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1 © 2011 The MathWorks, Inc. Designing Control Systems for Wind Turbines Steve Miller Technical Marketing, Physical Modeling MathWorks Root LocusBode Plot.

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Presentation on theme: "1 © 2011 The MathWorks, Inc. Designing Control Systems for Wind Turbines Steve Miller Technical Marketing, Physical Modeling MathWorks Root LocusBode Plot."— Presentation transcript:

1 1 © 2011 The MathWorks, Inc. Designing Control Systems for Wind Turbines Steve Miller Technical Marketing, Physical Modeling MathWorks Root LocusBode Plot Real AxisFrequency Park Startup Brake Generating Grid Pitch Yaw Rotor Speed Blades Tower GeartrainGenerator Hub Lift Wind

2 2 Key Points The time to develop a control system can be shortened by using control design tools Optimizing systems with respect to design requirements leads to optimal design choices Finding errors in supervisory controllers requires a model that can be easily built, understood, and tested Control + - A x + B u Root LocusBode Plot Real AxisFrequency

3 3 Agenda Wind turbine control system overview Compensator design for pitch control system –Using linear control theory –Applying optimization algorithms to nonlinear model Supervisory control using state machines

4 4 Grid Wind Turbine Control Systems Yaw Generator Speed Tower GeartrainGenerator Pitch Rotor Speed Blades Hub Lift, Drag Wind Nacelle Blade pitch control system –Adjust pitch angle to regulate rotational speed Supervisory control system –Analyze operating conditions to determine state of turbine to enable/disable operation

5 5 Controlling Rotor Speed Using the Pitch Angle Problem: Control the pitch angle so that the generator shaft spins at nominal speed Solution: Use Simulink to determine the pitch angle by controlling the angle of attack Model: Desired Rotor Speed Desired Angle of Attack Control Actual Rotor Speed Inflow Angle Pitch Angle Command + - Pitch Rotor Speed Lift

6 6 Overview of Pitch System Control Actuator Pitch Angle Command Measured Pitch Angle Determine State Event Based Control System changes mode based on events Compensator Design Actuation is based on deviation from a commanded value (PID, etc.)

7 7 Agenda Wind turbine control system overview Compensator design for pitch control system –Using linear control theory –Applying optimization algorithms to nonlinear model Supervisory control using state machines

8 8 Control + - Possibilities for Compensator Design Linear Control Theory – Linearize system using Simulink Control Design – Perform linear control design with Control System Toolbox – Retest controller in nonlinear system A x + B u Root LocusBode Plot Real AxisFrequency Control + - Specify System Response –Specify response characteristics –Automatic tuning using Simulink Design Optimization

9 9 Control Design on Linearized Plants Problem: Design and test a controller for a nonlinear system using linear methods to meet system specifications Solution: Use Simulink Control Design and Control System Toolbox to design, tune, and test the controller Model: A x + B u Root LocusBode Plot Real AxisFrequency Command Error Force Pitch Angle Control + -

10 10 Control Design on Linearized Plants Steps to Design Controller 1. Identify control loops of interest 2. Identify operating point 3. Linearize model about this point 4. Perform control design 5. Test controller in nonlinear system A x + B u = 0 Actuator Force Pitch Angle Command Control + - Root LocusBode Plot Real AxisFrequency

11 11 Control Design on Linearized Plants Advantages of Simulink Control Design and Control System Toolbox 1.Enable easy application of linear control theory Operating points from specification or simulation Graphical design with interactive plots 2.Rapid evaluation of designs with interactive analysis plots 3.Automatic tuning of parameters through various methods (PID, IMC, LQG) saves time 4.Optimize performance based on time, frequency, or root locus constraints

12 12 Agenda Wind turbine control system overview Compensator design for pitch control system –Using linear control theory –Applying optimization algorithms to nonlinear model Supervisory control using state machines

13 13 Compensator Design on Nonlinear Plants Problem: Design and tune the controller in this system to meet system requirements Solution: Use Simulink Design Optimization to design, tune, and test the controller Model: KpKp KiKi KpKp KiKi (K p s+K i ) s s

14 14 Compensator Design on Nonlinear Plants Steps to Optimize Response 1. Identify parameters to be tuned and their ranges 2. Specify desired response 3. Perform response optimization (K p s+K i ) s

15 15 Compensator Design on Nonlinear Plants Advantages of Simulink Design Optimization 1.Graphical interface makes it easy to map specification to tests. 2.Automatic tuning of parameters saves time. 3.Simulating plant and controller in one tool allows engineers to understand and optimize performance of the entire system.

16 16 Agenda Wind turbine control system overview Compensator design for pitch control system –Using linear control theory –Applying optimization algorithms to nonlinear model Supervisory control using state machines

17 17 Model the Supervisory Control of the Wind Turbine Problem: Create a supervisory controller that sets the state of the brake, generator, and pitch angle based on turbine conditions Model: Solution: Use Stateflow to model the event-based controller wind > cut in speed && wind < cut out speed turbine > min speed wind spd max spd || turbine spd < min spd || turbine spd > max spd Turbine spd < park spd park brake = 0 pitch brake = 0 generator = 0 Startup park brake = 0 pitch brake = 0 generator = 1 Generating park brake = 0 pitch brake = 1 generator = 0 Brake park brake = 1 pitch brake = 0 generator = 0 Park

18 18 Key Points The time to develop a control system can be shortened by using control design tools Optimizing systems with respect to design requirements leads to optimal design choices Finding errors in supervisory controllers requires a model that can be easily built, understood, and tested Control + - A x + B u Root LocusBode Plot Real AxisFrequency


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