Skip to main content
SpringerLink
Log in

Analysis of PQ Disturbances in Renewable Grid Integration System Using Non-parametric Spectral Estimation Approach

  • Conference paper
  • First Online:
Innovations in Computational Intelligence and Computer Vision

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1189))

  • 851 Accesses

Abstract

This paper presents non-parametric spectral estimation of power quality disturbances occurring in photovoltaic and wind-integrated systems. The primary non-parametric technique for spectral estimation is periodogram which suffers from a main limitation of offside lobe leakage due to finite signal length. Therefore, this work has proposed power spectral density estimation of voltage signals using Welch method that is a modified version of periodogram. Welch spectrum shows peaks only at the frequencies present in the power quality signal. Thus, it offers correct frequency estimation of non-stationary voltage signals and consequently helps in detection of power quality disturbances. The distributed generation model consisting of solar and wind energy integrated with grid is developed in MATLAB and three-phase disturbance signals are taken from point of common coupling for being segmented further. Three types of power quality disturbances, i.e., harmonics, transient and harmonics with transient are simulated for validating the efficacy of Welch method.

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 219.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 279.99
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. T. Kerekes, R. Teodorescu, P. Rodriguez, G. Vazquez, E. Aldabas, A new high-efficiency single-phase transformerless PV inverter topology. IEEE Trans. Industr. Electron. 58(1), 184–191 (2010)

    Article  Google Scholar 

  2. M.K. Saini, R. Kapoor, R.K. Beniwal, A. Aggarwal, Recognition of voltage sag causes using fractionally delayed biorthogonal wavelet. Trans. Inst. Measur. Control 41(10), 2851–2863 (2019)

    Article  Google Scholar 

  3. IEEE Standards. IEEE Recommended practice for powering and grounding sensitive electronic equipment. IEEE Std 1100–1992

    Google Scholar 

  4. F.D. Martzloff, Power quality work at the International electrotechnical commission, in International Conference on Power Quality—End-Use Applications and Perspectives (Europe, Sweden, 1997)

    Google Scholar 

  5. M.K. Saini, R. Kapoor, Classification of power quality events—a review. Int. J. Electr. Power Energy Syst. 43(1), 11–19 (2012)

    Article  Google Scholar 

  6. M.G. Ioannides, A new approach for the prediction and identification of generated harmonics by induction generators in transient state. IEEE Trans. Energy Convers. 10(1), 118–125 (1995)

    Article  Google Scholar 

  7. P. Sinha, S.K. Goswami, S. Nath, Wavelet-based technique for identification of harmonic source in distribution system. Int. Trans. Electr. Energy Syst. 26(12), 2552–2572 (2016)

    Article  Google Scholar 

  8. R. Kapoor, M.K. Saini, Multiwavelet transform based classification of PQ events. Int. Trans. Electr. Energy Syst. 22(4), 518–532 (2012)

    Google Scholar 

  9. M.K. Saini, R.K. Beniwal, Design of modified matched wavelet design using lagrange interpolation. In: Second International Conference on Innovative Applications of Computational Intelligence on Power, Energy and Controls with their Impact on Humanity (CIPECH 16) (Ghaziabad, India, 2016), pp. 264–268

    Google Scholar 

  10. M.K. Saini, R.K. Beniwal, Optimum fractionally delayed wavelet design for PQ event detection and classification. Int. Trans. Electr. Energy Syst. 27(10), 1–15 (2017)

    Article  Google Scholar 

  11. M.K. Saini, R.K. Beniwal, Detection and classification of power quality disturbances in wind-grid integrated system using fast time-time transform and small residual-extreme learning machine. Int. Trans. Electr. Energy Syst. 28(4), 1–23 (2018)

    Article  Google Scholar 

  12. P.R. Babu, P.K. Dash, S.K. Swain, S. Sivanagaraju, A new fast discrete S-transform and decision tree for the classification and monitoring of power quality disturbance waveforms. Int. Trans. Electr. Energy Syst. 24(9), 1279–1300 (2014)

    Article  Google Scholar 

  13. R. Kapoor, M.K. Saini, Detection and tracking of short duration variation of power system disturbances using modified potential function. Int. J. Electr. Power Energy Syst. 47, 394–401 (2013)

    Article  Google Scholar 

  14. D.D. Ferreira et al., Extracting the transient events from power system signals by independent component analysis. Int. Trans. Electr. Energy Syst. 26(4), 884–900 (2016)

    Article  Google Scholar 

  15. M.K. Saini, R.K. Beniwal, Recognition of multiple PQ issues using modified EMD and neural network classifier. Iranian J. Electr. Electron. Eng. 14(2), 188–203 (2018)

    Google Scholar 

  16. R.R. Kumar, S.S. Murugan, V. Natarajan, S. Radha, Analysis of power spectral density and development of an adaptive algorithm for filtering wind driven ambient noise in shallow water. In: 3rd International Conference on Electronics Computer Technology (Kanyakumari, 2011), pp. 163–167

    Google Scholar 

  17. J.B. Noshahr, B.M. Kalesar, Harmonic spectrum estimation and analysis of the voltage at the PCC of the distribution network connected to solar plant based on parametric algorithm (Music). In: IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe) (Milan, 2017), pp. 1–6

    Google Scholar 

  18. M.H.J. Bollen, E. Styvaktakis, I. Gu, Categorization and analysis of power system transients. IEEE Trans. Power Del. 20(3), 2298–2306 (2005)

    Article  Google Scholar 

  19. R. Zolfaghari, Y. Shrivastava, V.G. Agelidis, A comparison between different windows in spectral and cross spectral analysis techniques with Kalman filtering for estimating power quality indices. Electr. Power Syst. Res. 84, 128–134 (2012)

    Article  Google Scholar 

  20. N. Femia, G. Spagnuolo, Spectral analysis of switching converters using a generalized transfer function, in Technical Proceedings of Power Electronics Congress (1996), pp. 282–289

    Google Scholar 

  21. S.J. Finney, T.C. Green, B.W. Williams, Spectral characteristics of resonant link inverters. IEEE Trans. Power Electron. 8(4), 562–570 (1993)

    Article  Google Scholar 

  22. Z. Leonowicz, T. Lobos, Power quality evaluation using advanced spectrum estimation methods, in International Conference on Power System Technology (Chongqing, 2006), pp. 1–6

    Google Scholar 

  23. Z. Sun, H. Chen, Y. Chen, Application of periodogram and Welch based spectral estimation to vortex frequency extraction, in Second International Conference on Intelligent System Design and Engineering Application (Sanya, Hainan, 2012), pp. 1383–1386

    Google Scholar 

  24. M.H. Hayes, Statistical Digital Signal Processing and Modelling (Wiley, New York, 2003)

    Google Scholar 

  25. A. Alkan, A.S. Yilmaz, Frequency domain analysis of power system transients using Welch and Yule-Walker AR methods. Energy Convers. Manag. 48, 2129–2135 (2007)

    Article  Google Scholar 

  26. H. Akcay, Spectral estimation in frequency-domain by subspace techniques. Sig. Process. 101, 204–217 (2014)

    Article  Google Scholar 

  27. F. Adamo et al., A spectral estimation method for nonstationary signals analysis with application to power systems. Measurement 73, 247–261 (2015)

    Article  Google Scholar 

  28. R. Zolfaghari, Y. Shrivastava, V.G. Agelidis, Spectral analysis techniques for estimating power quality indices, in Proceedings of 14th International Conference on Harmonics and Quality of Power—ICHQP (Bergamo, 2010), pp. 1–8

    Google Scholar 

  29. J.L. Semmlow, Biosignal and biomedical image processing MATLAB-based applications. Marcel Dekker Inc. (2004)

    Google Scholar 

  30. P. Welch, The use of fast Fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms. IEEE Trans. Audio Electroacoust. 15(2), 70–73 (1967)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Electrical Engineering Department, Sobhasaria Group of Institutions, Sikar, 332001, India

    Rajender Kumar Beniwal

  2. Electrical Engineering Department, D. C. R. University of Science and Technology, Sonepat, 131039, India

    Manish Kumar Saini

Authors
  1. Rajender Kumar Beniwal
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Manish Kumar Saini
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rajender Kumar Beniwal .

Editor information

Editors and Affiliations

  1. Department of Computer and Communication Engineering, Manipal University Jaipur, Jaipur, Rajasthan, India

    Manoj Kumar Sharma

  2. Department of Computer and Communication Engineering, Manipal University Jaipur, Jaipur, Rajasthan, India

    Vijaypal Singh Dhaka

  3. Department of Computer Science, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang, Selangor, Malaysia

    Thinagaran Perumal

  4. Department of Information Technology, Techno India College of Technology, Kolkata, West Bengal, India

    Nilanjan Dey

  5. Faculdade de Engenharia da, Universidade do Porto, Porto, Portugal

    João Manuel R. S. Tavares

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Beniwal, R.K., Saini, M.K. (2021). Analysis of PQ Disturbances in Renewable Grid Integration System Using Non-parametric Spectral Estimation Approach. In: Sharma, M.K., Dhaka, V.S., Perumal, T., Dey, N., Tavares, J.M.R.S. (eds) Innovations in Computational Intelligence and Computer Vision. Advances in Intelligent Systems and Computing, vol 1189. Springer, Singapore. https://doi.org/10.1007/978-981-15-6067-5_17

Download citation

Publish with us

Policies and ethics

Search

Navigation