Artículos de revistas
Artificial neural network model of discharge lamps in the power quality context
Fecha
2013-06-01Registro en:
Journal of Control, Automation and Electrical Systems, v. 24, n. 3, p. 272-285, 2013.
2195-3880
2195-3899
10.1007/s40313-013-0027-0
2-s2.0-84879327371
4831789901823849
0000-0002-9984-9949
Autor
Universidade de São Paulo (USP)
Universidade Estadual Paulista (Unesp)
Institución
Resumen
This paper presents a methodology for modeling high intensity discharge lamps based on artificial neural networks. The methodology provides a model which is able to represent the device operating in the frequency of distribution systems, facing events related to power quality. With the aid of a data acquisition system to monitor the laboratory experiment, and using $$\text{ MATLAB }^{\textregistered }$$ software, data was obtained for the training of two neural networks. These neural networks, working together, were able to represent with high fidelity the behavior of a discharge lamp. The excellent performance obtained by these models allowed the simulation of a group of lamps in a distribution system with shorter simulation time when compared to mathematical models. This fact justified the application of this family of loads in electric power systems. The representation of the device facing power quality disturbances also proved to be a useful tool for more complex studies in distribution systems. © 2013 Brazilian Society for Automatics - SBA.
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