Skip to main content
SpringerLink
Log in

Study of the Intelligent Algorithm of Hilbert-Huang Transform in Advanced Power System

  • Conference paper
  • First Online:
Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2020 (AISI 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1261))

  • 2956 Accesses

Abstract

With the rapid increase in population and electricity consumption, power grid has long formed a large-scale interconnection of systems. The power system is a complex multi-dimensional dynamic system, the traditional system parameter processing method has gradually shown its limitations, which affects the stability and reliability analysis of the system. This study introduces a popular time-frequency intelligent application analysis methodology for nonlinear nonstationary signals–Hilbert-huang transform (HHT) algorithm, then summaries the applications of HHT method for low frequency oscillation of advanced power system, power quality detection and harmonic analysis with combining the research achievements of domestic and foreign scholars in recent years. However, this study discusses the interpolation function and endpoint effect of HHT method in practice and further research on its application in advanced power system.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. He, R., Ai, B., Stüber, G.L., Zhong, Z.: Mobility model-based non-stationary mobile-to-mobile channel modeling. IEEE Trans. Wirel. Commun. 17(7), 4388–4400 (2018)

    Article  Google Scholar 

  2. Zhang, J., Tan, X., Zheng, P.: Non-destructive detection of wire rope discontinuities from residual magnetic field images using the Hilbert-Huang transform and compressed sensing. Sensors 17, 608 (2017)

    Article  Google Scholar 

  3. Chang, K.C., Chu, K.C., Wang, H.C., Lin, Y.C., Pan, J.S.: Energy saving technology of 5G base station based on internet of things collaborative control. IEEE Access 8, 32935–32946 (2020)

    Article  Google Scholar 

  4. Huang, N.E., Shen, Z., Long, S.R., et al.: The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. 454(1971), 903–995 (1998)

    Google Scholar 

  5. Chen, D., Lin, J., Li, Y.: Modified complementary ensemble empirical mode decomposition and intrinsic mode functions evaluation index for high-speed train gearbox fault diagnosis. J. Sound Vib. 424, 192–207 (2018). https://doi.org/10.1016/j.jsv.2018.03.018

    Article  Google Scholar 

  6. Zheng, C., et al.: Analysis and control to the ultra-low frequency oscillation in southwest power grid of China: a case study. In: 2018 Chinese Control and Decision Conference (CCDC), Shenyang, pp. 5721–5724 (2018)

    Google Scholar 

  7. Jiang, K., Zhang, C., Ge, X.: Low-frequency oscillation analysis of the train-grid system based on an improved forbidden-region criterion. IEEE Trans. Ind. Appl. 54(5), 5064–5073 (2018)

    Article  Google Scholar 

  8. Chu, K.C., Horng, D.J., Chang, K.C.: Numerical optimization of the energy consumption for wireless sensor networks based on an improved ant colony algorithm. J. IEEE Access 7, 105562–105571 (2019)

    Article  Google Scholar 

  9. Wang, Y., Dong, R.: Improved low frequency oscillation analysis based on multi-signal power system. Control Eng. China 26(07), 1335–1340 (2019)

    Google Scholar 

  10. Lu, C.-C., Chang, K.-C., Chen, C.-Y.: Study of high-tech process furnace using inherently safer design strategies (IV). The advanced thin film manufacturing process design and adjustment. J. Loss Prev. Process Ind. 43, 280–291 (2016)

    Article  Google Scholar 

  11. Lijie, Z.: Application of Prony algorithm based on EMD for identifying model parameters of low-frequency oscillations. Power Syst. Protect. Control 37(23), 9–14+19 (2009)

    Google Scholar 

  12. Ucar, F., Alcin, O.F., Dandil, B., Ata, F.: Power quality event detection using a fast extreme learning machine. Energies 11, 145 (2018)

    Article  Google Scholar 

  13. Lu, C.-C., Chang, K.-C., Chen, C.-Y.: Study of high-tech process furnace using inherently safer design strategies (III) advanced thin film process and reduction of power consumption control. J. Loss Prev. Process Ind. 43, 280–291 (2015)

    Article  Google Scholar 

  14. Sahani, M., Dash, P.K.: Automatic power quality events recognition based on Hilbert Huang transform and weighted bidirectional extreme learning machine. IEEE Trans. Ind. Inf. 14(9), 3849–3858 (2018)

    Article  Google Scholar 

  15. Vergura, S., Carpentieri, M.: Phase coherence index, HHT and wavelet analysis to extract features from active and passive distribution networks. Appl. Sci. 8, 71 (2018)

    Article  Google Scholar 

  16. Zhao, J., Ma, N., Hou, H., Zhang, J., Ma, Y., Shi, W.: A fault section location method for small current grounding system based on HHT. In: 2018 China International Conference on Electricity Distribution (CICED), Tianjin, pp. 1769–1773 (2018)

    Google Scholar 

  17. Li, K., Tian, J., Li, C., Liu, M., Yang, C., Zhang, G.: The detection of low frequency oscillation based on the Hilbert-Huang transform method. In: 2018 China International Conference on Electricity Distribution (CICED), Tianjin, pp. 1376–1379 (2018)

    Google Scholar 

  18. Shi, Z.M., Liu, L., Peng, M., Liu, C.C., Tao, F.J., Liu, C.S.: Non-destructive testing of full-length bonded rock bolts based on HHT signal analysis. J. Appl. Geophys. 151, 47–65 (2018). https://doi.org/10.1016/j.jappgeo.2018.02.001

    Article  Google Scholar 

  19. Kabalci, Y., Kockanat, S., Kabalci, E.: A modified ABC algorithm approach for power system harmonic estimation problems. Electr. Power Syst. Res. 154, 160–173 (2018). https://doi.org/10.1016/j.epsr.2017.08.019

    Article  Google Scholar 

  20. Bečirović, V., Pavić, I., Filipović-Grčić, B.: Sensitivity analysis of method for harmonic state estimation in the power system. Electr. Power Syst. Res. 154, 515–527 (2018). https://doi.org/10.1016/j.epsr.2017.07.029

    Article  Google Scholar 

Download references

Acknowledgment

Project supported by Natural Science Foundation of Fujian Province, China (Grant No. 2015J01630) and Fujian University of Technology Research Fund Project (GY-Z18060).

Author information

Authors and Affiliations

  1. School of Information Science and Engineering, Fujian University of Technology, Fuzhou, China

    Cheng Zhang, Jia-Jing Liu, Kuo-Chi Chang & Yuh-Chung Lin

  2. Fujian Provincial Key Laboratory of Big Data Mining and Applications, Fujian University of Technology, Fuzhou, China

    Kuo-Chi Chang & Yuh-Chung Lin

  3. Institute of Environmental Engineering, National Taiwan University, Taipei, Taiwan

    Hsiao-Chuan Wang

  4. Department of Business Management, Fujian University of Technology, Fuzhou, China

    Kai-Chun Chu

  5. Institute of Construction Engineering and Management, National Central University, Taoyuan, Taiwan

    Tsui-Lien Hsu

  6. College of Mechanical and Electrical Engineering, National Taipei University of Technology, Taipei, Taiwan

    Kuo-Chi Chang

Authors
  1. Cheng Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jia-Jing Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kuo-Chi Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hsiao-Chuan Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yuh-Chung Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Kai-Chun Chu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Tsui-Lien Hsu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kuo-Chi Chang .

Editor information

Editors and Affiliations

  1. Faculty of Computers and Artificial Intelligence, Information Technology Department, and Chair of the Scientific Research Group in Egypt, Cairo University, Cairo, Egypt

    Aboul Ella Hassanien

  2. Department of Electronics and Computer Science, Koszalin University of Technology, Koszalin, Poland

    Adam Slowik

  3. Faculty of Electrical Engineering and Computer Science, VĹ B-Technical University of Ostrava, Ostrava-Poruba, Moravskoslezsky, Czech Republic

    Václav Snášel

  4. Rector of the Electronic Research Institute, Cairo, Egypt

    Hisham El-Deeb

  5. Faculty of computers and information, Ain Shams University, Cairo, Egypt

    Fahmy M. Tolba

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Zhang, C. et al. (2021). Study of the Intelligent Algorithm of Hilbert-Huang Transform in Advanced Power System. In: Hassanien, A.E., Slowik, A., Snášel, V., El-Deeb, H., Tolba, F.M. (eds) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2020. AISI 2020. Advances in Intelligent Systems and Computing, vol 1261. Springer, Cham. https://doi.org/10.1007/978-3-030-58669-0_52

Download citation

Publish with us

Policies and ethics

Search

Navigation