Smart utility meters enhance utility operations

The capabilities of advanced metering infrastructure offer opportunities for improving service and preventing lost revenue through phase error analysis.


 Figure 1: This circuit schematic details multiple issues that can cause phase errors. Advanced metering infrastructure (AMI) improves incident reporting, which accelerates response to minimize problems. All graphics courtesy: Burns & McDonnellLearning objectives

  • Understand advanced metering infrastructure in electric metering.
  • Evaluate early-detection options via data collection.
  • Learn to work with local utilities to provide customers with improved electrical service.

The onset of the advanced metering infrastructure (AMI) era of electricity metering has brought about numerous changes to utility-industry operations. A primary driver for the deployment of AMI meters and systems is their ability to bring more granular data into integrated back office utility systems. This data-regarding outage events, consumption, voltage, and more-can then be processed by systems to accelerate power-restoration times, improve end-user energy monitoring, and strengthen infrastructure analytics.

Many preliminary rollout and integration efforts have focused on replacing existing metering and system-to-system functionality with the newer AMI technology. Utilities have been able to successfully implement AMI systems to replace their aging meter-reading systems with equivalent AMI functionality. However, the majority of utilities have taken a wait-and-see approach to the additional reporting and analytical capabilities that AMI and advanced systems integrations have to offer. While some of these additional capabilities are still conceptual and in development, there are other lower-hanging capabilities, many of which are functionally developed and readily available from AMI vendors. These low-hanging capabilities are ripe for the picking and ready to be put into operational use today.

One often overlooked capability is phase error event reporting, whereby the AMI meter reports specific event messages to the AMI head-end system when phase overvoltage, undervoltage, and/or outage conditions are detected by the AMI meter. While outage- and restoration-event messages are typical integration points for AMI deployments to improve reliability and operational efficiency, voltage sag- and swell-event messages are not typically of interest to utilities without an accompanying advanced distribution- automation program. However, both of these types of event messages are of particular relevance and interest with regard to transformer-rated meters.

Transformer-rated meters do not actively measure power flowing in series through a meter into the target load. Rather, they passively measure power through a target load using potential transformers and current transformers. Thus, issues within the metering-transformer circuitry can lead to inaccuracies in measurement without an actual issue present in the power-delivery circuitry. When transformer-rated power measurement is combined with the fact that the largest utility customers are metered using transformer-rated meters, it becomes evident that accurate measurement of power delivery to transformer-rated electric services is critical. Accuracy is of utmost importance for protecting utility revenue streams and avoiding preventable revenue loss.

Some examples of issues that can cause inaccuracies within the metering circuitry include faulty connections, connection failures due to extreme climates, corrosion, water leaks, damaged potential transformers or current transformers, and blown fuses. These issues can be transient in nature, as when water in an improperly sealed fuse freezes overnight but thaws out during the daytime. When these issues occur on electromechanical meters and even automatic meter reading (AMR) devices, they would have to be "caught in the act" during field investigations to be noticed or corrected. With electromechanical meters, these issues are not detected outside of the impact they have on the accumulated usage information. With AMR, at best, these issues could trigger an event that would be logged in the meter. However, these event messages would not necessarily be noticed until quite some time after they had manifested themselves. As a result, lost revenue is likely to occur. 

Detection and analytics

Figure 2: This diagram indicates the relative financial effects of lost revenue due to phase errors (gray area) between expected revenue from electricity consumption (green line) and actual revenue from electricity consumption recorded by the meter (red lThe key to minimizing and preventing lost revenue is through early detection. Without daily event reporting and historical data trending offered by AMI meters, these issues could sit unnoticed for months or years until the next time the circuitry is serviced or investigated.

Prior to the adoption of AMI meters, most of these issues were not easily identifiable. Because the majority of these issues do not prevent the meter from accumulating usage information, and although the usage information is not accurate, meter readings still increase and do not necessarily present cause for investigation.

Most AMI meters and systems already are capable of bringing the data into utility systems, and many AMI meters and systems already include this data in default configurations. The key is to put effective reporting and analytics processes in place to turn the event data into useful information and work orders. Depending on the scale of the customer base and transformer-rated meter population, this analysis can begin manually and eventually become automated once useful data sets, processes, and integrations are developed.

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