In this piece, we explore how AI has the potential to deliver the active management that will be required for the grid of the future. Powerful intelligence will be able to balance grids, manage demand, negotiate actions, enable self-healing and facilitate a host of new products and services.

1. Artificial Intelligence
in Energy and
Utilities
2020 Indigo Insights Innovation Series
© Indigo Advisory Group 2020 | indigoadvisorygroup.com

2. Utilities and a host of energy companies are increasingly interacting with new technologies such as
Artificial Intelligence (AI), blockchain and robotics. In our latest #indigoinsights infographic below we
explore AI in the energy sector including emerging applications, key solution providers and how AI fits
into the broader trend of new energy technologies.
HOW THE POWER GRID IS BECOMING THE INFORMATION GRID
In combination with other technologies, AI has the potential to deliver the active management that
will be required for the grid of the future. Powerful intelligence will be able to balance grids, manage
demand, negotiate actions, enable self-healing and facilitate a host of new products and services.
Indeed, AI, will not just lend itself to the energy transition, it will also enable more efficient and
effective utility operations by helping to analyze unstructured data which typically makes up to
80 percent of data in an organization.
Over the next decade advancements in AI, distributed ledgers and robotics will impact a variety of
sectors. For utilities, these trends combined with the dramatic changes in the energy transition such
as distributed energy resources, increased proliferation of sensors on infrastructure and behind the
meter devices and demand management advances will unleash a variety of transformative use cases
in the sector. For example, devices which auto-detect demand levels on the grid and reduce power
could be powered by AI and recorded by blockchain (for more information on blockchain in the
sector, see our dedicated resource center). To that end, we are currently in the midst of what has
been termed the Fourth Industrial Revolution (4IR), and a central part of this revolution will be
energy and all of its components.

5. Artificial Intelligence in Energy and Utilities Infographic
For utilities there are some words of caution with AI however, just as with blockchain, many vendors
rush to be trend compliant and in their external materials often suggest that they have true AI and
distributed ledger technologies part of their solutions. This may not always be the case, and as with all
complex deployments of new technologies, use cases with achievable value propositions should be
first considered as well as those systems that satisfy the need currently. That said, in terms of
applications, and expanding on the infographic, the three largest segments of use case activity
currently include:

6. • Renewable management, where use cases run the gamut of renewable forecasting, equipment
maintenance, wind and solar efficiency and storage analysis. For example, in Germany a
machine-learning program, named EWeLiNE, could work as an early-warning system for grid-
operators to assist them in calculating renewable-energy output over the next 48 hours using
AI and in Japan, GE is using AI to enhance wind turbine efficiency and is raising power output
by around 5% and lowering maintenance costs by 20 percent.
• Demand management is also seeing an explosion of AI activity with use cases covering areas
such as demand response, building energy management systems, overall energy efficiency and
DR game theory. For example, using their AI focused company DeepMind, Google was able to
reduce its total data center power consumption by 15 percent which will translate to hundreds
of millions of dollars over the next several years. Google also suggest that they have already
saved 40 percent alone on power consumed for cooling purposes by using AI.
• Infrastructure management and managing the performance of the grid is also getting AI
attention. In this area use cases include digital asset management, equipment operation and
maintenance and generation management. For example, in a test by Siemens who are
deploying the technology in Asia, after AI took over control of a gas turbine combustion unit,
nitrogen oxide levels dropped by 20 percent. We are also seeing Siemens leverage their industrial
cloud platform, MindSphere, with IBM Watson to deliver predictive analytics, prescriptive analytics
and cognitive analytics.
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