National Grid examining artificial intelligence to make power grid 10 per cent more efficient

Power infrastructure monopoly in talks with DeepMind about applying AI to the power grid

National Grid is to examine how artificial intelligence can be used to make the UK's power distribution infrastructure more efficient.

The company admitted over the weekend that it is in talks with Google's DeepMind artificial intelligence unit, which it acquired for $400m in January 2014, as well as a number of other AI specialists.

"We are in the very early stages of looking at the potential of working with DeepMind and exploring what opportunities they could offer for us," a spokesperson for National Grid told City AM. "There's huge potential for predictive machine learning technology to help energy systems reduce their environmental impact," they added.

The news was broken on Saturday when DeepMind co-founder and CEO Demis Hassabis claimed in an interview with the Financial Times.

"We're [in] early stages talking to National Grid and other big providers about how we could look at the sorts of problems they have. It would be amazing if you could save 10 per cent of the country's energy usage without any new infrastructure, just from optimisation. That's pretty exciting," Hassabis told the FT.

He continued: "There's huge potential for predictive machine learning technology to help energy systems reduce their environmental impact… One really interesting possibility is whether we could help the National Grid maximise the use of renewables through using machine learning to predict peaks in demand and supply."

DeepMind co-founder Mustafa Suleyman claimed that the application of DeepMind's algorithms to Google's own power infrastructure has helped to reduce its cooling power needs by 40 per cent, and improved its overall energy efficiency by 15 per cent.

DeepMind is now talking about applying these algorithms on a grander scale.

At an event last year, Suleyman said: "All of our algorithms that we develop are inherently general and so given some data set, we should be able to train an algorithm based on some inputs, develop a model, predict some outputs, and then provided we have access to the controls, we should be able to deliver similar sorts of performance."

The National Grid faces a challenge accommodating the increasing output from renewable technologies, and re-shaping the power grid accordingly. The grid is currently largely shaped to accommodate major outputs from power stations located not too far from major centres of population.

However, renewables such as offshore wind generation is not only intermittent, but still requires heavyweight infrastructure - cables, transformers etcetera - to take its power to customers.