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Reduction Of Nitrous Oxide Emissions From A Mixed Fuel Power Plant
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Reduction Of Nitrous Oxide Emissions From A Mixed Fuel Power Plant

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Changing operational guidelines to reduce nitrogen oxide emissions without limiting generation capacity or availability.

Changing operational guidelines to reduce nitrogen oxide emissions without limiting generation capacity or availability.

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  • 1. Reduce Unit 3 NOx Emissions
    Project Background:
    The operation of Unit 3 results in the release of nitrogen oxides to the environment.
    Cumulative NOx emissions required unit 3 to be shutdown during normal production time in the past.
    JEA’s vision includes not only meeting, but exceeding environmental regulations.
    NOx emissions are marketable credits.
    Problem Statement:
    From 11/01/04 to 06/19/07, Northside Generating Station Unit 3 operated with an average NOx rate of 0.24735 lbs/mmBTU.
    Goal Statement:
    Decrease the average NOx rate from 0.24735 lbs/mmBTUby 10% to 0.222615 lbs/mmBTUby November 30, 2007 without exceeding opacity limits or limiting unit capacity.
    Project Summary:
    System designs limited some improvement potentials so work was focused on areas with a potential for high returns.
    Focus area procedures changed to proactively reduce and stabilize NOx production at lower loads.
    A hard savings of $408,250 annually was realized in addition to increasing overall system availability.
    Operations personnel continually seek to reach guidelines every time unit load is reduced for any period over 30 minutes.
    Initial reduction of 14.2% has been sustained for 7 months.
  • 2. About JEA
    JEA is the largest community owned utility in Florida and the eighth largest municipal utility in the United States providing electricity, water and sewer service to more than 750,000 electric, water and sewer accounts in Jacksonville, Florida and parts of three adjacent counties. Annual revenues are about $1.4 billion.
    JEA is committed to our mission:
    “To improve the quality of life in the communities we serve by being the best electric, water and sewer utility in the nation.”
  • 3. Process Improvement Mission and Goal
    Vision: Drive JEA to design and produce products/services to six sigma standards
    Goal: Use the tools and philosophy to produce products and services resulting in:
    Improved customer satisfaction and loyalty
    Reduced O&M and capital costs
    Improved work environment
    Initiated in 2000, our initiative has produced 32 Certified Six Sigma Black Belts and 270 Certified Green Belts
    500 projects have been completed with over $120 million in bottom-line impact.
  • 4. 4
    Project CharterReduce Unit 3 NOx Emissions
    Process Map Number:3056
    Customer CTQ(s): Instantaneous NOx levels, opacity, fuel mixture (oil/gas), excess air levels
    Green Belt: Jason Lankford
    Process Owner: Michael D’Avico
    Champion: Michael D’Avico
    Implementation Coordinator: Jason Lankford
    Data Coordinator: Jason Lankford
    Team Members:
    John Wiseman – Operations Manager
    John Kang – Optimization Specialist
    Joseph Werner – Engineer
    Jeff Blanchard – Unit Operator
    Brian Altman – Unit Operator
    Duane Yost – Unit Operator
    Problem Statement: From 11/01/04 to 06/19/07, Northside Generating Station Unit 3 operated with an average NOx rate of 0.24735 lbs/mmbtu. Reduction of this NOx rate is in direct support of environmental stewardship. NOx rate reductions could also yield a hard savings of $287,500/year.
    Project Scope:
    This project will focus on steady state operations of NGS Unit 3. This is defined as current NOx rates of 0.01 to 0.60 lbs/mmbtu.
    Project Timeline:
    Goal Statement: Decrease the average NOx rate from 0.24735 lbs/mmbtu by 10% to 0.222615 lbs/mmbtu by November 30, 2007 without exceeding opacity limits or limiting unit capacity.
    Expected Benefits:
    Hard Savings – $287,500 per year (with 10% reduction)
    Soft Savings – situational, based upon external costs and availability of other units
    Other Benefits:
    Voluntary reduction in environmental emissions
    Potential for increased unit availability
    Baseline Metric Performance (32 Months):
    Short Term Long Term
    Zbench 0.65 0.62
    DPMO 258,784 266,463
  • 5. 5
    Add Air
    Add Fuel
    Define; SIPOC
    Suppliers
    Process
    Outputs
    Customers
    Inputs
    Burn fuel in order to generate heat required for a given load.
    #6 Oil
    Fuels
    Megawatts
    SOCC
    Fuels
    Natural Gas
    NOx Emissions
    Thermal energy (waste)
    Atmosphere
    Atmosphere
    Air/Oxygen
    SOCC
    Load Demand
    NOx generated here
    Project Boundary
    Project Boundary
    Process Steps
    Arrange Burners
    Control Ratios
    Modulate based on load
  • 6. Document Existing Process
    We have regularly been exceeding our targeted average of .222615 lbs/mmBTU.
    Operational data from November, 2004 through June, 2007 was used for analysis.
    Blank months indicate where the unit was offline.
  • 7. 7
    Root Cause Investigation Matrix
    Root Cause Investigation Matrix
    Problem State-ment “Y"
    Probable / Possible Root Cause(s) "Xs"
    BB Con-currs
    Y/N
    Explain "WHY" - (Logic Flow for Verification Method)
    Statistical Test or Logical Analysis Treatment
    Statistical or Logical Analysis
    Burner arrangement
    Log
    Impacts available O2, air flow, local hot/cool spots, residency , limited data available
    Y
    Tree
    Excess Air
    Stat
    Impacts available O2 and stoking of fire, Pi data available
    Y
    Regression
    LIMIT INSTANTANEOUS NOx
    Neural Net
    Log
    Trim level control of dampers, NOx, O2, Pi data available
    Y
    TBD
    Crew Variability
    Stat
    Different crews may operate the boiler differently and yield different NOx levels, Pi data available
    Y
    1-Way ANOVA
    Fuel/Air mixture
    Stat
    Combustion support, opacity, Nox, Pi data available
    Y
    Regression
    CEMS Equipment
    Log
    Emission measurement, possible savings in measurement systems, limited RATA testing info available
    Y
    Graphs
  • 8. 8
    Determine Critical X’sBurner Placement
    We can determine two items here. How the fuel is burned by burner placement (operations) and what type of fuel we burn (purchase)
    Why do we have high temperatures in boiler?
    Individual burners create hot areas
    Why do we have clusters of burners?
    High temperatures (>1700F) create Thermal NOx
    Hot zones in boiler
    Improper burner placement can create unnecessary hot zones
    Burner clusters create hot zones
    Combustion Creates NOx
    NOx Production
    Why do we have hot zones in boiler?
    Why does combustion create NOx?
    Why do we generate NOx?
    Nitrogen is a naturally found in oil and coal
    Improper placement of burners in service can generate NOx unnecessarily. Reducing the instances where poor burner arrangements are used will reduce overall NOx production. Since poor placement of burners can be a major contributor to NOx, we will consider burner placement to be a critical X.
    Burning Oil releases nitrogen that can form Fuel NOx
    Nitrogen is a constituent of the oil
    Why don’t we remove the nitrogen?
    Nitrogen cannot be readily removed from fuel
    Why is there nitrogen in the fuel?
  • 9. Determine Critical X’sExcess Air
    Because of the nature of our system and our need to maintain many units at or near their base loads, unit 3 has essentially become a peaking unit.
    During the day, unit 3 is loaded up as needed by the system. It is not uncommon to see the unit above 400 MW and up to 540MW during a high demand day.
    In order to address the different loads, the data was broken down into load ranges, which were evaluated independently of each other.
    Upon breakdown of the data by load range, we found that lower load operations needed significant attention.
    Further breakdown illustrated that excess air at lower loads did explain a portion of our increased NOx rates.
    At higher loads, excess air had very little association with NOx production levels.
    Analysis of Variance
    Source DF SS MS F P
    Regression 1 0.052317 0.052317 15.20 0.000
    Residual Error 56 0.192747 0.003442
    Total 57 0.245063
    Unusual Observations
    Excess CEMS-NOx IN
    Obs Air lbs/mmBTUs Fit SE Fit Residual St Resid
    19 84.6 0.37044 0.21864 0.00931 0.15180 2.62R
    42 84.8 0.34238 0.21935 0.00941 0.12304 2.12R
    43 56.1 0.10643 0.12919 0.01932 -0.02276 -0.41 X
    49 50.6 0.13747 0.11227 0.02337 0.02520 0.47 X
    56 49.6 0.12777 0.10896 0.02417 0.01881 0.35 X
    R denotes an observation with a large standardized residual.
    X denotes an observation whose X value gives it large leverage.
    9
    Regression Analysis: CEMS-NOx IN lbs/mmBTUs versus Excess Air
    The regression equation is
    CEMS-NOx IN lbs/mmBTUs = - 0.0464 + 0.00313 Excess Air
    Predictor Coef SE Coef T P
    Constant -0.04642 0.06323 -0.73 0.466
    Excess Air 0.0031332 0.0008036 3.90 0.000
    S = 0.0586678 R-Sq = 21.3% R-Sq(adj) = 19.9%
    Low load excess air volumes are a critical X.
  • 10. 10
    Root Cause Investigation Matrix
    Root Cause Investigation Matrix
    Problem State-ment “Y"
    Probable / Possible Root Cause(s) "Xs"
    BB Con-currs
    Y/N
    Explain "WHY" - (Logic Flow for Verification Method)
    Statistical Test or Logical Analysis Treatment
    Statistical or Logical Analysis
    Burner arrangement
    Log
    Impacts available O2, air flow, local hot/cool spots, residency , limited data available
    Y
    Tree
    Excess Air
    Stat
    Impacts available O2 and stoking of fire, Pi data available
    Y
    Regression
    LIMIT INSTANTANEOUS NOx
    Neural Net
    Log
    Trim level control of dampers, NOx, O2, Pi data available
    Y
    TBD
    Crew Variability
    Stat
    Different crews may operate the boiler differently and yield different NOx levels, Pi data available
    Y
    1-Way ANOVA
    Fuel/Air mixture
    Stat
    Combustion support, opacity, Nox, Pi data available
    Y
    Regression
    CEMS Equipment
    Log
    Emission measurement, possible savings in measurement systems, limited RATA testing info available
    Y
    Graphs
  • 11. 11
    Deliverable 11: ImprovePrioritized List of Solutions
    There are 3 primary X’s that will be addressed:
    Excess Air – addressed during low load conditions, this X could be significantly reduced procedurally. By minimizing excess air during operations, NOx could also be reduced.
    Burner Arrangement – An already demonstrated method, this will be re-evaluated at low load, 100% oil conditions as well as high and low load 100% gas conditions. This will target a reduction in both the average and cumulative NOx emissions.
    CEMS Equation – A goal of reducing the difference between the reference method flow rate and our measured flow rate will yield a more accurate reporting of NOx generation rate. This will also reduce any over-reporting of NOx rates.
    Procedural changes for low load operations can be developed and followed to have the fastest, lowest cost results.
    How?
    How?
    As a result of EPA standards and operational requirements required to make adjustments, this solution had to be abandoned for the term of this project.
  • 12. 12
    ImproveTesting Summary
    Using existing data, different burner arrangements were tested to find a standard set up that allowed for the lowest NOx rates at low loads. Each was evaluated based upon its mean rate and ability to stay in control.
    A Mood’s Median Test was performed on the test data and initial data to determine test results vs. initial data.
    Test 9 showed the overall best results.
    Procedures to proactively reduce air flows to their minimum level and use the burner arrangement from test 9 were implemented. Dispatch took a more aggressive stance about going to low NOx runs when reduced loading was available. Both management and the operational crews were happy with the results.
  • 13. 13
    Deliverable 14Updated Process Capability
    During our control run, we found the test run data to be repeatable. Additionally, run for significantly longer than the test runs, the NOx production levels actually dropped further than the initial testing.
  • 14. 14
    Deliverable 14Updated Process Capability
    All data is from the 50-100 MW load range with specific attention paid to the 50-55 MW load range.
    To date, 24 hour NOx rates have remained low. Crews are self motivated to encourage low NOx runs. As of October 17, 2008, the 24 hour average was .11 lbs/mmBTU.
    Initial pull data went back to November 1, 2004
    There were a series of 6 tests run, each of which targeted NOx reduction
    Final controls yielded a mean NOx value of .11968 lbs/mmBTU
  • 15. Updated Benefits Document
    15