Germany enlists machine learning to boost renewables revolution

Renewable power sources such as wind now provide about one-third of Germany's electricity. The rows of towering wind turbines and legions of glistening solar panels spread across Germany's landscape are striking emblems of the country's shift to non-nuclear, low-carbon power. But although Germany is the world's poster child for renewable energy, its grids cannot yet cope with the erratic nature of wind and solar power. In June, German meteorologists, engineers and utility firms began to test whether big data and machine learning can make these power sources more grid-friendly. "To operate the grid more efficiently and keep fossil reserves at a minimum, operators need to have a better idea of how much wind and solar power to expect at any given time," says Malte Siefert, a physicist at the Fraunhofer Institute for Wind Energy and Energy System Technology in Kassel, Germany, and a leader on the project, called EWeLiNE.