WEC Workshop on the Performance of Generating Plant 18 March 2009, Cairo, Egypt

1. WEC Workshop on the Performance of Generating Plant18 March 2009, Cairo, Egypt Benchmarking with PGP Database G. Michael Curley, WG#2 Chair

2. Why Collect Power Plant Data? “Business today is awash in data and data crunchers but only a few companies have transformed this technology into a strategic weapon. Their ability to collect, analyze and act on data is the essence of their competitive advantage. These top companies are outsmarting and outmaneuvering the competition because they made information analysis and management a distinctive capability, one that is fundamental to their formula for doing business.” (Wall Street Journal April 2006.)

3. Why Collect Power Plant Data? Electric energy is a key factor to make the world a better place for all. We need more power and fewer green-house gases. US$80 Billion could be realized by the owners of plants in the top 25% of their category. In addition, a reduction of over 1 billion tons of CO2 plus proportional reductions of other pollutants would be realized at no extra costs. If we learn from each other and share information on power plant problems, then we can help the people we serve live a more productive life.

4. Two PGP Working Group #2 Objective: 1-Provide a benchmarking tool based on design & performance. 2-Help set realistic goals for power production.

5. World Energy Council PGP Update Performance of Generating Plant (PGP) created a database similar to NERC pc-GAR over the last several years. Presented PGP database to WEC at Rome Congress in November 2007 Updated in March 2009 with all 2007 North American data.

6. Why Use GADS as the Example? GADS has been collecting data for North American since 1982. 750,000+ MW in GADS; about 75% of the installed capacity of the USA 5,300+ generating units report annually. 11 million equipment outage events in GADS Pc-GAR takes the GADS histories and allows users to benchmark their own units against all others in GADS while keeping the data confidential! Pc-GAR is more detailed than PGP.

7. Unit Types in PGP Database Fossil-steam turbine Combined cycle blocks Co-generation blocks Gas turbines Diesel (internal combustion) engines Hydro Pumped storage units

8. What’s in the New PGP Database? Design data include: Steam pressures MW sizes Some environmental equipment Other basic boiler and turbine design data Annual unit performance summaries include: Number of actual starts Number of operating hours Number of unplanned outage incidents

9. KPI Calculated by Database Energy Availability Factor (EAF) Unit Capability Factor (UCF) Unplanned Capability Loss Factor (UCLF) Planned Capacity Loss Factor (PCLF) Load Factor (LF)

10. Benchmarking Research on Specific Fossil Units Suppose that you operate a controlled circulation, coal-fired fossil steam unit. The unit has a reference capacity of 350 MW. The furnace is balanced-draft. This unit’s EAF is 83.3%. Where does this unit fit within its peer group? Using the new PGP database, you can search the database using the following criteria: Fossil-steam units Circulation type: controlled Fuel: coal MW size between 250 and 450 MW Draft:  Balanced draft. Study period: 2003-2007. The study resulted in 59 units.

11. Adding Performance Criteria Suppose that the unit is base-loaded? What is “base-loaded” to you? Suppose that a base-loaded units is any unit with more than 4,000 hours of operation per year. By adding a filter to look at units with 6,000 to 7,500 hours of operation, the number of units is now, 50 units!

12. Benchmarking Results:

13. PGP Needs Your Data! Country “C” Country “D” Country “B” WEC PGP Country “A” Country “E” We encourage all WEC members to visit the WEC PGP website and support our new database by providing unit-by-unit data.

14. Questions?