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Edge Computing and Inside-the-Meter Intelligence Expand Utilities' Value Propositions

Michael Kelly
Oct 19, 2021

GHI Blog

The design architectures and delivery models for smart meter analytics solutions have undergone a series of evolutions over the last decade. In the past, all data had to be centrally stored and processed in an on-premise data center, and utilities would use their own staff to perform related business processes. In recent years, many utilities have pivoted to more flexible, cloud-based architectures and delivery models.

However, cloud architectures are not a panacea for smart meter analytics. With the advent of high frequency sampling and waveform data capture, transmitting larger volumes of smart meter data to the cloud will cause constrained bandwidth capacity. Furthermore, in scenarios where enhanced data processing can enable a fast, local decision, latency requirements exceed the capabilities of cloud-based architectures to deliver real-time insights.

Smart Meter Innovations Are Changing the Utility Landscape

In a white paper commissioned for Grid4C, Guidehouse Insights examines how innovative solutions providers are balancing these constraints to provide utilities with more options as new architectures are pushing analytics further to the edge of the distribution network, including inside-the-meter. This enables a range of real-time use cases without the communications constraints found with traditional analytics architectures. For example, utilities can provide customers with real-time notifications during higher pricing periods, creating multi-pronged benefits around peak demand and customer experience. The following figure presents the wide range of smart meter analytics applications available and highlights the breadth of applications now enabled or enhanced by inside-the-meter architectures.

Inside-the-Meter Intelligence Applications

(Sources: Guidehouse Insights)

This expanding ecosystem of localized analytics applications is being driven by advancements in smart metering technologies. Smart meter manufacturers such as Itron and Landis+Gyr have greatly enhanced the onboard computing power, memory, and programmability within their next-generation smart meters. This creates new data capture capabilities for sub-second data streams across energy, voltage, current, and waveform (i.e., enhanced data), enabling the development of new use cases inside-the-meter that were previously unavailable or illogical with traditional architectures.

Although product development and go-to-market strategies vary across the growing pool of vendors, the industry has aligned around facilitating open partnership ecosystems. Establishing a vibrant and diverse network of analytics partners is critical to enabling continuous innovation in an open standards market.

For example, Itron has been developing its portfolio of inside-the-meter applications for nearly a decade with its Distributed Intelligence platform. Grid4C has successfully installed its GridEdge AI solutions in Itron's next generation of smart meters, and has made its AI-powered solutions available to Itron's customers.

Vendors and Utilities Explore New Paradigms

Utilities are no longer content with the rudimentary value propositions of old and are searching for dynamic ways to create value from their smart meter deployments. Drivers for smart meter analytics are abundant and evolving rapidly as smart meters continue to saturate the market, new use cases are explored, market competition increases, and grid and data management become increasingly paramount. Furthermore, the growing number of second-generation smart meter projects are expected to heavily rely on advanced smart meter analytics to increase the value of these deployments. This is incentivizing utilities and vendors to explore new paradigms, such as inside-the-meter intelligence, that provide the next piece of the smart meter analytics puzzle.