IBM Researcher Hendrik Hamann talks about forecasting conditions for solar power generation.
"Solar is without a doubt the hardest to predict," said Hendrik F. Hamann, project lead for IBM's Watt Sun program, one of two funded by the U.S. Department of Energy to develop accurate forecasting systems for the energy industry.
The main issue is that solar panels turn on and off with little advanced notice, and require other power plants to increase or decrease output in response.
In a few years, when it is estimated that solar will make up a larger slice of New England's electric grid, the momentary shifts in power output will require immediate responses from power plants to maintain balance in the electric grid.
described the need for forecasting through this metaphor: If you need to write an email, but your computer is off, you will have to wait a few minutes for it to start up.
, 46, standing in front of a grid of four flat-screen computer displays, selected a small array in Rutland, Vt.
The volume of data and specificity of modeling need to accurately predict where, when and how long the sun will shine on solar panels throughout the country make the Watt Sun application a "perfect big data problem," Hamann