decision support with pi

TXU Energy OSI PI User’s Group Mar 2002

Decision Support with PI

Decision Support

With PI



PI System

• Fleet Wide Installation Review

• Lessons Learned

• Near Real Time Decision Support



TXU is one of the largest investor-owned energy services companies in the world with assets over $40 billion. The company is a multinational leader in electric and natural gas services, merchant trading, energy marketing, telecommunications and other energy-related services. TXU delivers energy to more than nine million customers primarily in Texas, the United Kingdom and continental Europe, and Australia.



Senate Bill 7 Impacts to Generation

• 50% reduction in NOx, 25% reduction in SO2 - for existing “grandfathered” electric generating facilities.

• Additionally, because of the proposed State Implementation Plan under the Federal Clean Air Act, TXU Electric plans to achieve an 88% reduction in NOx production from 1997 levels in the Dallas-Fort Worth non-attainment area.



The Need:

A System for Real Time NOx and SO2 Monitoring, Tracking, Alarming, Reporting and Optimization for all TXU Generating

Units at the Unit Level, Area/Region Level, and TXU System Level



NCMS - NOx Compliance Management SystemScope

•Control System Modifications for Data Access

•Plant Historian

•Accurate Heat Input

•Additional Instrumentation

•Advanced Emissions Controls



NCMS - NOx Compliance Management SystemInterface Requirements

•Foxboro IA

•Honeywell TDC3000

•Bailey Infi90/Net90

•Allen Bradley PLC

•Modbus - Smart Instrumentation



PI System

Exact duplicate machines. Dell 4300 servers.

22 servers at plant sites,

1 corporate data collector,

1 training/development server.



•Summer 1999 - Evaluation

•Trial complete 7/99

•Project funding requested 8/99

•Hardware/Software ordered 9/99

•18 Servers installed collecting from CEM PLCs and 14 control systems by 10/31/99



LESSONS LEARNED

• Duplication/Training

• Centralized Control of Servers

• Centralized Subject Matter Expert(s)

• Active Project Owner

• Tech Support vs Integrator

• IT



CURRENT STATUS

• NOx Bubble Management

• Advanced Emission Controls

• Cap Management

• Decision Support



NOX BUBBLE



ADVANCED EMISSIONS CONTROLS

• Software based optimization

• Pilots in progress



CAP MANAGEMENT (NOx)

• DFW Zonal Daily Tonnage Cap

• DFW Zonal Monthly Tonnage Cap

• East Region Annual Cap (Jan-Dec)

• West Region SIP Annual Cap (May-Apr)

• East Region SIP Annual Cap (May-Apr)



• Availability

• Reliability

• Performance

There are many inherent risks with the operation of Assets. Some of these are easily quantifiable, some are complex and some are just unexplainable. The operational risks associated with assets include availability, reliability and performance.

Availability and reliability are typically trends that can be predictably quantified using recent historical information. Performance is a moving target influenced by a variety of issues, some controllable and some not.

There are Operational Risks with Assets



• 80 – 90% of the cost basis is directly affected by performance

Performance information is utilized in budgeting, strategic planning, unit commitment, fuel acquisition, risk valuation, benchmarking, emissions management and unit dispatching, among others. The issue of concern is that performance measuring information is usually acquired under the best possible conditions, at infrequent intervals, and does not necessarily project current operations. The ability to accurately track and predict performance characteristics increases the accuracy of, and reduces the risk of, all facets of the planning, analysis and delivery process.

Performance information is the cornerstone for the decision making process



Performance characteristics include :

• Fuel Efficiency - known as heat rate and is measured in btu(of fuel) per kwh (of power produced).

• Emission Rates – typically measured in pounds per mmbtu heat input to the boiler. Cap limits are aggregated emissions over time.

• Unit operating ranges and ramp rates.

• Unit startups.

• Ancillary Services

Performance can change over time. Sometimes quite rapidly.



Performance can be affected by a number of influences including:

• Sudden equipment health issues.

• Fuel quality and quantity.

• Weather.

• Environmental influences including emissions, lake conditions and wildlife.

• Mode of Operation (AGC)

• Control Operator Influences.

Longer term influences can include normal wear and tear and unit operational excursions.



• Acquire

• Verify

• Process

• Disseminate

The Process of acquiring, verifying, processing and disseminating asset performance information in near real time provides instantaneous feedback to the decision making teams and engines that are continually optimizing and maximizing net portfolio positions. Although current optimization tools require static curves, near real time bias of the curves can more closely approximate real unit operations.

Real Time Process information can be used to optimize decision making routines.



SUMMARY

• Near Real-time

• Risk Support

• Benchmarking

• Operational Enhancements

decision support with pi

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