APPLICATION OF SUPERVISORY CONTROL FOR DOUBLY FED INDUCTION GENERATOR BASED WIND ENERGY CONVERSION SYSTEM
M. Vijayalaxmi N. ShanmugaVadivoo
industrial electrical power systems
This paper presents a method to identify, model and design supervisory controllers with intelligent techniques for real power of doubly fed induction generator based wind energy conversion system. A doubly fed induction generator based wind energy conversion system is designed, modelled and parameters were estimated using different non linear optimization techniques such as piecewise linear approximation method, sigmoid network and wavelet network for both the partial and full load region. Suitable model is selected based on the model properties and is used as a reference input for the supervisory controllers. The parameters of Proportional Integral and Derivative controller were auto tuned and fed into the supervisory controllers. The error signal is also given as input to the supervisory controllers along with the constant controller parameters and the control signal is obtained as output by training the error signal with intelligent techniques such as fuzzy logic, neural network and adaptive neuro-fuzzy inference system. The performance of controllers is analyzed with performance parameters such as Integral Square Error and average power of doubly fed induction generator based wind energy conversion system. Adaptive neuro-fuzzy inference system tuned PID controller shows the better performance comparing to fuzzy tuned and neural network tuned PID controller.
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