Cleantech Needs A Weatherman To Know Which Way The Wind Blows

Earlier this year President Obama blasted the nay-sayers ideologically opposed to renewables, comparing these “professional politicians” to the flat earthers of years gone by.

Obama chose to launch his attack from the Solar 1 plant in Boulder City, Nev., an impressive new facility with a 48-megawatt (MW) generating capacity.

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image via the White House

Coinciding with the president’s visit the plant had just been fitted with solar forecasting devices called sky imagers. The imagers scan the skies using a fish-eye lens for a 360-degree view of the horizon and the collected data is then used to generate a 3-D weather model of the upcoming 15 minutes.

More so than Obama’s rebuke, the sky imaging software provides an answer to one of the main drawbacks of renewables which those who are in the business of bashing them like to highlight.

This is the problem of variability. In simple terms, the fact that the sun doesn’t always shine; that wind doesn’t always blow; that the sea is sometimes becalmed.

The unpredictable nature of weather makes energy output from wind, wave and solar hard to accommodate into the energy mix. This is because utilities need a consistent, smooth-flowing supply, not the hikes and troughs produced when, say, clouds obscure the sun at a solar plant or a sudden gale starts blowing near a wind farm.

Proponents of further oil and gas exploration, and of nuclear, claim variability as a fatal flaw in green energy and the reason why traditional fuels will always be needed to make up the shortfall.

In response, clean tech proponents offer the smart grid as a possible solution. The grid, which is still in its infancy, could eventually allow for power to be stored and moved around in such a way that fluctuations in supply and demand are taken care of by the grid itself.

But the smart grid is still some way off and even then, it’s unlikely to be enough on its own to compensate for the variations.

In the meantime renewable energy providers are turning to more sophisticated weather forecasting systems, like the sky imaging devices in Boulder City, to give them a more accurate assessment of what their likely power output is going to be.

These systems are cropping up everywhere across the industry and if it’s true, as Bob Dylan sang, that you don’t need a weatherman to know which way the wind blows, well, that’s because you now need a specialized computer model composed of  high-resolution meteorological data and a complex set of algorithms.

Earlier this year, a team of engineers at Stanford used such a weather model to recommend optimal placement of four proposed interconnected wind farms off the eastern coast of the U.S.

The optimized grid was located in the waters from Long Island, N.Y., to Georges Bank, a shallows about 100 miles east of Cape Cod.

The model took in to account the need to offer a consistent power supply. As a result the researchers recommended placing some of the notional wind farms at near-shore locations where sea breezes blow with regularity, thanks to  the daily difference in temperature between land and sea.

But even the most astute planning can only do so much to mitigate the natural variability of weather and once a wind farm is up and running, its operators need the most up-to-the-minute information to know what to expect.

Paul Willis has been journalist for a decade. Starting out in Northern England, from where he hails, he worked as a reporter on regional papers before graduating to the cut-throat world of London print media. On the way he spent a year as a correspondent in East Africa, writing about election fraud, drought and an Ethiopian version of American Idol. Since moving to America three years ago he has worked as a freelancer, working for CNN.com and major newspapers in Britain, Australia and North America. He writes on subjects as diverse as travel, media ethics and human evolution. He lives in New York where, in spite of the car fumes and the sometimes eccentric driving habits of the yellow cabs, he rides his bike everywhere.