Frequency variations measurement techniques in power quality monitoring

Abstract

Power quality is a term used to describe electric power that motivates an electrical load and the load's ability to function properly with that electric power. Without the proper power, an electrical device load may malfunction, fail prematurely or not operate at all. There are many ways in which electric power can be of poor quality and many more causes of such poor quality power. The aim of this thesis is to study measurement techniques available in monitoring power system frequency particularly using the Least Square Error (LSE) method and neural network approach (ADALINE). The algorithms for the various measurement methods in this thesis were implemented using MATLAB. Results concluded that the neural network approach (ADALINE) is much better for frequency approximation although the LES algorithm provides an easier measurement method. The LES technique was found to be not accurate in the presence of noise and harmonics. Further studies could be done on recursive LES which may compensate the drawbacks of non-recursive LES algorithm which was studied in this work.