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  • Power-Gen InternationalNovember 29, 2006

    Maximizing Operating Effectiveness withIntegrated Combustion and Soot Blowing Optimization

    Presented by: Joe Naberhaus

    Dynegy Inc., Midwest Fleet Operations

  • 1

    AgendaAgenda

    Dynegy OverviewMotivations for OptimizationCCPI Project OverviewSoot Cleaning OptimizationLooking Ahead

  • 2

    About DynegyAbout Dynegy

    NEPO

    OL

    NEPO

    OL

    FRCCFRCC

    MAPPMAPP

    SPPSPP

    MAINMAIN

    ERCOTERCOT

    WECCWECC

    SERCSERC

    West

    43 MW Gas

    Texas

    610 MW Gas

    Midwest

    3,316 MW Coal/Oil442 MW Gas

    Southeast

    815 MW Gas

    Northeast

    1,507 MW Gas/Oil370 MW Coal

    1,137 MW Gas49 MW Hydro

    Midwest-Peakers

    2,970 MW Gas

    U.S. PORTFOLIO11,259 net MW

  • 3

    DynegyDynegys Baldwin Energy Complexs Baldwin Energy Complex

    3 - 600 MW Units1970-1975

    Units 1 & 2 Cyclone Fired14 Cyclones/Unit

    Unit 3 T-Fired6 Mills

    PRB CoalConversions1999 & 2000

  • 4

    Motivations for OptimizationMotivations for Optimization

    Full Load PRB operation requires tight control

    Loss of spare fuel delivery capacitySmall process changes have significant effectsSeasonal impacts to heat rate

    ExpectationsAbility to control key parameters on consistent basisAbility to compensate for changes in coal qualityImproved understanding of available data and its use for improved operationsAbility to optimize controls to meet plant objectives.

  • 5

    NeuCoNeuCos CCPI Project @ Baldwins CCPI Project @ Baldwin

    About the Clean Coal Power Initiative (CCPI)$1.3 B initiative to demonstrate clean coal technologies in the fieldSponsored by DOEs National Energy Technology LaboratoryNeuCos project at Baldwin selected as Round 1 winner in 2004

    Five integrated optimization modules, parallel development

    SCRCombustion Soot blowingPerformance Maintenance

    Products developed iteratively with multiple releases

  • 6

    Why Optimize Soot Cleaning?Why Optimize Soot Cleaning?

    Cleaning actions (or lack thereof) affect many plant parameters:

    Slagging/fouling impacts heat transferabilityCapacity: Steam and gas temperatures, spray flows, differential pressures, fan limitsPerformance: Boiler efficiency, heat rateEmissions: NOx, Opacity, LOI, COAvailability/Reliability: Waterwall/tube longevity, EFOR, equipment wear-and-tear

    Operational complexities:Fuel and equipment variationsSCR/SNCR systemsLOI control objectives

    Bottom line economic impact - $$$$

  • 7

    SootOptSootOpt

    BoilerEfficiency

    Steam Temperature OF

    950OF 1010OF1005OF

    NOx

    Attemperation

    Spraying

    Typical operating range

    Desired Setpoint

    SootOpt, because of its neural model, can operate in this narrower range

  • 8

    What SootOpt DoesWhat SootOpt Does

    Optimizes boiler cleaning based on unit-specific objectives:Improves emissions control (NOx, opacity, CO)

    Improves Heat Rate including Reheat & Superheat steam temperature control

    Balances tradeoffs between furnace/backpass absorption

    Reduces O&M costs by avoiding unnecessary boiler cleaning actions and reducing tube wear and thermal stressing

    Compensates for off-design fuels and operations

    Leverages existing soot cleaning instrumentation, models, equipment and control systems

  • 9

    How SootOpt WorksHow SootOpt Works

    Hybrid Expert

    Adaptive System

    Expert Fuzzy Component

    Heuristic Set 1 SH < 990 990 < SH < 995 995 < SH < Tset SH > TsetRH < 990 A A A A990 < RH < 995 A B C C995 < RH < Tset A B B or C CRH > Tset A B C B or C

    .

    .

    .

    .

    .

    .

    Boiler StateCF-SHDivCF-SHFin

    CF-SHPrimCF-RH

    Flux 1-16Freq IR -1Freq IR -2

    NOxSoot Blowing Control PLC

  • 10

    SootOpt at Baldwin Unit 3SootOpt at Baldwin Unit 3

    630 MW, Base-Loaded, T-FiredSOFA, Low NOx BurnersHigh variability in PRB coalHeat Flux Sensors and Water CannonsDiamond SentrySeries 1500 control system with locally intelligent controlsPrecisionClean and standard IKs in convection passAlso thermocouples and FEGTPrevailing sootblowing guidelines:

    ISB preset flux targets in the furnace, operators interveneOperator initiated in the convection pass

  • 11

    SootOpt - Diamond SentrySeries 1500 Interface

  • 12

    Optimization Benchmarks

    Optimization AlertsCurrent Events

  • 13

  • 14

    SootOpt Sensitivities: Net HR

  • 15

    SootOpt Causality Profile: RH Attemperation Sprays

  • 17

  • 18

  • 19

  • 20

  • 21

    SootOpt at Baldwin: Results Thus FarSootOpt at Baldwin: Results Thus Far

    Operating and Producing Results on Unit 3Initially operated only on Water Cannons for furnace cleaningNow operating on furnace and all convection pass regionsNow being integrated with CombustionOpt

    Being installed on Unit 2 nowUnique opportunity to quantify contributions of individual ISB control and instrumentation components

  • 22

    RH Temps with SootOpt (Furnace Only)RH Temps with SootOpt (Furnace Only)

    Hot RH Outlet Temp

    4/18

    /05

    5/8/

    05

    5/28

    /05

    6/17

    /05

    7/7/

    05

    7/27

    /05

    8/16

    /05

    9/5/

    05

    DateTime

    960

    970

    980

    990

    1000

    1010

    1020

    HO

    T R

    EHE

    AT

    OU

    TLE

    T TE

    MP

  • 23

    Net Unit Heat Rate

    500 400 300 200 100 0

    0

    2000

    4000

    6000

    8000

    1000

    0

    1200

    0

    1400

    0

    1600

    0

    1800

    0

    2000

    0

    2200

    0

    2400

    0

    DataIndex

    50

    55

    60

    65

    70

    75

    80

    85

    90

    95

    100

    Wet

    Bul

    b Te

    mp

    Heat Rate Heat Rate vsvs Wet Bulb over TimeWet Bulb over Time

  • 24

    Heat Rate Heat Rate vsvs CondCond Press over TimePress over Time

    Net Unit Heat Rate

    0

    2000

    4000

    6000

    8000

    1000

    0

    1200

    0

    1400

    0

    1600

    0

    1800

    0

    2000

    0

    2200

    0

    2400

    0

    DataIndex

    1.8

    2.0

    2.2

    2.4

    2.6

    2.8

    3.0

    3.2

    3.4

    3.6

    3.8

    4.0

    4.2

    CO

    ND

    3A

    PRE

    SS

  • 25

    NOx Model with CombustionOpt & SootOpt MVs as Inputs

    NOx Model with only CombustionOptMVs as Inputs

    Integration Improves Model Accuracy

  • 26

    SootOpt MVs added to CombustionOpt NOx Model

    Integration Increases Benefits

  • 27

  • 28

  • 29

    SootOpt SootOpt SummarySummary

    SootOpt improves control of heat-transfer process

    Relates impacts to global objectives. Searches for global optimum across multiple sometimes competing objectives

    SootOpt performance can be changed by changing relative priority of objectives, e.g., Steam Temperature Max vs. Heat Rate, or all can be given equal priority

    Lets user assess where priority should be given based on bottom line impact.

    The highly inter-related processes of combustion and boiler cleaning confirms the need for integration to achieve maximum benefits

  • 30

    Looking AheadLooking Ahead

    Complete Integration of CombustionOpt and SootOpt and at Unit 3Complete installation of SootOpt on Unit 2Integrate CombustionOpt, SCR-Opt, SootOpt, PerformanceOpt and MaintenanceOpt at Unit 2Further refine CombustionOpt, PerformanceOpt & MaintenanceOpt at Unit 1Further refine Unit and Plant AdvisorsSubsequent refinement and releases based on feedback from Baldwin and other NeuCo Showcase sites

    AgendaAbout DynegyDynegys Baldwin Energy Complex Motivations for OptimizationNeuCos CCPI Project @ BaldwinWhy Optimize Soot Cleaning?SootOpt What SootOpt DoesHow SootOpt WorksSootOpt at Baldwin Unit 3SootOpt at Baldwin: Results Thus FarRH Temps with SootOpt (Furnace Only)Heat Rate vs Wet Bulb over TimeHeat Rate vs Cond Press over TimeSootOpt SummaryLooking Ahead

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