Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Read chapter Read first chapter

2023 | OriginalPaper | Chapter

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

Authors : Yasin Asadi, Malihe Maghfoori Farsangi, Ali Moradi Amani, Hassan Haes Alhelou, Seyed Mehran Dibaji, Ehsan Bijami

Published in: Power Systems Cybersecurity

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

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.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Hybrid Physics-Based and Data-Driven Mitigation Strategy for Automatic Generation Control Under Cyber Attack
next chapter Cyberattack-Resilient Control in Multi-area Power Generation
Literature
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)CrossRef
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)CrossRef
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)MathSciNetCrossRefMATH
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)
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)
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)
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)MathSciNetCrossRefMATH
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)CrossRef
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
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)
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
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.
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)MathSciNetMATH
14.
15.
A.M. Amani, M. Jalili, Power grids as complex networks: resilience and reliability analysis. IEEE Access (2021)
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)CrossRef
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)CrossRef
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)CrossRef
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)CrossRef
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)CrossRef
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)CrossRef
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)MathSciNetCrossRefMATH
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)MathSciNetCrossRefMATH
24.
X. He, X. Liu, P. Li, Coordinated false data injection attacks in AGC system and its countermeasure. IEEE Access 8, 194640–194651 (2020)CrossRef
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)CrossRef
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)CrossRef
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)CrossRef
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)CrossRef
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)MathSciNetCrossRef
30.
X. Qiu, Y. Wang, X. Xie, H. Zhang, Resilient model-free adaptive control for cyber-physical systems against jamming attack. Neurocomputing 413, 422–430 (2020)CrossRef
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)CrossRef
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)MathSciNetCrossRefMATH
33.
T. Wonghong, S. Engell, Automatic controller tuning via unfalsified control. J. Process Control 22(10), 2008–2025 (2012)
34.
C. Tian, Y. Peng, Data-driven iterative tuning based active disturbance rejection control for piezoelectric nano-positioners. Mechatronics 65, 102321 (2021)CrossRef
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
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
37.
A. Allibhoy, J. Cortés, Data-based receding horizon control of linear network systems. IEEE Control Syst. Lett. 5(4), 1207–1212
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
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
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
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)CrossRef
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)
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)CrossRef
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)CrossRef
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)CrossRef
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)
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)CrossRef
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)
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)CrossRef
50.
Y. Guo, Z. Hou, S. Liu, S. Jin, 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)
51.
J. Yang, A controllable false data injection attack for a cyber physical system. IEEE Access 9, 6721–6728 (2021)CrossRef
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)MathSciNetCrossRef
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)
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)
Metadata
Title
Data-Driven Cyber-Resilient Control of Wide Area Power Systems
Authors
Yasin Asadi
Malihe Maghfoori Farsangi
Ali Moradi Amani
Hassan Haes Alhelou
Seyed Mehran Dibaji
Ehsan Bijami
Copyright Year
2023
Book
Power Systems Cybersecurity

Print ISBN: 978-3-031-20359-6

Electronic ISBN: 978-3-031-20360-2

Copyright Year: 2023

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