But getting wind turbines to be hyper-efficient means more than just plunking a few down in a generally windy area, and raking in the power and the money. Companies, investors, and power consumers must know what to expect to the highest degree of certainty. Having a turbine under-perform can drastically reduce the return on investment in these multi-million dollar machines. The opposite is true, as well. Put a wind turbine in a windier area for which it was designed, and you will damage a turbine faster, sometimes catastrophically.

This is the challenge that faces the Danish turbine manufacturer . The company has made and installed more than 43,000 land-based wind turbines in 66 nations since its inception in 1979. Vestas turbines are responsible for generating 90 terawatt-hours -- just over 20 percent -- of the world's wind power alone.

To help them achieve optimal wind turbine placement and better operational control and forecasting of the turbines once they are installed, Vestas has relied on its own wind library, which includes data from 35,000 global weather stations, as well as data that's incoming from its own turbines.

"That gives us a picture of the global flow scenario," explained Lars Christensen, the Vestas VP responsible for turbine placement and monitoring. "Those models are then cobbled to smaller models for the regional level called mesoscale models. The mesoscale models are used to establish our own huge wind library so we can pinpoint a specific location at a specific time of day and tell what the weather was like."

How detailed is the library? In its early versions, the library could give details for a grid with 27-by-27 kilometer sides (about 282 square miles). But with improvements in computational flow models, Vestas could massively increase the resolution to 10-by-10 meters-just over 1,075 feet, which is about the footprint of an average American home.