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Design and Study on Sliding Mode Extremum Seeking Control of the Chaos Embedded Particle Swarm Optimization for Maximum Power Point Tracking in Wind Power Systems

Author

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  • Jui-Ho Chen

    (Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan)

  • Her-Terng Yau

    (Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan)

  • Weir Hung

    (Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan)

Abstract

This paper proposes a sliding mode extremum seeking control (SMESC) of chaos embedded particle swarm optimization (CEPSO) Algorithm, applied to the design of maximum power point tracking in wind power systems. Its features are that the control parameters in SMESC are optimized by CEPSO, making it unnecessary to change the output power of different wind turbines, the designed in-repetition rate is reduced, and the system control efficiency is increased. The wind power system control is designed by simulation, in comparison with the traditional wind power control method, and the simulated dynamic response obtained by the SMESC algorithm proposed in this paper is better than the traditional hill-climbing search (HCS) and extremum seeking control (ESC) algorithms in the transient or steady states, validating the advantages and practicability of the method proposed in this paper.

Suggested Citation

  • Jui-Ho Chen & Her-Terng Yau & Weir Hung, 2014. "Design and Study on Sliding Mode Extremum Seeking Control of the Chaos Embedded Particle Swarm Optimization for Maximum Power Point Tracking in Wind Power Systems," Energies, MDPI, vol. 7(3), pages 1-15, March.
    • Handle: RePEc:gam:jeners:v:7:y:2014:i:3:p:1706-1720:d:34314
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    References listed on IDEAS

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    1. Liu, Bo & Wang, Ling & Jin, Yi-Hui & Tang, Fang & Huang, De-Xian, 2005. "Improved particle swarm optimization combined with chaos," Chaos, Solitons & Fractals, Elsevier, vol. 25(5), pages 1261-1271.
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    Cited by:

    1. Shoudao Huang & Yang Zhang & Zhikang Shuai, 2016. "Capacitor Voltage Ripple Suppression for Z-Source Wind Energy Conversion System," Energies, MDPI, vol. 9(1), pages 1-15, January.
    2. Jui-Ho Chen & Weir Hung, 2015. "Blade Fault Diagnosis in Small Wind Power Systems Using MPPT with Optimized Control Parameters," Energies, MDPI, vol. 8(9), pages 1-20, August.
    3. Oscar Barambones & Jose A. Cortajarena & Patxi Alkorta & Jose M. Gonzalez De Durana, 2014. "A Real-Time Sliding Mode Control for a Wind Energy System Based on a Doubly Fed Induction Generator," Energies, MDPI, vol. 7(10), pages 1-22, October.
    4. Hu, Lu & Xue, Fei & Qin, Zijian & Shi, Jiying & Qiao, Wen & Yang, Wenjing & Yang, Ting, 2019. "Sliding mode extremum seeking control based on improved invasive weed optimization for MPPT in wind energy conversion system," Applied Energy, Elsevier, vol. 248(C), pages 567-575.

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