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Correlating PQ Disturbances with Lightning Strikes

Categorizing the cause of faults is critical when using the information to prioritize maintenance and repairs to the power system.

Lightning-caused faults on a utility power system can lead to voltage sags affecting customers over a wide area or high transient voltages resulting in equipment failures on the power system and in customer facilities. Categorizing the cause of faults is critical when using the information to prioritize maintenance and repairs to the power system. For example, distinguishing lightning-caused faults from faults caused by tree contact can help establish tree-trimming priorities, and identifying the location of a lightning-caused fault can help determine the location of equipment failures, such as arresters.

One feature of a substation monitoring system can significantly increase the value of that system — automatic correlation of disturbances with lightning strikes. The Tennessee Valley Authority (TVA) implemented a prototype of this system.

Background on the TVA Application

TVA has been expanding its system-wide power quality monitoring system since 1994. In 1997, Electrotek and TVA implemented a system at TVA's Chattanooga, Tenn., facility that integrated lightning strike data, power quality data from PQView, and system operations data to provide a comprehensive view of the correlation of these data sources at the enterprise level.

TVA has about 17,000 miles of transmission lines spread across seven states. Lightning is a key cause (about 45%) of outages on its system. Correctly identifying events as being caused by lightning and then getting the information to the appropriate personnel in a timely manner, however, is a major challenge. TVA developed the Maintenance Improvement and Life Extension System (MILES) to improve response to disturbances and to help prioritize system maintenance requirements based on power quality information. The lightning correlation capability is an integral part of this system. Fig. 1 shows the graphical user interface to the system, with the location of power quality monitors around the system.

This system permits the user to display power quality events, system operation events, and lightning data together in a geographical context. It is also capable of showing TVA facilities, lines, crew work locations, geographical boundaries, and other geospatial information. The system even permits access to still- and full-motion images of individual towers and lines on the TVA network. It also takes full advantage of the Web interface to permit hyperlinking to related data sources and drilling down into successively greater levels of detail. The TVA can inspect the data gathered from system protective devices and correlate it with lightning and power quality events. The authority can then confirm whether the system protective devices operated as designed. If not, it can initiate measures to investigate and repair the affected systems.

The National Lightning Detection Network

It's not possible to correlate power quality disturbances with lightning strikes without knowledge of when and where the lightning strikes occur. This information comes from the National Lightning Detection Network (NLDN). NLDN consists of more than 100 remote, ground-based sensing stations located across the United States (see Fig. 2) that instantaneously detect the electromagnetic signals given off when lightning strikes the earth's surface. These remote sensors send the raw data via a satellite-based communications network to the Network Control Center (NCC) operated by Vaisala-GAI in Tucson, Ariz.

Within seconds of a lightning strike, the NCC's central analyzers process information on the location, time, polarity, and amplitude of each strike. The lightning information is then communicated to users across the country.

Since 1989, the NLDN has monitored the 20 to 25 million cloud-to-ground lightning strikes that occur every year across the contiguous 48 states. The network operates 24 hours per day, 365 days a year.

Recent developments allow the lightning data to be accessed continuously over the Internet so it can be seamlessly integrated with the power quality monitoring system.

Integration with a Power Quality Monitoring System

The TVA power quality monitoring system is Web-based. The authority has deployed monitors at substations, key customer service entrances, and even inside industrial facilities. TVA personnel have the monitors connected directly to the TVA network or they can access them via modem. In either case, the disturbances are GPS time-stamped so TVA personnel can correlate exactly the times of events with the times of lightning strikes. Personnel then download the information from the monitors to a central server, which is available to engineers throughout TVA on their internal network using the PQWeb software.

TVA personnel can then correlate power quality disturbances with lightning strikes at the central database or even within the substation monitors. Devices (called InfoNodes) located in the substations include integral analysis functions (called AnswerModules) that process the power quality disturbances as they occur. The Lightning Correlation AnswerModule is just one of the advanced functions that can be implemented at the substation.

When a new event comes in, the lightning correlation AnswerModule makes a query to the server by using a Web site command request via the Hyper Text Transport Protocol (HTTP) and a Common Gateway Interface (CGI) command. This command results in a response from the server formatted using the Extensible Markup Language (XML) and containing lightning flash data. This data is then stored locally along with the power quality monitoring information. It is available for display alongside the disturbance information. Disturbances that are correlated with lightning flashes are then tagged in the database accordingly for statistical reports and event notification messages.

Example of Lightning Correlation

An example is the best way to illustrate how the lightning correlation function can help distinguish events that are really caused by lightning from those that just might happen to occur during a storm.

On Easter Sunday of this year in Knoxville, Tenn., thunderstorms moved through the area. Fig. 3 shows the lightning strikes in the Knoxville area that day.

Signature System DataNodes are located at the substation that supplies the Electrotek office in Knoxville and also at the Electrotek service. The same InfoNode collects the power quality monitoring information from these DataNodes. A radio connection is used to collect the data from the substation site so that no special communication is needed at the substation.

During the time of the storm, the power monitoring system captured dozens of events. Without specific correlation, these events would probably all be tagged with a cause code such as “storm” or “lightning.” Detailed correlation with actual lightning strikes allows more definitive identification of the disturbances that were really caused by lightning.

Fig. 4 shows one of the fault events (11:34:36.870) that were recorded during the storm. Lightning did not cause this event. The only lightning strike in the time window for this event was 630 miles away, and the fault current clearly shows that this was a distribution fault on one of the local feeder circuits. The event could still be storm-related, but it is definitely not caused by lightning.

Fig. 5 shows the lightning strikes in the area of the distribution system that supplies Electrotek. Two of these events occurred within 100 milliseconds of power quality disturbances recorded by the monitoring system. (See the listing of disturbances in Fig. 6.) The output from the monitoring system indicates the events were correlated with lightning strikes. Both sites (the substation and the service entrance site) indicate this correlation. These events will also result in automatic e-mail messages with the same information if the notification system is configured to alarm on lightning events.

It's interesting to look at the actual characteristics of these lightning-caused events after identifying the cause. Fig. 7 shows the waveforms for one of the disturbances, which turned out to be a self-clearing fault. This disturbance did not result in operation of any protection equipment. Fig. 8 and Fig. 9 show the other lightning-caused event. This was a 42-cycle voltage sag at Electrotek. It resulted in a momentary interruption on one of the other feeder circuits.


Automatic correlation of lightning strikes with power quality disturbances can be an important benefit of a power quality monitoring system. It prevents incorrect identification of lightning as the cause of disturbances when a storm is in the area at the time of the event. If storms cause faults due to tree contact or lines slapping together, these are important to identify separately from lightning because maintenance can help avoid or reduce the impact of these faults.

Mark McGranaghan directs power quality projects and product development at Electrotek Concepts. You can reach him at [email protected]. Erich Gunther is a vice president of technology development with Electrotek Concepts. You can reach him at [email protected]. Theo Laughner is a program analyst with Tennessee Valley Authority. You can reach him at [email protected].

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