ADAPTIVE LINEAR ALGORITHMS FOR POWER SYSTEM FUNDAMENTAL AND HARMONIC ESTIMATION - MUBARAK MOHMMED, HUSSAM ALHAJ (2014)
Frequency and harmonics are two essential parameters for power system functions such as power quality monitoring, power system protection, economic dispatch and security assessment. Several approaches have been presented in the last two decades to estimate the fundamental frequency and harmonics. The most popular algorithm that has been implemented to estimate, and quantify power system fundamental frequency and harmonic components is the Fast Fourier Transform (FFT). However, this technique has a few negative implications such as spectral leakage and picketfence effect. On the other hand, Least Mean Square (LMS) algorithm is known for its ease of structure, computation and simplicity. Hence, one of the objectives of this thesis is to address and enhance the introduced fundamental frequency adaptive filter method which was based on modified variable step size LMS (MVSS) algorithm using generalized square error normalized LMS algorithm. This approach is aimed at reducing the number of parameters and steps in MVSS as well as to improve the convergence rate, quick tracking and low Mean Square Error (MSE). Moreover, in order to attain faster response and more harmonic estimation accuracy, a second order Recursive Levenberg Marquardt (RLM) harmonic estimator is presented.