Page 38 - EE Times Europe September 2021

38 EE|Times EUROPE

Adding Intelligence to the Grid

While yesterday’s grid was unidirectional, energy today needs to flow both to and from the consumer in a decentralized, digitized grid.
(Source: Veritone)

deployed in a desert state could be trained
partly with data from farther north that
would include more instances of those par-
ticular conditions.

GRID EDGE
The grid of the future will also make use of AI
at the edge. The “smart meter” of 10 years ago
will get smarter as the use case shifts further
from replacing human meter readers to taking
more of a role in predicting consumer demand
and supply from solar panels and EVs using AI.
According to Spieler, today’s smart meters
use very little of the data to which they have
access. A typical meter might have eight
channels of data available, while down-
stream devices such as smart thermostats
might be collecting as many as 20 or 30
channels of data.
“Every smart meter today has a chip in it,”
he said. “The question is, will it be powerful
enough to process the amount of data? We
envision the smart meter could become like
an iPhone: It captures a ton of data, and
then utilities, consumers, and others can
apply applications on top of that to optimize
energy efficiency.”
In one scenario, if a substation went down,
smart meters could provide the necessary
data to create a neighborhood microgrid,
which could share energy from solar or EV
batteries among neighbors. In the event of
extreme weather, AI-enabled smart meters
could also potentially be used to switch off
power to non-essential loads as a kind of
smart load-shedding scheme. During last win-
ter’s power grid crisis in Texas, for example, An overview of Veritone’s AI solution for monitoring and controlling the power grid in real
power to Houston’s pool pumps could have time (Source: Veritone)

SEPTEMBER 2021 | www.eetimes.eu