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Since last year, a joint DeepMind and Google project to apply ML to 700 MW of wind power in the central US has so far boosted the value of wind energy by ~20%.
Blog post: deepmind.com/blog/machine-l…
Blog post: deepmind.com/blog/machine-l…
A neural net trained on weather forecasts & historical turbine data predicts wind power output 36 hours ahead of actual generation. Based on these, our model recommends optimal hourly delivery commitments to the power grid 24 hours in advance.
These wind farms—part of Google’s global fleet of renewable energy projects—collectively generate as much electricity as is needed by a medium-sized city! While much remains to be done, this is a promising step forward in applying ML towards environmental challenges.
