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Arabian Journal for Science and Engineering

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13-02-2021 | Research Article-Electrical Engineering

An Investigation on Variational Mode Decomposition for Synchronization of Power Converters in Future Power Grids

Authors: Bhadra R. Warrier, A. Vijayakumari, T. Palanisami, Sasi K. Kottayil

Published in: Arabian Journal for Science and Engineering | Issue 10/2021

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Abstract

A primary investigation on variational mode decomposition (VMD) technique extended as a grid synchronizer for power converters in emerging electric grids with nonlinear characteristics is presented. Number of modes and data-fidelity parameter of VMD are tailored to achieve finer separation of the fundamental frequency in spite of the spectral band variations and minor frequency deviations of the grid voltage signals. The test cases are formulated based on CIGRÈ and IEEE Task Force 1159.2 repository on the foreseen power quality issues in the emerging power utilities. Two statistical indices viz. absolute error in percentage and RMS error are chosen to assess the compliance of extracted fundamental frequency signals with the applied values at cycle as well as sample level. A significant reduction in the tracking time across all the test conditions has been observed in simulation when compared to the conventional grid synchronizers. Appreciable accuracy levels are obtained in tracking the required signal attributes of the input signals even with multiple power quality issues. The frequency decomposition approach of VMD synchronizer exhibited an immunity toward random transient events like voltage surges, zero crossing disorders, phase and frequency jump, etc. Further, the validation in hardware has been conducted with emulated grid signals that represented mulitple power quality issues and wide range of transient events, and the results are analyzed and compared with those of the simulation.

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A Growing Reliance on Power Electronics. https://www.powerelectronicsworld.net/article/0/79149-a-growing-reliance-on-powerelectronics.html. Accessed 4 Apr 2018

Vijayakumari, A.; Warrier, B.R.; Devarajan, N.: Topologies and control of grid connected power converters. In: International Conference on Circuits, Power and Computing Technologies, pp. 401–410 (2014)

Shah, S.V.P.; Shah, M.T.: Three-phase front end converters and current control techniques for unity power factor. In: Nirma University International Conference on Engineering (NUiCONE), pp. 1–5 (2013)

Baek, J., et al.: Predictive current control of a voltage source inverter. In: IEEE APEC and Exposition, Charlotte, pp. 2256–2260 (2015)

El-Habrouk, M.; Darwish, M.K.; Mehta, P.: Active power filters: a review. IEEE Proc. Electr. Power Appl. 147, 403–413 (2000). https://doi.org/10.1049/ip-epa:20000522CrossRef

Liserre, M.; Rodriguez, P.; Teodorescu, R.: Grid Converters for Photovoltaic and Wind Power Systems. Wiley-IEEE Press, New York (2007)

Han, H.; Hou, X.; Yang, J.; et al.: Review of power sharing control strategies for islanding operation of AC microgrids. IEEE Trans. Smart Grid 7, 200–215 (2016). https://doi.org/10.1109/TSG.2015.2434849CrossRef

Al-Shetwi, A.Q.; Hannan, M.A.; Jern, K.P.; et al.: Grid-connected renewable energy sources: Review of the recent integration requirements and control methods. J. Clean. Prod. 253, 119831 (2020). https://doi.org/10.1016/j.jclepro.2019.119831CrossRef

Surprenant, M.; Hiskens, I.; Venkataramanan, G.: Phase locked loop control of inverters in a microgrid. In: IEEE Energy Conversion Congress and Exposition: Energy Conversion Innovation for a Clean Energy Future, pp. 667–672 (2011). https://doi.org/10.1109/ECCE.2011.6063833

10.

Hossain, M.A.; Pota, H.R.; Issa, W.; Hossain, M.J.: Overview of AC microgrid controls with inverter-interfaced generations. Energies 10, 1–27 (2017). https://doi.org/10.3390/en10091300CrossRef

11.

Ronnberg, S.K.; Bollen, M.H.J.; Meyer, S.J., et al.: Power Quality and EMC Issues With Future Electricity Networks (2018)

12.

Chung, S.-K.: A phase tracking system for three phase utility interface inverters. IEEE Trans. PE 15, 431–438 (2000). https://doi.org/10.1109/63.844502CrossRef

13.

Kanjiya, P.; et al.: A novel type-1 frequency-locked loop for fast detection of frequency and phase with improved stability margins. IEEE Trans. PE 31, 2550–2561 (2016). https://doi.org/10.1109/TPEL.2015.2435706CrossRef

14.

Kulkarni, A.; John, V.: A novel design method for SOGI-PLL for minimum settling time and low unit vector distortion. In: IECON 2013—39th Annual Conference of the IEEE Industrial Electronics Society, Vienna, pp. 274–279 (2013)

15.

Golestan, S.; Guerrero, J.M.; Vasquez, J.C.: Three-phase PLLs: a review of recent advances. IEEE Trans. PE 32, 1897–1907 (2017). https://doi.org/10.1109/TPEL.2016.2565642CrossRef

16.

Guo, X.Q.; Wu, W.Y.; Gu, H.R.: Phase locked loop and synchronization methods for grid interfaced converters: a review. Prz. Elektrotech. 87, 182–187 (2011)

17.

Lokesh, N.; Mishra, M.K.: A comparative performance study of advanced PLLs for grid synchronization. In: 2020 IEEE International Conference on Power Electronics, Smart Grid and Renewable Energy (PESGRE2020), pp. 1–6 (2020)

18.

Ghoshal, A.; John, V.: A method to improve PLL performance under abnormal grid conditions. Electr. Eng. (2007)

19.

Luna, A.; Citro, C.; Gavriluta, C.; et al.: Advanced PLL structures for grid synchronization in distributed generation. Renew. Energy Power Qual. J. 1, 1747–1756 (2012). https://doi.org/10.24084/repqj10.826CrossRef

20.

Rodríguez, P.; Luna, A.; Muñoz-Aguilar, R.S.; Etxeberria-Otadui, I.; Teodorescu, R.; Blaabjerg, F.: A stationary reference frame grid synchronization system for three-phase grid-connected power converters under adverse grid conditions. IEEE Trans. Power Electr. 27, 99–112 (2012). https://doi.org/10.1109/TPEL.2011.2159242CrossRef

21.

Montoya, F.G.; García-Cruz, A.; Montoya, M.G.; Agugliaro, F.M.: Power quality techniques research worldwide: a review. Renew. Sustain. Energy. Rev. 54, 846–856 (2016)CrossRef

22.

Vijayakumari, A.; Devarajan, A.T.; Devarajan, N.; Vijith, K.: Dynamic grid impedance calculation in D-Q frame for micro-grids. In: 014 power and energy systems: towards sustainable energy, pp. 1–6 (2014)

23.

Youssef, O.A.S.: A wavelet-based technique for discrimination between faults and magnetizing inrush currents in transformers. IEEE Trans. PD 18, 170–176 (2003). https://doi.org/10.1109/TPWRD.2002.803797CrossRef

24.

Bochner, Salomon; Chandrasekharan, K.: Fourier Transforms. Princeton University Press, Princeton (1949)MATH

25.

Levent, Sevgi: Numerical Fourier transforms: DFT and FFT. IEEE Antennas Proppag. Mag. 49, 238–243 (2007)

26.

Susan, T.: The Hilbert transform and empirical mode decomposition as tools for data analysis. In: University of Arizona, Tucson (2007)

27.

Luo, Z.; Liu, T.; Yan, S.: Qian M Revised empirical wavelet transform based on auto-regressive power spectrum and its application to the mode decomposition of deployable structure. J. Sound Vib. 431, 70–87 (2018). https://doi.org/10.1016/j.jsv.2018.06.001CrossRef

28.

Pereyra, C.; Mohlenkamp, M.J.: Wavelets, their friends, and what they can do for you, vol. 8. European Mathematical Society, Zürich (2008)MATH

29.

Gilles, J.: Emperical wavelet transform. IEEE Trans. SP 61, 3999–4010 (2013)MathSciNetCrossRef

30.

Toolbox, W.: Short-Time Fourier Analysis (2007)

31.

Giurgiutiu, V., Yu, L.: Comparison of short-time fourier transform and wavelet transform of transient and tone burst wave propagation signals for structural health monitoring. In: Structural Health Monitoring 2003: From Diagnostics and Prognostics to Structural Health Management—Proceedings of the 4th International Workshop on Structural Health Monitoring, IWSHM 2003, pp. 1267–1274 (2003)

32.

Daud, K.; Abidin, A.F.; Hamzah, N.; Singh, H.S.N.: Detection of sags, swells, and transients using windowing technique based on continuous S-transform (CST). Int. J. Electr. Comput. Energy Electr. Commun. Eng. 7, 568–575 (2013)

33.

Dash, P.K.; Panigrahi, B.K.; Panda, G.: Power quality analysis using S-transform. IEEE Trans. Power Deliv. 18, 406–411 (2003). https://doi.org/10.1109/TPWRD.2003.809616CrossRef

34.

Dragomiretskiy, K.; Zosso, D.: Variational mode decomposition. IEEE Trans. SP 62, 531–544 (2014)MathSciNetCrossRef

35.

Achlerkar, P.D.; Samantaray, S.R.; SabarimalaiManikandan, M.: Variational mode decomposition and decision tree based detection and classification of power quality disturbances in grid-connected distributed generation system. IEEE Trans. G 9, 3122–3132 (2018). https://doi.org/10.1109/TSG.2016.2626469CrossRef

36.

Aneesh, C.; Kumar, S.; Hisham, P.M.; Soman, K.P.: Performance comparison of Variational Mode Decomposition over Empirical Wavelet Transform for the classification of power quality disturbances using Support Vector Machine. Procedia Comput. Sci. 46, 372–380 (2015). https://doi.org/10.1016/j.procs.2015.02.033CrossRef

37.

Yang, W.; Peng, Z.; Wei, K.; et al.: Superiorities of variational mode decomposition over empirical mode decomposition particularly in time-frequency feature extraction and wind turbine condition monitoring. IET Renew. Power Gener. 11, 443–452 (2017). https://doi.org/10.1049/iet-rpg.2016.0088CrossRef

38.

Palanisamy, T.: Smoothing the difference-based estimates of variance using variational mode decomposition. Commun. Stat. Simul. Comput. 46, 4991–5001 (2017). https://doi.org/10.1080/03610918.2016.1140777MathSciNetCrossRefMATH

39.

Ahsan, M.K.; Pan, T.; Li, Z.: A three decades of marvellous significant review of power quality events regarding detection & classification. J. Power Energy Eng. 6, 1–37 (2017)CrossRef

40.

Bollen, M.H.J.: Signal Processing of Power Quality Disturbances. Wiley, New York (2005)

41.

Ray, P.; Budumuru, G.K.; Mohanty, B.K.: A comprehensive review on soft computing and signal processing techniques in feature extraction and classification of power quality problems. J. Renew. Sustain. Energy (2018). https://doi.org/10.1063/1.5006772CrossRef

42.

Venkatesh, C.; Siva Sarma, D.V.S.S.:, Techniques used for Detection of Power Quality Events—A Comparative Study. IEEE xplore, pp. 307–312 (2010)

43.

Baccigalupi, A.; Liccardo, A.: The Huang Hilbert Transform for evaluating the instantaneous frequency evolution of transient signals in nonlinear systems. J. Int. Meas. Conf. 86, 1–13 (2016). https://doi.org/10.1016/j.measurement.2016.02.018CrossRef

44.

Dragomiretskiy, K.; Zosso, D.: Two-dimensional variational mode decomposition. In: International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, pp. 197–208. Springer (2015)

45.

IEEE 1159.2: Power Quality Event Characterization IEEE Power Quality Standards (2018)

46.

Huang, N.E.; Wu, Z.; Long, S.R.; et al.: On instantaneous frequency. Adv. Adapt. Data Anal. 1, 177–229 (2009). https://doi.org/10.1142/S1793536909000096MathSciNetCrossRef

47.

Ali, Z.; Christofides, N.; Hadjidemetriou, L.; Kyriakides, E.: A new MAF based αβEPMAFPLL for grid connected RES with improved performance under grid faults. Electr. Power Syst. Res. 154, 130–139 (2018). https://doi.org/10.1016/j.epsr.2017.08.013CrossRef

48.

Ali, Z.; Christofides, N.; Hadjidemetriou, L.; et al.: Three-phase phase-locked loop synchronization algorithms for grid-connected renewable energy systems: a review. Renew. Sustain. Energy Rev. 90, 434–452 (2018). https://doi.org/10.1016/j.rser.2018.03.086CrossRef

49.

Mittal, D.: Classification of power quality disturbances in electric power system: a review. IOSR J. Electr. Electron. Eng. 3, 6–14 (2012). https://doi.org/10.9790/1676-0350614CrossRef

50.

Wang, H.; Sun, H.; Han, M.; Guerrero, J.M.: Phase-lock loop of Grid-connected Voltage Source Converter under non-ideal grid condition. In: 2015 IEEE 1st International Conference on Direct Current Microgrids, ICDCM 2015, pp. 124–128. https://doi.org/10.1109/ICDCM.2015.7152022

51.

Lu, Y.; Xiao, G.; Wang, X.; Blaabjerg, F.: Grid synchronization with selective harmonic detection based on generalized delayed signal superposition. IEEE Trans. Power Electron. 33, 3938–3949 (2018). https://doi.org/10.1109/TPEL.2017.2721461CrossRef

52.

Yuan, L.; Gu, P.; Yang, Z.; et al.: Research on power grid imbalance and harmonics based on improved phase-locked loop. IOP Conf. Ser. Mater. Sci. Eng. 394, 10 (2018). https://doi.org/10.1088/1757-899X/394/4/042012CrossRef

53.

Thirumala, K.; Umarikar, A.C.; Jain, T.: Estimation of single-phase and three-phase power-quality indices using empirical wavelet transform. IEEE Trans. PD 30, 445–454 (2015). https://doi.org/10.1109/TPWRD.2014.2355296CrossRef

54.

Tse, N.C.F.: Practical application of wavelet to power quality analysis. In: IEEE Power Engineering Society General Meeting, p. 5 (2006)

55.

Hadjidemetriou, L.; Kyriakides, E.; Blaabjerg, F.: An adaptive tuning mechanism for phase-locked loop algorithms for faster time performance of interconnected renewable energy sources. IEEE Trans. IA 51, 1792–1804 (2015). https://doi.org/10.1109/TIA.2014.2345880CrossRef

56.

Meral, M.E.: Improved phase-locked loop for robust and fast tracking of three phases under unbalanced electric grid conditions. IET Gener. Trans. Distrib. 6, 152–160 (2012). https://doi.org/10.1049/iet-gtd.2011.0189CrossRef

57.

Chen, J.; Pan, J.; Li, Z.; et al.: Generator bearing fault diagnosis for wind turbine via empirical wavelet transform using measured vibration signals. Renew. Energy 89, 80–92 (2016). https://doi.org/10.1016/j.renene.2015.12.010CrossRef

58.

Chegini, S.N.; Bagheri, A.; Najafi, F.: Application of a new EWT-based denoising technique in bearing fault diagnosis. Meas. J. Int. Meas. Conf. 144, 275–297 (2019). https://doi.org/10.1016/j.measurement.2019.05.049CrossRef

59.

Li, B.; Liu, M.; Guo, Z.; Ji, Y.: Mechanical fault diagnosis of high voltage circuit breakers utilizing EWT-improved time frequency entropy and optimal GRNN classifier. Entropy 20, 10 (2018). https://doi.org/10.3390/e20060448CrossRef

60.

Thirumala, K.; Pal, S.; Jain, T.; Umarikar, A.C.: A classification method for multiple power quality disturbances using EWT based adaptive filtering and multiclass SVM. Neurocomputing 334, 265–274 (2019). https://doi.org/10.1016/j.neucom.2019.01.038CrossRef

61.

Liao, C.-C.; Yang, H.-T.; Chang, H.-H.: Denoising techniques with a spatial noise-suppression method for wavelet-based power quality monitoring. IEEE Trans. IM 60, 1986–1996 (2011). https://doi.org/10.1109/TIM.2011.2115610CrossRef

62.

Biswal, B.; Dash, P.K.; Panigrahi, B.K.; Reddy, J.B.V.: Power signal classification using dynamic wavelet network. Appl. Soft Comput. J. 9, 118–125 (2009). https://doi.org/10.1016/j.asoc.2008.03.005CrossRef

63.

Ramya, S.; Hemalatha, M.: A review on signal decomposition techniques. Middle East J. Sci. Res. 15, 1108–1112 (2013). https://doi.org/10.5829/idosi.mejsr.2013.15.8.11152CrossRef

64.

Soman, K.P.; Poornachandran, P.; Athira, S.; Harikumar, K.: Recursive variational mode decomposition algorithm for real time power signal decomposition. Procedia Technol. 21, 540–546 (2015). https://doi.org/10.1016/j.protcy.2015.10.048CrossRef

Title: An Investigation on Variational Mode Decomposition for Synchronization of Power Converters in Future Power Grids
Authors: Bhadra R. Warrier
A. Vijayakumari
T. Palanisami
Sasi K. Kottayil
Publication date: 13-02-2021
Publisher: Springer Berlin Heidelberg
Published in: Arabian Journal for Science and Engineering / Issue 10/2021
Print ISSN: 2193-567X
Electronic ISSN: 2191-4281
DOI: https://doi.org/10.1007/s13369-020-05238-3

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