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Intellectual Property Statement. This proposal/presentation is strictly confidential. It is made available to prospective clients with the understanding that it will not be shown, read or passed to any other person who is not a current employee of your organization.

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
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intellectual property statement
Intellectual Property Statement
  • This proposal/presentation is strictly confidential. It is made available to prospective clients with the understanding that it will not be shown, read or passed to any other person who is not a current employee of your organization.
  • This proposal/presentation has been developed by Engineering Consultants Group Inc. and will remain its property until such a time as a formal contract for the project is finalized with the client, as such the content may not meanwhile be disclosed by the client to any third party, nor may any original concept devised by Engineering Consultants Group Inc. be used commercially. If the client decides not to proceed with the project, selects another consulting firm, or decides to conduct the project itself, we request return of this proposal/presentation together with assurances that no photocopies of this proposal/presentation have been made.
accutrack challenges tracking coal

Implementations of

Digital Fuel Tracking Systems at

Large Coal Fired Power Plants

AccuTrack – Challenges Tracking Coal

Mike Santucci, ECG

Michael Dunlap, DTE

Jim Mooney, JRM

Engineering Consultants


May 1 – 3, 2007

Rosemont, Illinois

the opportunity
The Opportunity

Fuels Opportunity


Objective to Achieve Success

  • Rising Coal Prices
  • Increased Market Volatility
  • New Regulations
  • Yard Constraints
  • Fuel Flexibility
  • Adaptive Compliance
  • Be a key provider and enabler of information
  • Enable Operational Excellence – Maximize Plant Output
  • Make Real Time Data Actionable
  • Minimize Risk while Capitalizing Fuel Opportunities “Timed Delivery”
example fuel blending for capacity
Example Fuel Blending for Capacity


August Lost Opportunity


Rail Delivery

Rail Delivery



full load fuels


Hi Value


Full Load Fuels

Design Fuel



Optimize “Hi Value Coal ” UtilizationCapture Value of Burning “The Right Fuel at the Right Time”Understand Coal QualityUnderstand the Risk

hurdles to overcome


Hurdles to Overcome

Equipment Deficiencies


  • Scales are not functioning properly, and are outdated.
  • Sampler Systems are inoperable.
  • Annunciator Alarm Panel is not functioning.
  • Some Equipment necessary to Automate Yard is missing.
  • No FEGT Monitors
  • Replace/Install 5 Scales
  • Replace As-Received and As-Fired Samplers with Modular Systems
  • Digitize Alarm Panel in PI
  • Install Necessary Equipment
  • Install FEGT Monitors

© 2007 Engineering Consultants Group, Inc. – All Rights Reserved.

hurdles to overcome8


Hurdles to Overcome

Data Deficiencies


  • Information is calculated or inferred
  • Corporate Fuels Data is not available at the Plant
  • Yard Equipment not Digitized
  • Stand Alone Spreadsheet Reporting “Satellites”
  • Use Plant Weights and Measures
  • Create Web Based System available to all.
  • Update Control System to Automate Coal Yard – Write Data to PI system.
  • Consolidate integrate and eliminate
hurdles to overcome9


Hurdles to Overcome

Operational Deficiencies


  • Pulverizer Capacity Limitations due to Fuel
  • Slagging Potential
  • No Coal Segregation
  • Coal yard is managed for the most efficient use of available manpower rather than the most efficient use of fuels.
  • Fuel Characterization - HGI Blending Mill Capacity Improvements
  • Operator Advisory Screen
  • Manufacture Coal to meet Mission
  • Staff Yard Appropriate to Mission

25 day inventory is about 300K

Hi Value





Hurdles to Overcome

overall project approach
Overall Project Approach

Phase I

Phase II

Phase III

Financial Processes

Validate and Develop Detailed Design

Implement and Install Processes and Reporting

Identify Current State

Identify Current Opportunity

Communication and Change

Value-Based Measures

benefits of overall approach
Benefits of Overall Approach

Undertaking these initiatives will maximize the return on efforts to achieve key elements of any Corporate strategy:

  • Maximizing Generation – In a market where Reserve Margin Forecasts are dropping from 11 to 6% over the next 3 years.
  • Fuel Flexibility – Burn the “right fuel at the right time”.
  • Environmental Compliance – Understand Fuel Impacts to the Boiler and Air Quality Control Systems in Complying with more stringent environmental limitations enacted by the state.
  • Accurate Reporting of Inventory – Asset Reporting Accuracy required by Sarbanes Oxley Legislation

© 2007 Engineering Consultants Group, Inc. – All Rights Reserved.

predicted burn time discussion
Most accurate methods available are used to calculate and display predicted burn timesPredicted Burn Time Discussion
  • AccuTrack Elemental Bunker Model calculates the predicted burn time by evaluating the predicted burn time of each element in the model
  • A simple model might capture a “slice” through the geometry of the bunker to calculate the predicted burn time.
overall project approach timing
Overall Project Approach - Timing

Phase I

Phase II

Phase III

Financial Processes

Validate and Develop Detailed Design

Implement and Install Processes and Reporting

Identify Current Opportunity

Develop and Validate Detailed Design

Communication and Change

Value-Based Measures

bringing all parties to the table


Calculations and Processing



Silo Fills


Shipment Unloads


Yard Inventory

Yard and Plant Real-Time Data

On-the-Belt Blending

Shipment Status

On-Hand Inventory

Quantities & Specs


Manual Inputs

Unload Quantities

Loading Destinations

Website Interface

MS SQL Server

Audit Inventories with Corporate

Fuel Type & Feeder Quantities

Unload Destinations

Corporate Fuel Data Systems

Process Book Client



Shipment Coal Specs

Vendor/ Internal Lab Data

Fill Coal Specs

Shipment Variance Results

Silo/Bunker Flow Model

On-Line Analyzer Data

DFTS Server

Day Ahead Dispatch

Bringing All Parties to the Table

Dedicated server with MS SQL and ECG’s server-side tracking software

accutrack objectives
AccuTrack Objectives:

Software Objectives:

  • Track incoming coal tons and fuel spec from Mine to Yard to Bunker to Burner
  • Blend Coal to Bunkers to meet Quality and Economic Objectives
  • Creates Transactions for each Fueling Event
  • Provide Tools to Avoid Boiler Upsets while Maintaining Consistent Emissions
fuel system overview

Rotary Rail Unloader

Ship Unloader

Overhead unload tripper

Low Sulfur Southern

Low Sulfur Western

Med Sulfur Eastern

Sampling building with analyzer off C4

Fuel System Overview
  • Ship Unloading System
    • Two 72 inch belts that support ~5000 TPH
    • Unloads a 32,000 ton ship in ~8 hours
  • Train Unloading System
    • 72 inch belt that supports ~5000 TPH
    • Unloads a 14,000 ton train in ~6 hours
  • Reclaim
    • 6 rotary plow feeders support ~2200 TPH
    • Specifically designed for blending 3 types of coal
    • An emergency reclaim is available at ~1400 TPH
    • 28 silos (7 per unit) that hold 380 tons each (10,640 total)
  • Consumption
    • 1350 TPH at full load (~5.5 hr capacity)
  • Overall
    • 13 belt scales
    • ~60 gates and over 160 field inputs used in tracking system
    • X-Ray type coal analyzer
fuel system overview18

13 belt scales

Calibrated Reference


6 Rotary plow feeders


28 silos


~60 gate indicators

Fuel System Overview
real time graphics overview
Real-time Graphics: Overview

System health

Inventory results

On-the-belt coal specs

Analyzer results

Silo desintations

Vendor supplied specs

Tripper locations

Blending results


Fuel Characterization – Blending Tools

Factors affecting Slag-Fouling

  • Coal Quality
  • Temperature
  • Atmosphere

Suggested Blend has a

Medium potential to form Slag in

This Furnace

unload bunker transactions
Unload/Bunker Transactions
  • Real Time Data Integrated and Processed into tables on the SQL Server
    • Simplifies the data management by summarizing “signals” in PI
    • Easier to maintain system data (database modifications)
    • Faster reporting
  • New bunker transactions created:
    • Conveyor scale reading is close to zero 30 seconds
    • Change in destination silo
    • Change in Blend

Scale Total

Scale 1

Scale 2

silo model
Silo Model

Example …


  • 25 data points from flow rate over 4 minutes
    • Integrated tons=44
  • 3 data points from on-line coal analyzer (updating every 2 min.)
    • Time-weighted average BTU=11414
  • This data is used to build a bunker transaction as shown above (i.e. start time, end time, tons, fuel type blend, unit, silo, analyzer data)
  • This 44-ton record will be used to build the layer in the bunker model
    • Bunker transactions are averaged (weighted) together to build the layer
silo model tracer testing27
Silo Model – Tracer Testing

RFID Chips

Tracer Testing Method

RFID Reader

other challenges
Other Challenges


  • Delay from one Scale to another
  • Update Frequency of Analyzer
  • Calibration of Analyzer
  • Bad Inputs
  • Mixing in Open Bunkers
  • Projecting Day Ahead Load
  • Handling Unit Derates
constraint tracking and capacity declarations
Constraint Tracking and Capacity Declarations

Unit Constraint Tracking

Fuel Quality’s impact on load.

scale validation

Upstream Scale

Downstream Scale



Steady state flow



Scale Validation
  • Compares upstream scales to downstream scales
  • Three different health conditions for scales
    • Good (Green)
    • Warning (Yellow)
    • Bad (Red)
  • Web reports are used to display scale comparison details
  • PI-ProcessBook is used to summarize health of scales
  • Email notification is used to alert scale problems
early warning indication
Early Warning Indication

Low Alarm: Opacity potential for the next 2 hours

  • PI-ProcessBook displays provide real-time data
  • Simple table of forecasted data allows operators to adjust for changes in coal
    • Adjust excess air
    • Bias mills on lower rows
    • Adjust load
    • Modify soot blowing schedule
  • Color-coded variables provide visual alarming
    • Green: Ok
    • Yellow: Low Alarm
    • Red: High Alarm

High Alarm: Slagging potential in 4 hours

Note: This screen was developed by Dave Tillman, DTE

web reporting bunker reports

All end-user reports support print versions and exporting to Excel. Some support charts.

  • One record per day
  • Four records per day (one for each unit)
  • Report selectors allow users to format the output
  • Raw transactions in database
  • Coal specs
  • CVC4 is used for total tons loaded
  • Plow feeder scales are used to calculate blend
Web Reporting: Bunker Reports
web reporting shipment unload reports

All unload reports use PI as data source. Plant belt scale tons are displayed. Tripper position is used for determining fuel type.

  • Shipment reports use corporate FMS as data source. Vendor tons are displayed. FMS data is downloaded once per hour.
  • Reports can be filtered by different variables using report selector
  • One record per day
Web Reporting: Shipment & Unload Reports
troubleshooting and reporting silo fills
Troubleshooting and Reporting Silo Fills
  • Historical reports via web browser
    • Exact on-the-belt blend results for any loading period
    • On-line analyzer results (wt. average) can be reported by silo
    • Many other operational details can be investigated though detailed reports
shipment unload variance reports
Shipment Unload Variance Reports

3,149 tonsdifferent


real time graphics analyzer samples
Real-time Graphics: Analyzer Samples
  • Current sample along with 8 samples back
coal analyzer vs lab sample reporting
Coal Analyzer vs Lab Sample Reporting
  • X-ray technology
  • ~20 coal property variables
  • 2 minute updates
  • Initial sampler problems
  • Reliable for the past 12 months
coal properties being tracked
Coal Properties Being Tracked
  • Coal properties tracked through the silos:
    • BTU (Btu/lb)
    • Cost ($/MBtu)
    • SO2 (lb/MBtu)
    • AshLoading (lb/MBtu)
    • BARatio
    • Moisture (%)
    • Iron (%)
    • Calcium (%)
    • Si+Al (%)
    • Alkalinity
    • Volatility
    • OLA Health
  • OLCA produces additional properties not listed
  • The list of coal properties being tracked through the silos was developed by Dave Tillman, DTE
    • Refer to Dave’s training for more information
  • Slag/Fouling Contol
  • Boiler Efficiency (I/O Method)
  • Fly Ash Resistivity Model
lessons learned
Lessons Learned
  • Key variables to track will depend on unit limitations and circumstances
    • Monroe: Opacity, slagging and fouling
  • Backup data (pile averages) for the analyzer was worthwhile
    • Sampler and analyzer outages
    • Estimation is surprisingly accurate while blending 2 or 3 coals
  • Permissives are required where operators are providing manual inputs
  • Belt scales will differ
    • Need continuous calibration and validation
  • Maintenance plan is needed
    • For PI and other IT outages
maintenance plan
Maintenance Plan
  • Software maintenance plan is advised to ensure system integrity
  • Daily tasks to check the system health
  • Correct AccuTrack database for missing or corrupt data due to PI or AccuTrack outages
  • Monthly tasks to verify data
  • Monthly reports on fuel activity and system availability
  • Training for new users
  • Software updates and enhancements
  • Inventory Control is accomplished by measuring the inputs from Corporate Fuel Management Systems and Plant Data Collection (scales-levels-meters)
  • Fuel Flexibility is created through real time integration of Accounting Fuel Management Systems with Plant Performance initiatives.
  • Operating with Precision is burning the “right fuel @ the right time” to support the plant mission and Environmental requirements

“One cannot manage what is not measured”

W. Edwards Deming, father of Total Quality Management

Philosophy of Mirant’s Coal Processes

accutrack references
AccuTrack References
  • Pennsylvania
    • Penn Power’s Bruce Mansfield Plant
    • 3 units
    • 2300 MW
    • Blends Three Primary Fuels
  • Ohio
    • FirstEnergy’s Eastlake Plant
    • 5 units
    • 1200 MW
    • Blending PRB
  • Michigan
    • Detroit Edison’s Monroe Plant
    • 4 units
    • 2600 MW
    • Undersized Precips are sensitive to fuel changes