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| Sun, 31st May 2020 13:04:00 |
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Thanks To Renewables And Machine Learning, Google Now Forecasts The Wind |
Wind farms have traditionally made less money for the electricity they produce because they have been unable to predict how windy it will be tomorrow.
"The way a lot of power markets work is you have to schedule your assets a day ahead," said Michael Terrell, the head of energy market strategy at Google. "And you tend to get compensated higher when you do that than if you sell into the market real-time.
"Well, how do variable assets like wind schedule a day ahead when you don't know the wind is going to blow?" Terrell asked, "and how can you actually reserve your place in line?"
"We're not getting the full benefit and the full value of that power."
Here's how: Google and the Google-owned Artificial Intelligence firm DeepMind combined weather data with power data from 700 megawatts of wind energy that Google sources in the Central United States. Using machine learning, they have been able to better predict wind production, better predict electricity supply and demand, and as a result, reduce operating costs.
"What we've been doing is working in partnership with the DeepMind team to use machine learning to take the weather data that's available publicly, actually forecast what we think the wind production will be the next day, and bid that wind into the day-ahead markets," Terrell said in a recent seminar hosted by the Stanford Precourt Institute of Energy. Stanford University posted video of the seminar last week.
The result has been a 20 percent increase in revenue for wind farms, Terrell said.
The Department of Energy listed improved wind forecasting as a first priority in its 2015 Wind Vision report, largely to improve reliability: "Improve Wind Resource Characterization," the report said at the top of its list of goals. "Collect data and develop models to improve wind forecasting at multiple temporal scales—e.g., minutes, hours, days, months, years."
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