Weather forecasts for the grid depend on supercomputers to calculate the flow of heat, water and radiation in the atmosphere and then spit out predictions about what could happen next.
These supercomputers are powerful. But they are also expensive and slow, relative to how quickly the weather changes. A new class of AI-based weather forecasts could change the game for grid operators and renewable energy developers. Will they take hold?
This week, we explore a variety of emerging applications for artificial intelligence in energy.
First, we’ll look at how machine learning can improve and democratize weather prediction with journalist Emma Woollacott, Jack Kelly of Open Climate Fix and Noelia Otero Felipe of the University of Bern.
Then we’ll hear from a few companies that are using AI for demand response, virtual power plants and EV charging. Latitude producer Erin Hardick explores AI trends at the grid edge with Apoorv Bhargava of WeaveGrid, Jae Beom Bae of Leap, Paul McDonald of Opower at Oracle Energy and Water, and Carlos Nouel of National Grid.
