Monday, October 29, 2012

Gleaning Clues on Sunny Days From the Clouds


Click Here
 

Business DayEnergy & Environment

 

Gleaning Clues on Sunny Days From the Clouds

Sandy Huffaker for The New York Times
Carlos F. Coimbra with equipment used to track cloud cover, on a rooftop at the University of California, San Diego.
By DAVID FERRIS
Published: October 23, 2012
CARLOS F. COIMBRA knew from the outset that he would have to crack the code of clouds. As an engineering professor new to the University of California’s campus in Merced, he led a successful drive to get 15 percent of the school’s power from an array of solar panels.

Related

Green
A blog about energy and the environment.
Go to Blog »
But clouds, wandering and capricious, had foiled his efforts on two occasions by casting sudden shadows, forcing the school to rely on conventional power instead. To neutralize the clouds, he would have to track them.
So Professor Coimbra, a Brazilian-born expert in fluid mechanics with a flair for computer modeling, tried a new kind of forecast. The campus would make better use of sun power if he could figure out exactly when a puffy drifter would arrive overhead. He wrote a computer algorithm to project how clouds move and change shape as they move across the sky — one of the most complex and chaotic phenomena on earth, influenced by an endless set of variables.
Now, six years later, Professor Coimbra, 44, and his collaborator, Jan P. Kleissl, 37, have created a forecasting engine that they say is 20 to 40 percent more accurate than the model in common use. Weather, energy and power grid experts said that the innovation could accelerate the adoption of renewable energy, save billions of dollars in energy costs and help turn cloud-watching from an idle pastime into a vital and profitable part of the weather forecast.
“I can’t tell you what’s going to happen at 4:23 p.m. on a Sunday,” said Professor Coimbra, whose forecasts extend to seven days but with decreasing accuracy. “But I can tell you what will happen between noon and 6 today.“
Potential cost savings are drawing the interest of companies that build and operate solar-power plants, as well as utilities and grid operators. Each bets a bottom dollar on when the sun will come out tomorrow. A fine-tuned forecast makes it easier for utilities and grid operators to use the sporadic power of sun and wind when they are available, giving renewable energy a reliability close to that of a fossil-fuel or nuclear power plant.
Furthermore, it could help utilities predict exactly when homeowners will turn on their air-conditioners in the summer, which could reduce the power grid’s need for backup power plants.
As it saves money in energy markets, the technology could also shake up the world of weather forecasting by providing greater resolution. Such data could give airports a firmer window of when storms will arrive and leave, resulting in fewer flight delays.
It could tell farmers when to expect the first frost, or when a rainstorm will hit, reducing the need to pump water for irrigation. A precise prediction could guide the maneuvers of forest firefighters, project the path of bioterror attack or pinpoint the path of a tornado.
Melinda C. Marquis, the renewable energy project manager at the government’s Earth System Research Laboratory in Boulder, Colo., speculated that this technology, born to serve renewable energy, might end up changing our relationship with weather. “Any improvement that we make here for renewable energy will be very, very important, in some cases more important, for other sectors of the economy,” she said.
But the forecasts are likely to find their first application at solar and wind farms. Currently, the caprice of weather makes electricity more expensive for producers and consumers of utility-scale renewable power. Traditional weather forecasts aren’t accurate enough to predict when the sun will poke through the clouds on a partly overcast day and make mistakes in estimating the length and strength of high winds.
To compensate, some solar and wind farms maintain large, expensive banks of backup batteries to store surplus energy and release it when needed. Grid operators scramble to buy power on the spot market when weather-related energy sources fall short, buying power for 10 to 100 times more than they would if they bought a day ahead, according to Manajit Sengupta, a scientist who leads solar-forecasting efforts at the National Renewable Energy Laboratory. A perfect forecast for wind, if it represented 20 percent of the power supply, would save $1.6 billion to $4.1 billion a year, according to several studies.
A version of this article appeared in print on October 24, 2012, on page F7 of the New York edition with the headline: Gleaning Clues on Sunny Days From the Clouds.
  • E-MAIL
  • SHARE
Get Free E-mail Alerts on These Topics
Alternative and Renewable EnergyElectric Light and Power
Solar EnergyWind Power
 
Posted by at
Labels:

No comments:

Post a Comment

Subscribe to: Post Comments (Atom)