Name
Abstract | ||
|---|---|---|
This paper proposes a multi-step prediction method for the total harmonic distortion (THD) in three-phase networks with nonlinear loads using a nonlinear autoregressive network with exogenous inputs (NARX).The prediction is performed in three stages: in an open-loop neural network, closed-loop mode, and open-loop mode with the removal of the delay time. To verify the accuracy of the proposed method for identifying the harmonic source, comparisons are performed with two types of neural networks, a feed-forward back-propagation (FFBP) neural network and a cascaded feedforward back-propagation (CFFBP) neural network. Moreover, three different cases of nonlinear loads are studied to validate the effectiveness of the proposed technique for harmonic prediction. A MATLAB/Simulink program is used for the modelling and simulation of the distribution system and all neural networks. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/IECON43393.2020.9254662 | IECON 2020: THE 46TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY |
Keywords | DocType | ISSN |
Distribution system, feed-forward propagation neural network, harmonic distortion, NARX, neural networks | Conference | 1553-572X |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Raseel Aljendy | 1 | 0 | 0.34 |
| Hamdy M. Sultan | 2 | 4 | 2.51 |
| Ameena Al-Sumaiti | 3 | 4 | 4.99 |
| Ahmed A. Zaki Diab | 4 | 3 | 3.14 |