A novel analytic method of power quality using extension genetic algorithm and wavelet transform

The power quality affects the power stability of power company and customers. In order to avoid economic losses caused by the power disturbances, it is necessary to monitor power parameters. This paper aimed at power quality analyses by wavelet transform and proposed a novel algorithm called extension genetic algorithm (EGA). The paper introduced the fundamental theory of wavelet transform, current applications and the theoretical framework of EGA. Then, it described the definition of power quality problems and the characteristics of power waves. Finally, this paper compared the analysis results of EGA and other methods. As the results of simulation, this paper mentioned of methods has a very high accuracy. It can also provide an application tool on power quality and data classification for future researchers.