Granted Patent B2

US 12,655,825 · App. 18/681,421 · Granted Jun 16, 2026

Inventors: Suhas Pol (Lubbock, TX); Ricardo Castillo (Lubbock, TX)

Assignee: TEXAS TECH UNIVERSITY SYSTEM

F03D7/049F03D7/022F05B2270/327

Abstract

Claims (58)

1 . A system for wind turbine optimization comprising:

a processor; and

a computer-usable medium embodying computer code, said computer-usable medium being coupled to said processor, said computer code comprising non-transitory instruction media executable by said processor configured for:

calibrating a controller wherein calibrating the controller comprises directly measuring wake trajectory deviations by measuring velocity time-series signal spectral energy amplitude changes at periods equivalent to one or more rotations obtained from experiments on models in wind tunnels;

setting a desired location range of a wind wake with the controller;

determining an error signal;

adjusting a speed of a rotor associated with a wind turbine according to the error signal in order to minimize the error signal; and

confining a real-time position of the wind wake to the desired location range of the wind wake by minimizing the error signal.

2 . The system of claim 1 further comprising:

generating a look up table of a yaw misalignment angle, a rotor speed, and cross-stream thrust.

3 . The system of claim 2 wherein calibrating the controller further comprises:

calibrating the controller with the look up table.

4 . The system of claim 3 wherein the look up table is associated with a specific turbine design.

5 . The system of claim 4 further comprising prescribing controller variables wherein the controller variables comprise at least one of:

pitch;

yaw; and

speed.

6 . The system of claim 1 wherein the error signal comprises:

a difference between a currently measured cross-stream thrust component of wind and an optimal cross-stream thrust component of wind.

7 . The system of claim 6 further comprising:

readjusting the rotor speed, to minimize the difference between the currently measured cross-stream thrust component of wind and the optimal cross-stream thrust component of wind.

8 . The system of claim 1 wherein setting the desired location range of a wind wake with a controller further comprises:

selecting the desired location range to maximize efficiency of a wind farm comprising a plurality of wind turbines.

9 . A wind turbine optimization method comprising:

calibrating a controller wherein calibrating the controller comprises directly measuring wake trajectory deviations by measuring velocity time-series signal spectral energy amplitude changes at periods equivalent to one or more rotations obtained from experiments on models in wind tunnels;

setting a desired location range of a wind wake with a controller;

determining an error signal in order to minimize the error signal;

adjusting a speed of a rotor associated with a wind turbine according to the error signal; and

confining a real-time position of the wind wake to the desired location range of the wind wake by minimizing the error signal.

10 . The method of claim 9 further comprising:

generating a look up table of a yaw misalignment angle, a rotor speed, and cross-stream thrust.

11 . The method of claim 10 wherein calibrating the controller further comprises:

calibrating the controller with the look up table.

12 . The method of claim 10 further comprising:

prescribing controller variables in response to changes in cross-stream thrust using unsupervised machine learning, wherein the controller variables comprise at least one of:

pitch;

yaw; and

speed.

13 . The method of claim 9 wherein the error signal comprises:

a difference between a currently measured cross-stream thrust component of wind and an optimal cross-stream thrust component of wind.

14 . The method of claim 13 further comprising:

readjusting rotor speed to minimize the difference between the currently measured cross-stream thrust component of wind and the optimal cross-stream thrust component of wind.

15 . The method of claim 14 further comprising:

mitigating wake meander from a set trajectory, the wake meander resulting from instantaneous changes in inflow wind conditions.

16 . The method of claim 14 further comprising:

mitigating adverse loads on the wind turbine due to instantaneous yaw misalignments caused by changes in inflow wind conditions, the inflow wind conditions comprising at least one of:

wind direction;

speed; and

atmospheric stratification.

17 . An apparatus for wind turbine optimization comprising:

a wind turbine;

a processor; and

a computer-usable medium embodying computer code, said computer-usable medium being coupled to said processor, said computer code comprising non-transitory instruction media executable by said processor configured for:

calibrating a controller with data obtained from experiments on models in wind tunnels the data comprising directly measured wake trajectory deviations collected by measuring velocity time-series signal spectral energy amplitude changes at periods equivalent to one or more rotations;

setting a desired location range of a wind wake with the controller;

determining an error signal;

adjusting a speed of a rotor associated with the wind turbine according to the error signal in order to minimize the error signal; and

confining a real-time position of the wind wake to the desired location range of the wind wake by minimizing the error signal.

Assignments (1)

Continuity (2)

References Cited (22)