Development of New Hybrid Artificial Neural Network Based Control of Doubly Fed Induction Generator
The performance of a hybrid Artificial Neural Network (ANN) with Proportional Integral (PI) control approach for a Doubly Fed Induction Generator (DFIG) based wind energy generation system is compared to that of NN and PI control techniques in this chapter. With the growing use of wind power, a dynamic performance analysis of the Doubly Fed Induction Generator under a variety of operating conditions is required. This chapter proposes three control strategies: the first employs a PI controller, the second uses an ANN controller, and the third utilises a PID controller. a combination of ANN and PI The results obtained using MATLAB/Simulink show that the proposed control strategies are effective. According to the findings, the Hybrid control technique improves the DFIG’s dynamic performance. As seen by the reported results, the Hybrid ANN-based system that estimates the generator’s control parameters has good qualities.
Author (S) Details
Dr. G. Venu Madhav
Department of Electrical and Electronics Engineering, Anurag University, India.
Dr. Y. P. Obulesu
School of Electrical Engineering, VIT University, India.
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