THE 1996 Olympics in Atlanta did not all go IBM’s way. For all its technical prowess, the computer giant managed to bungle the reporting of some competition results. On the plus side, it was at the Games that IBM first deployed Deep Thunder, a novel computer model which warned the organisers when and where to expect inclement weather—and correctly predicted that a thunderstorm forecast by other meteorologists would not affect the closing ceremony. Deep Thunder has since gone through countless iterations, or which the latest, called the Hybrid Renewable Energy Forecaster (HyREF) IBM unveiled on August 12th.
As its name suggests, HyREF is meant to make it easier to incorporate wind energy into the grid. Owing to Aeolian vagaries, it is hard for operators of wind farms to forecast output accurately—or indeed to work out where best to erect turbines in the first place. The ability to predict where wind will blow and how hard is therefore crucial if wind power is to live up to its boosters’ hopes.
IBM’s system increases this all-important predictability using a handful of sophisticated technologies. Clever sensors mounted on individual turbines gauge wind speed, temperature and direction. Their readings are combined with data from traditional measurement towers equipped with meteorological instruments, as well as past-weather data. Indeed, Brad Gammons, who runs IBM’s energy and utilities arm, says that most of the progress since Deep Thunder has taken place over the last two years, mainly thanks to the rapidly growing availability of information, both real-time and historical. In particular, Mr Gammons says, this is true for China, the world’s biggest greenhouse-gas emitter, but also its biggest investor in renewable energy.
Written by H.G. To read the full article, click here.