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Fractional Order Chaos Synchronization for Real-Time Intelligent Diagnosis of Islanding in Solar Power Grid Systems

Author

Listed:
  • Cheng-Biao Fu

    (College of Information Engineering, Qujing Normal University, Qujing 655011, China)

  • An-Hong Tian

    (College of Information Engineering, Qujing Normal University, Qujing 655011, China)

  • Yu-Chung Li

    (Department of Mechanical Engineering, National Cheng Kung University, 1 University Road, Tainan City 701, Taiwan)

  • Her-Terng Yau

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

Abstract

Many different methods have been proposed for determining islanding and most of them have drawbacks. The main issue is the difficulty of detecting islanding when the current and voltage values are of the same phase or the frequency remains within the normal range of the grid when islanding occurs. In this study, a non-autonomous Chua’s circuit was used to preprocess the grid signal after which a method based on the fractional Lorenz chaotic system and extension theory was used to analyze the preprocessed voltage signal. The capability of a chaotic system to amplify an extremely small signal was effectively utilized for the diagnosis of grid islanding. Simulation results showed that the diagnostic accuracy of the proposed method could be 100% and no other diagnostic method has offered such accuracy. Furthermore, the method proposed in this study is simple, easy to implement, and could be used as a portable system for the real-time monitoring and diagnosis of islanding in a conventional home grid system.

Suggested Citation

  • Cheng-Biao Fu & An-Hong Tian & Yu-Chung Li & Her-Terng Yau, 2018. "Fractional Order Chaos Synchronization for Real-Time Intelligent Diagnosis of Islanding in Solar Power Grid Systems," Energies, MDPI, vol. 11(5), pages 1-14, May.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:5:p:1183-:d:145147
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    References listed on IDEAS

    as
    1. Meng-Hui Wang & Her-Terng Yau, 2014. "New Power Quality Analysis Method Based on Chaos Synchronization and Extension Neural Network," Energies, MDPI, vol. 7(10), pages 1-18, October.
    2. Rita Pinto & Sílvio Mariano & Maria Do Rosário Calado & José Felippe De Souza, 2016. "Impact of Rural Grid-Connected Photovoltaic Generation Systems on Power Quality," Energies, MDPI, vol. 9(9), pages 1-15, September.
    3. Il-Keun Song & Won-Wook Jung & Chul-Min Chu & Seong-Soo Cho & Hyun-Koo Kang & Joon-Ho Choi, 2013. "General and Simple Decision Method for DG Penetration Level in View of Voltage Regulation at Distribution Substation Transformers," Energies, MDPI, vol. 6(9), pages 1-13, September.
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    Cited by:

    1. Wang, Cong & Zhang, Hong-li & Fan, Wen-hui & Ma, Ping, 2020. "Finite-time function projective synchronization control method for chaotic wind power systems," Chaos, Solitons & Fractals, Elsevier, vol. 135(C).

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