Análise de Impactos Harmônicos em Rede de Distribuição de Energia Elétrica de Média Tensão Utilizando Técnicas de Inteligência Computacional

Abstract

The growing demand for electrical energy and the increased use of non-linear loads in distribution systems have intensified the generation of harmonic distortions, compromising the quality of the energy supplied. This work presents an analysis of the harmonic impacts on medium-voltage electrical energy distribution networks, using computational intelligence techniques for modeling, simulation and diagnosis. Methods based on artificial neural networks and genetic algorithms were applied to identify and mitigate harmonic distortions, providing an efficient and automated approach for electrical energy quality control. The results demonstrate the feasibility of applying these techniques, evidencing improvements in the identification of distortions and in the definition of strategies to minimize their adverse effects on the electrical system.