Katie Fehrenbacher of GigaOM recently asked, “What happens when you leverage technologies like IBM’s artificial intelligence engine Watson for clean power? The answer is the awesomely named Watt-sun project, a machine learning platform that IBM Research has quietly been building over the last year, and which is now highly accurate at predicting how cloud cover, weather and atmosphere (among many other data points) affect the way solar panel systems operate.Solar forecasting has been around as long as solar panels have been plugged into the grid. But the forecasting systems historically haven’t been all that accurate, given that so many factors can contribute to the amount of sunlight that’s able to descend from the sky and onto the solar panel and then get converted into electricity.”
She continues, “To build a better system, Watt-sun created a platform that blends dozens of currently available solar forecasting models created by organizations, government bodies and companies throughout the years. Watt-sun then takes this blended forecasting model and adds in tons of data about environmental and atmospheric conditions, about the solar plants and about the surrounding power grid. The more information Watt-sun sucks in, the smarter it gets. On a couple test sites IBM Research has installed ‘sky cameras,’ fish-eye lens cameras that are pinned onto poles or the rooftops of buildings and continuously stream visual data about the atmosphere and cloud density over the solar site. Increasingly IBM is also adding in satellite data, looking down on the solar system from way up in space.” Read more here.
Learn more about the latest on IBM Watson from Chris Welty, Research Scientist, IBM T.J. Watson Research Center. Chris will be speaking at the Cognitive Computing Forum, August 20-21. Registration is open.
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