Wind Turbine Control based on Artificial Intelligence Methods

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Supervisor:
Dr. Harmati István
Department of Control Engineering and Information Technology

Wind energy is a clean energy source that is inexhaustible. With the burning of fossil fuels, the living environment of human beings has been destroyed. Therefore, clean energy, mainly wind power generation, is gradually replacing fossil fuel-based power generation. The core control technology for wind power generation is critical.

This paper mainly studies the wind turbine control technology based on artificial intelligence methods and also the pitch angle control technology of wind turbines. An enhanced control strategy based on fuzzy logic control is proposed to cope with the nonlinear characteristics of wind turbine as well as to reduce the loads on the blades. Firstly, based on the latest mathematical model of wind turbine, the wind turbine system is built under Matlab Simulink platform. The system is mainly composed of four parts: ro-dynamics system, transmission system, generator and pitch execution system. The inputs to the system are the wind speed (15m/s or non-constant) and reference pitch angle (step signal), and the output is wind turbine shaft speed. Secondly, the mathematical model of wind turbine is developed and is tested with three controllers PID, Fuzzy, and Adaptive Fuzzy-PID. Thirdly, after comparing all the three proposed strategies, the simulation results show that for the wind turbine system, when the wind speed is non-constant, compared with the fixed wind speed, the system tends to be stable for a long time. The PID controller has a large jitter at the beginning, while for the fuzzy logic controller can effectively suppress the oscillations and produces smooth response. By using adaptive fuzzy PID controller, where the PID gains are tuned by using fuzzy logic concepts, the results showed that it can reach the reference signal at an earlier time and gradually stabilize. Fourthly, we also test these three kind of controllers on pitch angle sub-system. As for pitch angle control, it shows the adaptive fuzzy-PID controller has the best performance as it regulates the system as well as the disturbances and uncertain factors associated with the system. we conclude that the adaptive fuzzy PID controller provides a relatively fast response to the system. This technology can better realize the control of the pitch system and ensure the stability of the wind turbine output power.

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