access icon free Fractional order Sprott chaos synchronisation-based real-time extension power quality detection method

It is known that real-time power quality monitoring is usually rather difficult to achieve due to the requirement of expensive equipments and necessary of more signals to be captured. To solve this problem, this study combines fractional order Sprott chaos synchronisation system with extension theory to detect power signal disturbance including voltage swell, sag, interruption, and harmonics for real-time power quality monitoring. The use of fractional order chaotic systems can significantly improve the situations of misjudgement due to the dynamic error is too large by using general integer order chaotic systems. Otherwise, the three-dimensional (3D) Sprott error dynamics can be reduced to 2D error system. It will become easier and cheaper to implement this scheme in the portable device. The results of numerical simulation show that the detection accuracy rate is 100% and it is better than the methods in previous studies. It should be able to get a very high diagnostic accuracy if this method can be applied to the actual power system.

Inspec keywords: chaos; power system faults; numerical analysis; synchronisation; power supply quality; power system measurement

Other keywords: voltage interruption; voltage swell; three-dimensional Sprott error dynamics; dynamic error; numerical simulation; fractional order Sprott chaos synchronisation; real time extension power quality detection; integer order chaotic systems; voltage sag; power signal disturbance; real-time power quality monitoring

Subjects: Power system measurement and metering; Power supply quality and harmonics; Other numerical methods

References

    1. 1)
    2. 2)
      • 11. Lai, T.M., Lo, W.C., To, W.M., et al: ‘RMS percent of wavelet transform for the detection of stochastic high impedance faults’. 2012 IEEE 15th Int. Conf. on Harmonics and Quality of Power (ICHQP), 2012.
    3. 3)
      • 14. Ozgonenel, O., Thomas, D.W.P., Yalcin, T., et al: ‘Detection of blackouts by using K-means clustering in a power system’. 11th Int. Conf. on Developments in Power Systems Protection, 2012. DPSP 2012, 2012.
    4. 4)
      • 22. Tan Chia, K., Kumaran, V., Siam, F.M., et al: ‘Power quality event characterization’. Fourth IET Conf. on Power Electronics, Machines and Drives, 2008. PEMD 2008, 2008.
    5. 5)
    6. 6)
      • 3. Kusko, A.: ‘Power quality in electrical systems’ (The McGraw-Hill Companies, Inc., 2007).
    7. 7)
    8. 8)
      • 16. Peisheng, G., Weilin, W.: ‘Power quality disturbances classification using wavelet and support vector machines’. Sixth Int. Conf. on Intelligent Systems Design and Applications, 2006. ISDA ’06, 2006.
    9. 9)
      • 4. Das, J.C.: ‘Power system analysis: short-circuit load flow and harmonics’ (CRC Press, 2011, 2nd edn.).
    10. 10)
    11. 11)
    12. 12)
    13. 13)
      • 18. Hongsheng, S., Feng, Z.: ‘Chaos detection method for power quality disturbance’. The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006, 2006.
    14. 14)
    15. 15)
      • 24. Abdullah, A.R., Sha'ameri, A.Z., Sidek, A.R.M., et al: ‘Detection and classification of power quality disturbances using time-frequency analysis technique’. Fifth Student Conf. on Research and Development, 2007. SCOReD 2007, 2007.
    16. 16)
    17. 17)
    18. 18)
    19. 19)
      • 17. Xu, W., Cheng, Y., Wang, B.: ‘Microgrid influence on power quality of distribution system and its solution’. 2014 Int. Conf. on Power System Technology (POWERCON), 2014.
    20. 20)
    21. 21)
      • 9. Collazo, L.J., O'Neill Carrillo, E.: ‘Comparison of windowed Fourier transform and dynamic phasors for power quality analysis’. Power Systems Conf. and Exposition, 2009. PSCE '09. IEEE/PES, (2009).
    22. 22)
      • 23. Bhattacharyya, S., Myrzik, J.M.A., Kling, W.L.: ‘Consequences of poor power quality – an overview’. 42nd Int. Universities Power Engineering Conf., 2007. UPEC 2007, 2007.
    23. 23)
    24. 24)
    25. 25)
      • 1. Liu, Y.-Q., Wu, G.-P., Hua, H.-S., et al: ‘Research for the effects of high-speed electrified railway traction load on power quality’. 2011 Fourth Int. Conf. on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), 2011.
    26. 26)
    27. 27)
    28. 28)
    29. 29)
      • 15. Nantian, H., Dianguo, X., Xiaosheng, L.: ‘Power quality disturbance recognition using S transforms and FCM-based decision tree’. IEEE Int. Conf. on Intelligent Computing and Intelligent Systems, 2009. ICIS 2009, 2009.
    30. 30)
      • 2. IEEE Recommended Practice for Monitoring Electric Power Quality’, IEEE Std. 1159–2009 (Revision of IEEE Std. 1159–1995), 2009, pp. c181.
    31. 31)
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