Name
Abstract | ||
|---|---|---|
In this paper, artificial neural networks are employed in a novel approach to identify harmonic components of single-phase nonlinear load currents, whose amplitude and phase angle are subject to unpredictable changes, even in steady-state. The first six harmonic current components are identified through the variation analysis of waveform characteristics. The effectiveness of this method is tested by applying it to the model of a single-phase active power filter, dedicated to the selective compensation of harmonic current drained by an AC controller. Simulation and experimental results are presented to validate the proposed approach. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1016/j.asoc.2010.07.017 | Appl. Soft Comput. |
Keywords | Field | DocType |
harmonic identification,ac controller,harmonic component,single-phase power system,artificial neural network,parallel neural network,single-phase active power filter,neural network application,novel approach,single-phase nonlinear load current,phase angle,harmonic current component,harmonic distortion,power electronics,single-phase system,power system,variational analysis,steady state,neural network | Control theory,Nonlinear system,Total harmonic distortion,Control theory,Waveform,Harmonic,Power electronics,Artificial neural network,Amplitude,Mathematics | Journal |
Volume | Issue | ISSN |
11 | 2 | Applied Soft Computing Journal |
Citations | PageRank | References |
3 | 0.41 | 8 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Claudionor Francisco do Nascimento | 1 | 3 | 0.41 |
| Azauri Albano de Oliveira, Jr. | 2 | 3 | 0.41 |
| Alessandro Goedtel | 3 | 27 | 8.62 |
| Paulo José Amaral Serni | 4 | 6 | 1.52 |