Risk Based Maintenance Scheduling of Circuit Breakers using Condition-Based Data

ERCPS

Risk Based Maintenance Scheduling of Circuit

Breakers using Condition-Based Data

Satish Natti

Graduate Student, TAMU

Advisor: Dr. Mladen Kezunovic

ERCPS

IAB Meeting, Dec. 4-5, 2008

ERCPS

Outline

• Introduction• CB Monitoring• Maintenance Quantification Model• Risk Based Maintenance Approach• Case Studies• Summary of Achievements


ERCPSIntroduction:Problem Formulation

• If it is the same availability of the labor crew, and the labor hours, and the given budget is constrained, how the maintenance decisions need to be implemented (revised)?

• Develop:

- Maintenance quantification model

- component level maintenance strategy

- system level maintenance strategy

• Apply the developments to:

- individual circuit breakers

- Multiple circuit breakers in a power system simultaneouslyIAB Meeting, Dec. 4-5, 2008

ERCPSIntroduction:Comparison of Existing and Proposed

Researches

Operationdecision

Maintenance Strategies

Quantification of maintenance

Condition-based Data

RCM, AMP, Risk-based, RCAM

Failure rate, Probabilistic maintenance

Models

Risk-based decision approach

Probabilistic approach via performance indices


ERCPSIntroduction:

Expected Contribution

8 10 12 14 16 18 20 0 0.05 0.1

0.15 0.2

0.25 0.3

0.35 Probability Between Limits is 0.94016

De

nsi

ty

Critical Value Lower Upper (msec)

ERCPSCB Monitoring

• Operating Mechanism

- Contact Travel time Measurement

- Control Circuit Monitoring- Vibration Analysis

• Contacts

- Resistance Test

- Temperature Monitoring

• Inspection of oil (oil circuit breakers)• Partial Discharge

Over view of monitoring choices:


ERCPSCB Monitoring: Data from CBMs

ControlDC +

Control DC _

52 TC

CC

52

Close Initiate

Trip Initiate

52a

52Y/a 52a

52Y/b

52X/a

52Y/b

X

Y CBM

PortableDevices



EVENTEVENT EVENT DECRIPTIONEVENT DECRIPTION SIGNALSIGNAL

11 Trip or close operation is initiated (Trip or close Trip or close operation is initiated (Trip or close initiate signal changes from LOW to HIGH)initiate signal changes from LOW to HIGH)

T1T1

22 Coil current picks upCoil current picks up T2T2

33 Coil current dips after saturationCoil current dips after saturation T3T3

44 Coil current drops offCoil current drops off T4T4

55 B contact breaks or makes (a change of status B contact breaks or makes (a change of status from LOW to HIGH or vice versa)from LOW to HIGH or vice versa)

T5T5

66 A contact breaks or makesA contact breaks or makes T6T6

77 Phase currents breaks or makesPhase currents breaks or makes T7T7

88 X coil current picks upX coil current picks up T8T8

99 X coil current drops offX coil current drops off T9T9

1010 Y coil current picks upY coil current picks up T10T10

Waveform abnormalities and signal parameters



Manufacturer and Type: GE VIB-15.5-20000-2

Date T2 (sec) T3(sec) T4(sec) T5(sec) T6(sec)

2/12/2002 0.001215 0.010417 0.028993 0.056597 0.0668402/12/2002 0.000868 0.012500 0.032639 0.058160 0.0682292/13/2002 0.001042 0.014236 0.048785 0.055903 0.0664932/13/2002 0.001736 0.011979 0.043229 0.052951 0.0661462/19/2002 0.001389 0.017361 0.037500 0.059896 0.0078132/21/2002 0.003819 0.004861 0.034375 0.056424 0.067535

6/11/2002 0.001736 0.011285 0.032292 0.063542 0.0729176/11/2002 0.000868 0.014236 0.031076 0.063021 0.0725696/11/2002 0.000694 0.010243 0.032465 0.060590 0.0708336/11/2002 0.000694 0.013889 0.032639 0.061458 0.0704866/11/2002 0.001042 0.011111 0.048958 0.057118 0.068056

Summary of Test Records During Closing Operation of Circuit Breaker

ERCPSMaintenance Quantification Model

8 10 12 14 16 18 20 0 0.05 0.1

0.15 0.2

0.25 0.3


De

nsi

ty


-4 -2 0 2 4 6 80

0.1

0.2

t1 (msec)

0 5 10 15 20 25 300

0.05

0.1

t2 (msec)

10 20 30 40 50 600

0.02

0.04

0.06

t3 (msec)

45 50 55 60 65 700

0.05

0.1

t4 (msec)

55 60 65 70 75 800

0.05

0.1

t5 (msec)

History of control

circuit signals

Extract signal parameters

(T1-T10) and fit distribution to each

parameter

Define performance indices using parameter

distributions

Bayesian approach to update parameter

distribution

Monitored control

circuit data

ERCPSAssessment of CB Condition

• P(ti) is defined as the probability that the parameter ti falls in the predefined interval, and is given by

• As long as the parameter ‘ti’ falls in the specified interval, it is said that there is no violation with ‘ti’.

8 10 12 14 16 18 20 0 0.05 0.1

0.15 0.2

0.25 0.3


De

nsity


pi

)Pr()( iiii utltp

ERCPSPerformance Indices

)()()(1)CC( 432 tptptpp f

)()(1)( 32 tptpFTp f

)()(1)AB( 65 tptpp f

)()(1)MT( 53 tptpp f

6

2

)(1)Br(i

if tpp

ERCPS

Bayesian Updating Approach


ERCPSSequential Bayesian Approach

y1

P(θ|Y)

π0

Data PosteriorPriorLikelihood

yn

L(Y)

P (θ| y1)π0

Data PosteriorPriorLikelihood

y1L(y1)

P (θ| yn)

y2L(y2)

ynL(yn)

P (θ| y2)

Bayesian

Sequential Bayesian


ERCPSConcept of Risk


ERCPS

Optimized problem formulation

Where,

iorxCxcST

xRMax

N

iii

N

iii

10:0

1

budget Total:

i''breaker maintaningby reduction Risk :

i''breaker ofcost eMaintenanc:

breakers ofnumber Total :

breakeronindex:

C

R

c

N

i

i

i

This optimization problem is a standard Knap-sack problem and can be solved using dynamic programming techniques

ERCPS

Case Studies

Category Case study # Details of the data

Maintenance Quantification Model

Case study I CB control circuit data during OPEN operation

Case study II CB control circuit data during CLOSE operation

Case study III Approximation to the Bayesian approach in case studies I & II

Risk based maintenance Optimization

Case study IV Bus 16 of IEEE Reliability Test System

List of case studies


ERCPS

Case Study I: Open Operation

• The sequence of occurrence of timing of parameters during opening is: t2-t3-t6-t4-t5. Rename them as y1-y5 in that order

• y1, y2 and y3 can be treated as independent.

• y4=β0+β1y3+ε4

• y5 = β0 + β1y3 + β2y4+ ε5

Scatter plot analysis of timing parameters

Tolerance Limits for Open Operation

Event Lower(msec)

Upper(msec)

t2 0 2

t3 13.6 18.6

t4 26.4 35.4

t5 28.7 38.7

t6 22.4 32.4


ERCPS

Case Study I: Open Operation

Performance indices for CB opening

Summary of Analysis for Open Operation

PerformanceIndex

Observations Maintenance required?

pf(TC) Abnormal behavior of trip coil current.

Yes

pf(AB) Auxiliary contacts are operating properly

No

pf(FT) Abnormal free travel times. Improper operation of trip latch mechanism

Yes

pf(MT) Abnormal mechanism travel times. Improper operation of operating mechanism.

Yes

pf(Br) Improper operation of breaker as a whole

Yes


ERCPS

Case Study II: Close Operation

• The sequence of occurrence of timing of parameters during opening is: t2-t3-t4-t5-t6. Rename them as y1-y5 in that order

• y1, y2, y3 and y4 can be treated as independent.

• y5=β0+β1y4+ε5.

Scatter plot analysis of timing parameters

Tolerance Limits for Close Operation

Event Lower(msec)

Upper(msec)

t2 0 5.5t3 9.8 16.4t4 26 43.4t5 49.9 67.5t6 62 75.8


ERCPS

Case Study II: Close Operation

Summary of Analysis for Close Operation

Performance indices for CB closing

PerformanceIndex

Observations Maintenance required?

pf(CC) Abnormal behavior of close coil current.

Yes

pf(AB) Auxiliary contacts are operating properly.

No

pf(FT) Abnormal free travel times. Improper operation of close latch mechanism.

Yes

pf(MT) Abnormal mechanism travel times. Improper operation of operating mechanism.

Yes

pf(Br) Improper operation of breaker as a whole.

Yes


ERCPSCase Study III: Comparison

CB opening

CB closing

Comparison of index pf(Br) between Bayesian and

Sequential Bayesian approaches

ERCPSCase Study IV:

Risk Based System Maintenance

• IEEE 24 bus RTS is considered

• Generator = 155MW and Load = 100MW

• 8 breakers (B1-B8)

• Which breaker needs immediate attention?

• How to spend a fixed pool of money towards the maintenance of these breakers?

Substation configuration of bus 16IAB Meeting, Dec. 4-5, 2008

ERCPSCase Study IV: List of Events

EventEvent ##

DefinitionDefinitionEventEvent

##DefinitionDefinition

EventEvent ##

DefinitionDefinition

E1 Fault on BB1 E15 Fault on L28 E29 Fault on B2, B3 fails

E2 Fault on BB1, B1 fails E16 Fault on L28, B5 fails E30 Fault on B3

E3 Fault on BB1, B4 fails E17 Fault on L28, B6 fails E31 Fault on B3, B6 fails

E4 Fault on BB1, B7 fails E18 Fault on L29 E32 Fault on B3, B8 fails

E5 Fault on BB2 E19 Fault on L29, B2 fails E33 Fault on B4

E6 Fault on BB2, B3 fails E20 Fault on L29, B3 fails E34 Fault on B4, B5 fails

E7 Fault on BB2, B6 fails E21 Fault on G E35 Fault on B4, B7 fails

E8 Fault on BB2, B8 fails E22 Fault on G, B7 fails E36 Fault on B5

E9 Fault on L23 E23 Fault on G, B8 fails E37 Fault on B5, B6 fails

E10 Fault on L23, B1 fails E24 Fault on B1 E38 Fault on B6

E11 Fault on L23, B2 fails E25 Fault on B1, B2 fails E39 Fault on B6, B8 fails

E12 Fault on L24 E26 Fault on B1, B4 fails E40 Fault on B7

E13 Fault on L24, B4 fails E27 Fault on B1, B7 fails E41 Fault on B7, B8 fails

E14 Fault on L24, B5 fails E28 Fault on B2 E42 Fault on B8


ERCPS

Case Study IV: Event Risk

Risk curvesRisk associated with each

event and breaker


ERCPSCase Study IV: Risk Reduction

Interesting to note that, the amount of risk reduced by maintaining B6 is less compared to B3 and B8

B3 and B8 should be given priority based on the risk reduction levels 0

2000

4000

6000

8000

10000

12000

14000

16000

18000

Ris

k R

edu

ctio

n

1 4 7 10 13 16 19 22 25 28 31 34 37 40

Event

For the test system under consideration, it can be concluded For the test system under consideration, it can be concluded that, breakers B3 and B8 are more important followed by B6 that, breakers B3 and B8 are more important followed by B6 and should be given priority in budget allocationand should be given priority in budget allocation

)()()( EConEpERisk

ERCPS

Summary of Achievements

• A probabilistic methodology, ‘Maintenance Quantification Model’ is proposed and implemented

• An approximation to the Bayesian approach, called Sequential Bayesian approach is implemented

• Risk based system level maintenance strategy is proposed and implemented


ERCPS

Financial Support

Power Systems Engineering Research Center (Pserc), Project:

“Automated Integration of Condition Monitoring with an Optimized Maintenance Scheduler for Circuit Breakers and Power Transformers”.

Iowa State University: James D. McCalley

Vasant Honavar

Texas A&M University: Mladen Kezunovic

Chanan Singh


ERCPS

Publications

• S. Natti and M. Kezunovic, “Assessing Circuit Breaker Performance Using Condition-Based Data and Bayesian Approach”, IEEE Trans. On Power Systems. (In Review).

• S. Natti and M. Kezunovic, “Risk-Based Decision Approach for Maintenance Scheduling Strategies for Transmission System Equipment Maintenance”, 10th Int. Conference on Probabilistic Methods Applied to Power Systems, Rincon, Puerto Rico, May 2008.

• M. Kezunovic, E. Akleman, M. Knezev, O. Gonan and S. Natti, “Optimized Fault Location”, IREP Symposium 2007, Charleston, South Carolina, August 2007.

• S. Natti and M. Kezunovic, “Model for Quantifying the Effect of Circuit Breaker Maintenance Using Condition-Based Data”, Power Tech 2007, Lausanne, Switzerland, July 2007.

ERCPS• S. Natti and M. Kezunovic, “Transmission System Equipment Maintenance: On-line

Use of Circuit Breaker Condition Data”, IEEE PES General Meeting, Tampa, Florida, June 2007.

• M. Kezunovic and S. Natti, “Risk-Based Maintenance Approach: A Case of Circuit Breaker Condition Based Monitoring”, 3rd International CIGRE Workshop on Liberalization and Modernization of Power Systems, Irkutsk, Russia, August 2006.

• M. Kezunovic and S. Natti, “Condition Monitoring and Diagnostics Using Operational and Non-operational Data”, CMD 2006, Pusan, Korea, March 2006.

• S. Natti, M. Kezunovic and C. Singh, “Sensitivity Analysis on Probabilistic Maintenance Model of Circuit Breaker”, 9th Int. Conference on Probabilistic Methods Applied to Power Systems, Stockholm, Sweden, June 11-15, 2006.

• S. Natti, P. Jirutitijaroen, M. Kezunovic and C. Singh, “Circuit Breaker and Transformer Inspection and Maintenance: Probabilistic Models”, 8th Int. Conference on Probabilistic Methods Applied to Power Systems, Ames, Iowa, September 2004.

Documents

Risk Based Maintenance Scheduling of Circuit Breakers using Condition-Based Data