Analysis of power system harmonics using singular value decomposition, least square estimation and FFT

This research work will examine singular value decomposition (SVD), Fast Fourier Transform (FFT) and least square technique for the estimation of harmonics in power system. Harmonics in power system disturbs the quality of energy supplied to load, increased energy losses and reduce the reliability of the power system. In some cases, the large power converter systems produce not only typical harmonics but also a significant amount of inter harmonics which can significantly deteriorate the quality of power supply voltage. Inter harmonics are those components of current or voltage waveform which are not integer multiple of fundamental frequency component. Since poor power quality cause losses in power system that's why researchers are working to find techniques to estimate and control the harmonics in power system. Singular value decomposition approach is an ideal technique to estimate harmonics in power system located far away. Since in most of the cases, power system produce over determine equations which can easily be solved using SVD for optimal solution. Singular vector decomposition, SVD is really a mathematical method to lessen a dataset containing an extensive number of qualities to a dataset containing fundamentally less values, yet which still contains a huge portion of the variability introduce in the first information. SVD investigation brings about a more reduced representation of correlations, particularly with multivariate datasets and can give knowledge into spatial and temporal variations exhibited in the fields of data being analysed under different circumstance. Similarly traditional least square method is also one of the most prominent method to estimate the line of best fit. This research work will show the analysis of said techniques to find the optimal approximation of noisy and distorted wave form. To investigate effectiveness of said techniques; simulations will be carried out in MATLAB with same parameters.