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Outage management system

An outage management system (OMS) is a computer system used by operators of electric distribution systems to assist in restoration of power.


Major functions of an OMSEdit

Major functions usually found in an OMS include:

  • Prediction of location of transformer, fuse, recloser or breaker that opened upon failure.
  • Prioritizing restoration efforts and managing resources based upon criteria such as locations of emergency facilities, size of outages, and duration of outages.
  • Providing information on extent of outages and number of customers impacted to management, media and regulators.
  • Calculation of estimation of restoration times.
  • Management of crews assisting in restoration.
  • Calculation of crews required for restoration.

OMS principles and integration requirementsEdit

At the core of a modern outage management system is a detailed network model of the distribution system. The utility's geographic information system (GIS) is usually the source of this network model. By combining the locations of outage calls from customers, a rules engine is used to predict the locations of outages. For instance, since the distribution system is primarily tree-like or radial in design, all calls in particular area downstream of a fuse could be inferred to be caused by a single fuse or circuit breaker upstream of the calls.

The outage calls are usually taken by call takers in a call center utilizing a customer information system (CIS). Another common way for outage calls to enter into the CIS (and thus the OMS) is by integration with an interactive voice response (IVR) system. The CIS is also the source for all the customer records which are linked to the network model. Customers are typically linked to the transformer serving their residence or business. It is important that every customer be linked to a device in the model so that accurate statistics are derived on each outage. Customers not linked to a device in the model are referred to as "fuzzies".

More advanced automatic meter reading (AMR) systems can provide outage detection and restoration capability and thus serve as virtual calls indicating customers who are without power. However, unique characteristics of AMR systems such as the additional system loading and the potential for false positives requires that additional rules and filter logic must be added to the OMS to support this integration.(Sridharan & Schulz 2001)

Outage management systems are also commonly integrated with SCADA systems which can automatically report the operation of monitored circuit breakers and other intelligent devices such as SCADA reclosers.

Another system that is commonly integrated with an outage management system is a mobile data system. This integration provides the ability for outage predictions to automatically be sent to crews in the field and for the crews to be able to update the OMS with information such as estimated restoration times without requiring radio communication with the control center. Crews also transmit details about what they did during outage restoration.

It is important that the outage management system electrical model be kept up to current so that it can accurately make outage predictions and also accurately keep track of which customers are out and which are restored. By using this model and by tracking which switches, breakers and fuses are open and which are closed, network tracing functions can be used to identify every customer who is out, when they were first out and when they were restored. Tracking this information is the key to accurately reporting outage statistics. (P.-C. Chen, et al., 2014)

OMS benefitsEdit

OMS benefits include:

  • Reduced outage durations due to faster restoration based upon outage location predictions.
  • Reduced outage duration averages due to prioritizing
  • Improved customer satisfaction due to increase awareness of outage restoration progress and providing estimated restoration times.
  • Improved media relations by providing accurate outage and restoration information.
  • Fewer complaints to regulators due to ability to prioritize restoration of emergency facilities and other critical customers.
  • Reduced outage frequency due to use of outage statistics for making targeted reliability improvements.

OMS based distribution reliability improvementsEdit

An OMS supports distribution system planning activities related to improving reliability by providing important outage statistics. In this role, an OMS provides the data needed for the calculation of measurements of the system reliability. Reliability is commonly measured by performance indices defined by the IEEE P1366-2003 standard. The most frequently used performance indices are SAIDI, CAIDI, SAIFI and MAIFI.

An OMS also support the improvement of distribution reliability by providing historical data that can be mined to find common causes, failures and damages. By understanding the most common modes of failure, improvement programs can be prioritized with those that provide the largest improvement on reliability for the lowest cost.

While deploying an OMS improves the accuracy of the measured reliability indices, it often results an apparent degradation of reliability due to improvements over manual methods that almost always underestimate the frequency of outages, the size of outage and the duration of outages. To compare reliability in years before an OMS deployment to the years after requires adjustments to be made to the pre-deployment years measurements to be meaningful.

Electric power outage map links, externalEdit

USA state / county/city Company wiki page link / Outage map
AR, Fayetteville, Texarkana SWEPCO (American Electric Power) [1]
AR, nw The Empire District Electric Company [2]
AR Entergy [3]
CA, PG&E Pacific Gas and Electric Company [4]
CA, southern Southern California Edison [5]
CA, San Diego San Diego Gas & Electric [6]
CO Black Hills Energy [7]
CO Xcel Energy [8]
CT Connecticut Light and Power [9]
CT United Illuminating [10]
D.C. Pepco [11]
DE Delmarva Power [12]
DE Delaware Electric Cooperative [13]
FL, Jacksonville Clay Electric Cooperative [14]
FL Duke Energy [15]
GA, Gwinnett,Hall,Jackson,Banks,Barrow,Clarke,Franklin,Lumpkin,Madison and Oglethorpe Counties Jackson EMC [16]
GA, Bartow,Cherokee,Cobb,Fulton and Paulding Counties Cobb EMC [17]
GA, central Flint Energies [18]
GA, Forsyth, Fulton, Dawson, Lumpkin, Cherokee, Hall, & Gwinnett Counties Sawnee EMC [19]
IA Alliant Energy [20]
IL Ameren [21]
IL Commonwealth Edison [22]
IN, Indianapolis Indianapolis Power & Light [23]
IN, Morgan,Brown,Clay,Johnson,Monroe,Owen and Putnam Counties South Central Indiana REMC [24]
IN Fayette, Rush, Vigo Duke Energy [25]
IN Indiana Michigan Power [26]
IO, Iowa Association of Electric Cooperatives [27]
KS, Kansas City, Anderson, Bourbon, Coffey, Douglas, Franklin, Johnson, Leavenworth, Linn, Miami, Osage, Wyandotte KCP&L [27]
KS, south east Empire Energy Empire District [28]
KS Westar Energy Westar Energy [29]
KY, Campbel, Boone, Kenton, Grant, Pendelton counties Duke Energy [30]
KY LGE KU Energy LGE KU [28]
KY, Breckinridge, Caldwell, Crittenden, Daviess, Hancock, Henderson, Hopkins, Livingston, Lyon, McClean, Muhlenburg, Ohio, Union, Webster Kenergy Corp [32]
KY Kentucky Power (American Electric Power) [33]
LA, East & West Feliciana,Ascension,East Baton Rouge,Livingston,Saint Helena and Tangipahoa Parishes Dixie Electric [29]
LA, Allen, Beauregard, Calcasieu, Rapides, Evangeline, Jefferson Davis, Vernon Beauregard Electric Cooperative, Inc.
LA, Shreveport SWEPCO
LA, Central CLECO
LA Entergy [30]
MA, west
MD, Baltimore
MD, Montgomery & Prince George's County Pepco [31]
MD, south SMECO [32]
MD, south Pepco [33]
MD Choptank Electric Cooperative [34]
ME, central
MI, SE, Detroit DTE Energy [35]
MI, SW Indiana Michigan Power|
MI, western
MI, Upper Peninsula Upper Peninsula Power Company [36]
MI Xcel Energy [37]
MN, Wright & Hennepin Counties
MN Minnesota Valley Electric Cooperative [38]
MN Xcel Energy [39]
MO, Kansas City
MO, sw
MO Ameren [40]
MS Entergy [41]
NC, Charlotte Duke Energy [42]
NC, Alexander,Alleghany,Ashe,Avery,Caldwell,Watauga and Wilkes Counties Blue Ridge EMC [43]
NC, Bladen,Brunswick,Columbus and Robeson Counties Brunswick EMC [44]
NC, Craven,Duplin,Jones,Lenoir,Onslow and Pender Counties Jones Onslow EMC [45]
NC, Cumberland,Hoke,Robeson and Scotland Counties Lumbee River EMC [46]
ND Xcel Energy [47]
NH, Belknap, Coos, Carroll, Cheshire, Grafton, Hillsborough, Merrimack, Rockingham, Strafford, Sullivan Counties New Hampshire Electric Cooperative [48]
NJ, Atlantic City, except Vineland Pepco Holdings [49]
NJ, JCP&L Zone: North West and South East, except AC FirstEnergy [50]
NJ, PSE&G Zone: Central west to North East Public Service Enterprise Group[51]
NJ, Vineland Vineland Municipal Utilities [52]
NJ, Sussex County and rural areas in state's North West corner Sussex Rural Electric Cooperative [53]
NM Xcel Energy [54]
NY, Long Island
NY, Syracuse
OH, Cincinnati
OH, Columbus
OH, Cleveland, Akron, Toledo
OH, Dayton
OK, ne
PA, southeast
PA, east
PA Versify Solutions
SC, Santee Cooper
SC, Abbeville,Anderson,Greenville,Laurens,Newberry,Spartanburg and Union Counties Laurens Electric [55]
TN, Knoxville
TN, Memphis
TN, Nashville
TX, Lubbock
TX, Southeast Entergy [56]
TX, Texarkana, Longview
TX Xcel Energy [57]
VA, north
VA, Shenandoah
WA, Puget Sound
WA, Seattle
Country Province, city/area Electric outage map link
Australia Central, Northern and Southern Queensland
Australia South Australia
Australia Victoria
Australia Western Australia
Canada Alberta
Canada British Columbia
Canada Newfoundland
Canada Ontario
Canada Toronto (Ontario)
Canada New Brunswick
Canada Nova Scotia Power
Canada Quebec
New Zealand Parts of the North Island
United Kingdom Central England
United States of America Entire Country


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  • P.C. Chen, T. Dokic, and M. Kezunovic, "The Use of Big Data for Outage Management in Distribution Systems," International Conference on Electricity Distribution (CIRED) Workshop, 2014.
  • Sridharan, K.; Shulz, N.N. (2001), "Outage management through AMR systems using an intelligent data filter", Power Delivery, IEEE Transactions on, 16 (4): 669–675, doi:10.1109/61.956755 
  • Sridharan, K.; Schulz, N.N. (2001), "Outage management through AMR systems using an intelligent data filter", Power Delivery, IEEE Transactions on volume 16, issue 4, October 2001, pages :669 - 675