Using data from meters and demographic sources, GridGlo
can create an energy efficiency profile of consumers and regions. Here, green
indicates relatively high energy efficiency.
With millions of smart meters being installed, utilities find themselves atop
a mountain of information but with a dearth tools to make sense of it all.
GridGlo is ready to dig into
all that data. The start-up today announced that it received $1.2 million to
build its business of providing applications and data collected from smart
meters and other sources to utilities and software developers. Nonprofit
research center CUBRC provided the funding
and will create the algorithms for analyzing meter data.
GridGlo now has trial programs with six utilities in the U.S. with its
services, which are built by combining meter data and publicly available
demographic data, financial records, and satellite imagery. The information can
be used to forecast power demand more accurately or to get a better picture on
how much energy customers consume, said CEO Isaias Sudit. Today, utilities rely
on weather information to forecast power demand for the following day.
The data could also used to measure the effectiveness of demand-response
programs in which utilities offer a financial incentive for customers to reduce
energy use during peak times.
GridGlo’s plan is to sell applications to utilities or access to its data.
Over time, it expects to make that data available to third-party companies to
create custom applications. For example, a developer could write an application
that links credit card reward programs to a utility energy-saving program, he
The system is designed with a privacy module so that aggregated data does not
reveal personal information. Some applications will require opt-in approvals,
GridGlo was formed about a year and a half ago to take advantage of the
amount of data now available from meters, which can report power consumption
figures in hourly or fifteen-minute intervals.
“If all the data from meters in the next two or three years becomes
available, we are talking about five to six billion data points every hour just
on the energy side. Imagine adding 1,300 attributes to that and 140,000
[utility] subscribers,” Sudit said. “We are talking about massive amounts of
data. Nobody knows how to understand it and monetize it.”
The company hopes to have its software and data in use at utilities in about
a year, he said.