Transient Stability Enhancement of Power System Using Intelligent Technique

In this paper, Automation of a power system fault detection using multi resolution analysis (MRA) wavelet transform is proposed and the various coefficients obtained from wavelet transform are given as an input to the probabilistic neural network (PNN). This PNN will classify and find the nature of fault occurring. Later, the decisions obtained from the output of PNN can be used to tune the power system stabilizer. The two-area 4-machine system with a double circuit transmission lines between the two areas is modified to include a fictitious bus for the study. The integral square error functions are used as a fitness function during the minimization operation. Results show that the proposed control of the Power System Stabilizer is more robust in damping the oscillations as compared to the fixed conventional PSS. The paper is simulated using the wavelet, neural network toolboxes and using power system block sets.