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Siemens makes wind power more efficient

Siemens Energy has entered into a cooperative research and development agreement (CRADA) with Lawrence Livermore National Laboratory (LLNL) to conduct atmospheric modelling research that is expected to help windfarms operators and owners increase operating efficiency and providing more power to power grids.

 

Under the two-year CRADA, Livermore will provide high-resolution, numerical weather prediction models to forecast power generated by the wind. Siemens will translate Livermore’s forecasts of wind speed and wind direction at each turbine into power collected.
 
Many US windfarms are yielding up to 20% less energy than predicted because of uncertain forecasts, according to Siemens Energy. More accurate wind predictions could enable windfarm operators and owners to know hours or days ahead of time how wind conditions will affect power generation.
 
“Accurate and timely forecasts of power availability will enable turbine owners and operators to generate optimal bids on wind turbine production and, in turn, maximise both financial benefit and grid support,” says Henrik Stiesdal, Chief Technology Officer at Siemens Wind Power.
 
“More accurate predictions also could reduce the investment risks in wind-powered projects and could improve the design of tall wind turbines to withstand the high-turbulence environment higher in the atmosphere.”
 
A recent study of 3.3 GW of wind generation in New York State quantified improved forecasting to be worth US$125 million a year to that region. Based on a conservative application of this figure, Stiesdal estimates that windfarm owners may be able to increase revenue by as much as 10%.
 

Wind turbine R&D competence centre

 
Siemens also established its first US wind turbine R&D competence centre in Boulder, Colorado, in 2008 and entered into a CRADA for the installation of a Siemens 2.3 MW pilot wind turbine with a 101 meter rotor at the National Wind Technology Center (NWTC).
 
The company will test basic wind turbine characteristics and verify new performance-enhancing features and turbine reliability under severe weather conditions over a minimum period of three years.

 

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