Int. J. of Wireless and Mobile Computing   »   2014 Vol.7, No.2

 

 

Title: A novel ANN-based harmonic extraction method tested with ESN, RNN and MLP in shunt active power filters

 

Authors: Jinbang Xu; Jun Yang; Anwen Shen; Junfeng Chen

 

Addresses:
Image Processing and Intelligent Control Key Laboratory of Education Ministry of China, Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Image Processing and Intelligent Control Key Laboratory of Education Ministry of China, Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Image Processing and Intelligent Control Key Laboratory of Education Ministry of China, Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Image Processing and Intelligent Control Key Laboratory of Education Ministry of China, Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China

 

Abstract: With the wide use of power conversion devices - 'nonlinear loads' - many harmonic currents are being injected into the power grid. Shunt Active Power Filters (SAPF) are the power electronic equipment to compensate the harmonic currents caused by nonlinear loads. As the foundation of the harmonics recognition and compensation, harmonic extraction is the key technology in SAPF. Artificial Neural Networks (ANN) method has the features of parallel computation and satisfactory results for distorted source voltages over traditional extraction methods. This paper proposes a new harmonic extraction method based on ANN. To test the feasibility of different types of neural networks in this application, this paper compares the performances of three types of ANN: Echo State Networks (ESN), Recurrent Neural Networks (RNN) and Multilayer Perceptron Networks (MLP).

 

Keywords: SAPF; shunt active power filters; harmonic extraction; ANNs; artificial neural networks; ESN; echo state networks; RNN; recurrent neural networks; MLP; multilayer perceptron; power conversion; harmonic currents; nonlinear loads.

 

DOI: 10.1504/IJWMC.2014.059708

 

Int. J. of Wireless and Mobile Computing, 2014 Vol.7, No.2, pp.123 - 131

 

Submission date: 07 May 2013
Date of acceptance: 07 Jul 2013
Available online: 06 Mar 2014

 

 

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