Smart meters are expected to serve nearly all electric customers within a few years, but the full value of their use has yet to be fully realized, according to a new report by Guidehouse Insights.
The immediate benefits include outage detection and billing accuracy, but smart meters can quickly evolve and produce large amounts of data that hasn’t been tapped to the benefit of those that use them. There also is a lack of investment in analyzing such data, the report says.
Smart meters currently serve nearly 65% of all US electric customers and that is expected to grow to 90% by 2028. Guidehouse Insights expects spending on smart meter analytics to grow annually by 13.4% over the next decade. Spending for demand management and energy efficiency is expected to grow from $1.6 billion in 2021 to $5.4 billion in 2030.
The US Energy Information Administration says as of 2019 there were electric utilities had 94.8 million smart meters installed in the country, with 88% of those being of residential use. There were 10.8 million meters installed for commercial practices.
With that growth in use, one smart meter could make 17,500 readings per year, more opportunities for using the data in beneficial ways results, Guidehouse Insights says. That data can then be used to help predict usage and power outages, among other information.
That analysis can be broken down into three areas, according to the report. They are descriptive, predictive and prescriptive analytics.
For the descriptive analytics, these can provide reactive information such as looking at outage information over large areas or to study low voltage problem areas. The report says there is a lot of historical data in this area.
Predictive analytics builds on descriptive information and attempts to forecast future problems. This can identify equipment failures and perform maintenance. They can forecast energy use and even alert customers when there are problems with their energy use.
Prescriptive analytics reveal what actions should be taken, using detailed information to automate complex decisions out of a range of possibilities. This approach is rarely used today, according to the report, but provides a great amount of potential such as promoting energy savings through a range of information available and not just a prediction.
The report says prescriptive analytics close a loop in action by letting customers know there are power issues before a problem has occurred.
Those types of analytics to improve energy use and efficiency are growing in focus, especially with the increased volume of information smart meters and grids are producing. The US Department of Defense implemented a program last year that analyzes such information from multiple data sources and to convert it into improved energy efficiency, resiliency and security enhancement.
Additionally, the smart meter technology has quickly advanced providing more real-time information. Built-in artificial intelligence, for example, can provide usage alerts, energy storage and fault detection, according to the Guidehouse Insights report.
Smart meters can also work together through networks enabling more widespread efficiency. Those networks can also help monitor usage helping cut use and costs and quickly detect and restore outages and predict possible disruptions, which can facilitate better maintenance.
The US Department of Energy announced $61 million investment in 10 pilot programs across the country to connect homes and businesses to interactive grids with a similar networking idea to cut costs and increase energy efficiency.
Smart meter implementation is being spurred by a demand in energy efficiency and driven by government initiatives that are mandating improved power infrastructure. A report by Allied Market Research in early 2021 said the market could reach $39.2 billion by 2027, the highest use in electricity, followed by gas and water. It says smart meter use will be most quickly utilized in residential areas, followed by commercial and industrial segments.