PROJECT TITLE :

A Fourier Based Wavelet Approach Using Heisenberg’s Uncertainty Principle and Shannon’s Entropy Criterion to Monitor Power System Small Signal Oscillations

ABSTRACT:

This paper presents a completely unique approach to estimate modal parameters of Power Systems for monitoring and analyzing the embedded modes of small signal oscillations. The proposed approach applies continuous wavelet transform (CWT) to identify damping and frequency of vital modes primarily based on its time-frequency localization capability. The CWT has modified Morlet perform as its mother wavelet. A procedure is also presented to fine-tune settings of the changed Morlet operate of the CWT based mostly on Heisenberg's uncertainty principle and Shannon's entropy criterion. Additionally, high computational burden of the time-frequency ways is an important obstacle in on-line monitoring of power systems by these methods. To remedy this problem, the convolution integral of the CWT is calculated by efficient quick Fourier transform (FFT) routine in the proposed approach leading to an occasional computational burden. The proposed approach is compared with several alternative Signal Processing ways for modal identification of power systems. These comparisons illustrate effectiveness of the proposed approach, relating to run time, persistency against noise and estimation accuracy for on-line monitoring of tiny signal oscillations.