A wind farm in West Texas DeepMind claims it has trained an artificial intelligence system how to predict the energy output of Google wind farms in the U.S. The variable nature of wind makes it difficult to accurately predict how much energy a wind farm could produce in any given time period. But DeepMind says that its AI system— a neural network trained on widely available weather forecasts and historical turbine data — can predict wind power output 36 hours ahead of actual generation with a reasonable degree of accuracy. "Based on these predictions, our model recommends how to make optimal hourly delivery commitments to the power grid a full day in advance," a team of DeepMind researchers wrote in a blog post on Tuesday. "This is important because energy sources that can be scheduled (i.e. can deliver a set amount of electricity at a set time) are often more valuable to the grid." Google claims that DeepMind's AI system has boosted the "value" of its wind energy by roughly 20 per cent. "We can't eliminate the variability of the wind, but our early results suggest that we can use machine learning to make wind power sufficiently more predictable and valuable," the researchers added. DeepMind is a London-headquartered AI lab that was acquired by Google for a reported £400 million in 2014. Today, Google and DeepMind sit under parent company Alphabet. DeepMind has been in talks with the UK's National Grid about how to use DeepMind's AI technology to better predict energy demand. In March 2017, DeepMind cofounder and CEO Demis Hassabis told The Financial Times: "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 optimisation. That's pretty exciting." So far, no major announcements have come from DeepMind and the National Grid. Xiaoqin Ma, head of technology at ONYX InSight, a provider of predictive maintenance for wind turbines, said: "In recent years, a variety of initiatives have brought AI to the renewables industry, from blade inspection to weather forecasting and predictive maintenance. This development from Google's DeepMind is the latest proof for operators that modern data use can bring substantial benefits to the renewable energy industry. "As subsidies for renewable energy begin to drop away, wind energy projects must protect their returns by looking at simple project economics: how much power is produced, how much it is worth, and how much money is spent maintaining the turbines. AI is crucial to streamlining power production and asset maintenance, allowing renewable energy to thrive in a post-subsidy world. "It is great to see DeepMind’s engagement with wind energy. It is the latest demonstration of how AI can accelerate the growing movement towards a smarter, more efficient industry."
Alphabet-owned, London-based DeepMind has developed an AI system, which it claims can accurately predict the energy output of Google's wind farms. DeepMind said its AI used weather forecasts and historical turbine data to estimate energy generation 36 hours ahead of real time, a move that Google said increased the grid value of its energy by about 20%.