Edison Mission Energy: PI for the Next Generation (of Generation)

1. Edison Mission Energy:PI for the Next Generation (of Generation) OSI Regional User Conference 10/09/08 Jerry Weber Manager of Operations Support Midwest Generation - EME

2. Our mix of Generation: Thermal • 8 coal-fired plants • 6 in Illinois (MWGen) • 1 in Pennsylvania • 1 in West Virginia • 9 gas-fired plants in California and Washington

3. About Edison Mission Group • A major Independent Power Producer (IPP), headquartered in Irvine, CA • 30 Power Plants, 10,634 megawatts • Energy marketing and trading center in Boston, MA • Sister company to Southern California Edison

4. Wind: our new generation of Generation! • 18 Wind farms in Iowa, Minnesota, New Mexico, Oklahoma, Pennsylvania, Texas and Wyoming. • Projects are pending in Illinois, Maine, Maryland, Nebraska, New York, Pennsylvania, Utah, West Virginia, Wisconsin and Wyoming. • We are one of the fastest growing developers of renewable energy.

5. PI in our Coal Fleet • We have a long and successful history (since mid 1990s) of using PI in our Coal power stations • PI is a vital operations tool • PI is used to: • Collect and archive data from our station control systems • Trending and troubleshooting • Predictive maintenance • Interface with other analysis tools

6. PI is very good at… • Collecting • Archiving • Displaying (OK, we knew that) • Trending • Correlating • Calculating • Make Decisions Tactical Strategic

7. Coal Plant Performance Monitoring Revolves Around PI • PI stores data from control system • Performance tags sent to Pmax • Pmax calculates • Heat Rate • Controllable losses • Boiler and turbine efficiency • Furnace cleanliness • Other performance parameters • Writes data back to PI for trending and storage • Data presented to operations using Process Book

8. PI examples in our Coal Fleet: Superheat and Reheat Furnaces

9. PI examples in our Coal Fleet:Steam Turbines Turbines

10. PI examples in our Coal Fleet: Controllable Loss Summary

11. PI examples in our Coal Fleet:LP Feedwater Heaters

12. PI examples in our Coal Fleet: High Pressure Feedwater Heaters

13. How do we apply this to Wind?

14. Wind Many generation units per site, 1-2.5 MW each All generation units are the same at each site Generation units are relatively simple in design Data sources are few and fairly uniform Major equipment is 200-300 feet in the air! Coal 1-3 generation units per site, 150-850 MW each Generation units are often of a unique design Generation units have multiple complex systems Data sources are many and diverse Major equipment generally in a building Wind and Coal Generation Differences

15. PI and Wind are a good fit • Quick results: For same manufacturer, “Do one, you’ve done them all”, all turbines have the same tag list • Need for monitoring: Wind sites are remote, sometimes un-staffed • Many needs for information: technical, operational, financial • Optimization opportunities: use PI information strategically

16. PI and Wind: our decision and strategy • Embed PI in EVERY Wind project • Became an Enterprise customer

17. Challenge #1:Establish a PI infrastructure design Master PI Server Irvine Wind Site C Wind Site A PI Node PI Node Wind Site B PI Node

18. Challenge #2:The PI – Turbine Tag Marriage The challenge: • We use Wind turbines from multiple manufacturers • Each manufacturer/turbine model has a a unique tag list and nomenclature • Tags must be used to provide common performance monitoring and measurement across multiple turbine types The solution: • A common strategy for tag collection and naming – tag aliasing • PI Module Database • PI ACE

19. Turning data into measurement and management • Calculate various operating parameters • Number of turbines running • Number of turbines in various outage states • Power curve • The generation industry has standard calculations to measure performance, including: • Operating hours, outage hours, low and high wind hours, etc. • Equivalent Availability Factor (EAF) • Net Capacity Factor (NCF) • Net Output Factor (NOF) • Etc • The PI Advanced Computing Engine (PI ACE) combined with the PI Module Database (PI MDB) are being used to develop these and other performance and measurement calculations for our Wind sites. • Project is currently on-going with Global Automation Partners (GAP)

20. Future opportunities:Using pattern recognition Turbine A Generation Wind Speed Temperature Turbine B Generation Wind Speed Temperature Turbine C Generation Wind Speed Temperature

21. Pattern Recognition • Coal and wind units data correlates well and is fairly consistent • What if we could automatically determine when a parameter was abnormal before we experienced an alarm from the control system? • Time to analyze the cause (instrument or process) • Time to schedule maintenance • Reduce unplanned events • Software available to analyze a large PI data sampling to determine patterns and make predictions • Write predicted values to Pi for storage • Automated reporting when parameters are out of limits • Project underway with Scientech - PDP Pattern recognition Software for both Wind and Coal Units