Autonomous drones could soon power the UK’s energy grid

“We’re moving into a future where these drones will fly all over the countryside themselves,” McKenna says. “But the long-term future of this software is that it will take people on a journey.”

With the UK’s National Grid, which manages the country’s energy supply, the relationship was more concrete, after the organization committed funds to accelerate the development of Sees.ai’s technology. The first objective of the partnership is to prove that the system can be used to better maintain the 21,900 steel pylons of the network.

The network needs constant tune-ups to remain reliable, and regular inspections are important. The national grid enjoys 99.99% reliability: something it wants to improve by locating critical problems long before failures occur. In the humid UK climate there is a high risk of corrosion, which is difficult to stop once it has started. Pylons should be replaced when rust has affected their structural integrity, so early detection can save costs in the long run.

The National Grid spends around £16m each year painting its pylons and forecasts a cost of £35m over the next five years to replace corroded steel. Taking into account the high R&D costs, Sees.ai’s drone system is not necessarily cheaper than other inspection methods, but the National Grid predicts that it will enable more frequent data capture and faster which, in turn, will reduce costs through more targeted assets. replacement. If the trials are successful, the National Grid predicts savings of over £1million for UK consumers by 2031.

But until cost-effective drones are deployed on a large scale, the only option is to use helicopters. A helicopter can inspect 16 pylons every hour at a cost of £2,000 per hour, but flying a VLOS drone isn’t much better as it’s laborious and slow with the pilot below. On a good day, VLOS drone teams can inspect no more than 10 pylons. “It’s the human element that causes the problems,” says Mark Simmons, National Grid’s condition monitoring manager.

Sees.ai is not alone in tackling this problem, but the systems that many other companies rely on use GPS and compass for positioning. The problem is that these technologies are vulnerable to failure, especially when in close proximity to steel or strong electromagnetic fields, which occur around high voltage power lines. Relying on pre-existing data can also be precarious as the world is constantly changing.

According to David Benowitz, research manager at the Drone Analyst research platform, GPS technology is also not always accurate, especially when used to measure elevations or in rural areas with poor satellite coverage. Because there will always be this “bubble of doubt”, he says, there is a higher risk of collisions in busy airspace. With more vulnerability comes more risk.

The only way to deploy these technologies is therefore to limit the risks in other ways, for example by performing simpler flights further away from potential collisions. But with each limitation imposed, “the applicability and scalability of the solution decreases,” says Benowitz. If we want to replace manned helicopters, we need to develop a solution that “does not have these limitations”, that can safely perform overviews and detailed inspections of assets on the majority of the network, not just sections distant.

For this to happen, there must be more reliable and robust technologies: every operating system must have several layers of security. “For us to fly close enough to the pylons to acquire the best data, we need more intelligence than GPS,” says Hjamlmarsson. But there also needs to be changes among regulators like the FAA and CAA to create the space for these more advanced systems to be developed and properly tested so that they can still be proven to be safe. “It’s the chicken or the egg scenario,” says Benowitz. “These systems are not state-of-the-art, so there is no problem deploying them on a large scale and at a lower cost, but the regulations need to be updated.”

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