A 2015 study by the National Renewable Energy Laboratory and IBM found that more accurate day-ahead predictions of solar energy generation levels would save ratepayers in California $5 million in avoided costs. Solar forecasts, which integrate weather patterns and solar production estimates to help grid managers predict how much solar energy will be produced across their system on a given day, allow utilities to better allocate resources and avoid the need to ramp up reserve power plants. But grid managers have run into a problem that’s as old as time: it’s hard to predict the future.

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