Impact of AI in energy and utilities

A few years ago, a friend of mine explained the concept of smart grids to me and how Utility companies were looking to partner with both software developers and appliance makers to make it a reality.

The concept was simple. Monitor the usage patterns, collect a lot of data and then recommend an economically rewarding usage pattern. My friend had multiple reasons to move to smart grid – to optimize the infrastructure behind the grids already in use, and to gain the maximum from the subscribers who wanted to utilize the energy.

Today, a few Utility companies have started to utilize Artificial Intelligence to lower utility bills. Not just that, Google announced in 2016 that it utilized its DeepMind algorithm to lower its energy bills. So, is AI still a hype or is it gaining a shape and form in the Energy and Utilities sector?

With all the talks on the Cleaner Energy, AI has taken a centerstage acting as a fuel cell and optimizing the gains. ZenRobotics of Finland uses AI to identify and extract recyclables from waste. Eddy by Flux Farms uses a combination of AI and sensors to allow hydroponic farmers to control and manage pH levels remotely.

NEXTracker who makes devices that shift solar panels to soak in as much direct sunlight as possible has recently acquired a startup called BrightBox Technologies to manage its hardware and add intelligence to it.

Going back to the use case of the smart grid, the power grid is now becoming the information grid. With the advent of smart sensors and smarter processors, the grid is able to optimize its resources and provide the best possible throughput to every consumer.

The use of AI as seen in this infographic by Indigo Advisory Group, is broadly termed into three major categories while shaping the Energy and Utilities sector –

  1. Renewables management
  2. Demand management
  3. Infrastructure management

At the same time, the technologies that are highly in demand for bringing the revolution are –

  1. Robotics – Sensory and control mechanisms
  2. Blockchain – Maturity in distributed ledger management
  3. Artificial Intelligence – Ability to process sensory information and provide signals for control

Nitin Rastogi

Nitin is an EIM enthusiast with a passion for finding patterns and use cases for technology to solve problems. He has a great penchant for noticing patterns and using them for the business growth. Nitin has been working in the field of BPM and ECM and helping his clients solve their problems.

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