Skip to main content

Cyber Security for Power System State Estimation

  • Chapter
  • First Online:
Smart Grid Control

Part of the book series: Power Electronics and Power Systems ((PEPS))

Abstract

State estimation is a critical application that provides situational awareness and permits efficient operation of the smart grid. The secure, accurate, and fast computation of the state estimates is crucial to execute the complex decisions and diverse control actions needed in real time to provide reliable, economic, and safe power systems that integrate distributed and intermittent renewable generation. This chapter discusses research directions to evaluate the cyber security and develop novel algorithms for securing today and tomorrow’s power state estimation and grid operation.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 139.99
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. Terrorism and the electric power delivery system. Technical Report (National Academy of Engineering Press, U.S., 2012)

    Google Scholar 

  2. S.K. Khaitan, J.D. McCalley, C.C. Liu, Cyber Physical Systems Approach to Smart Electric Power Grid (Springer, Heidelberg, 2015)

    Google Scholar 

  3. IR-ALERT-H-16-056-01-Cyber-attack against Ukrainian critical infrastructure. Technical Report Industrial Control Systems Cyber Emergency Response Team, https://ics-cert.us-cert.gov/alerts/IR-ALERT-H-16-056-01, Feb 2016

  4. Strengthening America’s energy security with offshore wind. Technical Report (U.S. Department of Energy (DoE)), http://www.nrel.gov/docs/fy12osti/49222.pdf, Apr 2012

  5. T.G. Lewis, Critical Infrastructure Protection in Homeland Security: Defending a Networked Nation (Wiley, New Jersey, second edition, 2015)

    Google Scholar 

  6. M. Govindarasu, P.W. Bauer (eds.), Special section on keeping the smart grid safe. IEEE Power Energy Mag. 10(1) (2012)

    Google Scholar 

  7. Y. Mo, T.H.-H. Kim, K. Brancik, D. Dickinson, H. Lee, A. Perrig, B. Sinopoli, Cyber-physical security of a smart grid infrastructure. Proc. IEEE 100(1), 195–209 (2012)

    Article  Google Scholar 

  8. A. Abur, A. Gomez-Exposito, Power System State Estimation: Theory and Implementation (CRC Press, New York, 2004)

    Book  Google Scholar 

  9. A. Monticelli, Electric power system state estimation. Proc. IEEE 88(2), 262–282 (2000)

    Article  Google Scholar 

  10. Y. Liu, M.K. Reiter, P. Ning, False data injection attacks against state estimation in electric power grids, in Proceedings of 16th ACM Conference on Computer and Communications Security (2009), pp. 21–32

    Google Scholar 

  11. Y. Liu, P. Ning, M.K. Reiter, False data injection attacks against state estimation in electric power grids. ACM Trans. Inf. Syst. Secur. 14(1), 1–33 (2011)

    Article  Google Scholar 

  12. A. Teixeira, S. Amin, H. Sandberg, K.H. Johansson, S.S. Sastry, Cyber security analysis of state estimators in electric power systems, in Proceedings of 49th IEEE Conference on Decision and Control (CDC) (2010), pp. 5991–5998

    Google Scholar 

  13. G. Hug, J.A. Giampapa, Vulnerability assessment of AC state estimation with respect to false data injection cyber-attacks. IEEE Trans. Smart Grid 3(3), 1362–1370 (2012)

    Article  Google Scholar 

  14. L. Jia, J. Kim, R.J. Thomas, L. Tong, Impact of data quality on real-time locational marginal price. IEEE Trans. Power Syst. 29(2), 627–636 (2014)

    Article  Google Scholar 

  15. W. Wang, Z. Lu, Cyber security in the smart grid: survey and challenges. Comput. Netw. 57(5), 1344–1371 (2013)

    Article  Google Scholar 

  16. R.A. Maronna, R.D. Martin, V.J. Yohai, Robust Statistics: Theory and Methods (Wiley Series in Probability and Statistics. Wiley, Chichester, 2006)

    Book  Google Scholar 

  17. O. Kosut, L. Jia, R.J. Thomas, L. Tong, Malicious data attacks on the smart grid. IEEE Trans. Smart Grid 2(4), 645–658 (2011)

    Article  Google Scholar 

  18. J. Kim, L. Tong, On topology attack of a smart grid: undetectable attacks and countermeasures. IEEE J. Sel. Areas Commun. 31(7), 1294–1305 (2013)

    Article  Google Scholar 

  19. A. Ashok, M. Govindarasu, Cyber attacks on power system state estimation through topology errors, in IEEE Power Energy Society General Meeting (2012), pp. 1–8

    Google Scholar 

  20. Y. Chakhchoukh, H. Ishii, Coordinated cyber-attacks on the measurement function in hybrid state estimation. IEEE Trans. Power Syst. 30(5), 2487–2497 (2015)

    Article  Google Scholar 

  21. Y. Chakhchoukh, H. Ishii, Cyber attacks scenarios on the measurement function of power state estimation, in Proceedings of American Control Conference (ACC), June 2015, pp. 3676–3681

    Google Scholar 

  22. M.G. Cheniae, L. Mili, P.J. Rousseeuw, Identification of multiple interacting bad data via power system decomposition. IEEE Trans. Power Syst. 11(3), 1555–1563 (1996)

    Article  Google Scholar 

  23. L. Mili, M.G. Cheniae, P.J. Rousseeuw, Robust state estimation of electric power systems. IEEE Trans. Circuits and Syst. I Fundam. Theory Appl. 41(5), 349–358 (1994)

    Article  Google Scholar 

  24. Y. Chakhchoukh, H. Ishii, Robust estimation for enhancing the cyber security of power state estimation, in IEEE PES General Meeting, July 2015, pp. 1–6

    Google Scholar 

  25. A.M. Zoubir, V. Koivunen, Y. Chakhchoukh, M. Muma, Robust estimation in signal processing: a tutorial-style treatment of fundamental concepts. IEEE Signal Process. Mag. 29(4), 61–80 (2012)

    Article  Google Scholar 

  26. L. Mili, C.W. Coakley, Robust estimation in structured linear regression. Ann. Statist. 24(6), 2593–2607 (1996)

    Article  MathSciNet  Google Scholar 

  27. A. Chakrabortty, P.P. Khargonekar, Introduction to wide-area control of power systems, in Proceedings of American Control Conference, June 2013, pp. 6758–6770

    Google Scholar 

  28. F. Aminifar, M. Fotuhi-Firuzabad, A. Safdarian, A. Davoudi, M. Shahidehpour, Synchrophasor measurement technology in power systems: panorama and state-of-the-art. IEEE Access 2, 1607–1628 (2014)

    Article  Google Scholar 

  29. M. Kezunovic, S. Meliopoulos, V. Venkatasubramanian, V. Vittal, Application of Time-Synchronized Measurements in Power System Transmission Networks (Springer, Heidelberg, 2014)

    Book  Google Scholar 

  30. A.G. Phadke, J.S. Thorp, Synchronized Phasor Measurements and Their Applications, Power Electronics and Power Systems, 2nd edn. (Springer, New York, 2008)

    MATH  Google Scholar 

  31. Map of PMUs in North America. Technical Report (North American Synchrophasor Initiative, March 2015)

    Google Scholar 

  32. B. Xu, A. Abur, Optimal placement of phasor measurement units for state estimation. Technical Report (Power Systems Engineering Research Center (PSERC), 2005)

    Google Scholar 

  33. Q. Zhang, Y. Chakhchoukh, V. Vittal, G.T. Heydt, N. Logic, S. Sturgill, Impact of PMU measurement buffer length on state estimation and its optimization. IEEE Trans. Power Syst. 28(2), 1657–1665 (2013)

    Article  Google Scholar 

  34. M. Göl, A. Abur, A hybrid state estimator for systems with limited number of PMUs. IEEE Trans. Power Syst. 30(3), 1511–1517 (2015)

    Article  Google Scholar 

  35. A. Rouhani, A. Abur, Linear phasor estimator assisted dynamic state estimation. IEEE Trans. Smart Grid 9(1), 211–219 (2018)

    Article  Google Scholar 

  36. V. Murugesan, Y. Chakhchoukh, V. Vittal, G.T. Heydt, N. Logic, S. Sturgill, PMU data buffering for power system state estimators. IEEE Power Energy Technol. Syst. J. 2(3), 94–102 (2015)

    Article  Google Scholar 

  37. Y. Wang, A. Chakrabortty, Distributed monitoring of wide-area oscillations in the presence of GPS spoofing attacks, in Proceedings of IEEE Power and Energy Society General Meeting (PESGM), July 2016, pp. 1–5

    Google Scholar 

  38. Y. Chakhchoukh, V. Vittal, G.T. Heydt, H. Ishii, LTS-based robust hybrid SE integrating correlation. IEEE Trans. Power Syst. 32(4), 3127–3135 (2017)

    Article  Google Scholar 

  39. Y. Chakhchoukh, H. Ishii, Enhancing robustness to cyber-attacks in power systems through multiple least trimmed squares state estimations. IEEE Trans. Power Syst. 31(6), 4395–4405 (2016)

    Article  Google Scholar 

  40. Y. Chakhchoukh, V. Vittal, G.T. Heydt, PMU based state estimation by integrating correlation. IEEE Trans. Power Syst. 29(2), 617–626 (2014)

    Article  Google Scholar 

  41. M. Wu, L. Xie, Online identification of bad synchrophasor measurements via spatio-temporal correlations, in Proceedings of Power Systems Computation Conference (PSCC), June 2016, pp. 1–7

    Google Scholar 

  42. M. Glavic, T. Van Cutsem, Reconstructing and tracking network state from a limited number of synchrophasor measurements. IEEE Trans. Power Syst. 28(2), 1921–1929 (2013)

    Article  Google Scholar 

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

    Article  Google Scholar 

  44. S. Wang, W. Gao, A.P.S. Meliopoulos, An alternative method for power system dynamic state estimation based on unscented transform. IEEE Trans. Power Syst. 27(2), 942–950 (2012)

    Article  Google Scholar 

  45. A.K. Singh, B.C. Pal, Decentralized dynamic state estimation in power systems using unscented transformation. IEEE Transa. Power Syst. 29(2), 794–804 (2014)

    Article  Google Scholar 

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

    Article  Google Scholar 

  47. O. Kosut, Malicious data attacks against dynamic state estimation in the presence of random noise, in Proceedings of IEEE Global Conference on Signal and Information Processing, Dec 2013, pp. 261–264

    Google Scholar 

  48. A. Teixeira, I. Shames, H. Sandberg, K.H. Johansson, A secure control framework for resource-limited adversaries. Automatica 51, 135–148 (2015)

    Article  MathSciNet  Google Scholar 

  49. J. Kim, L. Tong, On phasor measurement unit placement against state and topology attacks, in Proceedings of IEEE International Conference on Smart Grid Communications (SmartGridComm), Oct 2013, pp. 396–401

    Google Scholar 

  50. Y. Lin, A. Abur, Strategic use of synchronized phasor measurements to improve network parameter error detection. IEEE Trans. Smart Grid 9(5), 5281–5290 (2018)

    Article  Google Scholar 

  51. A. Ashok, M. Govindarasu, V. Ajjarapu, Online detection of stealthy false data injection attacks in power system state estimation. IEEE Trans. Smart Grid 9(3), 1636–1646 (2018)

    Google Scholar 

  52. A. Teixeira, K.C. Sou, H. Sandberg, K.H. Johansson, Secure control systems: a quantitative risk management approach. IEEE Control Syst. 35(1), 24–45 (2015)

    Article  MathSciNet  Google Scholar 

  53. C.M. Davis, J.E. Tate, H. Okhravi, C. Grier, T.J. Overbye, D. Nicol, SCADA cyber security testbed development, in Proceedings of 38th North American Power Symposium, Sept 2006, pp. 483–488

    Google Scholar 

  54. A. Hahn, A. Ashok, S. Sridhar, M. Govindarasu, Cyber-physical security testbeds: Architecture, application, and evaluation for smart grid. IEEE Trans. Smart Grid 4(2), 847–855 (2013)

    Article  Google Scholar 

  55. T. Yardley, R. Berthier, D. Nicol, W.H. Sanders, Smart grid protocol testing through cyber-physical testbeds, in Proceedings of IEEE PES Innovative Smart Grid Technologies Conference (ISGT), Feb 2013, pp. 1–6

    Google Scholar 

  56. V. Venkataramanan, A. Srivastava, A. Hahn, Real-time co-simulation testbed for microgrid cyber-physical analysis, in Proceedings of Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES), April 2016, pp. 1–6

    Google Scholar 

  57. M. Esmalifalak, N.T. Nguyen, R. Zheng, Z. Han, Detecting stealthy false data injection using machine learning in smart grid, in Proceedings of IEEE Global Communications Conference (GLOBECOM), Dec 2013, pp. 808–813

    Google Scholar 

  58. M. Esmalifalak, L. Liu, N. Nguyen, R. Zheng, Z. Han, Detecting stealthy false data injection using machine learning in smart grid. IEEE Syst. J. 11(3), 1644–1652 (2017)

    Article  Google Scholar 

  59. Y. Chakhchoukh, S. Liu, M. Sugiyama, H. Ishii, Statistical outlier detection for diagnosis of cyber attacks in power state estimation, in Proceedings of IEEE PES General Meeting, July 2016, pp. 1–5

    Google Scholar 

  60. M. Sugiyama, T. Suzuki, T. Kanamori, Density Ratio Estimation in Machine Learning (Cambridge University Press, 2012)

    Google Scholar 

  61. L. Xie, D.H. Choi, S. Kar, H.V. Poor, Fully distributed state estimation for wide-area monitoring systems. IEEE Trans. Smart Grid 3(3), 1154–1169 (2012)

    Article  Google Scholar 

  62. W. Jiang, V. Vittal, G.T. Heydt, A distributed state estimator utilizing synchronized phasor measurements. IEEE Trans. Power Syst. 22(2), 563–571 (2007)

    Article  Google Scholar 

  63. V. Kekatos, G.B. Giannakis, Distributed robust power system state estimation. IEEE Trans. Power Syst. 28(2), 1617–1626 (2013)

    Article  Google Scholar 

  64. M.A. Rahman, E. Al-Shaer, R.B. Bobba, Moving target defense for hardening the security of the power system state estimation, in Proceedings of the First ACM Workshop on Moving Target Defense, Nov 2014, pp. 59–68

    Google Scholar 

  65. Y. Yao, Z. Li, MTD-inspired state estimation based on random measurements selection, in North American Power Symposium (NAPS), Sept 2016, pp. 1–6

    Google Scholar 

  66. R. Singh, B.C. Pal, R.A. Jabr, Choice of estimator for distribution system state estimation. IET Gener. Trans. Distrib. 3(7), 666–678 (2009)

    Article  Google Scholar 

  67. Y. Isozaki, S. Yoshizawa, Y. Fujimoto, H. Ishii, I. Ono, T. Onoda, Y. Hayashi, Detection of cyber attacks against voltage control in distribution power grids with PVs. IEEE Trans. Smart Grid 7(4), 1824–1835 (2016)

    Article  Google Scholar 

  68. A. Teixeira, G. Dan, H. Sandberg, R. Berthier, R.B. Bobba, A. Valdes, Security of smart distribution grids: Data integrity attacks on integrated volt/var control and countermeasures, in Proceedings of American Control Conference, June 2014, pp. 4372–4378

    Google Scholar 

  69. A. Chakrabortty, Co-designing communication and control systems for wide-area control of power systems, in Proceedings of American Control Conference (ACC), July 2016, pp. 2667–2667

    Google Scholar 

  70. S. Sridhar, M. Govindarasu, Model-based attack detection and mitigation for automatic generation control. IEEE Trans. Smart Grid 5(2), 580–591 (2014)

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by Japan Science and Technology Agency under the CREST Program, Grant No. JPMJCR15K3.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hideaki Ishii .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Chakhchoukh, Y., Ishii, H. (2019). Cyber Security for Power System State Estimation. In: Stoustrup, J., Annaswamy, A., Chakrabortty, A., Qu, Z. (eds) Smart Grid Control. Power Electronics and Power Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-98310-3_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-98310-3_15

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-98309-7

  • Online ISBN: 978-3-319-98310-3

  • eBook Packages: EnergyEnergy (R0)

Publish with us

Policies and ethics