Wind prediction for wind farms through the use of weather radar

• US 8,606,418 B1
• Filed: 03/18/2011
• Issued: 12/10/2013
• Est. Priority Date: 03/18/2011
• Status: Active Grant

• Current Assignee: Rockwell Collins, Inc. (Raytheon Technologies Corporation d/b/a RTX)
• Original Assignee: Rockwell Collins, Inc. (Raytheon Technologies Corporation d/b/a RTX)
• Inventors: Engler, Joseph J., Myers, Michael R.
• Primary Examiner(s): SHECHTMAN, SEAN P
• Application Number:
  US13/051,787
• Time in Patent Office: 998 Days
• Field of Search: None
• US Class Current: 700/287
• CPC Class Codes: F03D 7/046 with learning or adaptive control, e.g. self-tuning, fuzzy logic or neural network
• CPC Class Codes: F03D 7/048 controlling wind farms
• CPC Class Codes: F05B 2260/8211 of the weather
• CPC Class Codes: F05B 2270/20 to optimise the performance of a machine
• CPC Class Codes: F05B 2270/805 Radars
• CPC Class Codes: Y02E 10/72 Wind turbines with rotation axis in wind direction

Abstract

A control system is provided. The control system comprises an electronic processor configured to control operation of at least one wind turbine. The control system further comprises at least one weather radar unit positioned proximate to the at least one wind turbine and configured to generate weather data. The electronic processor is configured to control the operation of the at least one wind turbine based on the weather data generated by the at least one weather radar unit.

Claims

1. A control system, comprising:

at least one weather radar unit positioned proximate to at least one wind turbine and configured to generate weather data; and

an electronic processor configured to;

evaluate a fitness of solutions associated with a plurality of individuals in a population for a current operating environment of the at least one wind turbine, each individual comprising a dominant genotype and a recessive genotype, wherein each genotype represents a solution for controlling the at least one wind turbine, wherein a fitness function is applied to the dominant genotype of each individual, wherein the fitness function is based on weather data received from the at least one weather radar unit positioned proximate to the at least one wind turbine;

store previously encountered genotypes in the recessive genotype of the individuals; and

select a solution for controlling operation of the at least one wind turbine based on the fitness evaluation.

2. The control system of claim 1, wherein the weather data comprises wind velocity data.

3. The control system of claim 1, wherein the weather data is based on a local forecast of weather and comprises at least one of forecasted wind velocity, forecasted turbulence, forecasted severe weather, and forecasted freezing rain.

4. The control system of claim 2, wherein the weather data further comprises at least one of precipitation data, turbulence data, and wind shear data.

5. The control system of claim 4, wherein the processor is configured to identify the existence of a severe weather event based on at least one of the wind velocity data, precipitation data, turbulence data, and wind shear data received from the at least one weather radar unit.

6. The control system of claim 1, wherein the at least one wind turbine comprises a wind farm including a plurality of wind turbines, wherein the at least one weather radar unit comprises a plurality of weather radar units configured to provide weather data that covers the entire perimeter of the wind farm.

7. A method of controlling at least one wind turbine, comprising:

evaluating, using at least one processor, a fitness of solutions associated with a plurality of individuals in a population for a current operating environment of the at least one wind turbine, each individual comprising a dominant genotype and a recessive genotype, wherein each genotype represents a solution for controlling the at least one wind turbine, wherein a fitness function is applied to the dominant genotype of each individual, wherein the fitness function is based on weather data received from at least one weather radar unit positioned proximate to the at least one wind turbine;

storing, in at least one memory operably coupled to the at least one processor, previously encountered genotypes in the recessive genotypes of the individuals; and

selecting, using the at least one processor, a solution for controlling operation of the at least one wind turbine based on the fitness evaluation.

8. The method of claim 7, wherein the weather data comprises wind velocity data.

9. The method of claim 8, wherein the weather data further comprises at least one of precipitation data, turbulence data, and wind shear data.

10. The method of claim 7, further comprising identifying the existence of a severe weather event based on the weather data received from the at least one weather radar unit.

11. The method of claim 7, wherein the at least one wind turbine comprises a wind farm including a plurality of wind turbines, wherein the at least one weather unit comprises a plurality a weather units configured to provide weather data that covers the entire perimeter of the wind farm.

12. The method of claim 7, further comprising predicting at least one future state related to the at least one wind turbine, wherein the at least one future state comprises at least one of a wind state, a wind turbine system load state, and a power demand state, wherein the fitness function is further based on the at least one predicted future state.

13. The method of claim 12, wherein predicting the at least one future state comprises:

collecting data related to operation of the at least one wind turbine;

embedding the data in a reconstructed phase space to generate embedded data; and

predicting the at least one future state based on a rate of separation of trajectories of the embedded data within the reconstructed phase space.

14. The method of claim 7, further comprising detecting a change in the operating environment of the at least one wind turbine by comparing a best fitness of a current generation of the population with a best fitness of a previous generation of the population.

15. A control system, comprising:

an electronic processor configured to

evaluate a fitness of solutions associated with a plurality of individuals in a population for a current operating environment of at least one wind turbine, each individual comprising a dominant genotype and a recessive genotype, wherein each genotype represents a solution for controlling the at least one wind turbine, wherein a fitness function is applied to the dominant genotype of each individual, wherein the fitness function is based on weather data received from at least one weather radar unit positioned proximate to the at least one wind turbine;

store previously encountered genotypes in the recessive genotype of the individuals; and

select a solution for controlling operation of the at least one wind turbine based on the fitness evaluation.

16. The control system of claim 15, wherein the weather data comprises wind velocity data.

17. The control system of claim 15, wherein the weather data comprises forecasted weather data, and wherein the forecasted weather data comprises forecasted wind velocity data.

18. The control system of claim 16, wherein the weather data further comprises at least one of precipitation data, turbulence data, and wind shear data.

19. The control system of claim 15, wherein the processor is configured to identify the existence of a severe weather event based on the weather data received from the at least one weather radar unit.

20. The control system of claim 15, wherein the at least one wind turbine comprises a wind farm including a plurality of wind turbines, wherein the at least one weather unit comprises a plurality a weather units configured to provide weather data that covers the entire perimeter of the wind farm.

21. The control system of claim 15, wherein the processor is further configured to

embed time series data relating to the at least one wind turbine within a reconstructed phase space to generate embedded data;

and

predict at least one future state related to the at least one wind turbine based on a rate of separation of trajectories of the embedded data within the reconstructed phase space,

wherein the fitness function is further based on the at least one predicted future state.

22. The control system of claim 15, wherein the processor is configured to detect a change in the operating environment of the at least one wind turbine by comparing a best fitness of a current generation of the population with a best fitness of a previous generation of the population.