access icon free Simultaneous denoising and compression of power system disturbances using sparse representation on overcomplete hybrid dictionaries

© The Institution of Engineering and Technology
Received 25/02/2014, Accepted 19/12/2014, Revised 02/12/2014, Published 20/02/2015

This study introduces a novel unified framework for simultaneous denoising and compression of electric power system disturbance signals using sparse signal decomposition and reconstruction on overcomplete hybrid dictionary (OHD) matrix. In the proposed method, the power quality signal is first decomposed into deterministic sinusoidal components and non-deterministic components using the OHD matrix, including discrete impulse dictionary ( I ), cosine dictionary ( C ), sine dictionary ( S ) and the ℓ1-norm optimisation algorithm. Then, the hard-thresholding, uniform threshold dead-zone quantisation, modified index coding and Huffman coding techniques are used for compression of significant detail signal samples and approximation coefficients. To justify the selection of OHD matrix, four compression methods are implemented using the decomposition techniques based on the dictionaries Ψ = [ I C S ] and Ψ = [ I C ], the wavelet transform (WT) and the discrete cosine transform (DCT). The performance of each method is tested and validated using a wide variety of typical power quality disturbance (PQD) signals taken from the IEEE-1159-PQE and GIM–PQE databases and generated using the Microgrid model. The results show that the method with dictionary Ψ = [ I C S ] is capable of effectively compressing the PQD signals as well as suppressing the noise components in the signals.

Inspec keywords: signal representation; discrete cosine transforms; power supply quality; Huffman codes; wavelet transforms; distributed power generation; power system faults; signal denoising; signal reconstruction; dictionaries

Other keywords: power quality signal; discrete cosine transform; microgrid; electric power system disturbance signals; GIM–PQE databases; deterministic sinusoidal components; sparse signal decomposition; ℓ1-norm optimisation; simultaneous denoising; IEEE-1159-PQE; sparse signal reconstruction; power quality disturbance signals; nondeterministic components; sparse representation; uniform threshold dead-zone quantisation; overcomplete hybrid dictionary matrix; hard thresholding; power system disturbances; modified index coding; unified framework; Huffman coding; cosine dictionary; simultaneous compression; wavelet transform; discrete impulse dictionary

Subjects: Distributed power generation; Codes; Power supply quality and harmonics; Signal processing and detection; Integral transforms

References

    1. 1)
    2. 2)
    3. 3)
    4. 4)
      • 24. Power Quality Events Data Collection, Instituto de Telecomunicaes 2008. Available at: http://www.gim.lx.it.pt/fct57708/data/.
    5. 5)
    6. 6)
      • 18. Lin, L., Huang, N., Huang, W.: ‘Review of power quality signal compression based on wavelet theory’. Int. Conf. on Test and Measurement (ICTM), 2009, vol. 1, pp. 235–238.
    7. 7)
    8. 8)
    9. 9)
      • 25. Kar, S., Samantaray, S.R.: ‘Data-mining based intelligent anti-islanding protection relay for distributed generations’, IET Gener. Transm. Distrib., 2013, doi: pi10.1049/iet-gtd.2013.0494 [Available Online]2014, 8, (4), pp. 629–639.
    10. 10)
    11. 11)
    12. 12)
    13. 13)
    14. 14)
    15. 15)
    16. 16)
    17. 17)
    18. 18)
      • 1. ‘IEEE Recommended Practice for Monitoring Electric Power Quality’, IEEE Std 1159-1995, 1995.
    19. 19)
    20. 20)
    21. 21)
      • 32. Grigoryan, R., Jensen, T.L., Arildsen, T., Larsen, T.: ‘Reducing the computational complexity of reconstruction in compressed sensing nonuniform sampling’. Proc. 21st European Signal Processing Conf. (EUSIPCO), September 2013, pp. 1–5.
    22. 22)
    23. 23)
    24. 24)
    25. 25)
      • 29. Chen, S.S., Donoho, D.L., Saunders, M.A.: ‘Atomic decomposition by basis pursuit’, SIAM J. Sci. Comput., 1998, 20, p. 3361.
    26. 26)
      • 23. IEEE 1159.2: Power Quality Event Characterization, IEEE power quality standards. Available at: http://www.grouper.ieee.org/groups/1159/2/testwave.html.
    27. 27)
    28. 28)
    29. 29)
    30. 30)
    31. 31)
    32. 32)
    33. 33)
      • 22. Kathirvel, P., Sabarimalai Manikandan, M., Maya, P., Soman, K.P.: ‘Detection of power quality disturbances with overcomplete dictionary matrix and l1-norm minimization’. IEEE Int. Conf. Power and Energy Systems (ICPS), December 2011, pp. 1–6.
    34. 34)
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