Systems

Marine Alga

BiologicalSequestration

Storage as a solid in anInsulated Repository

Utilization Schemes(e.g. Polymerization)

OtherMethods

CO2 Disposal / Storage Options

Modeling Framework for CarbonModeling Framework for CarbonManagement OptionsManagement Options

Power Generation

CO2 Capture

CO2 Storageor Disposal

CO2Transport

AbsorptionAdsorptionCryogenicsMembranes

PipelineOther

Deep Saline ReservoirsOil and Gas WellsDeep Coal Seams

OceansByproduct Utilization

Air orPure O2

Coal orNatural Gas

Simple CycleCombined Cycle

Energy ConsiderationsEnergy Considerations

ProcessHeat

Capture Process

Compression

Transport

Storage/Disposal

Electricity

Total Energy Requirement

Important Factors•Gas Stream Flow and Composition•Choice of CO2 Capture Technology•Desired CO2 Capture Efficiency•Process Parameters•Desired CO2 Product Specifications•Mode of Transport•Transportation Distance•Choice of Disposal Method

~ 60-80% cost ofseparation & capture

Current StatusCurrent Status

Developed preliminary models (performance,emissions, and cost) for several CO2 captureoptions, CO2 transport options, and CO2 storageoptions

Initial focus on modeling of current commercialtechnologies (amine scrubbing systems) forcombustion-based power systems

Integrated the new CO2 module with the IECMcombustion-based power plant model developedfor the USDOE

Integrated EnvironmentalIntegrated EnvironmentalControl Model (IECM)Control Model (IECM)

CoalCleaning

CombustionControls

Flue Gas Cleanup & Waste Management

NOxRemoval

ParticulateRemoval

CombinedSOx/NOxRemoval

AdvancedParticulateRemoval

SO2Removal

ObjectivesObjectives

Develop a comprehensive modelingframework to estimate the performance,environmental emissions, and cost of coal-based power generation technologies

Develop a method for comparingalternative options on a systematic basis,including the effects of uncertainty

Probabilistic Software CapabilityProbabilistic Software Capability

Allows you to specify parameter values asdistribution functions, as well as conventionaldeterministic (point) estimates

Allows you to explicitly quantify the effectsof uncertainty in performance, emissions, andcost, yielding confidence intervals foruncertain results

Conventional Process ModelingConventional Process Modeling(Deterministic Simulation)(Deterministic Simulation)

ProcessModel

ParameterValues

ResultsResults

Parameter UncertaintyParameter UncertaintyDistributionsDistributions

NORMAL UNIFORM LOGNORMAL

FRACTILETRIANGULAR BETA

Stochastic SimulationStochastic Simulation

StochasticModeler

SAMPLINGLOOP

ProcessModel

ParameterUncertainty

DistributionsResultsResults

SorbentSulfur

Loading

GasifierFines

Carryover

CarbonRetention inBottom Ash

353025201510500.0

0.1

0.2

0.3

Sorbent Sulfur Loading, wt-%20151050

0.0

0.1

0.2

0.3

Carbon Retention in Bottom Ash% of coal feed carbon

3025201510500.00

0.05

0.10

0.15

0.20

Fines Carryover, % of coal feed

Expert Judgments onExpert Judgments onKey Model ParametersKey Model Parameters

Calculated Plant EfficiencyCalculated Plant Efficiency

444342414039380.0

0.2

0.4

0.6

0.8

1.0

ProbabilisticDeterministic

Net Plant Efficiency (%, HHV basis)

Cu

mu

lati

ve P

rob

abil

ity

Total Plant Capital CostTotal Plant Capital CostC

um

ula

tive

Pro

bab

ilit

y

Total Capital Requirement ($1994/kW)1000 1100 1200 1300 1400 1500

DOE (1989)Probabilistic

0.0

0.2

0.4

0.6

0.8

1.0

524 MW net

Value of Targeted ResearchValue of Targeted Research

1201101009080706050400.0

0.2

0.4

0.6

0.8

1.0

Base Case UncertaintiesReduced Uncertainties inSelected Performanceand Cost Parameters

Levelized Cost of Electricity, Constant 1989 mills/kWh

Input Uncertainty Assumptions

Cu

mu

lati

ve P

rob

abil

ity

Probabilistic Comparison ofProbabilistic Comparison ofCompeting TechnologiesCompeting Technologies

IECM Software PackageIECM Software Package

Fuel PropertiesFuel Properties Heating Value Heating Value Composition Composition Delivered Cost Delivered Cost

Plant DesignPlant Design Furnace Type Furnace Type Emission Controls Emission Controls Solid Waste Mgmt Solid Waste Mgmt Chemical Inputs Chemical Inputs

Cost DataCost Data O&M Costs O&M Costs Capital Costs Capital Costs Financial Factors Financial Factors

PowerPowerPlantPlantModelModel

GraphicalGraphicalUserUser

InterfaceInterface

SessionSession& Fuel& Fuel

DatabasesDatabases

Plant & ProcessPlant & Process Performance Performance

EnvironmentalEnvironmental Emissions Emissions

Plant & ProcessPlant & Process Costs Costs

The IECM is Available forThe IECM is Available forDownloadingDownloading

Web Access:

ftp://ftp.netl.doe.gov/pub/IECM

Preliminary IECM User GroupPreliminary IECM User Group

ABB Power Plant Control American Electric Power Consol, Inc. Energy & Env. Research Corp. Exportech Company, Inc. FirstEnergy Corp. FLS Miljo A/S Foster Wheeler Development Corp. Lehigh University Lower Colorado River Authority McDermott Technology, Inc. Mitsui Babcock Energy LTD.

National Power Plc. Niksa Energy Associates Pacific Corp. Pennsylvania Electric Association Potomac Electric Power Co. Savvy Engineering Sierra Pacific Power Co. Southern Company Services, Inc. Stone & Webster Engineering Corp. Tampa Electric Co. University of California, Berkeley US Environmental Protection Agency

COCO22 Module Results Module Results

Flue gas (out) composition CO2 emission level

(kg CO2/hr) Amount of CO2 product

(ton/hr) Purity of CO2 product (%) Solvent circulation rate

(m3/hr) Make-up solvent rate

(kg MEA/hr) Make-up rate relative to

the circulation rate (%)

Waste generation rate(kg/hr)

Energy penalty (% ofMWg)

Net power generation Cost of CO2 captured

($/ tonCO2 captured) Cost increase in electricity

(cents/kWh) Cost of CO2 avoided

($/ tonCO2 avoided)

Additional Technology OptionsAdditional Technology Options

Just Completed Combustion NOx Controls

– Selective Non-CatalyticReduction (SNCR)

– Low NOx Burners (LNB)– LNB + Overfire air– LNB + SNCR– Natural Gas Reburn– Tangential, Wall &

Cyclone Firing

Just Started Post-Combustion

Controls– Air Toxics (mercury)

Other Fossil Fuels Alternative Power

Generation Systems CO2 Sequestration

Options

Future Developments:Future Developments:A Menu of Technology OptionsA Menu of Technology Options

SelectSelect Gasification Gasification Combined CombinedCycle (IGCC) OptionsCycle (IGCC) Options

ASPEN Model of anASPEN Model of anIGCC SystemIGCC System

CoalHandling

Gasification,Particulate &Ash Removal,Fines Recycle

GasTurbines

BoilerFeedwaterTreatment

SteamTurbine

SteamCycle

& SCR

SteamCycle

& SCR

ZincFerriteProcess

ZincFerriteProcess

SulfuricAcid PlantSulfuric

Acid Plant

SulfuricAcid

Rawwater

Coal Coal

CleanSyngas

Exhaust Gas

Gasifier Steam

Boiler Feedwater

Exhaust Gas

Shift & Regen.Steam

Cyclone

RawSyngas

Cyclone

Blowdown

Return Water

CoolingWater

Makeup

CoolingWaterBlowdown

Air

NetElectricityOutput

InternalElectricLoads

Ash Gasifier Air

AirTailgas

Off-GasCaptured Fines

Response Surface ModelResponse Surface Modelfor an IGCC Systemfor an IGCC System

0.39

0.4

0.41

0.42

0.43

0.39 0.4 0.41 0.42 0.43

Actual Efficiency

Pred

icted

Effi

cienc

y

Desktop Model of an IGCC SystemDesktop Model of an IGCC System

Model ApplicationsModel Applications

Process design Technology

evaluation Cost estimation R&D management

Risk analysis Environmental

compliance Marketing studies Strategic planning

Com

mun

icat

ion

A Hierarchy of Process ModelsA Hierarchy of Process Models

EnterpriseEnterpriseEnterprise

System ModelsSystem ModelsSystem Models

Integrated ModelsIntegrated ModelsIntegrated Models

Component ModelsComponent ModelsComponent Models

Mechanistic/Empirical ModelsMechanistic/Empirical ModelsMechanistic/Empirical Models

Val

idat

ion