ADDED VALUE APPLICATIONS ~ ENABLED THROUGH PI Jerry Weber, Thermal Performance Specialist Frank Borth, Performance & Data Engineer Wayne Benedeck, Thermal Performance Specialist ComEd

Changes in Generation in the Utility Business BEFORE COMPETITION Monopoly business Staff for All Needs Cost-plus Pricing Make Capital Investments to Maintain Plant Availability at All Costs Produce MWh’s UNDER COMPETITION Competitive market Minimum Operating Staff Market-based Pricing Make Capital Investments Based upon Return on Investment ‘Commercial Availability’ Market Energy AND Supplementary Services

Utilize INFORMATION TECHNOLOGY to Enhance Operational Capabilities to Better Manage Assets to Better Serve ‘Customers’ How Will Utilities Meet the Challenge of Deregulation and Competition

Unit 6 DCSUnit 7 DCSUnit 8 DCS Westation JOPN16 API Node JOPN78 PI Server JOPH01 PMAX & FactNet Node JOPX01 Client PC’s Station LAN -Company WANComEd Typical Fossil GeneratingStationBusinessInformationSystemLayoutComEd GeneratingStationBusinessInformationSystemLayout

Client Applications Adhoc Applications –PI ProcessBook –PI DataLink in Excel Prepared Applications –DataMine Performance Analysis –Generation Commercial Management (GCM) –Operations Information (OI) using PMAX –FactNet Sensor Analysis

Thermal Performance Analysis Using PMAX, PI and Excel

Thermal Modeling Utilize PMAX to construct thermal models of all fossil units Perform efficiency calculations –Unit cost of generation –Turbine heat rate –Boiler efficiency –Net unit heat rate –Controllable costs

Controllable Costs Throttle Temperature and Pressure Hot RH Temperature RH Pressure Drop RH Attemperation Flow Turbine Condition Condenser Performance Feedwater Heater Cycle Auxiliary Power

Controllable Costs Station Heating Steam and Water Losses Sootblowing Flow Air preheating Flow Blowdown Boiler Excess Air Excess Stack Temperature Coal Moisture Unburned Carbon in Ash

Historical Data is Valuable Determine largest cost drivers –Utilize Excel with a PI add-in tool –Generate scatter plots Help determine root causes Make recommendations to plant –Process Improvements –Capital Improvements

Heat Rate Deviation Reconciliation Construct Scatter Plots for ALL Controllable Costs Reconciliation at 300 MW –Condenser Performance BTU/KWh –Steam & Water Loss BTU/KWh –Sootblowing BTU/KWh –Throttle Temperature 0-40 BTU/KWh –Stack Loss 0-30 BTU/KWh

Data Validation and MORE Cost Monitoring Input Data Must Be Validated (PMAX Inputs) Selected Monitor Outputs Also Need Validation Sensor and Process Deviations Must Be Identified and Timely Corrective Action Taken Knowledge of Proper System Operation MUST Be Leveraged Automated Monitoring and Data Reduction Allows Station Staff to do MORE with LESS

Pattern Recognition Software Tool Chosen: –FactNet from Pacific Simulation Multi-year Development History Excellent Model Construction User Interface Flexible PI Interface Capabilities Proven Implementation Capabilities in Process Industry

FactNet Modeling DIVIDE AND CONQUER Generating Units have Analog Points Separate Whole Unit into System/Sub-System Blocks Individual Blocks May Have UP TO 127 Sensed Data Points Historical Data for Model Construction –Sampled Evenly –Over Operating Range –Encompass 1 Year –Up to 16,000 Snapshots

FactNet Modeling Building a Process Model Input-Output Identification Dataset Conditioning –Min / Max –Suspect Data

FactNet Modeling Building a Process Model Correlation Matrix Factor Extraction

FactNet Modeling Model Validation Factor Strength Inspection Factor Network Simulator

FactNet Modeling Model Testing / Production Run Model Interactively –Correct Operation –Expected Results Add Model to FactNet Production Server Meet with Station for Rollout

FactNet Modeling Current End User Toolset On-Demand Reporting in MS Excel Configurable Timespan Worksheet Tabs for Each System Model Drives Sensor Maintenance

FactNet Modeling Preliminary Results Model Implementation Identifies Vibration Problem on Turbine Generator Condenser Performance Issue Confirmed and Effect Minimized Sensor Dropouts Identified and Maintenance Implemented Abnormal Process Values Highlighted and Investigation In-Progress

FactNet Modeling Future Directions Improved Input Validation for PMAX Performance Monitor Cost Outputs NOx Modeling and Reduction Activity Recommendations Boiler Cleanliness Modeling

Thanks from Jerry and Frank Questions