The number and complexity of control systems in wind turbines is expanding rapidly, and their design can be the difference between an immensely profitable system and a dormant or damaged system. Designing a robust control system requires an accurate model of the plant, and tools that enable rapid iteration to find the best design, not simply the first design that works. The control system must be as optimized as possible, while meeting multiple (and sometimes conflicting) system requirements. Pitch and yaw controllers must also interact with supervisory logic controllers in order to operate and protect the turbine under a wide range of operating conditions.
The model of a complete wind turbine (including mechanical, electrical and hydraulic systems) will be used to show:
• How to easily apply linear control theory to rapidly design controllers for nonlinear systems, and to verify their performance on the nonlinear system
• How to use optimization algorithms to optimize system performance with respect to multiple design requirements
• How to define supervisory logic using state machines
• How to integrate and test all of these models in a single environment to test for integration issues and test overall system performance
These points will be illustrated with demonstrations using the model and the simulation software. Experience with MATLAB and Simulink is helpful, but not required to learn from this webinar.
This webinar is part of a recorded webinar series demonstrating how MathWorks tools enable Model-Based Design for wind turbine development.
You can download the model used in this webinar from MATLAB Central.