Skip to main content
SpringerLink
Log in

Accelerated Generalized Correntropy Interior Point Method in Power System State Estimation

  • Conference paper
  • First Online:
CONTROLO 2020 (CONTROLO 2020)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 695))

Included in the following conference series:

Abstract

Classical Weighted Least Squares (WLS) is a well-known and broadly applicable method in many state estimation problems. In power system networks, WLS is particularly used because of its stability and reliability in the cases that measurement noise are Gaussian. Nowadays, with the use of renewable energy sources and the migration to smart grids WLS is no more appropriate because the noises are far from being Gaussian. Recently, a novel state estimation algorithm denoted Generalized Correntropy Interior-Point method (GCIP) was presented that can deal with measurements contaminated by gross errors. Under that conditions, the superiority of GCIP is confirmed in a variety of tests. This paper presents an improved GCIP in terms of computational efficiency. The main computational burden of GCIP arises from a large dimension matrix of the correction equation. By looking into the structure of the data, a new arrangement for this matrix with lower order is presented that helps to reduce computational time remarkably. The efficiency of new method was tested with different IEEE benchmark systems.

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 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 329.99
Price excludes VAT (USA)
  • Durable hardcover 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. Schweppe, F.C., Wildes, J.: Power system static state estimation, part 1: exact model. IEEE Trans. Power Appl. Syst. 89, 120–125 (1970)

    Article  Google Scholar 

  2. Schweppe, F.C., Rom, D.B.: Power system static-state estimation, Part II: Approximate model. IEEE Trans. Power Apparatus Syst. 1, 125–130 (1970)

    Article  Google Scholar 

  3. Monticelli, A.: State Estimation in Electric Power Systems: A Generalized Approach. Springer Science & Business Media, New York (1999)

    Google Scholar 

  4. Carquex, C., Rosenberg, C., Bhattacharya, K.: State estimation in power distribution systems based on ensemble Kalman filtering. IEEE Trans. Power Syst. 33(6), 6600–6610 (2018)

    Article  Google Scholar 

  5. Jabr, R.A., Pal, B.C.: Iteratively reweighted least-squares implementation of the WLAV state estimation method. IEE Proc. Gener. Transm. Distrib. 151(1), 103–108 (2004)

    Article  Google Scholar 

  6. Mili, L., Cheniae, M.G., Vichare, N.S., Rousseeuw, P.J.: Robust state estimation based on projection statistics of power systems. IEEE Trans. Power Syst. 11(2), 1118–1127 (1996)

    Article  Google Scholar 

  7. Zhuang, F., Balasubramanian, R.: Bad data suppression in power system state estimation with a variable quadratic-constant criterion. IEEE Trans. Power Apparatus Syst. 4, 857–863 (1985)

    Article  Google Scholar 

  8. He, G., et al.: Robust state estimator based on maximum normal measurement rate. IEEE Trans. Power Syst. 26(4), 2058–2065 (2011)

    Article  Google Scholar 

  9. Wu, W., et al.: Robust state estimation method based on maximum exponential square. IET Gener. Transm. Distrib. 5(11), 1165–1172 (2011)

    Article  Google Scholar 

  10. Chen, Y., et al.: Maximum exponential absolute value approach for robust state estimation. In: 2012 IEEE International Conference on Power System Technology (POWERCON). IEEE (2012)

    Google Scholar 

  11. Tukey, J.W.: A survey of sampling from contaminated distributions. Contributions to probability and statistics, pp. 448–485 (1960)

    Google Scholar 

  12. Liu, W., Puskal, P.P., José, C.P.: Correntropy: properties and applications in non-Gaussian signal processing. IEEE Trans. Signal Process. 55(11), 5286–5298 (2017)

    Article  MathSciNet  Google Scholar 

  13. Chen, B., et al.: Generalized correntropy for robust adaptive filtering. IEEE Trans. Signal Process. 64(13), 3376–3387 (2016)

    Article  MathSciNet  Google Scholar 

  14. Pesteh, S., Moayyed, H., Miranda, V., Pereira, J., Freitas, V., Costa, A.S., London Jr., J.B.A.: A new interior point solver with generalized correntropy for multiple gross error suppression in state estimation. Electr. Power Syst. Res. 176, 105937 (2019)

    Article  Google Scholar 

  15. Moayyed, H., et al.: Impact of different central path neighborhoods on gross error identification in State Estimation with generalized correntropy interior point method. In: 2019 International Conference on Smart Energy Systems and Technologies (SEST). IEEE (2019)

    Google Scholar 

  16. Pesteh, S., Moayyed, H., Miranda, V.: Favorable properties of interior point method and generalized correntropy in power system state estimation. Electr. Power Syst. Res. 178, 106035 (2020)

    Article  Google Scholar 

  17. Wu, W., Guo, Y., Zhang, B., Bose, A., Hongbin, S.: Robust state estimation method based on maximum exponential square. IET Gener. Transm. Distrib. 5(11), 1165–1172 (2011). https://doi.org/10.1049/iet-gtd.2011.0100

    Article  Google Scholar 

  18. Renyi, A.: Some fundamental questions of information theory. In: Selected Papers of Alfred Renyi, vol. 2, Akademia Kiado, pp. 526–552 (1976)

    Google Scholar 

  19. Ponnambalam, K., Quintana, V., Vannelli, A.: A fast algorithm for power system optimization problems using an interior point method. In: IEEE Power Industry Computer Application Conference (1991)

    Google Scholar 

  20. Momoh, J.A., Guo, S.X., Ogbuobiri, E.C., Adapa, R.: The quadratic interior point method solving power system optimization problems. IEEE Trans. Power Syst. 9(3), 1327–1336 (1994)

    Article  Google Scholar 

  21. Wei, H., Sasaki, H., Nagata, T.: An application of interior point quadratic programming algorithm to power system optimization problems. IEEE Trans. Power Energy 116(2), 174–180 (1996)

    Article  Google Scholar 

  22. Clements, K.A., Davis, P.W., Frey, K.D.: An interior point algorithm for weighted least absolute value power, system state estimation. In: IEEE Winter Power Meeting (1991)

    Google Scholar 

  23. Wei, H., et al.: An interior point method for power system weighted nonlinear L1 norm static state estimation. IEEE Trans. Power Syst. 13(2), 617–623 (1998)

    Article  Google Scholar 

  24. Wei, H., Sasaki, H., Kubokawa, J., Yokoyama, R.: An interior point method for power system weighted nonlinear L/sub 1/norm static state estimation. IEEE Trans. Power Syst. 13(2), 617–623 (1998)

    Google Scholar 

  25. Wei, H., et al.: An interior point method for power system weighted nonlinear L/sub 1/norm static state estimation. IEEE Trans. Power Syst. 13(2), 617–623 (1998)

    Article  Google Scholar 

  26. Zimmerman, R.D., Murillo-Sánchez, C.E., Thomas, R.J.: MATPOWER: steady-state operations, planning and analysis tools for power systems research and education. IEEE Trans. Power Syst. 26(1), 12–19 (2011)

    Google Scholar 

Download references

Acknowledgements

This work was supported in part by R&D Unit UIDB+P/00147/2020 funded FCT/MCTES (PIDDAC) and by projects: STRIDE – NORTE-01-0145-FEDER-000033, funded by N2020, ERDF; IMPROVE - POCI-01-0145-FEDER-031823, MAGIC PTDC/EEI-AUT/32485/2017 and HARMONY - POCI-01-0145-FEDER-031411 funded by FEDER funds through COMPETE2020 – POCI and by national funds (PIDDAC).

Author information

Authors and Affiliations

  1. Faculty of Engineering, University of Porto, Porto, Portugal

    Hamed Moayyed, Diyako Ghaderyan, Yassine Boukili & A. Pedro Aguiar

Authors
  1. Hamed Moayyed
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Diyako Ghaderyan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yassine Boukili
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. A. Pedro Aguiar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hamed Moayyed .

Editor information

Editors and Affiliations

  1. Escola Superior de Tecnologia e Gestão, Instituto Politécnico de Bragança, Bragança, Portugal

    José Alexandre Gonçalves

  2. Escola Superior de Tecnologia e Gestão, Instituto Politécnico de Bragança, Bragança, Portugal

    Manuel Braz-César

  3. Escola Superior de Tecnologia e Gestão, Instituto Politécnico de Bragança, Bragança, Portugal

    João Paulo Coelho

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

Moayyed, H., Ghaderyan, D., Boukili, Y., Aguiar, A.P. (2021). Accelerated Generalized Correntropy Interior Point Method in Power System State Estimation. In: Gonçalves, J.A., Braz-César, M., Coelho, J.P. (eds) CONTROLO 2020. CONTROLO 2020. Lecture Notes in Electrical Engineering, vol 695. Springer, Cham. https://doi.org/10.1007/978-3-030-58653-9_63

Download citation

Publish with us

Policies and ethics

Search

Navigation