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Two Ways to Make U.S. Distribution Systems Self-Healing

To improve the self-healing capability of the distribution-level smart grid in United States, the distribution outage management system has been evolving with exploration of two complementary technologies: feeder level fault detection, isolation and service restoration; and smart meter-based outage analysis. Both technologies are essential to elements in any smart grid blueprint.

In the power system, a majority of faults occur in the distribution network, often resulting in the direct interruption of the supply of electricity to end customers. Because most U.S. distribution grids lack sensors, distribution system outage management has traditionally relied on a trouble call system in which customers report outages to the utility. When a fault occurs and causes a disturbance in electricity service, customers may call the utility. After receiving the power outage report, the utility sends a field crew that investigates the location of the fault, determines and implements a switching scheme to isolate the fault, and restores service to as many impacted customers as possible while repairing the faulty system part.

This trouble call outage management procedure may take several hours to complete. The efficiency of outage management can depend on any of the following factors: the timeliness of power outage reports, depending for example on whether customers are asleep or at home; how long it takes field crews to arrive at the scene to make repairs; and finally, the amount of time it takes field crews to identify the exact location of the fault based on the estimation of the fault location inferred from trouble calls.

As the industry progresses toward the smart grid, many distribution utilities have deployed more and more devices that measure, monitor, protect, control and communicate at both the feeder and customer levels. Examples of such devices are smart meters on customer premises and feeder switching devices—circuit breakers, reclosers, and sectionalizers—with intelligent electronic devices (IEDs). American Electric Power (AEP) and Xcel Energy, among others, have installed IEDs to monitor system operating conditions and apply control actions.

Automated fault detection, isolation and service restoration (FDIR), when used in connection with network communication, can handle faults that appear in feeders. For example, when a short-circuit fault occurs, the upstream switch will open, controlled by its associated IED, which immediately notifies the substation or control center so that an FDIR program can be initiated. The program can provide a switching scheme—the open/close sequences of the feeder switche—for fault isolation and service restoration purposes, which the substation or control center thereupon sends to corresponding IEDs associated with switches.

An FDIR program can eliminate the dependency of the outage management on trouble calls and crew dispatches to the field. Accordingly, an FDIR-based self-healing solution can expedite the outage management procedure and reduce the outage time experienced by customers from several hours to several minutes.

One limitation of the automated FDIR technology, however, is that it depends on an IED signal to initiate; therefore, it is applicable only to faults on feeders equipped with IEDs. Regarding faults occurring on distribution lines other than feeders, such as laterals, which usually use fuses instead of IEDs to isolate faults, a utility could improve outage analysis by using a complementary outage management technology enabled by the advanced metering infrastructure (AMI).

With substantial funding from the 2009 U.S. stimulus bill, most U.S. states have begun the process of deploying AMI in the distribution network. At the beginning of 2009, for example, Texas initiated a project of deploying six million smart meters and expects completion of the project by this year; and California plans to install 10 million smart meters.

The major function of AMI technology is to provide utilities with the ability to remotely and automatically collect customer energy consumption data from meters at customer sites. Due to the large number of smart meters available, the potential ability of smart meters to provide additional information for outage analysis going beyond trouble calls is also being investigated.

In particular, the "last gasp" sent out by smart meters in an outage area can alert the control center to a power outage occurrence in real time or near real time; cessation of communications from smart meters, with loss of power, is instantaneous and therefore provides faster warning of an outage than trouble calls possibly could. Besides the quick outage notification, smart meters have an on-demand polling capability that the control center can use to check whether meters are energized. This feature is particularly useful in resolving any uncertainty about the outage area during multiple outages and assists with fault location.

Effectively handling the large amount of smart meter last gasp information and utilizing the on-demand polling function can accelerate the initiation of the distribution system outage management process, provide accurate outage analysis results and implement fast power restoration.

In the distribution system, how to quickly and accurately detect and isolate a fault as well as restore power service has been a challenge for many years. As the smart grid evolves, utilities have deployed various types of sensors and advanced communication mechanisms. Such advances facilitate the two types of outage management technologies that handle faults occurring in different locations. These technologies, which significantly enhance the self-healing capability in the distribution-level smart grid, are critical to achieve high system reliability and customer satisfaction.


  • Zhao LiZhao Li, a member of IEEE, works as a senior software architect with the ABB Inc. US Corporate Research Center in Raleigh, N.C. He received his M.S. degree in computer science from the Georgia Institute of Technology. His research interests include the application of software technologies in process automation and power systems, performance analysis, and information system design and tuning.

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  • Fang YangFang Yang, a member of IEEE, works as a senior research and development engineer with the ABB Inc. US Corporate Research Center in Raleigh, N.C. She received her Ph.D. degree in electrical engineering from the Georgia Institute of Technology. Her research interests include distribution automation, power system reliability analysis, and the application of intelligent techniques in power system control.

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About the Smart Grid Newsletter

A monthly publication, the IEEE Smart Grid Newsletter features practical and timely technical information and forward-looking commentary on smart grid developments and deployments around the world. Designed to foster greater understanding and collaboration between diverse stakeholders, the newsletter brings together experts, thought-leaders, and decision-makers to exchange information and discuss issues affecting the evolution of the smart grid.


Massoud AminMassoud Amin is a senior member of IEEE, chairman of the IEEE smart grid newsletter, and a fellow of ASME.
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Fang YangFang Yang, a member of IEEE, works as a senior research and development engineer with the ABB Inc. US Corporate Research Center in Raleigh, N.C.
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Zhao LiZhao Li, a member of IEEE, works as a senior software architect with the ABB Inc. US Corporate Research Center in Raleigh, N.C.
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Diane CookDiane Cook, an IEEE Fellow, is Huie-Rogers Chair Professor in the School of Electrical Engineering and Computer Science at Washington State...
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Chao ChenChao Chen is a doctoral student in the School of Electrical Engineering and Computer Science at Washington State University.
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Sandeep AgrawalSandeep Agrawal obtained a B.E. degree in electronics and power engineering from Nagpur University, in Nagpur, India in 1986.
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Manoj B. DaigavaneManoj B. Daigavane obtained a B.E. degree in power electronics engineering from Nagpur University, in Nagpur, India in 1988.
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