Google’s machine learning technology likely to better predict UK electricity demand
Google’s DeepMind is in discussions with the UK’s National Grid to use artificial intelligence to help balance energy supply and demand in Britain.
“We're 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,” Demis Hassabis, DeepMind’s chief executive told the Financial Times.
National Grid operates, as well as owns, infrastructure that carries electricity around the UK. It serves the crucial role of ensuring there is enough power to meet demand at all times.
National Grid’s role in balancing the system has become more difficult in recent years, however, as intermittent renewable sources of electricity — such as wind and solar power — have become a bigger part of Britain's energy mix.
DeepMind’s algorithms could more accurately predict demand patterns and help balance the national energy system more efficiently.
“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 said, adding that it was in the process of exploring a “possible partnership”.
National Grid said: “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.
“We are always excited to look at how the latest advances in technology can bring improvements in our performance, ensure we are making the best use of renewable energy, and help save money for bill payers.” Last July, London-based DeepMind announced that its machine learning algorithms had cut electricity usage at Google’s data centres by 15 per cent.
The smart algorithms were able to predict load on the data centres’ cooling systems and control equipment more efficiently, resulting in a 40 per cent reduction in the amount of energy used for cooling. Analysts estimate that could translate to savings of hundreds of millions of dollars for Google over several years.
“Because that’s worked so well we're obviously expanding that capability around Google, but we'd like to look at doing it at National Grid-scale,” Mr Hassabis said. “We think there’s no reason why you can't think of a whole national grid of a country in the same way as you can the data centres.”
Google’s DeepMind is in discussions with the UK’s National Grid to use artificial intelligence to help balance energy supply and demand in Britain.
“We're 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,” Demis Hassabis, DeepMind’s chief executive told the Financial Times.
National Grid operates, as well as owns, infrastructure that carries electricity around the UK. It serves the crucial role of ensuring there is enough power to meet demand at all times.
National Grid’s role in balancing the system has become more difficult in recent years, however, as intermittent renewable sources of electricity — such as wind and solar power — have become a bigger part of Britain's energy mix.
DeepMind’s algorithms could more accurately predict demand patterns and help balance the national energy system more efficiently.
“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 said, adding that it was in the process of exploring a “possible partnership”.
National Grid said: “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.
“We are always excited to look at how the latest advances in technology can bring improvements in our performance, ensure we are making the best use of renewable energy, and help save money for bill payers.” Last July, London-based DeepMind announced that its machine learning algorithms had cut electricity usage at Google’s data centres by 15 per cent.
The smart algorithms were able to predict load on the data centres’ cooling systems and control equipment more efficiently, resulting in a 40 per cent reduction in the amount of energy used for cooling. Analysts estimate that could translate to savings of hundreds of millions of dollars for Google over several years.
“Because that’s worked so well we're obviously expanding that capability around Google, but we'd like to look at doing it at National Grid-scale,” Mr Hassabis said. “We think there’s no reason why you can't think of a whole national grid of a country in the same way as you can the data centres.”
