in News Departments > Products & Technologies
print the content item

GE Global Research and Sandia National Laboratories have research that could significantly impact the design of future wind turbine blades.

Using high-performance computing to perform complex calculations, engineers have overcome previous design constraints, allowing them to begin exploring ways to design re-engineered wind blades that are low-noise and are more prolific power-producers.

According to GE, its scope of work focused on advancing wind turbine blade noise prediction methods. Aerodynamic blade noise is the dominant noise source on modern, utility-scale wind turbines and represents a key constraint in wind turbine design. Efforts to reduce blade noise can help reduce the cost of wind energy and increase power output.

GE predicts that a 1-decibel quieter rotor design would result in a 2% increase in annual energy yield per turbine. With approximately 240 GW of new wind installations forecast globally over the next five years, a 2% increase would create more than 5 GW of additional wind power capacity.

"There's no question; aerodynamic noise is a key constraint in wind turbine blade design today," explains Mark Jonkhof, wind technology platform leader at GE Global Research. "By using high-performance computing to advance current engineering models that are used to predict blade noise, we can build quieter rotors with greater blade tip velocity that produce more power. This not only means lower energy costs for consumers, but also a significant reduction in greenhouse gas emissions."

To ensure that GE’s wind blades do not pose noise issues, airfoil level acoustic measurements are performed in wind tunnels, field measurements are done to validate acceptable noise levels and noise-reducing operating modes are implemented in the control system. Better modeling will help maintain the current low noise levels while boosting output.

GE’s testing involved Sandia’s Red Mesa supercomputer's running a high-fidelity Large Eddy Simulation (LES) code, developed at Stanford University, to predict the detailed fluid dynamic phenomena and resulting wind blade noise.

For a period of three months, this LES simulation of the turbulent air flow past a wind blade section was continuously performed on the Red Mesa HPC. The resulting flow-field predictions yielded valuable insights that were used to assess current engineering design models, the assumptions they make that most impact noise predictions, and the accuracy and reliability of model choices.

"We found that high fidelity models can play a key role in accurately predicting trailing edge noise," adds Jonkhof. “We believe that the results achieved from our simulations would, at the very least, lay the groundwork for improved noise design models."


Trachte Inc._id1770
Latest Top Stories

Bird Groups Target LEEDCo's Icebreaker Offshore Wind Pilot

Two bird conservation groups that helped halt a wind project earlier this year argue that Lake Erie Energy Development Corp.'s (LEEDCo) 18 MW offshore demo poses a major risk to regional wildlife.


Report Disputes U.S. Agency's Renewable Energy Projections

A new analysis from the Sun Day Campaign says renewables are slated to provide 16% of U.S. generating capacity by 2018 - over 20 years earlier than forecast by the Energy Information Administration.


Kansas Renewables Mandate Survives Yet Another Attack, But Is It Too Early To Celebrate?

Over the past three years, some legislators have tried to either weaken or repeal the state's renewable portfolio standard, which requires Kansas utilities to reach 20% renewables by 2020.


AWEA Highlights U.S. Wind Success Stories Of 2013

Despite a 92% drop in new capacity last year, the sector still has myriad reasons to celebrate, according to a new report from the American Wind Energy Association.


Feds List New Bird Species As Threatened - Should Wind Developers Be Worried?

The U.S. Fish and Wildlife Service is designating the lesser prairie-chicken as threatened under the Endangered Species Act. An expert explains how this might affect the wind industry.

UEA_id1896
WomenofWind_id
JLG_id1900
Acciona_id1907
bonfiglioli_id1913
AWEA_id1886