Skip to main content
SpringerLink
Log in

Local and Wide-Area Sliding-Mode Observers in Power Systems

  • Chapter
  • First Online:
Variable-Structure Systems and Sliding-Mode Control

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 271))

Abstract

This chapter presents a review of sliding-mode estimation techniques recently proposed by the authors in the area of power systems. The power grid is interpreted as a large-scale system, composed of an interconnection of generator nodes and load nodes. The analysis starts at the local level by considering a single generator node for which two dynamical models are presented. The first model relies on the well-established swing equations, while the second one is a nonlinear and more accurate model accounting for the transient voltage dynamics. Dedicated sliding-mode estimators are proposed to estimate the unmeasured states of a single generator node. In addition, the assessment based on real data is discussed, which employs both the lumped generator node model for the Nordic Power System and the data relevant to the major faults which happened in 2015. Then, the attention is focused on the wide-area level by considering an interconnection of generator nodes and load nodes. A structure-preserving power network dynamical model is presented, which exhibits a differential-algebraic equations (DAE) structure. For this large-scale system, a distributed observer scheme is designed, which combines both the use of a super-twisting-like architecture and iterative algorithms for the algebraic part of the system. The distributed observer scheme is validated by using the IEEE 39 bus benchmark.

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 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
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. Kayastha, N., Niyato, D., Hossain, E., Han, Z.: Smart grid sensor data collection, communication, and networking: a tutorial. Wirel. Commun. Mobile Comput. 14(11), 1055–1087 (2014)

    Article  Google Scholar 

  2. Ellabban, O., Abu-Rub, H., Blaabjerg, F.: Renewable energy resources: current status, future prospects and their enabling technology. Renew. Sustain. Energy Rev. 39, 748–764 (2014)

    Article  Google Scholar 

  3. Mohanta, D.K., Murthy, C., Sinha Roy, D.: A brief review of phasor measurement units as sensors for smart grid. Electr. Power Compon. Syst. 44(4), 411–425 (2016)

    Article  Google Scholar 

  4. Zhao, J., Zhang, G., Das, K., Korres, G.N., Manousakis, N.M., Sinha, A.K., He, Z.: Power system real-time monitoring by using pmu-based robust state estimation method. IEEE Trans. Smart Grid 7(1), 300–309 (2016)

    Article  Google Scholar 

  5. Aminifar, F., Shahidehpour, M., Fotuhi-Firuzabad, M., Kamalinia, S.: Power system dynamic state estimation with synchronized phasor measurements. IEEE Trans. Instrum. Meas. 63(2), 352–363 (2014)

    Article  Google Scholar 

  6. Kang, W., Barbot, J.P., Xu, L.: On the observability of nonlinear and switched systems. In: Emergent Problems in Nonlinear Systems and Control, pp. 199–216. Springer (2009)

    Google Scholar 

  7. Ghahremani, E., Kamwa, I.: Dynamic state estimation in power system by applying the extended Kalman filter with unknown inputs to phasor measurements. IEEE Trans. Power Syst. 26(4), 2556–2566 (2011)

    Article  Google Scholar 

  8. Paul, A., Kamwa, I., Joos, G.: Centralized dynamic state estimation using a federation of extended Kalman Filters with intermittent PMU data from generator terminals. IEEE Trans, Power Syst (2018)

    Book  Google Scholar 

  9. Qi, J., Sun, K., Wang, J., Liu, H.: Dynamic state estimation for multi-machine power system by unscented Kalman filter with enhanced numerical stability. IEEE Trans. Smart Grid 9(2), 1184–1196 (2018)

    Article  Google Scholar 

  10. Zhao, J., Netto, M., Mili, L.: A robust iterated extended kalman filter for power system dynamic state estimation. IEEE Trans. Power Syst. 32(4), 3205–3216 (2017)

    Article  Google Scholar 

  11. Gomez-Exposito, A., Abur, A.: Power System State Estimation: Theory and Implementation. CRC Press, Boca Raton (2004)

    Google Scholar 

  12. Koenig, D.: Unknown input proportional multiple-integral observer design for linear descriptor systems: application to state and fault estimation. IEEE Trans. Autom. Control 50(2), 212–217 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  13. Pasqualetti, F., Dörfler, F., Bullo, F.: Attack detection and identification in cyber-physical systems. IEEE Trans. Autom. Control 58(11), 2715–2729 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  14. Cui, Y., Xu, L., Fei, M., Shen, Y.: Observer based robust integral sliding mode load frequency control for wind power systems. Control Eng. Pract. 65, 1–10 (2017)

    Article  Google Scholar 

  15. Mellucci, C., Menon, P.P., Edwards, C., Ferrara, A.: Second-order sliding mode observers for fault reconstruction in power networks. IET Control Theory Appl. 11(16), 2772–2782 (2017)

    Article  MathSciNet  Google Scholar 

  16. Rinaldi, G., Cucuzzella, M., Ferrara, A.: Sliding mode observers for a network of thermal and hydroelectric power plants. Automatica 98, 51–57 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  17. Rinaldi, G., Ferrara, A.: Higher order sliding mode observers and nonlinear algebraic estimators for state tracking in power networks. In: Proceedings of 56th IEEE Conference on Decision and Control, Melbourne, Australia, pp. 6033–6038 (2017)

    Google Scholar 

  18. Rinaldi, G., Menon, P.P., Edwards, C., Ferrara, A.: Design and validation of a distributed observer-based estimation scheme for power grids. IEEE Trans. Control Syst. Technol

    Google Scholar 

  19. Rinaldi, G., Menon, P.P., Ferrara, A., Edwards, C.: A super-twisting-like sliding mode observer for frequency reconstruction in power systems: Discussion and real data based assessment. In: Proceedings of 15-th International Workshop on Variable Structure Systems (VSS), Graz, Austria, pp. 444–449 (2018)

    Google Scholar 

  20. Su, X., Liu, X., Song, Y.D.: Fault-tolerant control of multiarea power systems via a sliding-mode observer technique. IEEE/ASME Trans. Mechatron. 23(1), 38–47 (2018)

    Article  Google Scholar 

  21. Rinaldi, G., Menon, P.P., Edwards, C., Ferrara, A.: Distributed super-twisting sliding mode observers for fault reconstruction and mitigation in power networks. In: Proceedings of 57th IEEE Conference on Decision and Control, Miami, FL, USA, p. accepted (2018)

    Google Scholar 

  22. Tan, C.P., Edwards, C.: Sliding mode observers for robust detection and reconstruction of actuator and sensor faults. Int. J. Robust Nonlinear Control: IFAC-Affil. J. 13(5), 443–463 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  23. Cucuzzella, M., Incremona, G.P., Ferrara, A.: Design of robust higher order sliding mode control for microgrids. IEEE J. Emerg. Sel. Topics Circuits Syst. 5(3), 393–401 (2015)

    Article  MATH  Google Scholar 

  24. Loukianov, A.G., Cañedo, J.M., Utkin, V.I., Cabrera-Vázquez, J.: Discontinuous controller for power systems: sliding-mode block control approach. IEEE Trans. Ind. Electron. 51(2), 340–353 (2004)

    Article  Google Scholar 

  25. Mi, Y., Hao, X., Liu, Y., Fu, Y., Wang, C., Wang, P., Loh, P.C.: Sliding mode load frequency control for multi-area time-delay power system with wind power integration. IET Gener. Transm. Distrib. 11(18), 4644–4653 (2017)

    Article  Google Scholar 

  26. Trip, S., Cucuzzella, M., De Persis, C., van der Schaft, A., Ferrara, A.: Passivity-based design of sliding modes for optimal load frequency control. IEEE Trans. Control Syst. Technol. 99, 1–14 (2018)

    Google Scholar 

  27. Trip, S., Cucuzzella, M., Ferrara, A., De Persis, C.: An energy function based design of second order sliding modes for automatic generation control. In: Proceedings of 20th IFAC World Congress, Toulouse, France, pp. 11613–11618 (2017)

    Google Scholar 

  28. Vrdoljak, K., Perić, N., Petrović, I.: Sliding mode based load-frequency control in power systems. Electr. Power Syst. Res. 80(5), 514–527 (2010)

    Article  Google Scholar 

  29. Li, J., Liu, X., Su, X.: Sliding mode observer-based load frequency control of multi-area power systems under delayed inputs attack. In: Proceedings of Chinese Control And Decision Conference (CCDC), Shenyang, China, pp. 3716–3720 (2018)

    Google Scholar 

  30. Rinaldi, G., Cucuzzella, M., Ferrara, A.: Third order sliding mode observer-based approach for distributed optimal load frequency control. IEEE Control Syst. Lett. 1(2), 215–220 (2017)

    Article  Google Scholar 

  31. Mi, Y., Fu, Y., Li, D., Wang, C., Loh, P.C., Wang, P.: The sliding mode load frequency control for hybrid power system based on disturbance observer. Int. J. Electr. Power Energy Syst. 74, 446–452 (2016)

    Article  Google Scholar 

  32. Hussein, A.A., Salih, S.S., Ghasm, Y.G.: Implementation of proportional-integral-observer techniques for load frequency control of power system. Proc. Comput. Sci. 109, 754–762 (2017)

    Article  Google Scholar 

  33. Kundur, P., Balu, N.J., Lauby, M.G.: Power System Stability and Control, vol. 7. McGraw-hill, New York (1994)

    Google Scholar 

  34. Sauer, P.W., Pai, M.A., Chow, J.H.: Power System Dynamics and Stability: With Synchrophasor Measurement and Power System Toolbox. Wiley (2017)

    Google Scholar 

  35. Ørum, E., Kuivaniemi, M., Laasonen, M., Bruseth, A.I., Jansson, E.A., Danell, A., Elkington, K., Modig, N.: Future system inertia. Technical Report, ENTSOE, Brussels (2015)

    Google Scholar 

  36. Davila, J., Fridman, L., Levant, A.: Second-order sliding-mode observer for mechanical systems. IEEE Trans. Autom. Control 50(11), 1785–1789 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  37. Machowski, J., Bialek, J., Bumby, J.: Power System Dynamics: Stability and Control. Wiley (2011)

    Google Scholar 

  38. Shtessel, Y., Edwards, C., Fridman, L., Levant, A.: Sliding Mode Control and Observation, vol. 10. Springer, Berlin (2014)

    Book  Google Scholar 

  39. Fridman, L., Levant, A.: Higher order sliding modes. Sliding Mode Control Eng. 11, 53–102 (2002)

    Google Scholar 

  40. Moreno, J.A., Osorio, M.: Strict Lyapunov functions for the super-twisting algorithm. IEEE Trans. Autom. Control 57(4), 1035–1040 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  41. Fingrid frequency - historical data. https://data.fingrid.fi/en/dataset/frequency-historical-data

  42. Fingrid: Frequency quality analysis for year 2015. Report 2015, pp. 1–91 (2015)

    Google Scholar 

  43. Randall, S.P., Sudgen, D.M., Vail, W., Brown, G.T.: Rotor position encoder having features in decodeable angular positions, US Patent 5,637,972 (1997). Accessed 10 June 1997

    Google Scholar 

  44. Team, N.E.A.T.: Phase angle calculations: Considerations and use cases. NASPI-2016-TR-006 (2016)

    Google Scholar 

  45. Isidori, A.: Nonlinear Control Systems. Springer Science & Business Media, Berlin (2013)

    MATH  Google Scholar 

  46. Yan, X.G., Edwards, C.: Robust sliding mode observer-based actuator fault detection and isolation for a class of nonlinear systems. Int. J. Syst. Sci. 39(4), 349–359 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  47. Rinaldi, G., Menon, P.P., Edwards, C., Ferrara, A.: Sliding mode based dynamic state estimation for synchronous generators in power systems. IEEE Control Syst. Lett. 2(4), 785–790 (2018)

    Article  Google Scholar 

  48. Poznyak, A.: Stochastic output noise effects in sliding mode state estimation. Int. J. Control 76(9–10), 986–999 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  49. Hiskens, I.: IEEE PES task force on benchmark systems for stability controls. Technical Report (2013)

    Google Scholar 

  50. Watts, D.J., Strogatz, S.H.: Collective dynamics of ‘small-world’ networks. Nature 393(6684), 440 (1998)

    Article  MATH  Google Scholar 

  51. Dorfler, F., Bullo, F.: Kron reduction of graphs with applications to electrical networks. IEEE Trans. Circuits Syst. I: Regul. Pap. 60(1), 150–163 (2013)

    Article  MathSciNet  Google Scholar 

  52. Purchala, K., Meeus, L., Van Dommelen, D., Belmans, R.: Usefulness of DC power flow for active power flow analysis. In: Proceedings of Power Engineering Society General Meeting, San Francisco, California, USA, pp. 454–459 (2005)

    Google Scholar 

  53. Kansal, P., Bose, A.: Bandwidth and latency requirements for smart transmission grid applications. IEEE Trans. Smart Grid 3(3), 1344–1352 (2012)

    Article  Google Scholar 

  54. Saad, Y.: Iterative Methods for Sparse Linear Systems. SIAM (2003)

    Google Scholar 

  55. James, K.R., Riha, W.: Convergence criteria for successive overrelaxation. SIAM J. Numer. Anal. 12, 137–143 (1975)

    Article  MathSciNet  MATH  Google Scholar 

  56. Rinaldi, G., Menon, P.P., Edwards, C., Ferrara, A.: Distributed observers for state estimation in power grids. In: Proceedings of American Control Conference, Seattle, WA, USA, pp. 5824–5829 (2017)

    Google Scholar 

  57. Edwards, C., Tan, C.P.: A comparison of sliding mode and unknown input observers for fault reconstruction. Eur. J. Control 12(3), 245–260 (2006)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy

    Gianmario Rinaldi & Antonella Ferrara

  2. College of Engineering, Mathematics, and Physical Sciences, University of Exeter, Exeter, UK

    Prathyush P. Menon & Christopher Edwards

Authors
  1. Gianmario Rinaldi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Prathyush P. Menon
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Christopher Edwards
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Antonella Ferrara
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Gianmario Rinaldi .

Editor information

Editors and Affiliations

  1. Institute of Automation and Control, Graz University of Technology, Graz, Austria

    Martin Steinberger

  2. Institute of Automation and Control, Graz University of Technology, Graz, Austria

    Martin Horn

  3. Control Engineering and Robotics Department, National Autonomous University of Mexico, Mexico City, Distrito Federal, Mexico

    Leonid Fridman

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Rinaldi, G., Menon, P.P., Edwards, C., Ferrara, A. (2020). Local and Wide-Area Sliding-Mode Observers in Power Systems. In: Steinberger, M., Horn, M., Fridman, L. (eds) Variable-Structure Systems and Sliding-Mode Control. Studies in Systems, Decision and Control, vol 271. Springer, Cham. https://doi.org/10.1007/978-3-030-36621-6_12

Download citation

Publish with us

Policies and ethics

Search

Navigation