Inter-harmonic parameter identification method based on transform with local maximum spectrum

• Autorzy: Sun Lin , Song Jing , Jin Yan

Identyfikatory

DOI

10.24425/aee.2022.140205

• Języki publikacji: EN

Abstrakty

EN

In order to improve the detection accuracy of harmonics/inter-harmonics in power systems, a new method of harmonic/inter-harmonic detection based on synchrosqueezed transform and the Hilbert operator based on local spectrum maximum is proposed. Firstly, the spectrum of inter-harmonic signals is obtained through short-time Fourier transform, and the local maximum value of the spectrum in the frequency direction is detected. Then, based on the maximum frequency of the spectrum, a new frequency redistribution operator and synchronous extraction operator are constructed. It combines the operators with ridge detection for the decomposition of harmonic/inter-harmonic signals, so as to obtain a series of intrinsic mode function (IMF) components. Finally, the instantaneous amplitude and frequency of the IMF components is obtained by using the Hilbert operator. Meanwhile, according to the instantaneous frequency mutation point in the spectrum, the starting and ending time of transient harmonics/inter-harmonics is located accurately. Based on a low signal-to-noise ratio (SNR), the wavelet packet method (WP), Hilbert Marginal Spectrum method (HMS), synchrosqueezing wavelet transform method (SST), the Hybrid SST method (HSST), enhanced empirical wavelet transform (EEWT) and the proposed method are used to identify the harmonic/inter-harmonic parameters, respectively. The experimental results show that the proposed LMSST method can effectively separate the steady-state and transient harmonic/inter-harmonic signals, and has higher detection accuracy and better noise robustness.

Słowa kluczowe

EN

inter-harmonic; parameter identification; power system; synchrosqueezed transform; time-frequency analysis

• Wydawca: Polish Academy of Sciences, Committee on Electrical Engineering
• Czasopismo: Archives of Electrical Engineering
• Rocznik: 2022
• Tom: Vol. 71, nr 1
• Strony: 189--209
• Opis fizyczny: Bibliogr. 33 poz., rys., tab., wz.

Twórcy

autor

Sun Lin

• Wuchang University of Technology China

autor

Song Jing

• National University of Defense Technology, China

autor

Jin Yan

• Wuchang University of Technology, China

Bibliografia

• [1] Hou C., Zhu M., Chen Y., Cai X., Pre-filter phase-locked loop: principles and effects with interharmonic perturbation, IET Renewable Power Generation, vol. 14, no. 16, pp. 3088–3096 (2020), DOI: 10.1049/iet-rpg.2020.0448.
• [2] Jove E., Gonzalev C.J.M., Casteleiro R.J.L. et al., An intelligent system for harmonic distortions detection in wind generator power electronic devices, Neurocomputing, vol. 456, pp. 609–621 (2021), DOI: 10.1016/j.neucom.2020.07.155.
• [3] Altintasi C., Aydin O., Taplamacioglu M.C. et al., Power system harmonic and interharmonic estimation using Vortex Search Algorithm, Electric Power Systems Research, vol. 182, pp. 106187 (2020), DOI: 10.1016/j.epsr.2019.106187.
• [4] Sun Y., Lin Y., Wang Y. et al., Theory of symmetric winding distributions and a general method for winding MMF harmonic analysis, IET Electric Power Applications, vol. 14, no. 13 (2021), DOI: 10.1049/iet-epa.2020.0553.
• [5] Cao Q., Shen Q.T., An improved 𝑖𝑝 − 𝑖𝑞 harmonic current detecting method and digital LPF filter’s study, Techniques of Automation and Applications, vol. 29, no. 3, pp. 74–76 (2010), http://en.cnki.com.cn/Article_en/CJFDTotal-ZDHJ201003022.htm.
• [6] Paplinski J.P., Cariow A., Fast 10-Point DFT Algorithm for Power System Harmonic Analysis, Applied Sciences, vol. 11, no. 15, p. 7007 (2021), DOI: 10.3390/app11157007.
• [7] Wu J.Z., Mei F., Chen C., Power system harmonic detection method based on empirical wavelet transform, Power System Protection and Control, vol. 48, no. 6, pp. 136–143 (2020), DOI: 10.19783/j.cnki.pspc.190470.
• [8] Li J., Lin H., Teng Z. et al., Digital prolate spheroidal window-based S-transform for time-varying harmonic analysis, Electric Power Systems Research, vol. 187 (2020), DOI: 10.1016/j.epsr.2020.106512.
• [9] Zhang Y.L., Chen H.W., Parameter identification of harmonics and inter-harmonics based on ceemdwpt and Prony algorithm, Power System Protection and Control, vol. 46, no. 12, pp. 115–121 (2018), DOI: 10.7667/PSPC170866.
• [10] Yang Y.K., Yang M.Y., Application of prony algorithm in parameter identification of harmonics and inter-harmonics, Proceedings of the CSU-EPSA, vol. 24, no. 3, pp. 121–126 (2012), http://en.cnki.com.cn/Article_en/CJFDTOTAL-DLZD201203024.htm.
• [11] Zhang Y., Fan W., Zhang Q., Li X., Harmonic separation from grid voltage with EEMD-ICA and SVD, Computer Measurement and Control, vol. 27, no. 3, pp. 39–43 (2019), http://www.jsjclykz.com/ch/reader/view_abstract.aspx?file_no=201809061095.
• [12] Chen Q., Cai W., Sun L. et al., Harmonic detection method based on VMD, Electrical Measurement and Instrumentation, vol. 55, no. 2, pp. 59–65 (2018), https://doi.org/10.1088/1742-6596/2095/1/012057.
• [13] Thirumala K., Umarikar A.C., Jian T., Estimation of single-phase and three -phase power -quality indices using empirical wavelet transform, IEEE Transactions on Power Delivery, vol. 30, no. 1, pp.445–454 (2015), DOI: 10.1109/TPWRD.2014.2355296.
• [14] Desai V.A., Rathore S., Harmonic detection using Kalman filter, In Proceedings of the 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT), Chennai, India, pp. 858–863 (2016), DOI: 10.1109/ICEEOT.2016.7754808.
• [15] Tiyarachakun S., Areerak K.L., Areerak K.N., Instantaneous Power Theory with Fourier and Optimal Predictive Controller Design for Shunt Active Power Filter, Model. Simul. Eng., pp. 1–20 (2014), DOI: 10.1155/2014/381760.
• [16] Habrouk M., Darwish M.K., Design and implementation of a modified Fourier analysis harmonic current computation technique for power active filters using DSPs, IEEE Proc. Electr. Power Appl., vol. 148, pp. 21–28 (2001), DOI: 10.1049/ip-epa:20010014.
• [17] Karimi H., Karimi G.M., Reza I.M., Bakhshai A.R., An adaptive filter for synchronous extraction of harmonics and distortions, IEEE Trans. Power Deliv., vol. 18, pp. 1350–1356 (2003), DOI: 10.1515/ijeeps2013-0145.
• [18] Musa S., Mohd M.A., Hoon Y., Modified Synchronous Reference Frame Based Shunt Active Power Filter with Fuzzy Logic Control Pulse Width Modulation Inverter, Energies, vol. 10, no. 758 (2017), DOI: 10.3390/en10060758.
• [19] Narongrit T., Areerak K.L., Areerak K.N., A New Design Approach of Fuzzy Controller for Shunt Active Power Filter, Electr. Power Compon. Syst., vol. 43, pp. 685–694 (2015), DOI: 10.1080/15325008.2014.996680.
• [20] Sujitjorn S., Areerak K.L., Kulworawanichpong T., The DQ Axis with Fourier (DQF) Method for Harmonic Identification, IEEE Trans. Power Deliv., vol. 22, pp. 737–739 (2007), DOI: 10.1109/TPWRD.2006.882465.
• [21] Daubechies I., Jianfeng L., Synchrosqueezed wavelet transforms: An empirical mode decompositionlike tool, Applied and Computational Harmonic Analysis, vol. 30, no. 2, pp. 243–261 (2011), DOI: 10.1016/j.acha.2010.08.002.
• [22] Li L., Cai H.Y., Jiang Q.T., Ji H.B., Adaptive synchrosqueezing transformwith a time-varying parameter for non-stationary signal separation, Applied and Computational Harmonic Analysis, vol. 49, no. 3, pp. 1884–2020 (2019), DOI: 10.1016/j.acha.2019.06.002.
• [23] Gang Y., Zhonghu W., Ping Z., Zhen L., Local maximum synchrosqueezing transform: An energyconcentrated time-frequency analysis tool, Mechanical Systems and Signal Processing, vol. 117, pp. 537–552 (2019), DOI: 10.1016/j.ymssp.2018.08.006.
• [24] Lin L., Haiyan C., Qiangtang J., Hongbing J., An empirical signal separation algorithm for multicomponent signals based on linear time-frequency analysis, Mechanical Systems and Signal Processing. vol. 121, pp. 791–809 (2019), DOI: 10.1016/j.ymssp.2018.11.037.
• [25] Rasoul M.M., Alan F.L., Yunwei L., Adaptive control of an active power filter for harmonic suppression and power factor correction, International Journal of Dynamics and Control, pp. 1–10 (2021), DOI: 10.1007/s40435-021-00825-0.
• [26] Avalos O., Cuevas E., Becerra H.G. et al., Kernel Recursive Least Square Approach for Power System Harmonic Estimation, Electric Power Components and Systems, vol. 48, no. 16–17, pp. 1708–1721 (2021), DOI: 10.1080/15325008.2021.1908457.
• [27] Mert A., Celik H.H., Emotion recognition using time-frequency ridges of EEG signals based on multivariate synchrosqueezing transform, Biomedizinische Technik. Biomedical Engineering, vol. 66, no. 4, pp. 345–352 (2021), DOI: 10.1515/bmt-2020-0295.
• [28] Yang C., Ban L., Research on Harmonic Detection System Based on Wavelet Packet Transform, IOP Conf. Series: Journal of Physics: Conf. Series, vol. 1314, no. 012038 (2019), DOI: 10.1088/1742-6596/1314/1/012038.
• [29] Gong M.F. et al., A New Method to Detect Harmonics and Inter-Harmonics Based on Hilbert Marginal Spectrum, Applied Mechanics and Materials, vol. 229–231, pp. 1060–1063 (2012), DOI: 10.4028/ www.scientific.net/AMM.229-231.1060.
• [30] Yu M., Wang B., Wang W.B. et al., An inter-harmonic detection method based on synchrosqueezing wavelet transform, Proceedings of the CSEE, vol. 36, no. 11, pp. 2944–2951 (2016), DOI: 10.13334/j.0258-8013.pcsee.2016.11.010.
• [31] Chang G.W. et al., A Hybrid Approach for Time-Varying Harmonic and Interharmonic Detection Using Synchrosqueezing Wavelet Transform, Applied Sciences, vol. 11, no. 2, pp. 752 (2021), DOI:10.3390/app11020752.
• [32] Khoa N.M., Le V.D., Tung D.D., Toan N.A., An advanced IoT system for monitoring and analysing chosen power quality parameters in micro-grid solution, Archives of Electrical Engineering, vol. 70, no. 1, pp. 173–188 (2021), DOI: 10.24425/aee.2021.136060.
• [33] Yudaev I.V., Rud E.V., Yundin M.A., Ponomarenko T.Z., Isupova A.M., Analysis of the harmonic composition of current in the zero-working wire at the input of the load node with the prevailing non-linear power consumers, Archives of Electrical Engineering, vol. 70, no. 2, pp. 463–473 (2021), DOI: 10.24425/aee.2021.136996

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).