The company's intention is to schedule the deliveries of energy output 36 hours ahead based on knowledge from prior data. To achieve this, Google employs a software developed by its subsidiary, DeepMind. The software utilizes machine learning algorithms to foresee the future energy production of wind farms. Google has been successfully using AI software for many years. In 2016, the company cut its power cost by 15% utilizing AI lab's help.
Google has been trying for years to obtain its energy usage completely by renewable sources. And in 2018, after investing in solar and wind farms, the company succeeded to do so. But, the manipulation of wind power is challenging as the energy production of a particular farm is unstable and therefore, storing and delivering procedures frequently have to change. “The variable nature of wind itself makes it an unpredictable energy source — less useful than one that can reliably deliver power at a set time,” Google stated.
According to Google officials, machine learning energy predictions are 20% more accurate than those from common approaches. No further investigation regarding the long-term profits and the total energy output of wind farms have yet been conducted but it is certain that the software's impact is beneficial. “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. This approach also helps bring greater data rigor to wind farm operations, as machine learning can help wind farm operators make smarter, faster and more data-driven assessments of how their power output can meet electricity demand,” Sims Witherspoon, a product manager at DeepMind and Will Fadrhonc, Google’s Carbon Free Energy program lead, stated in a common post.
Google supports and highly invests in DeepMind despite being a loss-making company (loss of $368 million in 2017). DeepMind has carried out significant scientific work and it will become a profitable firm as long as its software will be further utilized in industry.