A Novel Control Strategy For Shunt Active Power Filter Using NARX Neural Network
Journal Title: International Journal of engineering Research and Applications - Year 2018, Vol 8, Issue 9
Abstract
This paper presents a novel control strategy for shunt active power filter (APF) based on Nonlinear AutoRegressive with eXogenous neural network (NARX). The proposed series parallel NARX neural network is trained by using static backpropagation learning algorithm to model the nonlinearity of electric loads. Then the well trained NARX neural network is tested after converting the series-parallel architecture NARX neural network to parallel architecture one. Instantaneous reactive power algorithm is integrated with NARX neural networks to decompose the dominant harmonics. Finally, the control reference signal of shunt APF is designed. The proposed method is applied on an Electrical Submersible Pump (ESP) driven by three-phase induction motor which is one of most commonly used loads in petroleum industry field. The results show very good behavior of the NARX neural network in harmonic detection and mitigation.
Authors and Affiliations
Tarek M. N. Alkhaldi
Keywords
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- EP ID EP395126
- DOI 10.9790/9622-0809012430.
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