Data-Driven Cyber-Resilient Control of Wide Area Power Systems

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Power Systems Cybersecurity

Abstract

With the uptake of advanced communication technologies, monitoring and operation of power systems have been experiencing a paradigm shift. Many centralized algorithms can now be implemented in a distributed scheme. For example, local decisions can make faster actions resulting in a resilient power grid. Despite these advantages, these communication networks have made power networks vulnerable to cyber-attacks. Therefore, only attack-resilient algorithms can be reliably implemented using these technologies. In this chapter, a Data-Driven Cyber-Resilient Control (DDCRC) method is proposed for the frequency stability of wide area power grids. In the proposed method, the automatic generation control signals are generated without using a predefined model such that the frequency stability of the power system in the presence of Deception Attacks (DA) is guaranteed. Simulation results on a three-area power grid show the efficiency and superiority of the proposed method.

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References

  1. G. Bedi, G.K. Venayagamoorthy, R. Singh, R.R. Brooks, K.-C. Wang, Review of Internet of Things (IoT) in electric power and energy systems. IEEE Internet Things J. 5(2), 847–870 (2018)

    Article  Google Scholar 

  2. M. Tan, Z. Song, X. Zhang, Robust leader-following consensus of cyber–physical systems with cyber-attack via sampled-data control. ISA Trans. 109, 61–71 (2021)

    Article  Google Scholar 

  3. D. Ye, S. Luo, A co-design methodology for cyber-physical systems under actuator fault and cyber-attack. J. Franklin Inst. 356(4), 1856–1879 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  4. S.A.G.K. Abadi, S.I. Habibi, T. Khalili, A. Bidram, A model predictive control strategy for performance improvement of hybrid energy storage systems in DC microgrids. IEEE Access 10, 25400–25421 (2022)

    Google Scholar 

  5. S.A.G.K. Abadi, A. Bidram, A distributed rule‐based power management strategy in a photovoltaic/hybrid energy storage based on an active compensation filtering technique. IET Renew. Power Gener. 15(15), 3688–3703 (2021)

    Google Scholar 

  6. S.D. Bopardikar A. Speranzon, On analysis and design of stealth-resilient control systems, in Resilient Control Systems (ISRCS), 6th International Symposium on Resilient Control Systems (ISRCS) 2013 vol. 48, no. 53, pp. 13–15. (Aug 2013)

    Google Scholar 

  7. H. Fawzi, P. Tabuada, S. Diggavi, Secure estimation and control for cyber-physical systems under adversarial attacks. IEEE Trans. Autom. Control 59(6), 1454–1467 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  8. Z. Pang, G. Liu, Design and implementation of secure networked predictive control systems under deception attacks. IEEE Trans. Control Syst. Technol. 20(5), 1334–1342 (2012)

    Article  Google Scholar 

  9. J.Y. Keller, D. Sauter, K. Chabir, State filtering for discrete-time stochastic linear systems subject to random cyber attacks and losses of measurements, in 2012 20th Mediterranean Conference on Control & Automation (MED) (3–6 July 2012) , pp 935,940

    Google Scholar 

  10. S. Deshmukh, B. Natarajan, A. Pahwa, State estimation over a Lossy network in spatially distributed cyber-physical systems. IEEE Trans. Signal Process. 62(15), 3911–3923 (1 Aug 2014)

    Google Scholar 

  11. A. Rosich, H. Voos, Li. Yumei, M. Darouach, A model predictive approach for cyber-attack detection and mitigation in control systems, in 52nd Annual Conference on Decision and Control (CDC) (IEEE, 2013). (Dec 2013), pp. 6621–6626, 10–13

    Google Scholar 

  12. A. Teixeira, H. Sandberg, K.H. Johansson, Networked control systems under cyber attacks with applications to power networks, in American Control Conference (ACC), 2010 (June 30 2010–July 2 2010), pp. 3690–3696.

    Google Scholar 

  13. A.F. Taha, A. Elmahdi, J.H. Panchal, D. Sun, Unknown input observer design and analysis for networked control systems. Int. J. Control 88(5), 920–934 (2015)

    MathSciNet  MATH  Google Scholar 

  14. A. Ahmadi, Y. Asadi, A.M. Amani, M. Jalili, X. Yu, Resilient model predictive adaptive control of networked Z-source inverters using GMDH. IEEE Trans. Smart Grid. https://doi.org/10.1109/TSG.2022.3174250

  15. A.M. Amani, M. Jalili, Power grids as complex networks: resilience and reliability analysis. IEEE Access (2021)

    Google Scholar 

  16. K. Wang, M. Du, S. Maharjan, Y. Sun, Strategic honeypot game model for distributed denial of service attacks in the smart grid. IEEE Trans. Smart Grid 8(5), 2474–2482 (2017)

    Article  Google Scholar 

  17. X. Liu, Z. Li, Z. Li, Optimal protection strategy against false data injection attacks in power systems. IEEE Trans. Smart Grid 8(4), 1802–1810 (2016)

    Article  Google Scholar 

  18. Y. Wu, Z. Wei, J. Weng, X. Li, R.H. Deng, Resonance attacks on load frequency control of smart grids. IEEE Trans. Smart Grid 9(5), 4490–4502 (2017)

    Article  Google Scholar 

  19. J. Liu, Y. Gu, L. Zha, Y. Liu, J. Cao, Event-triggered h∞ load frequency control for multiarea power systems under hybrid cyber attacks. IEEE Trans. Syst. Man Cybern. Syst. 49(8), 1665–1678 (2019)

    Article  Google Scholar 

  20. C. Peng, J. Zhang, H. Yan, Adaptive event-triggering H∞ load frequency control for network-based power systems. IEEE Trans. Ind. Electron. 65(2), 1685–1694 (2017)

    Article  Google Scholar 

  21. C. Wu, Z. Hu, J. Liu, L. Wu, Secure estimation for cyber-physical systems via sliding mode. IEEE Trans. Cybern. 48(12), 3420–3431 (2018)

    Article  Google Scholar 

  22. M.A. Sid, S. Chitraganti, K. Chabir, Medium access scheduling for input reconstruction under deception attacks. J. Franklin Inst. 354(9), 3678–3689 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  23. J.Y. Keller, K. Chabir, D. Sauter, Input reconstruction for networked control systems subject to deception attacks and data losses on control signals. Int. J. Syst. Sci. 47(4), 814–820 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  24. X. He, X. Liu, P. Li, Coordinated false data injection attacks in AGC system and its countermeasure. IEEE Access 8, 194640–194651 (2020)

    Article  Google Scholar 

  25. M. Khalaf, A. Youssef, E. El-Saadany, Joint detection and mitigation of false data injection attacks in AGC systems. IEEE Trans. Smart Grid 10(5), 4985–4995 (2018)

    Article  Google Scholar 

  26. S. Zuo, T. Altun, F.L. Lewis, A. Davoudi, Distributed resilient secondary control of DC microgrids against unbounded attacks. IEEE Trans. Smart Grid 11(5), 3850–3859 (2020)

    Article  Google Scholar 

  27. S. Zuo, O.A. Beg, F.L. Lewis, A. Davoudi, Resilient networked AC microgrids under unbounded cyber attacks. IEEE Trans. Smart Grid 11(5), 3785–3794 (2020)

    Article  Google Scholar 

  28. G. Liang, J. Zhao, F. Luo, S.R. Weller, Z.Y. Dong, A review of false data injection attacks against modern power systems. IEEE Trans. Smart Grid 8(4), 1630–1638 (2016)

    Article  Google Scholar 

  29. X. Huang, D. Zhai, J. Dong, Adaptive integral sliding-mode control strategy of data-driven cyber-physical systems against a class of actuator attacks. IET Control Theory Appl. 12(10), 1440–1447 (2018)

    Article  MathSciNet  Google Scholar 

  30. X. Qiu, Y. Wang, X. **e, H. Zhang, Resilient model-free adaptive control for cyber-physical systems against jamming attack. Neurocomputing 413, 422–430 (2020)

    Article  Google Scholar 

  31. C.C. Hang, K.J. Åström, W.K. Ho, Refinements of the Ziegler-Nichols tuning formula. Control Theory Appl. 138(2), 111–118 (1991)

    Article  Google Scholar 

  32. D. Selvi, D. Piga, G. Battistelli, A. Bemporad, Optimal direct data-driven control with stability guarantees. Eur. J. Control. 1(59), 175–187 (2021)

    Article  MathSciNet  MATH  Google Scholar 

  33. T. Wonghong, S. Engell, Automatic controller tuning via unfalsified control. J. Process Control 22(10), 2008–2025 (2012)

    Google Scholar 

  34. C. Tian, Y. Peng, Data-driven iterative tuning based active disturbance rejection control for piezoelectric nano-positioners. Mechatronics 65, 102321 (2021)

    Article  Google Scholar 

  35. C.L. Remes, R.F. Binz, J.V. Flores, L. Campestrini, Virtual reference feedback tuning applied to cascade control. IET Control Theory Appl. 14(20), 3738–3746

    Google Scholar 

  36. E. Aggelogiannaki, H. Sarimveis, Nonlinear model predictive control for distributed parameter systems using data driven artificial neural network models. Comput. Chem. Eng. 32(6), 1225–1237

    Google Scholar 

  37. A. Allibhoy, J. Cortés, Data-based receding horizon control of linear network systems. IEEE Control Syst. Lett. 5(4), 1207–1212

    Google Scholar 

  38. J. Berberich, J. Köhler, M.A. Müller, F. Allgöwer, Data-driven model predictive control with stability and robustness guarantees. IEEE Trans. Autom. Control 66(4), 1702–1717

    Google Scholar 

  39. Z. Hou, W. Huang, The model-free learning adaptive control of a class of SISO nonlinear systems, in Proceedings of the 1997 American Control Conference (Cat. No. 97CH36041), vol. 1, (1997), pp. 343–344

    Google Scholar 

  40. V. Krishnan, F.P Asqualetti, On direct vs indirect data-driven predictive control, in 2021 60th IEEE Conference on Decision and Control (CDC) (IEEE, 2021), pp. 736–741

    Google Scholar 

  41. Y. Asadi, M. Maghfoori, E. Bijami, The design of data-driven adaptive predictive controller for a class of unknown no-linear system featuring output saturation. J. Control 15(3), 23–33 (2021)

    Article  Google Scholar 

  42. Z. Hou, Y. Zhu, Controller-dynamic-linearization-based model free adaptive control for discrete-time nonlinear systems. IEEE Trans. Ind. Inf. 9(4), 2301–2309 (2013)

    Google Scholar 

  43. Y. Asadi, A. Ahmadi, S. Mohammadi, A.M. Amani, M. Marzband, B. Mohammadi-Ivatloo, Data-driven model-free adaptive control of Z-source inverters. Sensors 21(22), 7438–7444 (2021)

    Article  Google Scholar 

  44. Y. Asadi, M.M. Farsangi, E. Bijami, A.M. Amani, K.Y. Lee, Data-driven adaptive control of wide-area nonlinear systems with input and output saturation: a power system application. Int. J. Electr. Power Energy Syst. 133, 107225 (2021)

    Article  Google Scholar 

  45. Z. Hou, C. Ronghu, G. Huijun, An overview of dynamic-linearization-based data-driven control and applications. IEEE Trans. Ind. Electron. 64(5), 4076–4090 (2017)

    Article  Google Scholar 

  46. Z. Hou, J. Shangtai, Model-free adaptive control for a class of nonlinear discrete-time systems based on the partial form linearization, in IFAC Proceedings 41(2), 3509–3514 (2008)

    Google Scholar 

  47. X. Bu, Z. Hou, Q. Yu, Y. Yang, Quantized data driven iterative learning control for a class of nonlinear systems with sensor saturation. IEEE Trans. Syst. Man Cybern. Syst. 50(12), 5119–5129 (2018)

    Article  Google Scholar 

  48. Z. Hou, L. Ting, Constrained model free adaptive predictive perimeter control and route guidance for multi-region Urban traffic systems. IEEE Trans. Intell. Transp. Syst. (2020)

    Google Scholar 

  49. Y. Wang, H. Mingdong, Model-free adaptive integral terminal sliding mode predictive control for a class of discrete-time nonlinear systems. ISA Trans. 93, 209–217 (2019)

    Article  Google Scholar 

  50. Y. Guo, Z. Hou, S. Liu, S. **, Data-driven model-free adaptive predictive control for a class of MIMO nonlinear discrete-time systems with stability analysis. IEEE Access 7, 102852–102866 (2019)

    Google Scholar 

  51. J. Yang, A controllable false data injection attack for a cyber physical system. IEEE Access 9, 6721–6728 (2021)

    Article  Google Scholar 

  52. S.M. Dibaji, M. Pirani, D.B. Flamholz, A.M. Annaswamy, K.H. Johansson, A. Chakrabortty, A systems and control perspective of CPS security. Annu. Rev. Control. 47, 394–411 (2019)

    Article  MathSciNet  Google Scholar 

  53. A. Ahmadi, M. Nabipour, S. Taheri, B. Mohammadi-Ivatloo, V. Vahidinasab, A new false data injection attack detection model for cyberattack resilient energy forecasting. IEEE Trans. Ind. Inf. (2022)

    Google Scholar 

  54. X. Zhou, Z. Gu, F. Yang, Resilient event-triggered output feedback control for load frequency control systems subject to cyber attacks. IEEE Access 58951–58958 (2019)

    Google Scholar 

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Correspondence to Yasin Asadi or Hassan Haes Alhelou .

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Asadi, Y., Farsangi, M.M., Amani, A.M., Alhelou, H.H., Dibaji, S.M., Bijami, E. (2023). Data-Driven Cyber-Resilient Control of Wide Area Power Systems. In: Haes Alhelou, H., Hatziargyriou, N., Dong, Z.Y. (eds) Power Systems Cybersecurity. Power Systems. Springer, Cham. https://doi.org/10.1007/978-3-031-20360-2_7

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  • DOI: https://doi.org/10.1007/978-3-031-20360-2_7

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