Smart Cities

DeepMind and National Grid Announce Potential Partnership

An electricity grid has often been equated to a central nervous system, sending signals across its extensive network to bring its body of connections to life. Like a central nervous system the power grid needs a brain to turn intention into action, one that can learn and anticipate in order to develop efficiency and functionality. A budding technology partnership in the UK seeks to add an intelligent mind to the country’s rapidly evolving national grid. Google-owned, artificial intelligence (AI) company DeepMind is in talks with the UK’s National Grid about a possible partnership, that highlights the potential of using AI technology to make the supply of energy across the UK more efficient. As the UK continues to strive for greater adoption of renewable energy, power system intelligence has never been more important. “There's huge potential for predictive machine learning technology to help energy systems reduce their environmental impact," said a spokesperson for the company. "One […]

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An electricity grid has often been equated to a central nervous system, sending signals across its extensive network to bring its body of connections to life. Like a central nervous system the power grid needs a brain to turn intention into action, one that can learn and anticipate in order to develop efficiency and functionality. A budding technology partnership in the UK seeks to add an intelligent mind to the country’s rapidly evolving national grid.

Google-owned, artificial intelligence (AI) company DeepMind is in talks with the UK’s National Grid about a possible partnership, that highlights the potential of using AI technology to make the supply of energy across the UK more efficient. As the UK continues to strive for greater adoption of renewable energy, power system intelligence has never been more important.

“There's huge potential for predictive machine learning technology to help energy systems reduce their environmental impact," said a spokesperson for the company. "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’s advanced machine learning system rose to fame early last year after beating world champion Lee Sedol at the ancient Chinese chess-like game ‘Go.’ Perhaps more impressively, it increased efficiency at Google’s data centers by 15% and reduced their need for cooling by 40%. Speaking at a conference late last year the FTSE 100 firm’s co-founder Mustafa Suleyman said the technology used to help Google and one designed for the national energy infrastructure "essentially all have the same characteristics."

“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,” he explained.

Power and cooling capabilities are maxed out in many data centers; expenses frequently outstrip the cost of IT equipment. Typically power distribution and cooling equipment consume as much as 60% of data centre power. As we previously reported, the rampant energy consumption of data centers often undermines the energy efficiency gains their servers help create for customers.

Helping giant data centers go green seems no more challenging than aiding an electricity grid reduce unnecessary wastage. Even small efficiency gains on a National Grid scale would represent huge benefits for the provision of electricity, the utility bill payer and the environment.

“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% of the country’s energy usage without any new infrastructure, just from optimization. That’s pretty exciting,” Demis Hassabis, DeepMind’s chief executive said in an interview with the Financial Times.

Not only is this type of development great because it creates efficiency, but it is also necessary for the inclusion of cleaner, renewable power into the energy mix. We are reaching the point, in some regions, where the limitation of renewable energy is not due to the lack of generation but the inability of the grid to incorporate such fluctuating energy sources.

It will take all our smartest technologies, including AI, energy storage, blockchain and others to reach our full renewable energy potential.

“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 maximize the use of renewables through using machine learning to predict peaks in demand and supply,” DeepMind announced.

In addition, an AI enabled grid will no doubt play well into the on-going harmonization of smart grid & smart buildings, which promises further savings.

The energy and technology sectors will be watching this space, anticipating what this potentially powerful partnership may achieve. In a significant and ambitious market like the UK, AI developments for the power grid could have huge implications for larger power systems around the world. It is still early days, as the National Grid reminds us, but the prospective benefits to all stakeholders are clear and great.

“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," said National Grid. “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.”

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