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The Use of PI at International Power

Regional Seminar Series. The Use of PI at International Power. Lee Kean Senior Business Analyst International Power PLC. 5 th October 2009. Agenda. Introduction to International Power How PI is used Value derived from having PI “Plain Vanilla” PI

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The Use of PI at International Power

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  1. Regional Seminar Series The Use of PI at International Power Lee Kean Senior Business Analyst International Power PLC 5th October 2009

  2. Agenda • Introduction to International Power • How PI is used • Value derived from having PI • “Plain Vanilla” PI • Data source for “added value applications” • Real Time Integration with “core applications” • Making a success of your investment • Conclusion • One final tip • Questions

  3. Who Do I Work For? www.ipplc.com

  4. What we do?

  5. IPR’s Capability 33GW • IPR is a leading independent power generator • 33.2GW (21.4GW net) capacity in operation • 3.3GW (988MW net) under construction.

  6. IPR’s Assets 2 OIL 1430MW GROSS

  7. IPR’s Assets 3 HYDRO 2176MW GROSS

  8. IPR’s Assets 7 COAL 7012MW GROSS

  9. IPR’s Assets 32 GAS 24.5GW GROSS

  10. IPR’s Assets +800 Wind Turbines 1265MW GROSS

  11. Portfolio Approach • Risk mitigation across 5 core regions with fuel diversity • • Balance of contracted and merchant markets • • Access to growth opportunities - Greenfield & acquisitions

  12. Where is PI Used?

  13. How is PI Used?

  14. How do we use PI? Data historians are typically used to support the following key processes Real ime Graphical & Trend Displays Pattern Recognition and Anomaly Detection Trading Alert Notifications Condition Based Maintenance Operational Shift Logging Online Plant Performance Monitoring

  15. How do we use PI? Data historians are typically used to support the following key processes Real ime Plant Capacity Analysis Under Performance Investigation Dispute Resolution Process Analysis & Optimisation Failure Analysis

  16. How do we use PI? Data historians are typically used to support the following key processes Real ime Environmental Reporting Settlement Calculation (Invoicing) Efficiency Monitoring Reliability Monitoring Management Reporting (KPI’s) Plant Degradation Analysis Key Asset Performance Monitoring

  17. How do we use PI? Data historians are typically used to support the following key processes Real ime Final Settlement Calculation & Invoicing Outage Planning Plant Capability Projections Generate Plant Production Profiles

  18. Value Derived – “Plain Vanilla PI”

  19. “Plain Vanilla PI” – Case Study 1 Commissioning New Gas Fired Station • Plant Operators identified over sensitive steam attemperation control • Proved to equipment supplier using historical data in PI • Equipment supplier refurbished valves valued at $240 000 • Cost of un-planned outage avoided • PI had been installed for only a few months

  20. “Plain Vanilla PI” – Case Study 2 Commissioning New Gas Fired Station • A Plant Operator proved Inlet Guide Vanes (IGV) positioning on one unit had drifted 1% over a 3 month period • A sustained loss of plant performance • Equipment supplier rectified the mechanical fault in the linkage of the IGV’s. • PI had only been installed for a few months.

  21. “Plain Vanilla PI” – Case Study 3 Hydro Pumped Storage Optimising Plant Operations

  22. Derived Value - Data source for “added value applications”

  23. PI as Data Source: Case Study 1 Thermal Performance Monitoring • Proved to gas supplier that gas flow measurements were incorrect • Gas supplier reimbursed > £1million

  24. PI as Data Source: Case Study 2 Gas Turbine Fleet EOH Monitoring / Outage Planning • Issue • Planning production and outages • Communication • Operations • Maintenance • Fleet Outage Group • Trading • Finance • Solution • PI Data & Trading Data • PI Tags, PI Processbook, PI-ACE, Rt Web Parts

  25. PI as Data Source: Case Study 2 Fleet View Point

  26. PI as Data Source: Case Study 2 Unit View Point

  27. Derived Value – Real Time Integration with “core” applications

  28. Real Time Integration – Case Study 1 • Operational Shift Logging – Aims • Provide a flexible and configurable solution for recording, and reporting on significant plant events • Improve the quality, consistency and search-ability of information • Simplify ad hoc reporting tools

  29. Real Time Integration – Case Study 1 • Operational Shift Logging – Benefits • Provides a single focal point for plant data • Reduces the number of independent reports • Releases users from repetitive logging of plant state changes by automatically importing PI data

  30. Real Time Integration – Case Study 1 Operational Shift Logging – Plant Overview RT Web Parts are used within a SharePoint environment to provide a common overview of the plants key performance indices to the operations team.

  31. Real Time Integration – Case Study 1 Operational Shift Logging – Plant Status Similarly PI Processbook, Datalink and RT Web Parts used to allow operators to record and display the status of the plant in place of a traditional white board

  32. Real Time Integration – Case Study 1 Operational Shift Logging – Automated Entries PI digital tag changes are used to trigger automated event entries within predefined operator logs

  33. Real Time Integration – Case Study 2 • Condition Based Maintenance • Aims • Optimise Maintenance Effectiveness by: • Changing planned maintenance intervals: • From “time” based (e.g. every 3 months) • To “condition” based (e.g. every 2000 running hours) • Benefits • 1 plant reduced boiler maintenance costs by $120 000pa

  34. Real Time Integration – Case Study 2 PI Server(s) Maximo PIMax Software Interface Maximo Meter Physical Equipment Asset • Additional Properties include: • Early Warning • Generate Work Order in advance Meter 1234 hrs • Examples: • Running Hours • No of Starts • No of Trips • Example Limits: • 1000 Hours • 50 Starts • 10 Trips PM

  35. Making a success of your investment • Needs management support • Requires a culture change • Needs appointed “PI Champions” • Install before commissioning • Annual user meetings: • Internal • OSIsoft Conferences

  36. Conclusion • PI is a functionality rich product with excellent support • Has huge potential for obtaining benefits • Cost savings • Maximising Income • Managing risks • To get value from it • Needs management support • Requires a culture change • Needs appointed “PI Champions”

  37. One Final Tip To err is human, but to really mess things up requires a computer

  38. Questions Further questions, contact me on Linked In

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