Integration of Asset and Outage Management Tasks for ... · Data ”. IEEE PES 41st North America Power Symposium (NAPS) , Starkville, Mississippi, USA, October, 2009. • Yimai Dong,

Integration of Asset and Outage Management Tasks for Distribution Application

Mladen KezunovicDepartment of Electrical and Computer Engineering

Texas A&M [email protected]

©2010 Mladen Kezunovic, All Rights Reserved

PSERC Webinar, April 13, 2010

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PSERC T-36June 1, 2007~August 31, 2009

• PROJECT TEAM MEMBERS:- Project Lead:

Mladen Kezunovic (TAMU)- Co-PI:

Ward Jewell (WSU)- Participating students

Yimai Dong (TAMU)Visvakumar Aravinthan (WSU)Prasad Dongale (WSU)

• INDUSTRY TEAM MEMBERS:

- Ali Chowdhury (California ISO) - Robert Saint (NRECA)- Ben Tatera (PG&E)- Bruce Rogers (TVA)- Devin Van Zandt (GE) - Doug Fitchett (AEP) - James Stoupis (ABB)


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• Contact information:Mladen Kezunovic (TAMU)Tel: (979) 845-7509E-mail: [email protected]

Ward Jewell(WSU)Tel: (316) 978-6340E-mail: [email protected]

• Final report: http://tiny.cc/5eua3 (also at www.pserc.org)


mailto:[email protected]�


http://tiny.cc/5eua3�

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Outline

• Introduction• Evaluation of distribution reliability• Optimized Practices in Outage and Asset Management• Integration of Outage and Asset Management Tasks• Conclusion• Q/A


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Introduction

• Status: existing utility business process• Status: outage management process• Status: asset management process• Status: emerging IED data• Questions


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Status: Existing business process

©2010 Mladen Kezunovic, All rights reserved

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Status: Outage management process

t0Outage occurAffecting Ncustomers and LkW of power

t1Cause of outage foundFault isolated

t2Fault clearedService restoredSystem back to normal

time


r : duration of an outage

Trouble-callsSCADA

GISReal-time System Configuration

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Status: Asset management process


- Time-based preventive maintenance

- Corrective maintenance (run-to-failure strategy)

TF 1=

lkF ,~ λ

frequency fixed time period

failure rate

component failure mode Lack of operational/non-

operational data

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Status: Emerging IED data


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Introduction- Questions

Will new data help improving system reliability?

- How to evaluate improvement in system reliability?- What are the new technologies in asset and outage

management?- What needs to be done to implement those

technologies?


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Evaluation of System Reliability

• Correlation of reliability with outage cost• Formulation of outage cost• Cost reduction by implementing new

technologies• Evaluation of the benefit of data


12©2010 Mladen Kezunovic, All Rights Reserved

Distribution System Reliability

Outages

Features

Duration

Frequency

Scale

Cost

Utility(revenue loss, labor, repair/replacement,

maintenance…)

Customer

Reliability Indices

Outage Cost

Correlation of reliability with outage cost

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• Related reliability indices- System Average Interruption Frequency Index

SAIFI=(ΣNumber of Customers Interrupted)/(Total Number of Customers Served)= Σ Ni / NT

- System Average Interruption Duration IndexSAIDI=(ΣCustomer Interruption Durations)/(Total Number of Customers Served)

= Σ (ri⋅ Ni) / NT

- Average System Interruption Duration IndexASIDI=(ΣConnected kVA Duration of Load Interruption)/(Total kVA served)

=Σ (ri⋅ Li) / LT

- Momentary Average Interruption Event Frequency Index (for sensitive load)MAIFI=(ΣNumber of Momentary Interruption Evernts)/(Total Number of Customers)

=Σ (IMi⋅ Nmi) / NT

- Major Event DayMED=Σ {SAIDIi | SAIDIi >TMED}


Formulation of outage cost


Formulation of outage cost Para Description Correlated

FeatureCorrelated Practices

Correlated indices

F D S O.M. A.M.

ri duration of interruption event X X X SAIDI, ASIDI, MED

Ni number of customers interrupted X X X SAIFI, SAIDI

Σ Ni Total number of interrupted customers

X X X SAIFI

Li connected kVA load interrupted X X X ASIDI

IMi number of momentary interruptions

X X MAIFI

Nmi number of interrupted customers for momentary interruptions

X X MAIFI

TMED major event day threshold -- -- -- -- -- MED

NT total number of customers -- -- -- -- -- SAIFI, SAIDI, MAIFI, MED

LT total connected kVA load -- -- -- -- -- ASIDI

* Para: parameters; F: frequency; D: duration; S: scale; O.M.: Outage Management; A.M.: Asset Management.


Formulation of outage cost

* α1~ α4, β1~ β4: weights for units coordination

• Concerns→ Utility: ASIDI (revenue), DevRisk (repair/replacement cost)

→ Customer: SAIFI, SAIDI

→Other: reconfiguration (MED), penalty to important customers(MAIFI’,

ASIDI’), etc.

• Formulation

MEDASIDIMAIFIDevRiskASIDISAIDISAIFICost

⋅++⋅+⋅+⋅+⋅+⋅=

65

4321

)''( αααααα

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Failure 1 Failure

i

Failure m

Fault Detection→ Fault Location → Fault Clearance

… …

Σ CostOM (i)

SAIDI

ASIDI

MAIFI’

MED

SAIDI’

DevRisk

… …

Σ CostAM (k)

Maintenance of Component k… …

Maintenance

ri, IMi, etc

λ(k), MTTF (k), etc

Report Period

Cost of Outage

t

Outage Management

Asset Management

System

Outage

Fault location technology

Condition-based maintenance


•Reduction associated with a scheduled outage event k

• Reduction associated with a fault event I

• Total reduction in a reporting period


Cost reduction caused by implementing new technologies

∆⋅

∂∂

+

∆⋅

∂∂

⋅+

∆⋅∂

∂⋅+∆⋅

∂∂⋅+∆⋅

∂∂⋅=∆

)()()()(

)()(

)()(

)()()(

)()()(

)()(

4

321

kMTTFkMTTFkDevRiskk

kkDevRisk

kk

kASIDIkk

kSAIDIkk

kSAIFIkCostAM

λλ

α

λλ

αλλ

αλλ

α

ii

ii

mimi

ii

ii

ii

OM

rr

iMEDrr

iASIDINN

iMAIFI

IMIM

iMAIFIrr

iASIDIrr

iSAIDIiCost

∆⋅∂

∂⋅+∆⋅

∂∂

+∆⋅∂

∂+

∆⋅∂

∂⋅+∆⋅

∂∂⋅+∆⋅

∂∂⋅=∆

)(])(')('

)('[)()()(

6

532

α

ααα

)()( iCostkCostCost OMAM ∑∑ ∆+∆=∆

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• Approximate estimation (RBTS4, Feeder 1)

- If with new data, we are able to improve some of the factors: By condition-based maintenance: E(∆λ/λ)= -10%, E (∆MTTF/MTTF)=10%By accurate fault location: E(∆r/r)= -10%

- Reduction in outage cost: 1673.66 $ /yr (reduced by 14.6%)

SAIFITimes/(customer.yr)

SAIDIhr/(customer.yr)

ENSkWhr/yr

SAIDIhr/yr

Maint. Cost$

Cost of Outage$ /yr

0.302 3.47 12926 0.32315 5000 11468.4

SAIFITimes/(customer.yr)

SAIDIhr/(customer.yr)

ENSkWhr/yr

SAIDIhr/yr

Maint. Cost$

Cost of Outage$ /yr

0.2718 2.8107 10470 0.26175 4500 9794.74


Evaluate the benefit of data

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Optimized practices in outage and asset management

• Outage management: overview• Accurate fault location• Efficient field inspection• Asset management: condition-based

preventive maintenance


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- What can we do {

- Methodology: 1). Accurate fault location;2). Efficient field inspection.


∆r- duration of outage

∆N- affected area

Outage management: overview

21©2010 Mladen Kezunovic, All rights reserved

time

t0

t1

t2

∆r, ∆N

Outage management: overview

Work order for dispatching

crews

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- Use of IED data;

- Ability to deal with insufficient and inaccurate data;

- Pinpoint fault;

- Impact: reduction in duration of outage (∆r).


Example: Fault location using voltage sags from PQ meters.

Accurate fault location

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Model-based Fault Location Using Voltage Measurement- Input: V, I from feeder root; |V| from sparse measurements;

measurement accuracy (nominal variance); System model.- Output: list of suspect nodes.

Read pre-fault data

Pre-fault load flow solution

Applicability assessment

Fault case simulation

Bad data elimination

Faulted node selection

Exit


Accurate fault location

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- Problem: How to dispatch field crew to minimize time and impact of field inspection to customers

- Concern: minimum time to find fault; area with more customers/ loads/ quality-sensitive customers prioritized to inspection.

- Solution: optimization problem


Efficient field inspection


Efficient field inspection

Run fault location algorithm

Take the top 5 nodes

Nodes are in one area?

Schedule field crew to inspect on the area

Form 2 suspect areas and calculate probabilities

Y

N

Calculate outage cost for 3 scenarios

Identify the scenario with minimum outage cost

End

26©2010 Mladen Kezunovic, All rights reserved

Optimized asset management tasks

- What can we do - ∆λ, ∆MTTF

- Methodology: Condition-based maintenance

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Integration of outage and asset management tasks

• Integration: Why• Integration: What• Integration: How• Integration: benefit• One step further


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Integration- Why

- Lack of information from field

→ what we are using for fault location: information from trouble call, GIS and metering system.

- New data required by fault location algorithm

→ model-based fault location algorithm.

- Able to improve asset management too

→ from time-based maintenance to condition-based maintenance.


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Integration- What

IEDs!- DFRs, Digital Relays, Power Quality Meters…

- What is provided: Voltage (magnitudes, phasors, sags,

even samplings!); Current; Power…

- Sparse but good enough!


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Integration- How


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Integration- Benefit

- Savings in IED installation expenditures;

- Efficient collection and use of non-operational data;

- Reduced failure cost and better system reliability, and finally more return on investment.


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One Step Further


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Thank you!Questions?


Mladen KezunovicTel: (979) 845-7509E-mail: [email protected]


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Publications

• M. Kezunovic, W. Jewell, Y. Dong, V. Aravinthan, "Integration of Asset and Outage Management Tasks for Distribution Application". Final Project Report, PSERC Publication 09-11. [Online]. Available: http://www.pserc.org/cgi-pserc/getbig/publicatio/reports/2009report/kezunovic_distribution_app_pserc_t-36_final_report_2009.pdf

• Yimai Dong, Visvakumar Aravinthan, Mladen Kezunovic and Ward Jewell, “Integration of Asset and Outage Management Tasks for Distribution Systems”. Accepted for IEEE PES General Meeting 2009.

• Yimai Dong, Mladen Kezunovic, “Fault Location Algorithm for Radial Distribution Systems Capable of Handling Insufficient and Inaccurate Field Data ”. IEEE PES 41st North America Power Symposium (NAPS) , Starkville, Mississippi, USA, October, 2009.

• Yimai Dong, Mladen Kezunovic, “Improvement in Distribution reliability by Integrating Asset Management and Outage Management Tasks”. Accepted for 2010 CIRED Workshop, Lyon, France, June, 2010.


http://www.pserc.org/cgi-pserc/getbig/publicatio/reports/2009report/kezunovic_distribution_app_pserc_t-36_final_report_2009.pdf�



Documents

Integration of Asset and Outage Management Tasks for ... · Data ”. IEEE PES 41st North America Power Symposium (NAPS) , Starkville, Mississippi, USA, October, 2009. • Yimai Dong,