EPRI examines radio frequency smart meter safety

Palo Alto, Calif., February 22, 2011 — Radio-frequency exposure levels from one type of smart meter, even at close range, fall substantially below the protective limits set by the Federal Communications Commission for the general public, according to a new report from the Electric Power Research Institute.

The report presents findings that serve as a valuable first step in characterizing RF exposures associated with smart meter technology.

“RF is a ubiquitous and increasing presence in our daily lives as evidenced by the expanding use of cell phones and other wireless technologies,” said Dr. Rob Kavet, senior technical executive at EPRI. “Smart meters are integral technology to a modern smart grid, but consumers need to be assured that health issues associated with RF exposures from new technologies have been carefully examined and are well understood.

The EPRI research addressed RF from a specific type of smart meter with measurements conducted at the manufacturer’s test facility. For a continuously-operating rack of 10 meters, each operating at a nominal power rating of 250 milliwatts (typical of many residential units), the RF power density level 1 foot in front of the rack was 8 percent of the FCC limit; at 20 and 50 feet, these values dropped to 0.18 and 0.11 percent, respectively. From 8 inches behind the rack, RF power density was 0.6 percent of the FCC limit.

The EPRI report also included detailed characterization of RF emissions from individual meters under laboratory conditions, analysis of individual smart meter activity from more than 53,000 meters deployed in the Southern California area, and measurements of RF in a variety of ambient residential and community environments.

Smart meters of the type measured in the EPRI study use wireless communications to transmit data on electricity use, report outages, regulate load flow and other functions. They are integral in the development of a smart grid that can provide electricity customers pricing options, help system operators pinpoint outages more quickly and improve reliability and efficiency.

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