Fuzzy Regulator Design for Wind Turbine Yaw Control (original) (raw)
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A Comparative Study and Analysis of Different Yaw Control Strategies for Large Wind Turbines
—In this paper, we introduce three different nacelle yaw controllers that use distinct techniques and study their performances in improving the captured energy by the turbine. The first one is a carefully tuned Proportional-Integral-Differential (PID) controller with its simple design; the second one is a linguistic fuzzy logic controller with its intuitive flexible design; and the third one is a Model-Predictive-Controller (MPC) with its adaptive functionality. The control objective of the developed controllers is to effectively track the wind direction by the yaw motion of the turbine nacelle; and consequently to improve the energy capture. A comparative study and a thorough analysis among the three controllers' performances are carried out using extensive MATLAB/SIMULINK simulations.
Analysis of Various Yaw Control Techniques for Large Wind Turbines
The Journal of Engineering Research, 2019
In this paper, we introduce three different nacelle yaw controllers that use distinct techniques and study their performances in improving the captured energy by the turbine. The first one is a carefully tuned Proportional-Integral-Differential (PID) controller with its simple design; the second one is a linguistic fuzzy logic controller with its intuitive flexible design; and the third one is a Model-Predictive-Controller (MPC) with its adaptive functionality. The control objective of the developed controllers is to effectively track the wind direction by the yaw motion of the turbine nacelle; and consequently to improve the energy capture. A comparative study and a thorough analysis among the three controllers’ performances are carried out using extensive MATLAB/SIMULINK simulations.
To extract maximum power, at below rated speed of wind, the speed of the generator rotor is adjusted for maximum power extraction. But for higher wind speed, however the output power is monitored and controlled at rated power by pitch angle adjustments. In this paper attempt has been made to design and implement a fuzzy controller, which is applicable for both below rated wind speed region as well as above that. It is proposed and shown that how framing control rules using only the desired extremity conditions helps attaining the desired result with a reduced rule set, making it easy for further fine tuning too.
Pitch Angle Control of Variable Low Rated Speed Wind Turbine Using Fuzzy Logic Controller
2013
Pitch angle control of wind turbine has been used widely to reduce torque and output power variation in high rated wind speed areas. It is a challenge to maximize available energy in the low rated wind speed areas. In this paper, a wind turbine prototype with a pitch angle control based on fuzzy logic to maximize the output power is built and demonstrated. In the varying low rated wind speed of 4-6 m/s, the use of fuzzy logic controller can maximize the average output power of 14.5 watt compared to 14.0 watt at a fixed pitch angle of the blade. Implementation of pitch angle fuzzy logic-based control to the wind turbine is suitable for the low rated wind speed areas
Modeling and control of wind turbine powers by – A perspective PI and fuzzy logic controller
Utilization of the electrical energy is increasing day by day, and to satisfy the load demanded by the load centres has to satisfy the generating units. As the fossil fuels are depleting day by day, in order to save these fossil fuels we have to use the “Renewable energy sources”. Developing countries like Algeria, India, Nigeria, Ethiopia etc., are having tremendous wind energy, which is the most promising sources of energy. A case study has been conducted on the wind turbines that are controlled to provide constant active and reactive power during a certain period. In this paper, we model three different controllers of active and reactive power for horizontal axis wind turbine in order to compare their performance: the direct method with a PI and a Fuzzy Logic controller, and also the indirect method control with powers feedback. We aim to improve performance and reduce the number of controllers used. A series of simulation results obtained by Matlab / Simulink software are compared and analyzed.