Development of New Hybrid Artificial Neural Network Based Control of Doubly Fed Induction Generator

In this chapter, a hybrid Artificial Neural Network (ANN) with Proportional Integral (PI) control technique for a Doubly Fed Induction Generator (DFIG) based wind energy generation system is developed and its performance is compared with NN and PI control techniques. With the increased utilisation of wind power generation, a dynamic performance analysis of the Doubly Fed Induction Generator under varied operating situations is necessary. Three control strategies are proposed in this Chapter: the first uses a PI controller, the second uses an ANN controller, and the third uses a mix of ANN and PI. The findings obtained using MATLab/Simulink indicate the performance of the proposed control techniques. The dynamic performance of the DFIG is improved with the Hybrid control technique, according to the findings. The Hybrid ANN-based system that estimates the control parameters of the generator showed satisfactory characteristics as was verified in the presented results.