PI-BASED PERFORMANCE MONITORING SYSTEM FOR COMBINED CYCLE POWER GENERATION TECHNOLGY4/21/2004

2004 OSI UC 2

About Calpine

Founded in 1984

Headquartered in San Jose, Calif.

Calpine has 87 energy centers in 21 states in the U.S., as well as in Canada and the United Kingdom with a total capacity of about 22,000 megawatts

Uses clean, proven technologies: natural gas combined-cycle and geothermal energy

2004 OSI UC 3

A Large Portfolio

Calpine offices Boston, MA

Calgary, Canada

Dublin, CA

Ft. Collins, CO

Houston, TX

Jupiter, FL

Northbrook, IL

Portland, OR

Tampa, FL

Folsom, CA

Corporate headquarters

San Jose, CA

As of 4/21/2003

2004 OSI UC 4

Growth History

Calpine Growth History

0

5000

10000

15000

20000

25000

30000

2000 2001 2002 2003 2004

Fle

et C

apac

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- M

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40

60

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120

Pla

nts

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ion

Fleet Capacity - MW Plants in Operation

2004 OSI UC 5

Performance

Monitoring Necessity

Large, regionally diverse fleet requires central performance monitoring to provide

the following;

Standard fleet reporting/comparison

Operational benchmarking

Asset improvement and degradation quantification

Value

Economic decisions based on operating performance data

Internal knowledge and understanding of equipment

Efficient and reliable operation

2004 OSI UC 6

Why Use PI?

Calpine chose to use OSI-PI as the foundation for our Performance Monitoring System

Existing PI infrastructure eliminated additional capital expense

Internal reliance and control

PI provides all the required functional components of 3rd party systems

Development team and end-users already familiar with PI tools/systems

Value

Zero additional capital cost associated with PI

Zero new training

Zero external reliance

Zero risk

2004 OSI UC 7

 

Overview of Calpine PI network

PI Performance Equations

PI Process Book as GUI

PI Datalink and Excel employed as on-line QC

Consumable Products

Wholesale Energy Products

Retail Power

Renewable Energy

PERFORMANCE

MONITORING SYSTEM

ARCHITECTURE

2004 OSI UC 8

Calpine PI

Infrastructure

PI at Calpine

Calpine standardized on PI as their operations historian in early 2001

PI is installed at 86 of Calpine’s 89 generating facilities

The fleet PI infrastructure consists of 62 production PI servers and 24 PI API nodes

Calpine PI data for every site is available remotely to every Calpine employee, from plant personnel to executive management, because all Calpine PI systems are connected to the Calpine WAN

2004 OSI UC 9

2004 OSI UC 10

PI Performance

Equations

PI Performance Equation Subsystem used as backbone to calculate performance data

Average of 350 Performance Equations per site constructed by Calpine Performance Engineers

Calculations based on standard calculations as well as plant specific calculations

Daily averaging functions used to easier identify performance trends and create summary

reporting

2004 OSI UC 11

PI Process Book as

GUI

PI Process Book used to view raw and calculated performance data

13 Monitoring Displays and 14 Trend Displays

Multiple individual PDI files used as opposed to a single PIW file

Navigation created using VB Code

2004 OSI UC 12

C O M P OU N D A N N U A L G R O W T H R A T E

1 9 9 7 T O 2 0 0 2

2004 OSI UC 13

2004 OSI UC 14

PI Datalink as On-

Line Quality Control

Data Quality Critical

PI Datalink used to ensure data integrity

Standard statistical evaluation of data used to evaluate data integrity

PI Datalink used to summarize data and draw conclusions

2004 OSI UC 15

 

Text Based Filtering in Performance Equations

Getting the Most out of the Performance Equation Subsystem

Correction Calculation Challenges

TECHNICAL CHALLENGES

2004 OSI UC 16

Text Based Filtering

Identified a need to display why corrections were not being applied

Solution must not affect summary data

Early solution was to display “-1” when corrections not applied

2004 OSI UC 17

2004 OSI UC 18

Text Based Filtering

Solution

Final solution was to display text when corrections not applied

Text to be used in the tags must be present in the “System” Digital Set within the PI System

Text is not taken into account when summary equations are applied

2004 OSI UC 19

2004 OSI UC 20

Maintaining the PI-PE

Subsystem

Found that 200 calculations is the approximate limit for a Performance Equation Scheduler

Set up multiple schedulers to spread the load

With the number of equations, and the complexity of the equations, Performance Equation

Schedulers would fail from time to time

Set up Performance Equation Schedulers to be restarted regularly to minimize impact.

Used 3rd Party Software to notify when calculations are experiencing issues

2004 OSI UC 21

Technical

Challenges

The Challenges

• Site instrumentation errors / lack of site instrumentation

• Each plant uses different tag naming conventions

• PI was originally configured primarily as a Data Historian – PI tags typically have various levels of compression and exception enabled

• Gas Turbine based performance indicators vary drastically with load and ambient conditions

The Solutions

• Correction, re-calibration, procurement of critical site instrumentation

• Standard PI tag naming convention applied to primary site tags (fuel, power, ambient conditions)

• PI compression and exception removed on critical performance tags – filtering applied where required

• Load Normalization

• Apply OEM ambient corrections at normalized (base) load

• Use PI-based text substitution to allow functional averaging and Process Book trending

2004 OSI UC 22

  Performance Trend of

CTG Corrected MW

2004 OSI UC 23

Value Realization

Value

Eliminate dedicated on-site test personnel and temporary test instrumentation – Estimated savings of $200K annually

Accurate recoverable degradation data allows the sites to optimize CTG water washing based on market conditions

In a low spark spread market, every optimization opportunity can significantly contribute to Calpine’s profitability

Examples Use PI based Performance Monitoring to conduct DWR

contractual annual capacity tests on (15) simple cycle peakers in CA

Quantify recoverable CTG degradation by analyzing pre and post offline water wash performance

Remote monitoring identifies operational procedure mispractice and optimizes plant performance

2004 OSI UC 24

Performance

Monitoring System

vs. Performance Test

CALPINE UNIT TEST DATE CONFIGURATION CORR MW - TEST CORR MW - PI DELTA % DELTA MWPeaker 1 3/27/2003 Chiller On - 8 Test Intervals 47.139 47.093 0.098% 0.046Peaker 2 3/18/2003 Chiller On - 8 Test Intervals 48.380 48.305 0.156% 0.076Peaker 3 3/20/2003 Chiller On - 8 Test Intervals 48.042 48.166 0.257% 0.124Peaker 4 3/25/2003 Chiller On - 3 Test Intervals 46.771 46.608 0.348% 0.163Peaker 5 4/2/2003 Chiller On - 1 Test Interval 45.459 45.513 0.118% 0.054AVERAGE Chiller On - Total 14 Hours 47.158 47.137 0.195% 0.092

CALPINE SAMPLE ENERGY CENTER OVERALL PLANT RESULTS Guarantee Test #1 Test #2 Test #3 AVERAGE Delta % DeltaPT - *Plant Corrected Net Pow er (MW) 720.702 724.218 723.020 728.250 725.163Perf Mon - *Plant Corrected Net Pow er (MW) 722.677 721.735 719.409 721.274 3.889 0.54%

PT - *Plant Corrected Net Heat Rate (BTU/kWh-HHV) 7,647 7,605 7,620 7,587 7,604Perf Mon - *Plant Corrected Net Heat Rate (BTU/kWh-HHV) 7,717 7,728 7,765 7,737 132 1.74%

The Performance Monitor calculations fall within the 1% uncertainty band for power and slightly outside the 1.5% uncertainty band for heat rate. This is very good considering that the tests use different instrumentation and the acceptance test uses more measurements and more corrections in their calculations.

Calpine 3 x 1 Combined Cycle Plant Performance Test Results Comparison

Calpine Simple Cycle Peaker Plant Performance Test Results Comparison

2004 OSI UC 25

Performance

Quantification

CTG Inlet D/P - Raw Readings

11/1/2003 12:00:00 AM 3/31/2004 12:00:00 AM151.00 Day(s)

2PDT35104

INWC

3PDT35104

INWC

1

2

3

4

5

6

7

8

9

0

108.0068E-02

1.281E-02

2PDT35104

INWC

3PDT35104

INWC

2004 OSI UC 26

Performance

Quantification

CTG Inlet D/P - Filtered Daily Averages

11/1/2003 12:00:00 AM 3/31/2004 12:00:00 AM151.00 Day(s)

PRT_2CTG1INDP_BL_AVG

INWC

PRT_2CTG2INDP_BL_AVG

INWC

1

2

3

4

5

6

7

8

9

0

10Calc Failed

Calc Failed

PRT_2CTG1INDP_BL_AVG

INWC

PRT_2CTG2INDP_BL_AVG

INWC

2004 OSI UC 27

Performance

Quantification

CTG 1 Water Wash

CTG 2 Water Wash

CTG Corrected MW - Daily Averages

3/1/2004 12:00:00 AM 3/31/2004 12:00:00 AM30.00 Day(s)

PRT_CTG1MWAVG

MW

PRT_CTG2MWAVG

MW

172

174

176

178

180

182

184

186

188

170

190182.59984

182.70833

PRT_CTG1MWAVG

MW

PRT_CTG2MWAVG

MW

CTG 1 Water Wash

CTG 2 Water Wash

2004 OSI UC 28

Performance

Reporting

CALPINE SAMPLE CTG CTG 1TIME CORRECTED MW

DAILY LOG CORR TOTAL TIME AVG CORR MW CORR MW DEVIATION CORR MW DEVIATION (%)PRT_CTG1CORRTIME PRT_CTG1MWAVG PRT_CTG1MWDEV PRT_CTG1MWPCTDEV

DATE / TIME HOURS MW (BASE REF) MW %2/1/04 12:05 AM Not at Base Load Not at Base Load Not at Base Load Not at Base Load2/2/04 12:05 AM 0.07 Under 10 Min at Base Load Under 10 Min at Base Load Under 10 Min at Base Load2/3/04 12:05 AM Not at Base Load Not at Base Load Not at Base Load Not at Base Load2/4/04 12:05 AM Not at Base Load Not at Base Load Not at Base Load Not at Base Load2/5/04 12:05 AM Not at Base Load Not at Base Load Not at Base Load Not at Base Load2/6/04 12:05 AM Not at Base Load Not at Base Load Not at Base Load Not at Base Load2/7/04 12:05 AM Not at Base Load Not at Base Load Not at Base Load Not at Base Load2/8/04 12:05 AM Not at Base Load Not at Base Load Not at Base Load Not at Base Load2/9/04 12:05 AM Not at Base Load Not at Base Load Not at Base Load Not at Base Load2/10/04 12:05 AM 17.33 168.12 2.62 1.562/11/04 12:05 AM 1.02 168.64 1.53 0.912/12/04 12:05 AM 5.63 168.28 2.64 1.572/13/04 12:05 AM 1.52 168.46 1.83 1.092/14/04 12:05 AM 4.28 169.02 5.64 3.342/15/04 12:05 AM Not at Base Load Not at Base Load Not at Base Load Not at Base Load2/16/04 12:05 AM 5.64 168.29 4.19 2.492/17/04 12:05 AM 0.04 Under 10 Min at Base Load Under 10 Min at Base Load Under 10 Min at Base Load2/18/04 12:05 AM 0.03 Under 10 Min at Base Load Under 10 Min at Base Load Under 10 Min at Base Load2/19/04 12:05 AM Not at Base Load Not at Base Load Not at Base Load Not at Base Load2/20/04 12:05 AM 4.15 168.21 2.25 1.342/21/04 12:05 AM 0.09 Under 10 Min at Base Load Under 10 Min at Base Load Under 10 Min at Base Load2/22/04 12:05 AM 9.88 167.96 5.30 3.152/23/04 12:05 AM Not at Base Load Not at Base Load Not at Base Load Not at Base Load2/24/04 12:05 AM Not at Base Load Not at Base Load Not at Base Load Not at Base Load2/25/04 12:05 AM 16.35 167.50 3.65 2.182/26/04 12:05 AM 2.05 167.44 2.26 1.352/27/04 12:05 AM 15.83 167.84 3.80 2.262/28/04 12:05 AM 2.14 168.06 3.19 1.902/29/04 12:05 AM 2.90 167.32 2.19 1.31

TOTAL / AVERAGE 88.95 168.09 3.16 1.88

2004 OSI UC 29

Performance

Reporting

PERFORMANCE MONITOR MONTHLY AVERAGES - CTG 2DESCRIPTION ENG UNITS Nov-03 Dec-03 Jan-04 Feb-04BASE LOAD HOURS HOURS 28.96 13.02 16.71 49.42CORR MW - BASE REF MW 171.72 172.19 170.16 170.57CORR MW - DEVIATION FROM LAST MONTH MW 0.47 -2.03 0.41CORR MW - % DEVIATION FROM LAST MONTH % 0.27% -1.19% 0.24%CORR MW - BENCHMARK ** MW 169.18 169.18 169.18 169.18CORR MW - DEVIATION FROM BENCH MW 2.54 3.01 0.98 1.39CORR MW - % DEVIATION FROM BENCH % 1.50% 1.78% 0.58% 0.82%CORR HR - BASE REF BTU/KWH HHV 10,190 10,308 10,241 10,212CORR HR - DEVIATION FROM LAST MONTH BTU/KWH HHV 118 -67 -29CORR HR - % DEVIATION FROM LAST MONTH % 1.15% -0.66% -0.29%CORR HR - BENCHMARK ** BTU/KWH HHV 10,088 10,088 10,088 10,088CORR HR - DEVIATION FROM BENCH BTU/KWH HHV -102 -220 -153 -124CORR HR - % DEVIATION FROM BENCH % -1.01% -2.18% -1.52% -1.23%CORR MW - ISO MW 177.91 178.39 176.28 176.71CORR HR - ISO BTU/KWH HHV 10,090 10,208 10,141 10,112CTG INLET D/P AT BASE LOAD IN WC 6.64 6.75 6.79 6.92HRSG SCR D/P AT BASE LOAD IN WC 2.10 2.11 2.28 2.31

2004 OSI UC 30

Summary

Calpine is successfully leveraging OSI-PI technology in a Performance Monitoring environment directly resulting in;

Increased plant availability and reliability

Predictive maintenance scheduling

A historical plant performance database that can be used to effectively optimize plant and fleet performance

Better decision support data available to dispatch and trading

INCREASED CALPINE PROFITABILITY !