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Making Large Wind Farms More Productive, Less Expensive

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Sanjiva K. Lele, Aeronautics and Astronautics, and Mechanical Engineering; John Weyant, Management Science and Engineering

Large wind farms typically produce about 25% less power than the cumulative output that would be expected by the windmills cited separately. This is due, in part, to rear windmills operating in the turbulent wakes of those up front. These wakes also increase strain on the downwind blades and, thus, raise operating costs. This project, funded jointly with the Precourt Institute for Energy, is testing whether positioning smaller mixing turbines among the primary turbines, in conjunction with other new management approaches, will significantly increase output and cut costs. The researchers are developing and testing software for designing more efficient large-scale wind farms.

This project has shown that wake skewing is a viable technique for mitigating wake loss at farm scale. Researchers developed a novel approach to stochastically simulate the effect of stratified atmospheric turbulence on unsteady loading of wind turbine blades. Specifically, the Kinematic Simulation approach for farm scale performance assessment (including fatigue) is two orders of magnitude cheaper than conventional Actuator-Line/Large Eddy Simulation. The KS model predicts planetary boundary layer turbulence with correct space-time statistics, as was validated using high fidelity data.

“SU FarmSim v1.0” code written in Modern FORTRAN simulates the performance of an arbitrarily large wind farm with arbitrary layout. Performance and scaling have been tested on up to 1024 processors. An experimental study is possible if researchers obtain additional funding. The researchers have discussed some of their results with GE's research division. 

Read the spotlight article about the project

Publications and media

“A modeling framework for wind farm analysis: Wind turbine wake interactions” 33rd Wind Energy Symposium/AIAA SCITECH Forum(2015): 1-15.

“Sweeping based kinematic simulation for the stably stratified surface layer” (abstract submitted for the 67th Annual Meeting of the APS Division of Fluid Dynamics) Bulletin of the American Physical Society 59 (2014).

Awarded 2013

Funded by the TomKat Center with support from the Precourt Institute for Energy.