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Volume 4 Issue 3
Jul.  2017

IEEE/CAA Journal of Automatica Sinica

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Naresh Malla, Ujjwol Tamrakar, Dipesh Shrestha, Zhen Ni and Reinaldo Tonkoski, "Online Learning Control for Harmonics Reduction Based on Current Controlled Voltage Source Power Inverters," IEEE/CAA J. Autom. Sinica, vol. 4, no. 3, pp. 447-457, July 2017. doi: 10.1109/JAS.2017.7510541
Citation: Naresh Malla, Ujjwol Tamrakar, Dipesh Shrestha, Zhen Ni and Reinaldo Tonkoski, "Online Learning Control for Harmonics Reduction Based on Current Controlled Voltage Source Power Inverters," IEEE/CAA J. Autom. Sinica, vol. 4, no. 3, pp. 447-457, July 2017. doi: 10.1109/JAS.2017.7510541

Online Learning Control for Harmonics Reduction Based on Current Controlled Voltage Source Power Inverters

doi: 10.1109/JAS.2017.7510541
Funds:  This work was partly supported by Microsoft Inc.Recommended by Associate Editor Qinglai Wei
More Information
  • Nonlinear loads in the power distribution system cause non-sinusoidal currents and voltages with harmonic components. Shunt active filters (SAF) with current controlled voltage source inverters (CCVSI) are usually used to obtain balanced and sinusoidal source currents by injecting compensation currents. However, CCVSI with traditional controllers have a limited transient and steady state performance. In this paper, we propose an adaptive dynamic programming (ADP) controller with online learning capability to improve transient response and harmonics. The proposed controller works alongside existing proportional integral (PI) controllers to efficiently track the reference currents in the d -q domain. It can generate adaptive control actions to compensate the PI controller. The proposed system was simulated under different nonlinear (three-phase full wave rectifier) load conditions. The performance of the proposed approach was compared with the traditional approach. We have also included the simulation results without connecting the traditional PI control based power inverter for reference comparison. The online learning based ADP controller not only reduced average total harmonic distortion by 18.41 %, but also outperformed traditional PI controllers during transients.

     

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  • [1]
    ECPE Europen Center for Power Electronics, EPE European Power Electronics and Drives Association, Position paper on energy efficiencythe role of power electronics, in European Workshop on Energy Efficiencythe Role of Power Electronics, 2007.
    [2]
    D. O. Abdeslam, P. Wira, J. Merckle, D. Flieller, and Y. A. Chapuis, "A unified artificial neural network architecture for active power filters, " IEEE Trans. Industr. Electron., vol. 54, no. 1, pp. 61-76, Feb. 2007.
    [3]
    F. S. dos Reis, J. Ale, F. D. Adegas, R. Tonkoski, S. Slan, and K. Tan, "Active shunt filter for harmonic mitigation in wind turbines generators, " in Proc. 37th IEEE Power Electronics Specialists onf., Jeju, Korea, 2006, pp. 1-6. http://www.academia.edu/5228523/Active_Shunt_Filter_for_Harmonic_Mitigation_in_Wind_Turbines_Generators
    [4]
    L. Asiminoael, F. Blaabjerg, and S. Hansen, "Detection is key-harmonic detection methods for active power filter applications, " IEEE Ind. Appl. Mag., vol. 13, no. 4, pp. 22-33, Jul.-Aug. 2007.
    [5]
    L. Marconi, F. Ronchi, and A. Tilli, "Robust nonlinear control of shunt active filters for harmonic current compensation, " Automatica, vol. 43, no. 2, pp. 252-263, Feb. 2007.
    [6]
    IEEE recommended practice and requirements for harmonic control in electric power systems, IEEE Standard 519-2014, 2014, pp. 1-29.
    [7]
    J. Vazquez and P. Salmeron, "Active power filter control using neural network technologies, " IEEE Proc. Electr. Power Appl., vol. 150, no. 2. pp. 139-145, Mar. 2003.
    [8]
    H. Akagi, A. Nabae, and S. Atoh, "Control strategy of active power filters using multiple voltage-source PWM converters, " IEEE Trans. Ind. Appl., vol. IA-22, no. 3, pp. 460-465, May 1986.
    [9]
    V. Soares, P. Verdelho, and G. D. Marques, "An instantaneous active and reactive current component method for active filters, " IEEE Trans. Power Electron., vol. 15, no. 4, pp. 660-669, Jul. 2000.
    [10]
    S. Buso, L. Malesani, and P. Mattavelli, "Comparison of current control techniques for active filter applications, " IEEE Trans. Industr. Electron., vol. 45, no. 5, pp. 722-729, Oct. 1998.
    [11]
    L. L. Lai, Intelligent System Applications in Power Engineering:Evolutionary Programming and Neural Networks. Chichester, England, New York, USA:John Wiley & Sons, Inc., 1998.
    [12]
    M. A. M. Radzi and N. A. Rahim, "Neural network and bandless hysteresis approach to control switched capacitor active power filter for reduction of harmonics, " IEEE Trans. Industr. Electron., vol. 56, no. 5, pp. 1477-1484, May 2009.
    [13]
    X. G. Fu, S. H. Li, M. Fairbank, D. C. Wunsch, and E. Alonso, "Training recurrent neural networks with the Levenberg-Marquardt algorithm for optimal control of a grid-connected converter, " IEEE Trans. Neural Netw. Learn. Syst., vol. 26, no. 9, pp. 1900-1912, Sep. 2015.
    [14]
    R. P. Aguilera, P. Acuna, P. Lezana, G. Konstantinou, B. Wu, S. Bernet, and V. G. Agelidis, "Selective harmonic elimination model predictive control for multilevel power converters, " IEEE Trans. Power Electron., vol. 32, no. 3, pp. 2416-2426, Mar. 2017.
    [15]
    H. A. Young, M. A. Perez, and J. Rodriguez, "Analysis of finite-controlset model predictive current control with model parameter mismatch in a three-phase inverter, " IEEE Trans. Industr. Electron., vol. 63, no. 5, pp. 3100-3107, May 2016.
    [16]
    F. L. Lewis and D. R. Liu, Reinforcement Learning and Approximate Dynamic Programming for Feedback Control. Piscataway, NJ, USA:Wiley-IEEE Press, 2012.
    [17]
    J. Si, A. G. Barto, W. B. Powell, and D. C. Wunsch, Handbook of Learning and Approximate Dynamic Programming. Hoboken, NJ, USA:IEEE Press and John Wiley Sons, 2004.
    [18]
    J. Si and Y. T. Wang, "Online learning control by association and reinforcement, " IEEE Trans. Neural Netw., vol. 12, no. 2, pp. 264-276, Mar. 2001.
    [19]
    H. B. He, Z. Ni, and J. Fu, "A three-network architecture for on-line learning and optimization based on adaptive dynamic programming, " Neurocomputing, vol. 78, no. 1, pp. 3-13, Feb. 2012.
    [20]
    W. T. Guo, F. Liu, J. Si, D. W. He, R. Harley, and S. W. Mei, "Approximate dynamic programming based supplementary reactive power control for DFIG wind farm to enhance power system stability, " Neurocomputing, vol. 170, pp. 417-427, Dec. 2015.
    [21]
    H. G. Zhang, X. Zhang, Y. H. Luo, and J. Yang, "An overview of research on adaptive dynamic programming, " Acta Automat. Sinica, vol. 39, no. 4, pp. 303-311, Apr. 2013.
    [22]
    Q. L. Wei, D. R. Liu, Q. Lin, and R. Z. Song, "Adaptive dynamic programming for discrete-time zero-sum games, " IEEE Trans. Neural Netw. Lear. Syst., to be published. doi:10.1109/TNNLS.2016.2638863.
    [23]
    Z. Ni, H. B. He, J. Y. Wen, and X. Xu, "Goal representation heuristic dynamic programming on maze navigation, " IEEE Trans. Neural Netw. Lear. Syst., vol. 24, no. 12, pp. 2038-2050, Dec. 2013.
    [24]
    C. Lu, J. Si, and X. R. Xie, "Direct heuristic dynamic programming for damping oscillations in a large power system, " IEEE Trans. Syst. Man Cybern. B Cybern., vol. 38, no. 4, pp. 1008-1013, Aug. 2008.
    [25]
    Y. F. Tang, H. B. He, Z. Ni, J. Y. Wen, and X. C. Sui, "Reactive power control of grid-connected wind farm based on adaptive dynamic programming, " Neurocomputing, vol. 125, pp. 125-133, Feb. 2014.
    [26]
    Y. F. Tang, H. B. He, Z. Ni, J. Y. Wen, and T. W. Huang, "Adaptive modulation for DFIG and STATCOM with high-voltage direct current transmission, " IEEE Trans. Neural Netw. Lear. Syst., vol. 27, no. 8, pp. 1762-1772, Aug. 2016.
    [27]
    W. T. Guo, F. Liu, J. Si, D. W. He, R. Harley, and S. W. Mei, "Online supplementary ADP learning controller design and application to power system frequency control with large-scale wind energy integration, " IEEE Trans. Neural Netw. Lear. Syst., vol. 27, no. 8, pp. 1748-1761, Aug. 2016.
    [28]
    J. Na and G. Herrmann, "Online adaptive approximate optimal tracking control with simplified dual approximation structure for continuous-time unknown nonlinear systems, " IEEE/CAA J. Automat. Sinica, vol. 1, no. 4, pp. 412-422, Oct. 2014.
    [29]
    W. Guo, F. Liu, J. Si, and S. W. Mei, "Incorporating approximate dynamic programming-based parameter tuning into PD-type virtual inertia control of DFIGs, " in Proc. 2013 Int. Joint Conf. Neural Networks (IJCNN), Dallas, TX, USA, 2013, pp. 1-8.
    [30]
    Z. Ni, Y. F. Tang, X. C. Sui, H. B. He, and J. Y. Wen, "An adaptive neuro-control approach for multi-machine power systems, " Int. J. Electr. Power Energy Syst., vol. 75, pp. 108-116, Feb. 2016.
    [31]
    Z. Ni, Y. F. Tang, H. B. He, and J. Y. Wen, "Multi-machine power system control based on dual heuristic dynamic programming, " in Proc. 2014 IEEE Symp. Computational Intelligence Applications in Smart Grid (CIASG), Orlando, FL, USA, 2014, pp. 1-7. http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=7011566&abstractAccess=no&userType=inst
    [32]
    U. Tamrakar, N. Malla, D.Shrestha, Z. Ni, and R. Tonkoski, "Design of online supplementary adaptive dynamic programming for current control in power electronic systems, " in Proc. of IEEE Energy Conversion Congress and Exposition (ECCE'17), Cincinnati, OH, USA, Oct. 1-5, 2017, pp. 1-5.
    [33]
    Q. L. Wei, D. R. Liu, G. Shi, and Y. Liu, "Multibattery optimal coordination control for home energy management systems via distributed iterative adaptive dynamic programming, " IEEE Trans. Industr. Electron., vol. 62, no. 7, pp. 4203-4214, Jul. 2015.
    [34]
    S. Poudel, Z. Ni, and N. Malla, "Real-time cyber physical system testbed for power system security and control, " Int. J. Electr. Power Energy Syst., vol. 90, pp. 124-133, Sep. 2017.
    [35]
    Z. Ni, H. B. He, D. B. Zhao, X. Xu, and D. V. Prokhorov, "Grdhp:A general utility function representation for dual heuristic dynamic programming, " IEEE Trans. Neural Netw. Lear. Syst., vol. 26, no. 3, pp. 614-627, Mar. 2015.
    [36]
    Y. F. Tang, H. B. He, J. Y. Wen, and J. Liu, "Power system stability control for a wind farm based on adaptive dynamic programming, " IEEE Trans. Smart Grid, vol. 6, no. 1, pp. 166-177, Jan. 2015.
    [37]
    L. Dong, Y. F. Tang, H. B. He, and C. Y. Sun, "An event-triggered approach for load frequency control with supplementary ADP, " IEEE Trans. Power Syst., vol. 32, no. 1, pp. 581-589, Jan. 2017.
    [38]
    Y. F. Tang, J. Yang, J. Yan, and H. B. He, "Intelligent load frequency controller using GrADP for island smart grid with electric vehicles and renewable resources, " Neurocomputing, vol. 170, pp. 406-416, Dec. 2015.
    [39]
    S. H. Li, D. C. Wunsch, M. Fairbank, and E. Alonso, "Vector control of a grid-connected rectifier/inverter using an artificial neural network, " in Proc. 2012 Int. Joint Conf. Neural Networks (IJCNN), Brisbane, QLD, Australia, 2012, pp. 1-7.
    [40]
    S. H. Li, M. Fairbank, C. Johnson, D. C. Wunsch, E. Alonso, and J. L. Proao, "Artificial neural networks for control of a grid-connected rectifier/inverter under disturbance, dynamic and power converter switching conditions, " IEEE Trans. Neural Netw. Lear. Syst., vol. 25, no. 4, pp. 738-750, Apr. 2014.
    [41]
    M. Fairbank, S. H. Li, X. G. Fu, E. Alonso, and D. Wunsch, "An adaptive recurrent neural-network controller using a stabilization matrix and predictive inputs to solve a tracking problem under disturbances, " Neural Netw., vol. 49, pp. 74-86, Jan. 2014.
    [42]
    S. H. Li, M. Fairbank, X. G. Fu, D. C. Wunsch, and E. Alonso, "Nestedloop neural network vector control of permanent magnet synchronous motors, " in Proc. 2013 Int. Joint Conf. Neural Networks (IJCNN), Dallas, TX, USA, 2013, pp. 1-8. https://www.researchgate.net/publication/261283493_Nested-loop_neural_network_vector_control_of_permanent_magnet_synchronous_motors
    [43]
    N. Malla, D. Shrestha, Z. Ni, and R. Tonkoski, "Supplementary control for virtual synchronous machine based on adaptive dynamic programming, " in Proc. 2016 IEEE Congr. Evolutionary Computation (CEC), Vancouver, BC, Canada, 2016, pp. 1998-2005. http://ieeexplore.ieee.org/abstract/document/7744033/
    [44]
    U. Tamrakar, R. Tonkoski, Z. Ni, T. M. Hansen, and I. Tamrakar, "Current control techniques for applications in virtual synchronous machines, " in Proc. 2016 IEEE 6th Int. Conf. Power Systems (ICPS), New Delhi, India, 2016, pp. 1-6. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7584166
    [45]
    R. Bellman, Dynamic Programming. Princeton, UK:Princeton University Press, 1957.
    [46]
    Q. L. Wei, D. R. Liu, and H. Q. Lin, "Value iteration adaptive dynamic programming for optimal control of discrete-time nonlinear systems, " IEEE Trans. Cybern., vol. 46, no. 3, pp. 840-853, Mar. 2016.
    [47]
    Q. L. Wei, D. R. Liu, and X. Yang, "Infinite horizon self-learning optimal control of nonaffine discrete-time nonlinear systems, " IEEE Trans. Neural Netw. Lear. Syst., vol. 26, no. 4, pp. 866-879, Apr. 2015.
    [48]
    Q. L. Wei, F. L. Lewis, D. R. Liu, R. Z. Song, and H. Q. Lin, "Discretetime local value iteration adaptive dynamic programming:Convergence analysis, " IEEE Trans. Syst. Man Cybern. Syst., to be published. doi: 10.1109/TSMC.2016.2623766.
    [49]
    Q. L. Wei, D. R. Liu, and Q. Lin, "Discrete-time local value iteration adaptive dynamic programming:Admissibility and termination analysis, " IEEE Trans. Neural Netw. Lear. Syst., to be published. doi: 10.1109/TNNLS.2016.2593743.
    [50]
    Z. Ni, H. B. He, and J. Y. Wen, "Adaptive learning in tracking control based on the dual critic network design, " IEEE Trans. Neural Netw. Lear. Syst., vol. 24, no. 6, pp. 913-928, Jun. 2013.
    [51]
    X. Luo and J. Si, "Stability of direct heuristic dynamic programming for nonlinear tracking control using PID neural network, " in Proc. 2013 Int. Joint Conf. Neural Networks (IJCNN), Dallas, TX, USA, 2013, pp. 1-7. https://asu.pure.elsevier.com/en/publications/stability-of-direct-heuristic-dynamic-programming-for-nonlinear-t
    [52]
    X. N. Zhong, Z. Ni, and H. B. He, "A theoretical foundation of goal representation heuristic dynamic programming, " IEEE Trans. Neural Netw. Lear. Syst., vol. 27, no. 12, pp. 2513-2525, Dec. 2016.
    [53]
    F. Liu, J. Sun, J. Si, W. T. Guo, and S. W. Mei, "A boundedness result for the direct heuristic dynamic programming, " Neural Netw., vol. 32, pp. 229-235, Aug. 2012.
    [54]
    L. Yang, J. Si, K. S. Tsakalis, and A. A. Rodriguez, "Direct heuristic dynamic programming for nonlinear tracking control with filtered tracking error, " IEEE Trans. Syst. Man Cybern. B Cybern., vol. 39, no. 6, pp. 1617-1622, Dec. 2009.
    [55]
    H. G. Zhang, J. L. Zhang, G. H. Yang, and Y. H. Luo, "Leader-based optimal coordination control for the consensus problem of multiagent differential games via fuzzy adaptive dynamic programming, " IEEE Trans. Fuzzy Syst., vol. 23, no. 1, pp. 152-163, Feb. 2015.
    [56]
    Q. L. Wei, R. Z. Song, and P. F. Yan, "Data-driven zero-sum neurooptimal control for a class of continuous-time unknown nonlinear systems with disturbance using ADP, " IEEE Trans. Neural Netw. Lear. Syst., vol. 27, no. 2, pp. 444-458, Feb. 2016.

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