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ISSN 2753-7757 (Online)

How artificial intelligence will make the electricity grid smarter

3/8/2022

6 min read

Electricity pylon in foreground with dramatic blue and yellow sky behind Photo: Freepik
Artificial intelligence and machine learning can help adapt the electricity grid for the energy transition without the need to rebuild its infrastructure

Photo: Freepik

Advances in artificial intelligence (AI) and deep machine learning (ML) have the potential to make the electricity transmission and distribution grids more reliable and better able to cope with historic changes in the way power is generated and consumed – including the predicted mass uptake of electric vehicles (EV), explains John Langley-Davis, Head of Technology at Fundamentals.

The key problem for UK grid operators is that they have inherited a system which was designed for an era of centralised generation and relatively predictable consumption, running on assets which are getting old. Some underground low voltage (LV) cables, for example, were installed more than 100 years ago and have been patched and mended many times. Many transformers, which control voltages, were built well over 50 years ago and have yet to be upgraded to modern standards.

 

Rebuilding the grid infrastructure wholesale is not an option. It is far too expensive and disruptive. Nor is it entirely necessary, apart from targeted reinforcement and replacement. The real challenge is to make maximum use of the assets we already have by making them smarter – and using smarter technology to better manage them. So how can AI and deep ML help?

 

Old tech costs 
Take the thousands of miles of buried LV cables which are the final links between the grid and consumers. Deteriorating joints and disintegrating insulation cause many thousands of failures of supply each year – representing 40% of customer complaints and 75% of customer minutes lost being the average amount of time that a customer is without power in a year. The first thing a network operator knows about an incident is usually when customers report an outage, because a fuse on the network has ruptured and tripped out the power.

 

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