This paper investigates the load frequency control (LFC) problem in a complex microgrid containing renewable energy source and electric vehicles under false data injection (FDI) attacks. To address this issue, we formulate a resilient control strategy combining active disturbance rejection control (ADRC) with the backstepping method. First, a complex microgrid incorporating a wind turbine generation system, load disturbance, and electric vehicles is constructed, with all sensor networks subjected to FDI attacks related to real states. Then, the state variables subjected to FDI attacks and the unknown disturbance are considered as unknown uncertainties and are estimated by extended state observers (ESOs) separately. An adaptive robust controller is designed by integrating ESO and the backstepping method to compensate for the state variables, while the Nussbaum function is introduced to address the issue of unknown control direction. The stability of all the states in the power system is proven using the Lyapunov function. Finally, the efficacy of this control strategy under FDI attacks is verified through different cases and simulation comparisons.
AbbaspourASargolzaeiAForouzannezhadP, et al. (2020) Resilient control design for load frequency control system under false data injection attacks. IEEE Transactions on Industrial Electronics67(9): 7951–7962.
2.
AnLYangG (2018) Improved adaptive resilient control against sensor and actuator attacks. Information Sciences423: 145–156.
3.
AnLYangG (2019) Decentralized adaptive fuzzy secure control for nonlinear uncertain interconnected systems against intermittent DoS attacks. IEEE Transactions on Cybernetics49(3): 827–838.
4.
AyadAKhalafMSalamaM, et al. (2022) Mitigation of false data injection attacks on automatic generation control considering nonlinearities. Electric Power Systems Research209: 107958.
5.
BiWZhangKLiY, et al. (2019) Detection scheme against cyber-physical attacks on load frequency control based on dynamic characteristics analysis. IEEE Systems Journal13(3): 2859–2868.
6.
ChenHZongGLiuX, et al. (2023a) A sub-domain-awareness adaptive probabilistic event-triggered policy for attack-compensated output control of Markov jump CPSs with dynamically matching modes. IEEE Transactions on Automation Science and Engineering21(3): 4419–4431.
7.
ChenZWangXPangN, et al. (2023b) Adaptive resilient neural control of uncertain time-delay nonlinear CPSs with full-state constraints under deception attacks. Entropy25(6): 900.
8.
ChengZBuXLiangJ, et al. (2024) Indirect–direct secure load frequency control against false data injection attacks. IEEE Transactions on Industrial Informatics20(3): 4850–4862.
9.
DingDHanQGeX, et al. (2021) Secure state estimation and control of cyber-physical systems: A survey. IEEE Transactions on Systems Man Cybernetics-Systems51(1): 176–190.
10.
DongLZhangYGaoZ (2012) A robust decentralized load frequency controller for interconnected power systems. ISA Transactions51(3): 410–419.
11.
FuCTanW (2018) Decentralised load frequency control for power systems with communication delays via active disturbance rejection. IET Generation, Transmission & Distribution12: 1397–1403.
12.
GuoWLiuFWangY, et al. (2025) Adaptive event-triggered sliding mode load frequency control for cyber-physical power systems under false data injection attacks. IEEE Transactions on Industrial Informatics21(4): 2947–2956.
13.
JainSHoteV (2023) Predictive generalised active disturbance rejection for load frequency control with communication delay. Transactions of the Institute of Measurement and Control45(11): 2027–2042.
14.
JavanmardiHDehghaniMMohammadiM, et al. (2022) BMI-based load frequency control in microgrids under false data injection attacks. IEEE Systems Journal16(1): 1021–1031.
15.
JiYGaoQLiuJ (2023) Adaptive resilient control for cyber-physical systems against unknown injection attacks in sensor networks. Nonlinear Dynamics111: 11105–11114.
16.
JinXHaddadWMYucelenT (2017) An adaptive control architecture for mitigating sensor and actuator attacks in cyber-physical systems. IEEE Transactions on Automatic Control62(11): 6058–6064.
17.
LiWCaiDWuS, et al. (2023) The impact of supplementary active power control of wind turbine on power system low frequency oscillations. Electric Power Systems Research224: 109746.
18.
LiXZhouQLiP, et al. (2020) Event-triggered consensus control for multi-agent systems against false data-injection attacks. IEEE Transactions on Cybernetics50(5): 1856–1866.
19.
LiuJYaoQHuY (2019) Model predictive control for load frequency of hybrid power system with wind power and thermal power. Energy172: 555–565.
20.
LiuWMuCWangD, et al. (2017) Neural adaptive control of microgrid frequency regulation with wind power. In: 2017 43rd annual conference of the IEEE industrial electronics society (IEEE IECON). Available at: https://ieeexplore.ieee.org/document/8217305
21.
LuKWuZ (2023) Resilient event-triggered load frequency control for cyber-physical power systems under DoS attacks. IEEE Transactions on Power Systems38(6): 5302–5313.
22.
LuKWuZHuangT (2023) Differential evolution-based three stage dynamic cyber-attack of cyber-physical power systems. IEEE/ASME Transactions on Mechatronics28(2): 1137–1148.
23.
MiYBaoXYangY, et al. (2014) The sliding mode pitch angle controller design for squirrel-cage induction generator wind power generation system. In: Proceedings of the 2014 China control conference, pp. 8113–8117. Available at: https://ieeexplore.ieee.org/document/6896358
24.
PengCLiJFeiM (2017) Resilient event-triggering H∞ load frequency control for multi-area power systems with energy-limited DoS attacks. IEEE Transactions on Power Systems32(5): 4110–4118.
25.
PhamTNNahavandiSHienLV, et al. (2017) Static output feedback frequency stabilization of time-delay power systems with coordinated electric vehicles state of charge control. IEEE Transactions on Power Systems32(5): 3862–3874.
26.
QuZYangJWangY, et al. (2024) Detection of false data injection attack in power system based on Hellinger distance. IEEE Transactions on Industrial Informatics20(2): 2119–2128.
27.
RenXYangG (2020) Adaptive control for nonlinear cyber-physical systems under false data injection attacks through sensor networks. International Journal of Robust and Nonlinear Control30: 65–79.
28.
SafiullahSRahmanALoneS (2022) A 2nd order active disturbance rejection controller for coordinated frequency-voltage control of deregulated hybrid power system with optimal electric-vehicle integration. Electric Power Systems Research210: 108129.
29.
SenjyuTSakamotoRUrasakiN, et al. (2006) Output power leveling of wind turbine generator for all operating regions by pitch angle control. IEEE Transactions on Energy Conversion21(2): 467–475.
30.
ShangguanXZhangCHeY, et al. (2021) Robust load frequency control for power system considering transmission delay and sampling period. IEEE Transactions on Industrial Informatics17(8): 5292–5303.
31.
SilaniACucuzzellaMScherpenJMA, et al. (2022) Output regulation for load frequency control. IEEE Transactions on Control Systems Technology30(3): 1130–1144.
32.
SuZSunLXueW, et al. (2023) A review on active disturbance rejection control of power generation systems: Fundamentals, tunings and practices. Control Engineering Practice141: 105716.
33.
TianEWuZXieX (2024) Codesign of FDI attacks detection, isolation, and mitigation for complex microgrid systems: An HBF-NN-based approach. IEEE Transactions on Neural Networks and Learning Systems35(5): 6156–6165.
34.
WangQSunC (2020) Adaptive consensus of multiagent systems with unknown high-frequency gain signs under directed graphs. IEEE Transactions on Systems Man Cybernetics-Systems50(6): 2181–2186.
35.
WangXDingDDongH, et al. (2023) PI-based security control against joint sensor and controller attacks and applications in load frequency control. IEEE Transactions on Systems Man Cybernetics-Systems53(2): 970–980.
36.
WengTXieYChenG, et al. (2022) Load frequency control under false data inject attacks based on multi-agent system method in multi-area power systems. International Journal of Distributed Sensor Networks18(4): 155013292210904.
37.
XueWBaiWYangS, et al. (2015) ADRC with adaptive extended state observer and its application to air–fuel ratio control in gasoline engines. IEEE Transactions on Industrial Electronics62(9): 5847–5857.
38.
YangYHuangJSuX, et al. (2022) Adaptive control of second-order nonlinear systems with injection and deception attacks. IEEE Transactions on Systems Man Cybernetics-Systems52(1): 574–581.
39.
YeDZhangT (2020) Summation detector for false data-injection attack in cyber-physical systems. IEEE Transactions on Cybernetics50(6): 2338–2345.
40.
ZhangYWeiLFuW, et al. (2023) Secondary frequency control strategy considering DoS attacks for MTDC system. Electric Power Systems Research214: 108888.
41.
ZhaoJYangG (2024) Reinforcement-learning-based fuzzy adaptive finite-time optimal resilient control for large-scale nonlinear systems under false data injection attacks. IEEE Transactions on Fuzzy Systems32(4): 2483–2495.
42.
ZhaoKSongYMaT, et al. (2018) Prescribed performance control of uncertain Euler-Lagrange systems subject to full-state constraints. IEEE Transactions on Neural Networks and Learning Systems29(8): 3478–3489.
43.
ZhaoXMaZShiX, et al. (2024) Attack detection and mitigation scheme of load frequency control systems against false data injection attacks. IEEE Transactions on Industrial Informatics20(8): 9952–9962.
