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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)
©2010 Mladen Kezunovic, All Rights Reserved
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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)
©2010 Mladen Kezunovic, All Rights Reserved
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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
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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
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r : duration of an outage
Trouble-callsSCADA
GISReal-time System Configuration
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Status: Asset management process
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- 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
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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}
©2010 Mladen Kezunovic, All Rights Reserved
Formulation of outage cost
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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.
15©2010 Mladen Kezunovic, All Rights Reserved
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
©2010 Mladen Kezunovic, All rights reserved
•Reduction associated with a scheduled outage event k
• Reduction associated with a fault event I
• Total reduction in a reporting period
17©2010 Mladen Kezunovic, All Rights Reserved
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
©2010 Mladen Kezunovic, All Rights Reserved
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.
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∆r- duration of outage
∆N- affected area
Outage management: overview
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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).
©2010 Mladen Kezunovic, All Rights Reserved
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
©2010 Mladen Kezunovic, All Rights Reserved
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
©2010 Mladen Kezunovic, All Rights Reserved
Efficient field inspection
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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
©2010 Mladen Kezunovic, All Rights Reserved
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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.
©2010 Mladen Kezunovic, All Rights Reserved
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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.
©2010 Mladen Kezunovic, All Rights Reserved
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One Step Further
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Thank you!Questions?
©2010 Mladen Kezunovic, All Rights Reserved
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.
©2010 Mladen Kezunovic, All Rights Reserved