New industry report explains how utilities are investing in inside-the-meter analytics for valuable new use cases.
A free report by Guidehouse Insights projects utility spending on smart meter analytics to triple over the next decade. AI at the Grid Edge: How Inside-the-Meter Analytics Drive Value at the Grid Edge estimates smart meters currently serve nearly 65% of electric utility customers across the U.S. However, the report states the full value proposition behind smart meter deployments is only starting to be realized.
Newer smart meters, capable of running AI-driven solutions, make it easier for utilities to see and collect functional and ROI benefits, said Guidehouse in a press release. As a result, Guidehouse Insights says investments in inside-the-meter analytics will grow at a CAGR of 13.3%. Solutions for demand-side management and energy efficiency are expected to lead global spending across the forecast period, growing from approximately $1.6 billion in 2021 to nearly $5.4 billion in 2030.
Use cases enabled by grid-edge AI include real-time anomaly and fault detection for grid operators and customers, real-time load disaggregation for load shifting and demand side management, as well as tools for detecting and integrating distributed energy resources (DERs) like residential solar and electric vehicles. According to the report, inside-the-meter architectures offer utilities new options for where, when, and how to analyze high-resolution smart meter data.
“Between the cloud and now the meters themselves, we can create the right analytical architecture for each use case, balancing bandwidth, latency, reliability, and other factors,” said Dr. Noa Ruschin-Rimini, Founder and CEO of Grid4C, an AI-powered solution providers featured in the report for being one of the first companies to embed its AI-powered energy analytics inside smart meters of the world’s leading AMI vendors.
AI at the Grid Edge gives an evolutionary framework for understanding AI advancements in smart meter analytics and suggests how utilities can evaluate different analytics architectures and delivery models.
The 22-page report is available as a complimentary download from Grid4C.