Application of Artificial Neural Networks for Shunt Active Power Filter Control

Artificial neural network (ANN) is becoming an attractive estimation and regression technique in many control applications due to its parallel computing nature and high learning capability. There has been a lot of effort in employing the ANN in shunt active power filter (APF) control applications. Adaptive Linear Neuron (ADALINE) and feed-forward multilayer neural network (MNN) are the most commonly used ANN techniques to extract fundamental and/or harmonic components present in the nonlinear currents. This paper aims to provide an in-depth understanding on realizing ADALINE and feed-forward MNN-based control algorithms for shunt APF. A step-by-step procedure to implement these ANN-based techniques in MATLAB/Simulink environment is provided. Furthermore, a detailed analysis on the performance, limitation, and advantages of both methods is presented in the paper. The study is supported by conducting both simulation and experimental validations.

[1]  Cheng-I Chen,et al.  Radial-Basis-Function-Based Neural Network for Harmonic Detection , 2010, IEEE Transactions on Industrial Electronics.

[2]  H. Lin.  Intelligent Neural Network-Based Fast Power System Harmonic Detection , 2007, IEEE Transactions on Industrial Electronics.

[3]  Kamal Al-Haddad,et al.  A review of active filters for power quality improvement , 1999, IEEE Trans. Ind. Electron..

[4]  Alexandru Bitoleanu,et al.  A DSP-Based Implementation of the p-q Theory in Active Power Filtering Under Nonideal Voltage Conditions , 2013, IEEE Transactions on Industrial Informatics.

[5]  Maciej Krawczak,et al.  Multilayer Neural Networks: A Generalized Net Perspective , 2013 .

[6]  Mohd Amran Mohd Radzi,et al.  Neural Network and Bandless Hysteresis Approach to Control Switched Capacitor Active Power Filter for Reduction of Harmonics , 2009, IEEE Transactions on Industrial Electronics.

[7]  Mark Sumner,et al.  Control and Modulation of a Multilevel Active Filtering Solution for Variable-Speed Constant-Frequency More-Electric Aircraft Grids , 2013, IEEE Transactions on Industrial Informatics.

[8]  Bhim Singh,et al.  Neural Network-Based Selective Compensation of Current Quality Problems in Distribution System , 2007, IEEE Transactions on Industrial Electronics.

[9]  Patrice Wira,et al.  A Unified Artificial Neural Network Architecture for Active Power Filters , 2007, IEEE Transactions on Industrial Electronics.

[10]  Kamal Al-Haddad,et al.  Digital Control of a Shunt Hybrid Power Filter Adopting a Nonlinear Control Approach , 2013, IEEE Transactions on Industrial Informatics.

[11]  Yaow-Ming Chen,et al.  Active power line conditioner with a neural network control , 1996, IAS '96. Conference Record of the 1996 IEEE Industry Applications Conference Thirty-First IAS Annual Meeting.

[12]  Yoichi Hori,et al.  An Adaptive Speed Sensorless Induction Motor Drive With Artificial Neural Network for Stability Enhancement , 2012, IEEE Transactions on Industrial Informatics.

[13]  Ronald G. Harley,et al.  Recurrent Neural Networks Trained With Backpropagation Through Time Algorithm to Estimate Nonlinear Load Harmonic Currents , 2008, IEEE Transactions on Industrial Electronics.

[14]  Hao Yu,et al.  Selection of Proper Neural Network Sizes and Architectures—A Comparative Study , 2012, IEEE Transactions on Industrial Informatics.

[15]  Gil D. Marques,et al.  An instantaneous active and reactive current component method for active filters , 2000 .

[16]  P.L. So,et al.  Improvement of power quality using adaptive shunt active filter , 2005, IEEE Transactions on Power Delivery.

[17]  João Luiz Afonso,et al.  Real time digital control system for a single-phase shunt active power filter , 2012, IEEE 10th International Conference on Industrial Informatics.

[18]  R. Ghazi,et al.  IEEE-519-Based Real-Time and Optimal Control of Active Filters under Nonsinusoidal Line Voltages Using Neural Networks , 2002, IEEE Power Engineering Review.

[19]  R.G. Harley,et al.  Neural Network Based Method for Predicting Nonlinear Load Harmonics , 2007, IEEE Transactions on Power Electronics.

[20]  Avik Bhattacharya,et al.  A Shunt Active Power Filter With Enhanced Performance Using ANN-Based Predictive and Adaptive Controllers , 2011, IEEE Transactions on Industrial Electronics.

[21]  Cheng-I Chen,et al.  Radial basis function-based neural network for harmonics detection , 2010, 2010 5th IEEE Conference on Industrial Electronics and Applications.

[22]  Eduard Aved’yan,et al.  Multilayer Neural Networks , 1995 .

[23]  Taotao Jin,et al.  One-cycle control of three-phase active power filter with vector operation , 2004, IEEE Transactions on Industrial Electronics.

[24]  J. H. Marks,et al.  Predictive transient-following control of shunt and series active power filters , 2002 .

[25]  Hatem H. Zeineldin,et al.  A Noniterative Optimized Algorithm for Shunt Active Power Filter Under Distorted and Unbalanced Supply Voltages , 2013, IEEE Transactions on Industrial Electronics.

[26]  Mukhtiar Singh,et al.  Real-Time Implementation of ANFIS Control for Renewable Interfacing Inverter in 3P4W Distribution Network , 2013, IEEE Transactions on Industrial Electronics.

[27]  James G. Kelly.  Talking Nets: An Oral History of Neural Networks , 2001 .

[28]  Teresa Orlowska-Kowalska,et al.  FPGA Implementation of ADALINE-Based Speed Controller in a Two-Mass System , 2013, IEEE Transactions on Industrial Informatics.

[29]  Takeshi Furuhashi,et al.  A study on the theory of instantaneous reactive power , 1990 .