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Next-Generation Smart Meters Are Unlocking the Value of True Edge Computing

Michael Kelly
Sep 13, 2022

Guidehouse Insights

The concept of edge computing is top of mind for today’s electric utilities. Over the past two decades, global grids have evolved from simple power delivery systems to data-rich, intelligent networks with distributed computing power moving further downstream toward the grid edge. The full value of edge computing, however, remains largely untapped as opportunities found at the true edge of the grid, i.e., at the home, have been hampered by the technical limitations of first-generation smart meters.

From Data Sources to Edge Computing Devices

Nearly all smart meters installed across the globe still classify as first-generation devices. These smart meters lack the technical requirements (compute, memory, programmability) and data capture capabilities (real-time, waveform data) to constitute second-generation or next-generation devices. Although these embedded capabilities have been a constant source of product evolution since the dawn of advanced metering infrastructure, it is only recently that industry-leading manufacturers, most notably Landis+Gyr and Itron, have achieved a paradigm-shift-level progression in smart meter technologies and edge computing functionality, such as:

  • High resolution waveform data with sample rates capable of enabling real-time device identification
  • Edge computing in the meter itself that has access to the raw data stream
  • Low latency networking via Wi-Fi or cellular to support real-time consumer experiences

Prior to these technological advancements, there was little to no value in performing smart meter analytics at the edge, i.e., inside the meter, as the same insights could be generated by performing this analysis in the back office. The current set of smart meter analytics solutions on the market primarily use low resolution interval data and basic analytics techniques to deliver insights into: What has already happened? rather than What is happening? or What will happen? This has fostered a perception across much of the industry that these types of solutions can only provide limited operational value for utilities and their customers. However, the next generation of smart meters aim to disrupt these traditional lines of thinking and redefine the potential value of smart meter analytics moving forward.

Maximizing the Value of Smart Meter Analytics

It’s been established that the next generation of smart meters can capture massive amounts of data across several parameters (i.e., current and voltage waveform data). The question then becomes, so what? This treasure trove of data is essentially useless if not properly acted upon by grid operators and their customers. Where use cases demand real-time intelligence, such as notifying a customer that they have activated an appliance or EV during a higher priced time interval or sending real-time notifications regarding detected faults and anomalies, the logical solution is to tap into analytics engines on the meter itself. 

This approach is fostering a new wave of innovation among both meter manufacturers and dedicated analytics providers. These companies are working in unison through open partnership ecosystems, with analytics providers developing applications that can be installed directly on the meter itself. 

In the case of Landis+Gyr, US-based energy management provider Sense has arisen as one of the company’s flagship partners in the development of inside-the-meter intelligence. Sense uses high resolution energy monitoring and machine learning algorithms to provide detailed real-time insights into how home devices are being used right now. For example, customers can watch on an app as they turn on and off the stove or plug and unplug devices, seeing in real time how these actions translate into energy consumption; the app can also provide alerts, for example, if the stove has been left on too long. As the next generation of smart meters is rolled out over the next decade and beyond, the ability to tap into these types of analytics applications on the meter itself and deliver real-time insights will help to unlock new use cases, efficiencies, and benefit streams for utilities and customers alike. 

This example represents only the tip of the iceberg in terms of what inside-the-meter analytics can and will ultimately support in enhancing the value of utility smart meter investments. This example, among many others, are explored in more detail in Guidehouse Insights’ Inside-the-Meter Intelligence to Become the Norm white paper.