Machine learning can boost the value of wind energy | Google Keyword blog

Also see Google and DeepMind are using AI to predict the energy output of wind farms | The Verge, which notes "This isn’t the first time DeepMind’s AI expertise has been used in this way. Back in 2016, Google announced that it had cut the power costs of its data centers by 15 percent thanks to the AI lab’s help. In 2018, Google went further and gave these AI systems even more control. And there were reports in 2017 that DeepMind was in talks with the UK’s national electricity grid agency to help it balance supply and demand."

"Using a neural network trained on widely available weather forecasts and historical turbine data, we configured the DeepMind system to predict wind power output 36 hours ahead of actual generation. Based on these predictions, our model recommends how to make optimal hourly delivery commitments to the power grid a full day in advance. 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.
Although we continue to refine our algorithm, our use of machine learning across our wind farms has produced positive results. To date, machine learning has boosted the value of our wind energy by roughly 20 percent, compared to the baseline scenario of no time-based commitments to the grid."

Machine learning can boost the value of wind energy | Google Keyword blog