Google is predicting wind patterns a day in advance so grids can rely on it more

Wind power has become increasingly popular, but its success is limited by the fact that wind comes and goes as it pleases, making it hard for power grids to count on the renewable energy and less likely to fully embrace it. While we can’t control the wind, Google has an idea for the next best thing: using machine learning to predict it.

Beginning last year, Google fed weather forecasts and existing turbine data into a machine learning platform, which churned out wind power predictions 36 hours ahead of actual power generation. Google could then make supply commitments to power grids a full day before delivery. That predictability makes it easier and more appealing for energy grids to depend on wind power, and as a result, it boosted the value of Google’s wind energy by roughly 20 percent.

Not only is this a testament to how machine learning could boost the adoption of wind energy, it’s also an example of machine learning being put to good use—instead of jumping into your text thread to recommend a restaurant when you start talking about tapas.

This story was one of the best from 2019, and we are happy to include it in our “12 Days of Optimism” as we get ready to welcome 2020!

Solution News Source

Google is predicting wind patterns a day in advance so grids can rely on it more

Wind power has become increasingly popular, but its success is limited by the fact that wind comes and goes as it pleases, making it hard for power grids to count on the renewable energy and less likely to fully embrace it. While we can’t control the wind, Google has an idea for the next best thing: using machine learning to predict it.

Beginning last year, Google fed weather forecasts and existing turbine data into a machine learning platform, which churned out wind power predictions 36 hours ahead of actual power generation. Google could then make supply commitments to power grids a full day before delivery. That predictability makes it easier and more appealing for energy grids to depend on wind power, and as a result, it boosted the value of Google’s wind energy by roughly 20 percent.

Not only is this a testament to how machine learning could boost the adoption of wind energy, it’s also an example of machine learning being put to good use—instead of jumping into your text thread to recommend a restaurant when you start talking about tapas.

This story was one of the best from 2019, and we are happy to include it in our “12 Days of Optimism” as we get ready to welcome 2020!

Solution News Source

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