Performance comparison of hybrid ANN based control of DFIG for various faulty conditions

Abstract

Wind Energy Conversion Systems (WECS) are mostly installed in remote locations; therefore, these systems are prone to various fault conditions. The control of active and reactive power control is very important when WECS are succumbed to faults. In this research paper, the Doubly Fed Induction Generator (DFIG) based WECS operation is analyzed for single and three phase faults near and far away from the DFIG. In this paper, a new hybrid controller, which is the combination of Artificial Neural Network (ANN) and Proportional Integral (PI) controller is developed to mitigate the above said problem. The performance of the hybrid controller is compared with the individual control performances of ANN and PI applied to DFIG. The results are presented for various fault conditions for these three different controllers. Results clearly show the uniqueness of the hybrid controller compared to individual performances of ANN and PI controllers. Also the results are examined with the Integral Square Error (ISE) values of active and reactive powers for hybrid, ANN and PI controllers for various fault conditions.