Wind turbine model based control and estimation with accurate online models

Patent metadata

Field	Value
Publication number	US-11629694-B2
Application number	US-201916660084-A
Country	US
Kind code	B2
Filing date	Oct 22, 2019
Priority date	Oct 22, 2019
Publication date	Apr 18, 2023
Grant date	Apr 18, 2023

Abstract

A system for computing wind turbine estimated operational parameters and/or control commands, includes sensors monitoring the wind turbine, a control processor implementing a model performing a linearization evaluation to obtain a structural component dynamic behavior, a fluid component dynamic behavior, and/or a combined structural and fluid component dynamic behavior of wind turbine operation, and a module performing a calculation utilizing the linearization evaluation of the structural component dynamic behavior, the fluid component dynamic behavior, and/or the combined structural and fluid component dynamic behavior. The module being at least one of an estimation module and a multivariable control module. The estimation module generating signal estimates of turbine or fluid states. The multivariable control module determining actuator commands that include wind turbine commands that maintain operation of the wind turbine at a predetermined setting in real time. A method and a non-transitory medium are also disclosed.

First claim

The invention claimed is:

1. A wind turbine system, comprising:
a sensor suite comprising a plurality of sensors positioned to monitor wind turbine operational parameters and environmental conditions of the wind turbine system, the sensor suite in communication with a data store and configured to provide sensor dynamic data to the data store;
a control processor in communication with the data store, the control processor comprising a processor unit;
a control model configured to perform a linearization evaluation at a turbine operating point, the linearization evaluation being performed on a model generated by applying an analytic differentiation technique on a surrogate model to obtain at least one of a structural component dynamic behavior, a fluid component dynamic behavior, and a combined structural and fluid component dynamic behavior of wind turbine operation, the analytic differentiation technique being one of algorithmic differentiation or symbolic differentiation;
the control model comprising a coupling between the structural component dynamic behavior and the fluid component dynamic behavior, the coupling implemented by introduction of a generalized fluid force in a structural model of the wind turbine system and comprising in the fluid component dynamic behavior a dependence of the generalized fluid force on a structural state of the wind turbine system, the structural model comprising structural features accurate to at least one of a first bending natural mode of a tower of the wind turbine system, a first bending natural mode of one or more rotor blades of the wind turbine system, and a rotation of the drive-train of the wind turbine system; and
a module configured to perform a calculation utilizing at least one of the linearization evaluation of the structural component dynamic behavior, the fluid component dynamic behavior, and the combined structural and fluid component dynamic behavior.

2. The system of claim 1 , comprising:
the module is an estimation module configured to generate one or more estimates selected from a group that includes a turbine state signal estimate, a turbine performance signal estimate, a fluid state signal estimate, and a fluid performance signal estimate; and
each of the one or more estimates based on the one or more elements of sensor dynamic data, the structural component dynamic behavior, and the fluid component dynamic behavior.

3. The system of claim 2 , the estimation module configured to generate the one or more estimates by implementing an extended Kalman filter.

4. The system of claim 2 , wherein an interconnected structural component dynamic behavior model and the fluid component dynamic behavior model are augmented with a wind disturbance dynamic behavior model to estimate the wind parameters, the wind parameters including one or more of mean wind speed, misalignment, shear, veer, harmonic variations, and an effective wind speed per blade represented as a harmonic variation of wind.

5. The system of claim 1 , wherein at least a portion of the fluid component dynamic behavior included in a lookup table contains representations of one or more rotor plane fluidic properties and their derivatives, the rotor plane traversed by at least one of the one or more blades.

6. The system of claim 5 , the lookup table comprising:
respective elements containing a data set for a respective one of the one or more blades, each data set including a dependence on at least one of one or more of a blade tip-to-wind speed ratio, a pitch angle, an azimuth angle, and a representative dynamic pressure parameter; and
wherein the data set can be applied to determine at least one of blade forces and blade twist.

7. The system of claim 1 , wherein the structural model comprises a blade twist effect resulting from one or more of a fluid, inertial, and mass blade force.

8. The system of claim 1 , comprising:
the module is a multivariable control module configured to determine actuator commands based on the one or more control states; and
the actuator commands including wind turbine commands to maintain operation of the wind turbine at the predetermined setting in about real time.

9. The system of claim 8 , the multivariable control module including a model predictive controller.

10. The system of claim 1 , wherein the fluid component dynamic behavior comprises:
a contribution of local forces applied to blade segments based on local aerodynamic properties of airfoils augmented to apply corrections for three-dimensional effects; and
a dynamic wake effect from wind turbine operation.

11. The system of claim 1 , wherein the fluid component dynamic behavior comprises data from a remote wind measurement system sensor and at least one of a model of wind propagation upstream to a rotor face and a model of wind propagation downstream of a rotor face.

12. The system of claim 1 , wherein the control model is configured to obtain an analytical representation of the structural component dynamic behavior by a multi-body dynamic modeling technique.

13. The system of claim 1 , wherein the control model is configured to obtain the fluid component dynamic behavior by implementing a Blade Element Momentum (BEM) model, the BEM model containing representations of one or more fluidic properties of a rotor plane, the rotor plane traversed by at least one of the one or more blades.

14. The system of claim 1 , wherein the control model is configured to:
comprising a coupling for at least one of the structural component dynamic behavior and the fluid component dynamic behavior; and
construct an analytic derivative from the surrogate function.

15. A method of computing at least one of wind turbine estimated operational parameters and control commands, the method comprising:
a sensor suite monitoring wind turbine operational parameters and environmental conditions to obtain sensor dynamic data to the data store;
performing a linearization evaluation at a turbine operating point, the linearization evaluation being performed on a model generated by applying an analytic differentiation technique on a surrogate model to obtain at least one of a structural component dynamic behavior, a fluid component dynamic behavior, and a combined structural and fluid component dynamic behavior of wind turbine operation, the analytic differentiation technique being one of algorithmic differentiation or symbolic differentiation;
implementing a coupling between the structural component dynamic behavior and the fluid component dynamic behavior by introduction of a generalized fluid force in a structural model of the wind turbine and includes in the fluid component dynamic behavior a dependence of the generalized fluid force on a structural state of the wind turbine, the structural model including structural features accurate to at least one of a first bending natural mode of a tower, a first bending natural mode of one or more blades, and a rotation of the drive-train of the wind turbine; and
at least one of an estimation module and a multivariable control module performing a calculation utilizing at least one of the linearization evaluation of the structural component dynamic behavior, the fluid component dynamic behavior, and the combined structural and fluid component dynamic behavior.

16. The method of claim 15 , comprising:
the estimation module generating one or more estimates selected from a group that includes a turbine state signal estimate, a turbine performance signal estimate, a fluid state signal estimate, and a fluid performance signal estimate; and
basing each of the one or more estimates on t

Assignees

• Gen Electric

Inventors

• D'Amato Fernando Javier
• Daher Adegas Fabiano
• Barton Justin
• Luenenschloss Alexander

Classifications

• F05B2270/404

  active, predictive, or anticipative · CPC title

• Y02E10/72

  Wind turbines with rotation axis in wind direction · CPC title

• F05B2260/84

  Modelling or simulation · CPC title

• F05B2270/324

  Air pressure · CPC title

• G05B17/02

  electric · CPC title