The U.S. Electric Industry faces an interesting challenge ¡ª more than three-quarters of Americans do not recognize or understand the industry's best available technologies to improve energy efficiency, reduce energy costs and curb global warming ¡ª the smart grid and smart meters.
Seventy-nine percent of Americans claim to know little or nothing about the smart grid, while 76 percent lack knowledge or understanding of smart meters, according to results of the latest Market Strategies International E2 (Energy + Environment) Study, a national survey designed to gain an understanding of American's attitudes and opinions about energy and energy-related issues.
However, the study also shows that Americans are very supportive once the technologies have been explained to them.
The smart grid is an electricity distribution network that uses digital sensing technology (smart meters) to manage the flow of electricity from the utility to its customers. Smart meters communicate between the customers and the utility, providing data about electricity usage so the utility can monitor demand, adjust availability and improve reliability.
"There are very clear benefits to these technologies," said Jack Lloyd, a vice president in the Energy Division at Market Strategies. "Still, the lack of knowledge of the smart grid and smart meters could hinder their implementation and delay the energy and environmental benefits they can provide," he said.
There remains room for education about both technologies. According to the survey:
"The evidence is clear. The electric industry must make smart grid and smart meter education a top priority if it hopes to implement the technologies successfully across the U.S.," said Lloyd.
This latest version represents the ninth wave of the long-term survey. For this most recent version, Market Strategies interviewed a national sample of 1,168 adults between October 14 and October 25, 2010. Respondents were recruited via an online panel to reflect key demographic characteristics of the U.S. population. The data also were weighted by age, gender, race/ethnicity and census region to bring the sample into alignment with the U.S. Census.
