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134:(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.
154:(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.
168:. 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.
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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
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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
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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
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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
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Robinson, R.L.; Hall, D.F.; Warren, C.A.; Werner, V.G. (2006), "Collecting and categorizing information related to electric power distribution interruption events: customer interruption data collection within the electric power distribution industry",
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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".
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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.
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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
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Prioritizing restoration efforts and managing resources based upon criteria such as locations of emergency facilities, size of outages, and duration of outages.
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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.
142:(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
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systems which can automatically report the operation of monitored circuit breakers and other intelligent devices such as SCADA reclosers.
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Improved customer satisfaction due to increase awareness of outage restoration progress and providing estimated restoration times.
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Fewer complaints to regulators due to ability to prioritize restoration of emergency facilities and other critical customers.
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At the core of a modern outage management system is a detailed network model of the distribution system. The utility's
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Nielsen, T.D. (2002), "Improving outage restoration efforts using rule-based prediction and advanced analysis",
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Providing information on extent of outages and number of customers impacted to management, media and regulators.
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Sridharan, K.; Shulz, N.N. (2001), "Outage management through AMR systems using an intelligent data filter",
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Integrated Outage
Management System: an effective solution for power utilities to address customer grievances
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Hall, D.F. (2001), "Outage management systems as integrated elements of the distribution enterprise",
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Reduced outage frequency due to use of outage statistics for making targeted reliability improvements.
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Transmission & Distribution
Construction, Operation & Live-Line Maintenance Proceedings
312:, 1998. ESMO '98. 1998 IEEE 8th International Conference on 26–30 April 1998, pages 172 – 178
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Frost, Keith (2007), "Utilizing Real-Time Outage Data for
External and Internal Reporting",
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defined by the IEEE P1366-2003 standard. The most frequently used performance indices are
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Reduced outage durations due to faster restoration based upon outage location predictions.
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Prediction of location of transformer, fuse, recloser or breaker that opened upon failure.
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Nielsen, T. D. (2007), "Outage
Management Systems Real-Time Dashboard Assessment Study",
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Kearney, S. (1998), "How outage management systems can improve customer service",
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Improved media relations by providing accurate outage and restoration information.
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Another system that is commonly integrated with an outage management system is a
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345:," International Conference on Electricity Distribution (CIRED) Workshop, 2014.
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International
Journal of Electronic Customer Relationship Management
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The Use of Big Data for Outage
Management in Distribution Systems
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Burke, J. (2000), "Using outage data to improve reliability",
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Outage management systems are also commonly integrated with
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Reduced outage duration averages due to prioritizing
305:, 28 October - 2 November 2001, pages 1175 - 1177
102:Major functions usually found in an OMS include:
90:(OMS) is a computer system used by operators of
43:but its sources remain unclear because it lacks
328:Power Engineering Society General Meeting, 2007
292:Power Engineering Society General Meeting, 2007
207:OMS based distribution reliability improvements
115:Calculation of estimation of restoration times.
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121:Calculation of crews required for restoration.
317:IEEE Power Engineering Society Winter Meeting
118:Management of crews assisting in restoration.
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126:OMS principles and integration requirements
336:Power Engineering Society General Meeting
74:Learn how and when to remove this message
341:P.C. Chen, T. Dokic, and M. Kezunovic, "
287:, issue 2, April 2000 Page(s):57 - 60
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323:, 27–31 January 2002, pages 866 - 869
338:, 2006. IEEE 18–22 June 2006, page 5.
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351:IEEE Transactions on Power Delivery
94:to assist in restoration of power.
294:. IEEE 24–28 June 2007 pages 1 – 2
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232:reliability for the lowest cost.
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281:Computer Applications in Power
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132:geographic information system
92:electric distribution systems
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254:Sridharan & Shulz 2001
174:(P.-C. Chen, et al., 2014)
140:interactive voice response
98:Major functions of an OMS
264:Sastry, M.K.S. (2007), "
88:outage management system
29:This article includes a
301:, 2001 IEEE/PES volume
152:automatic meter reading
58:more precise citations.
183:OMS benefits include:
276:, no. 1, pages: 30-40
166:mobile data system
31:list of references
363:10.1109/61.956755
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