May, 2008

Wind Power in Spain

Continued from Page 6

The model works by taking advantage of different global atmospheric models and the meteorological information available from various satellite systems. Engineers input this information along with the conditions on the ground. They have developed statistical models that learn from the wind farm’s actual performance and use that information, coupled with the input, to forecast conditions an hour to two days ahead.

“If a wind farm has been working for the last year, we know every hour how many megawatt-hours it produced,” Blanco says. “So we take this on-the-ground experience and use it with the information from the global atmospheric model. And we’ve developed the statistical relationship, the equation, that translates these atmospheric conditions into generation in megawatts.”

He admits that the model is weakest when a turbine first begins operation and works best after a wind farm has been running for a while. For the first week or two, the company makes its forecasts partly on the basis of simulations from other wind farms, but that’s not necessary for long.

“It has an exponential learning curve,” says Blanco. “In a few months the system has seen almost every atmospheric condition possible on that farm. And a month is nothing in the life of the wind farm”—a typical facility is usually expected to produce power for about 20 years. He says the company has probably improved the accuracy of its wind-power forecasting by about 40 percent since 2003.

Meteológica works with wind farms across Europe and in North America and Asia as well, though international expansion has been cautious and deliberate. Instead of opening marketing offices in a variety of countries, the company attracts new clients through personal meetings and the strength of its track record. All the computations
are done from the 17-person office in Madrid.

Another company important in forecasting is Kintech, which provides technology and equipment for collecting meteorological information. Its sensors and data loggers have captured most of the Spanish market, and its devices measure conditions in more than 50 countries. According to general manager Tirso Vasquez, the company has succeeded by customizing remote satellite communications from the data loggers to the customers’ needs.

Systems for understanding wind potential in a given region still have the capacity to get better. To that end, AWS Truewind, an American powerhouse in wind-farm siting and forecasting, joined forces with the Spanish company Meteosim, a spinoff of a meteorological research team at the University of Barcelona. Having honed its technique in small, narrowly focused areas, Meteosim began working with new models for mapping wind resources around the world, providing that information to governments, nonprofit institutions, and potential wind-farm developers.

“Typically the main approach has been to install a tower, wait for two years, and see how much wind the wind developers or someone has been measuring on that tower,” says Meteosim director Joan Aymamí. Instead, Meteosim provides mapping information on specific, narrowly defined sites. “With this approach, a client has a very accurate idea of where to go, where are the best places in a big region.”