Electric utilities around the world leverage smart meters and Advanced Metering Infrastructure (AMI) to enable remote meter readings, remote connect/disconnect, demand/response, and other operational efficiencies. Utilities are under constant pressure to improve operational efficiency while mitigating rate hikes and improving customer service. While smart meters and AMI remove the need for in-field meter readers, expensive work crews still need to be scheduled to replace meters that are nearing the end of their useful lives. As it turns out, the vast majority of those replaced meters are still operational and would be for many more years. What if a meter’s lifetime could be extended so that it was only replaced just before its decline in accuracy?
Extending the useful life of meters yields surprisingly high return. Consider a hypothetical utility that spends €100 ($119.77) on a meter and its installation. Assuming a 15-year starting useful life, extending the service life of a meter by just 2 years results in lifetime savings of €13.30 ($15.93) per meter. Extending the meter life by 3 years increases the savings to €20 ($23.95) permeter over its lifetime. If the current useful life of the meter is less than 15 years, or purchase and installation costs are higher than €100, the resulting savings are even more significant. In addition, extending the useful life of a meter improves customer service, as fewer service disruptions would be needed.
Current best practices require that utilities or regulatory bodies determine useful life of the meters based on statistical distribution of failures. Typically, this is done by reliability engineers using the Weibull function, otherwise known as the bath tub curve depicted in Figure 1. Reliability engineers use these techniques to ensure that a meter’s measurement accuracy remains within class before it is replaced.
Historically, a lot of attention was devoted to reducing the impact of Early Life failures. This is accomplished by improving the manufacturing process, environmental burn-in, and extensive testing. The Wear Out region of the curve, which typically has a Gaussian distribution, is avoided by using conservative (three or more standard deviations) statistical methods to minimize the possibility of an out-of-spec device remaining in service. Furthermore, sample testing is required in many global regions to spot check meter performance during deployment. However, the biggest drawback of these methods is that often well over 99% of meters removed from operation still performwithin specifications. There has never been a cost-effective way to verify the measurement accuracy of each device.
Adopting non-invasive, real-time accuracy monitoring technology in smart meters will extend the useful life of the meter without increasing the risk of out-of-spec devices in the field. One example is mSure technology from Analog Devices. mSure technology is integrated into an energy metering chip, which continuously monitors the accuracy of the entire measurement signal chain, including the current and voltage sensors in each meter. Meter accuracy is then communicated, along with the energy consumption and other data, via AMI to the cloud. Having the complete picture of each meter’s’ accuracy, enables the utility to make a data-driven decision on required meter replacements.
As with all new technologies, phasing-in real-time accuracy monitoring technology is a prudent approach. Existing field sampling protocols can be used to confirm effectiveness of the solution and to train predictive analytics. After a couple of years of data correlation, field sampling can be reduced or eliminated, realizing additional cost savings.
One question that often comes up is what about all other meter failure mechanisms, which include backup batteries, power supplies and LCD (liquid crystal displays)? Modern meters already monitor the health of the battery and can report this parameter to the meter data management software. Failure of the power supply will result in the meter becoming unreachable over the data network, thus flagging the service department. And with remote meter reading, the LCD is no longer of high importance, and its failure will eventually be reported by the customer.
Energy measurement accuracy is the last mission-critical parameter that can now be effectively monitored enabling the extension of a smart meter’s useful life. With the deployment of non-invasive, real-time accuracy monitoring technologies, smart meters can deliver added value and increase a utility’s return on investment.
To learn more about mSure technology from Analog Devices, please vist: www.analog.com/msure