Inteligência computacional aplicada à modelagem de cargas não-lineares e estimação de contribuição harmônica

Abstract

The harmonic distortin, among other forms of pollution to the electric power systems is an important issue for electric utilities. In fact, the increased use of nonlinear devices in industry has resulted in direct increase of harmonic distortion in industrial power grids in recent years. Thus, the modeling of these loads and the understanding of their interactions with the system have became of great importance, then the use of computational-based techniques has emerged as a suitable tool to deal with these requirements. In this context, this work describes a methodology based on Computational Intelligence (Artificial Neural Networks (ANN)s and Fuzzy Logic (FL)) for modeling nonlinear loads present in electric power systems, as well as the estimation of their contribution in the harmonic distortion. The main advantage of this technique is that only the waveforms of voltages and currents at the point of common coupling must be measured and it can be applied to model single and three phase loads.