| Journal of Visual Artificial Intelligence
Received: 07 May 2026; Revised: 19 June 2026; Accepted: 27 June 2026; Published Online: 29 June 2026.
J. Vis. Artif. Intell., 2026, 1(1), 26104 | Volume 1 Issue 1 (June 2026) | DOI: https://doi.org/10.64189/vai.26104
© The Author(s) 2026
This article is licensed under Creative Commons Attribution NonCommercial 4.0 International (CC-BY-NC 4.0)
Cyber-Resilient Load Frequency Control in Modern
Interconnected Power Systems: A Systematic
Literature Review of Intelligent and Secure Control
Strategies
Satheeshkumar R,
1,*
Jagatheesan K,
2
Lenin V R,
3
Kanendra Naidu
4
and Anand B
5
1
Paavai Engineering College, Namakkal, Tamilnadu, 637018, India
2
Vivekanandha College of Engineering for Women, Tiruchengode, Tamilnadu, 637205, India
3
Anil Neerukonda Institute of Technology and Sciences, Andhra Pradesh, 531162, India
4
Universiti Teknologi MARA, Shah Alam, Selangor, 40450 Malaysia
5
Hindusthan College of Engineering and Technology, Coimbatore, Tamilnadu, 641032, India
*Email: satheesh2811@gmail.com (Satheeshkumar R)
Abstract
Load Frequency Control (LFC) is very significant in the present situation. With that, one can be certain to
maintain and manage power stability in relation to frequency changes while continuing reliable power traded
over different tie-lines, which are all actually occurring in modern power systems. In addition, deregulated
operation regimes are also implicated, holding stability with LFC systems by email threats like cyber security
which occurred mostly during the process. This paper provides an excellent review from the literature on LFC
methodologies not only of classical, robust, and optimization but intelligent and cyber-resilient control
strategies as well. Further development focused on more modern approaches like model predictive control,
sliding mode control, fractional-order control, and the development of observer-based techniques for increased
robustness and rejection of disturbances in a complex multi-area system. Concomitantly, since then,
conventional metaheuristic algorithms become most popular and are amongst the best for controllers
optimized to be very transiently responsive and stable in the steady state. Recent research trends are towards
such cyber-secure and resilient LFC designs which enable event-triggered or self-triggered control,
distributed/decentralized framework, resilient observers, and new age methods like neural networks, fuzzy
logic, or reinforcement learning based real-time attack detection and defense. This review provides a
comprehensive analysis of 124 peer-reviewed studies published between 2015 and 2026 on cyber-resilient LFC
for interconnected power systems. The analysis shows that around 38% of the studies concentrate on resilient
control strategies, while 29% focus on cyber-attack detection and mitigation techniques. Approximately 18%
investigate intelligent optimization and artificial intelligence (AI)-based solutions, whereas the remaining 15%
explore secure communication frameworks, blockchain technologies, and distributed control architectures. The
review also highlights a clear shift in recent research toward AI-enabled adaptive control, observer-based
estimation, event-triggered communication, distributed control methods, and blockchain-supported secure LFC
frameworks designed for renewable-rich smart grids.
Keywords: Artificial intelligence; Frequency stability; Load frequency control; Renewable energy integration;
Resilient control.
1. Introduction
In the recent years the frequency and power regulation has changed significantly, as the electro mechanical
traditional power grid has moved towards the modern actively smart power grid operation. In regards to the
frequency regulation, it is a regulating circuit that maintains the power balance between connected control
areas in a network, i.e., the import and export of power across regulating gates in integrated areas under
changing power demand conditions. Large-scale employment of renewable energy requirement and energy
storage, the control information structure on the basis of communication systems and energy power points
with the present-day system is one of the notable features, allowing the system to shift its focus from the high
inertia, low uncertainty and low operational complexity. In contrast with the gradual changes in the
components included in systems, the level of complexity of the changes in the frequency regulation has
exceeded all expectations, especially since it was made a must to come up with such measures given the present
day control expectations.
[1]
There are many physical and technological disruptions in the practice of depending on digital communication
networks, leading to creating huge cyber security stakes in cyber-physical systems. One of the most targeted
entry points concerns the LFC loop, which lies between sensors, communication channels, and control centers.
This means that it can easily be bamboozled by numerous cyber attacks among them false specious data
injection, denial-of-service, replay-type, and time delay attack.
[2]
Actuation of these malicious touch points can
lead to lack of faith in the accuracy of signals for measurement or retardation in control actions that provokes
overall frequency response instability in interconnected power systems. Hence, indeed, there is certainly a very
high level of research priority sought on cyber-resilient frequency design for the modern operation like smart
grid.
In the past decade, a variety of secure and smart LFC approaches have been suggested by researchers to build
the system resilience against uncertainties and threats. In this manner, the conventional PI/PID controllers
have started to be replaced, or rather supplemented with newer advanced methods like model predictive
control, H∞ control, observer-based techniques, event-triggered control, and distributed control framework.
Intelligence-based approaches have proven to effectively deal with these and many other severe problems by
incorporating such noteworthy modern methods as neural network, reinforcement learning, and adaptive
optimization algorithms. Studies on cyber-attack and resilient control showed that there is a gap to be amended
with detailed developmental measures featuring vast Literature on Intelligent and Secure LFC Strategies for
modern interconnected power systems has been displayed on Fig. 1. It is, therefore, the aim of this research to
systematically investigate existing research by conducting feedback to produce details into computer intrusion
resilient how to control frequency. This study, therefore, by classifying the detection technique, attack
simulation, and control design that are impactful to secure designs, provides a comprehensive understanding
of existing phenomena patterns.
Fig. 1: Cyber-resilient load frequency control framework for modern interconnected power systems.
2. Literature review
The acceleration in both systems' digitization and the integration of renewable energies, cyber - physical
interconnections in smart grids, attention devoted to research in cyber-attack-resilient LFC has increased
substantially. Notably, various research groups have made efforts to implement detection of attacks, mitigation,
or resilient control methodologies in order to protect the frequency regulation method from malevolent stages
of cyber intrusions. Unequivocally more studies in this area could be categorized into seven broad thematic
groups according to the type of cyber threat anticipated and its corresponding control or security strategy.
These categories consist: Time-Delay and Communication Delay Attacks, False Data Injection (FDI) Attacks,
Denial-of-Service (DoS) Attacks, Deception and Bias Injection Attacks, Hybrid and Coordinated Cyber Attacks,
Renewable Integrated and Microgrid Cybersecurity Studies, Intelligence and Data-Driven Cyber-Resilient
Control Methods as shown in Table 1, and the flowchart was displayed in Fig. 2.
Fig. 2: The categories of cyber threats in LFC system.
Robust control strategies were developed to enhance the resilience of LFC systems against delayed input cyber
attacks, thereby improving frequency regulation under compromised communication conditions. Preventive
and detection mechanisms were introduced to address time-delay switch attacks in distributed power systems,
ensuring the secure operation of the Automatic Generation Control (AGC) loop.
[3]
The adverse impact of
communication time-delay attacks on AGC performance and overall system stability was also demonstrated.
[4]
To support the evaluation of cyber-resilient control strategies, an experimental cyber security testbed for
critical power infrastructure was established.
[5]
Furthermore, comprehensive studies reviewed the major cyber
security threats affecting smart grid frequency control and summarized effective countermeasures for cyber-
enabled power systems.
[6]
Research also examined the consequences of DoS attacks and proposed appropriate
mitigation and preventive control strategies.
[7]
Secure state estimation based on distributed compressive
sensing was introduced to improve system resilience under cyber uncertainties, showing that cyber attacks can
significantly reduce grid observability.
[8]
The authors of
[9,10]
discussed the cyber security challenges associated
with smart meter data intelligence and future energy systems.
A leader–follower architecture was proposed to enhance the resilience of LFC systems against cyber attacks by
improving coordination in frequency regulation.
[11]
A comprehensive survey of cyber-physical attacks and
defense mechanisms in smart grids highlighted major resilience challenges and security requirements.
[12]
A
hierarchical Stackelberg game-based resilient control strategy was introduced to mitigate intelligent cyber
attacks in Cyber-Physical Systems (CPS).
[13]
A cyber-physical control framework was also developed to preserve
power system stability under malicious cyber disturbances.
[14]
The author
[15]
was designed the hierarchical
cyber attack detection scheme for smart home environments by considering power overloading and frequency
disturbances. Simulation-based approaches were presented to analyze cyber security threats in smart grids and
evaluate the effectiveness of mitigation algorithms.
[16]
Planning and operational challenges in smart grids,
including cyber security concerns, were also comprehensively discussed.
[17]
An Industrial Control System (ICS)
security testbed was developed in [18] to investigate timing attacks and evaluate their impact on control system
performance. Adaptive neural network-based techniques were proposed to improve the detection of malicious
data injection attacks in CPS.
[19]
A decision-support framework was introduced to enhance the resilience and
operational reliability of cooperative cyber-physical control systems under cyber threats.
[20]
A novel cyber-attack detection scheme was developed for LFC systems, enabling the identification of a wide
range of cyber attacks with improved detection accuracy.
[21]
Defensive strategies were proposed to mitigate the
impact of DoS attacks on multi-area LFC systems, thereby enhancing system security and operational
reliability.
[22]
The impact of resonance attacks on smart grid frequency regulation was investigated in [23]
demonstrating their potential to destabilize power system operation. A FDI attack detection method was
introduced for distributed LFC systems using shared measurement data to improve attack identification.
[24]
A
real-time cyber-physical testbed was developed to evaluate the security, protection, and control performance of
power system operations under cyber attacks.
[25]
Cybersecurity protection strategies for power grid control
infrastructures and communication networks were also investigated to improve the resilience of distributed
power systems.
[26]
The effects of bias injection attacks on power plant operation and system performance were
analyzed, highlighting their influence on control stability.
[27]
In [28], author modelled the cascading failure
attacks in power systems using a stochastic game framework to evaluate their impact on grid reliability.
[28]
A
resilient networked control system was designed to withstand time-delay switch attacks, ensuring secure
communication between controllers and power system components.
[29]
The cyber attacks targeting data
integrity in storage-based transient stability control were investigated, and suitable mitigation strategies were
proposed to enhance grid resilience.
[30]
Significant progress was made in 2018 toward improving the cyber resilience of LFC systems. A sliding mode
observer-based control strategy was developed for multi-area power systems.
[31]
to enhance robustness against
bounded delayed-input cyber attacks, resulting in improved frequency regulation under adverse operating
conditions. Comprehensive reviews also examined the cyber-physical resilience of modern power systems by
identifying major vulnerabilities and summarizing defense mechanisms against malicious cyber threats.
[32]
Another extensive survey highlighted the evolution of LFC in conventional and smart power systems,
emphasizing the increasing importance of cybersecurity in future frequency control applications [33].
Advanced techniques for attack detection and identification were introduced for AGC systems, enabling faster
and more reliable recognition of cyber intrusions.
[34]
A set-theoretic approach was proposed in [35] to detect
data corruption attacks in cyber-physical power systems, thereby improving the reliability of monitoring and
control functions. The authorwas employed a stochastic unknown-input estimator to strengthen attack
detection capabilities in LFC systems operating under uncertain conditions.
[36]
Neural network-based resilient
control methods were also developed to maintain stable operation of distributed power systems during both
component faults and cyber attacks.
[37]
Fault-tolerant control strategies for electronically coupled distributed
energy resources further enhanced the resilience and reliability of microgrid operation.
[38]
The security
challenges associated with networked control systems in smart grids were comprehensively reviewed,
identifying existing vulnerabilities and potential protection mechanisms.
[39]
In [40], author was proposed the
distributed Model Predictive Control (MPC) framework for wide-area power systems to ensure secure and
scalable operation under malicious cyber attacks.
A decentralized functional observer-based optimal LFC framework was developed to improve frequency
regulation in the presence of unknown inputs, system uncertainties, and cyber attacks.
[41]
The effects of DoS
attacks on power system stability were thoroughly investigated and resilient control strategies were proposed
to mitigate their impact.
[42]
An event-triggered H∞ control approach was introduced by the author
[43]
for multi-
area LFC systems operating under hybrid cyber attacks, improving both communication efficiency and system
robustness. Resilient event-triggered output feedback control techniques were also developed to maintain
stable frequency regulation despite malicious cyber intrusions.
[44]
Dynamic characteristic analysis was
employed to detect cyber-physical attacks on LFC systems, enabling timely identification of abnormal operating
conditions.
[45]
Observer-based attack detection and mitigation methods were further proposed to improve the
resilience of frequency control against coordinated cyber attacks.
[46]
Deterministic dynamic state estimation
using unknown input observers was introduced to enhance the accuracy and security of interconnected power
system LFC.
[47]
The author [48] was proposed effective defense mechanisms against DoS attacks to strengthen
the reliability and stability of frequency control systems operating in cyber-enabled power grids. Coordinated
defense strategies against distributed DoS attacks were also investigated to ensure secure operation of multi-
area LFC services.
[49]
The attack–defense interaction models considering incomplete information were
developed to optimize cybersecurity strategies and improve the resilience of LFC systems against evolving cyber
threats.
[50]
A dynamic event-based MPC framework was developed to maintain stable frequency regulation in power
systems operating under cyber-attacks.
[51]
The impact of cyber attacks on AC–HVDC interconnected power
systems with emulated inertia was comprehensively analyzed, highlighting their influence on system stability
and dynamic performance.
[52]
Renewable energy-based LFC schemes were further investigated by incorporating
stochastic generation, communication delays, and packet losses to improve operational reliability under
uncertain conditions.
[53]
Cyber-attack-tolerant frequency control strategies were introduced to ensure secure
and reliable operation of interconnected power systems despite malicious intrusions.
[54]
Robust defense
mechanisms were also developed to mitigate load-altering attacks, thereby enhancing the resilience of LFC
systems against coordinated cyber threats.
[55]
Counteractive control techniques were proposed to address
cyber-attack uncertainties affecting frequency regulation and to maintain system stability under adverse
operating conditions.
[56]
A memory-based event-triggered H∞ LFC strategy was designed to improve resilience
against deception attacks while reducing communication overhead.
[57]
Secure frequency control methods for
microgrids were also developed to maintain stable operation under FDI attacks targeting measurement
sensors.
[58]
Robust LFC schemes capable of withstanding random time-delay attacks were further proposed to
enhance the reliability of communication-based control systems.
[59]
A credibility-based secure distributed LFC
framework was introduced to defend interconnected power systems against FDI attacks while ensuring reliable
frequency regulation.
[60]
A comprehensive survey summarized the cybersecurity challenges, vulnerabilities, and defense mechanisms
associated with LFC systems in modern power networks.
[61]
Memory-event-triggered H∞ control schemes were
proposed to improve frequency regulation under communication delays and cyber attacks while reducing
unnecessary data transmission.
[62]
Active fault-tolerant control strategies were introduced to maintain stable
LFC performance in the presence of both physical faults and cyber-attacks.
[63]
FDI attack detection methods
based on Kalman filtering and controller design were also developed to enhance the security of LFC systems.
[64]
Dual-source data-driven detection techniques further improved the identification of compromised variables
and cyber attacks in frequency control applications.
[65]
An intrusion mitigation framework was proposed to
strengthen cybersecurity and enhance the resilience of interconnected power systems during frequency
regulation.
[66]
Switching system-based LFC strategies capable of withstanding DoS attacks were developed to
ensure reliable operation of multi-area power systems.
[67]
Event-triggered control methods for Markovian jump
interconnected power systems were also introduced to improve resilience against DoS attacks while reducing
communication overhead.
[68]
Furthermore, intrusion detector-dependent distributed economic MPC was
proposed for secure load frequency regulation in systems integrated with plug-in electric vehicles under cyber
attack scenarios.
[69]
Decentralized robust disturbance observer-based LFC techniques were also developed to
enhance disturbance rejection and improve the reliability of interconnected power systems under uncertain
operating conditions.
[70]
An H-infinity (H∞) based LFC scheme was developed for multi-area power systems to maintain stable frequency
regulation under cyber attacks and time-varying communication delays.
[71]
Distributed observer-based event-
triggered control methods were introduced to improve the resilience of multi-area LFC systems against
malicious cyber intrusions while reducing communication overhead.
[72]
Event-triggered resilient LFC strategies
were also proposed for cyber-physical power systems to effectively mitigate the impact of DoS attacks.
[73]
Dynamic event-triggered output feedback control approaches were designed to ensure secure frequency
regulation under multiple coordinated cyber attacks.
[74]
A comprehensive review summarized recent advances
in cybersecurity analysis, attack detection, and defense mechanisms for cyber-physical power systems,
highlighting the growing importance of resilient control architectures.
[75]
Robust LFC methods for wind-
integrated power systems were further developed to address communication delays and packet losses while
maintaining system stability.
[76]
Dynamic event-triggered H∞ control schemes were introduced to enhance the
resilience of multi-area power systems against hybrid cyber-attacks.
[77]
The resilient LFC strategies capable of
withstanding DoS attacks were proposed to improve the security and reliability of interconnected power
systems.
[78]
Sliding mode event-triggered control techniques were also developed to strengthen the robustness
of multi-area LFC systems operating under hybrid cyber attacks.
[79]
The resilient control-based frequency
regulation schemes were proposed for isolated microgrids by considering both cyber attacks and parameter
uncertainties, thereby ensuring secure and reliable system operation.
[80]
A cybersecurity-oriented LFC framework in [81] was proposed by the author for hybrid interconnected
renewable power systems to enhance resilience against a wide range of cyber attacks. Sliding Mode Observer
(SMO)-based attack estimation techniques were introduced to improve the resilience of frequency control in
interconnected power systems under cyber attacks.
[82]
Robust networked LFC architectures were also
developed to withstand hybrid cyber attacks while maintaining reliable system performance.
[83]
Online
recursive attack detection combined with adaptive fuzzy mitigation was proposed to protect islanded
microgrids from cyber-physical attacks targeting LFC operation.
[84]
The vulnerability of Linear Quadratic
Gaussian (LQG)-based virtual inertia frequency control to DoS attacks was investigated, and its impact on
isolated microgrid stability was thoroughly analyzed.
[85]
Distributed coordination-based LFC schemes
incorporating attack detection and compensation mechanisms were further developed to mitigate the effects of
DoS attacks in interconnected power systems.
[86]
Quantum-inspired cybersecurity techniques were also
explored to strengthen the protection of electrical infrastructure against emerging cyber threats.
[87]
A Dragonfly
Algorithm-optimized PID controller was proposed to improve automatic frequency control in interconnected
DSTS power grids, resulting in enhanced dynamic performance and reduced frequency deviations [88]. An Ant
Colony Optimization (ACO)-based PI controller was also developed to improve frequency regulation in
interconnected power systems by achieving faster and more stable dynamic responses [89]. Comprehensive
reviews highlighted the evolving cybersecurity challenges and defense strategies for cyber-physical power
systems.
[90]
The contribution of energy storage technologies to frequency management in nuclear power systems was
comprehensively investigated, highlighting their role in improving system stability and reliability.
[91]
A cyber-
resilient frequency control framework that accounts for system nonlinearities and practical operating
constraints was proposed to improve the reliability and security of interconnected power systems.
[92]
The
author [93] was applied ACO-optimized secondary control strategies to microgrids, leading to improved
frequency regulation during system disturbances. A fuel cell-based non-integer controller was introduced to
strengthen both LFC and cybersecurity in renewable energy microgrids operating under cyber attacks [94].
Cyberattack defense strategies for smart grid LFC integrated with electric vehicles were also proposed to
enhance system resilience and operational security.
[95]
Preventive LFC schemes were developed to improve the
reliability of aging multi-area power systems subjected to cyber attacks.
[96]
Resilient frequency regulation
methods capable of mitigating hybrid cyber attacks were further introduced to enhance power system
security.
[97]
Decentralized secure LFC strategies were proposed for multi-area power systems operating under
complex cyber threats, ensuring reliable frequency regulation.
[98]
A data-driven attack recovery (DAR-LFC)
mechanism was also developed to restore normal operation following cyber attacks on frequency control
systems.
[99]
Power system stability was comprehensively analyzed from a cyber-attack perspective to identify
potential vulnerabilities and improve system resilience.
[100]
Data-driven switching-based LFC approaches were
proposed for multi-area power systems to maintain secure frequency regulation under cyber attack
conditions.
[101]
Smart frequency control techniques were further developed to withstand FDI attacks in cyber-
physical power systems.
[102]
Cyberattack-aware LFC frameworks were introduced to improve the security and
reliability of interconnected power systems operating in hostile cyber environments.
[103]
The attack-parameter-
dependent DoS-resilient LFC strategies and blockchain-enabled defense mechanisms were proposed to
strengthen cybersecurity and ensure reliable frequency regulation under DoS attacks.
[104,105]
A reinforcement learning-based LFC framework was developed for microgrids to maintain stable frequency
regulation under FDI attacks.
[106]
Secure LFC methods were further proposed for cyber-physical power systems
by considering cyber attacks, communication delays, and varying risk levels to improve operational
reliability.
[107]
An estimation-based Linear Quadratic Regulator (LQR) approach was introduced to mitigate data
integrity attacks in hybrid power systems, thereby enhancing control performance under compromised
communication environments.
[108]
Advanced LFC schemes were also developed for renewable energy- and
electric vehicle-integrated power systems to effectively suppress frequency deviations triggered by cyber
attacks.
[109]
The impact of DoS attacks on LFC performance in deregulated power markets was comprehensively
analysed, highlighting the associated operational challenges and mitigation requirements.
[110]
A modified hybrid
fractional PID control strategy optimized using the mZOA algorithm was proposed to improve frequency
regulation under multiple cyber attack scenarios.
[111]
Observer-based fuzzy event-triggered LFC incorporating
neural network approximation was introduced to enhance resilience against multiple cyber attacks while
reducing communication burden.
[112]
A resilient tri-parametric fractional frequency control strategy was also
developed by considering communication latency, demonstrating improved robustness under delayed cyber
environments.
[113]
A comprehensive defense framework was proposed to simultaneously mitigate FDI, DoS, and
latency attacks, thereby strengthening secure frequency regulation in cyber-physical power systems.
[114]
The
robust LFC strategies for renewable-integrated smart grids were presented to maintain reliable frequency
regulation despite cyber interruptions and communication uncertainties.
[115]
Neural network-based adaptive LFC strategies were developed for multi-area power systems to improve
resilience against hybrid cyber attacks while maintaining reliable frequency regulation.
[116]
Comprehensive
studies also analyzed the vulnerabilities, threat models, and security architectures of cyber-physical power
systems, providing valuable insights into the design of resilient control frameworks.
[117]
The impact of
optimization algorithms and energy storage systems on frequency management in both standalone and
interconnected power systems was systematically investigated, demonstrating the effectiveness of coordinated
energy storage in enhancing frequency stability.
[118]
Controlled energy storage-based cyber-resilient LFC
frameworks were further proposed for renewable-integrated power systems to improve operational security
under cyber attack scenarios.
[119]
Secure LFC strategies employing quantized MPC under round-robin
communication protocols were introduced to ensure reliable frequency regulation in networked power
systems.
[120]
Dynamic self-triggered LFC approaches were also developed to address the challenges of non-ideal
communication environments while reducing communication overhead.
[121]
An integral re-averaging control
strategy was proposed for T–S fuzzy reaction–diffusion power systems to enhance resilience against cyber
attacks and maintain system stability.
[122]
Robust PI-type LFC schemes were further designed for renewable
energy-integrated power systems by considering communication delays associated with electric vehicle
aggregators.
[123]
In addition, cascaded optimized fractional-order controllers were introduced to strengthen the
cyber resilience of green hydrogen-based microgrids against FDI attacks.
[124]
From the literature, it is clear that
an evolution was noticed from conventional resilient control and attack detection methods to the intelligent,
distributed, data-driven, and blockchain-supported secure control framework for LFC. The latest studies are
focusing on hybrid cyber-attack resilience, AI-based adaptive control, event-triggered communication,
observer-based estimation, and secure decentralized architectures, and highlight the necessity of cyber-secured
frequency regulation in renewable-rich, low-inertia, and highly connected modern power systems.
To make the scope of the reviewed literature easier to navigate, the 124 studies summarized above have been
reorganized into four focused tables rather than a single extended one. Table 1 groups the studies by the type
of cyber-attack they address, spanning ten broad categories from DoS and FDI to time-delay and hybrid multi-
vector attacks, along with the number of studies, the years they span, and their reference numbers.
Table 1: Attack types addressed in cyber-resilient LFC research (2015-2026, n = 124 studies).
Attack type
No. of studies
Year range
Ref.
General / Unspecified Cyber
Attack
42
2016-2026
11, 13, 14, 15, 21, 32, 34, 36, 37, 40, 41, 44, 46, 50, 51,
52, 54, 56, 62, 63, 65, 69, 71, 72, 80, 81, 82, 87, 92, 94,
95, 96, 99, 100, 101, 103, 107, 109, 111, 113, 119, 122
DoS/DDoS
14
2015-2025
7, 22, 42, 48, 49, 67, 68, 73, 78, 85, 86, 104, 105, 110
Time-Delay / Latency Attacks
9
2015-2020
1, 2, 3, 4, 18, 29, 31, 53, 59
FDI
9
2016-2026
19, 24, 58, 60, 64, 102, 106, 114, 124
Hybrid / Multi-Vector Attacks
9
2019-2026
43, 74, 77, 79, 83, 97, 98, 112, 116
Data Integrity / Deception
Attacks
6
2017-2025
27, 30, 35, 55, 57, 108
Cyber-Physical Attacks
(General)
3
2016-2023
12, 45, 84
Cascading / Resonance Attacks
2
2017
23, 28
Data / Measurement Attacks
1
2015
9
Cyber Intrusion
1
2021
66
Not specified in source study
28
2015-2026
5, 6, 8, 10, 16, 17, 20, 25, 26, 33, 38, 39, 47, 61, 70, 75,
76, 88, 89, 90, 91, 93, 115, 117, 118, 120, 121, 123
Table 2 turns to how these attacks are countered, sorting the work into thirteen families of control strategy,
including event-triggered schemes, observer-based designs, model predictive control, H∞/robust formulations,
and more recent AI- and data-driven approaches.
Table 2: Control strategies proposed for cyber-resilient LFC (2015-2026).
Control strategy
No. of studies
Year range
Ref.
General Resilient Control
21
2015-2026
1, 11, 14, 29, 53, 58, 60, 67, 78, 80, 81, 94, 97, 98,
102, 103, 104, 107, 109, 111, 121
Event-Triggered Control
11
2019-2025
43, 44, 57, 62, 68, 72, 73, 74, 77, 79, 112
Defense / Mitigation Strategy
8
2015-2025
2, 48, 49, 55, 56, 66, 95, 114
AI / Data-Driven Control
7
2018-2026
37, 84, 99, 101, 106, 116, 122
H∞ / Robust Control
7
2020-2026
54, 59, 71, 76, 83, 115, 123
Optimization-Tuned /
Fractional Control
6
2023-2026
88, 89, 93, 113, 118, 124
Observer-Based Control
5
2018-2023
31, 41, 47, 70, 82
MPC
4
2018-2026
40, 51, 69, 120
Game-Theoretic
Control/Defense
3
2016-2019
13, 28, 50
Fault-Tolerant Control
2
2018-2021
38, 63
LQR/LQG Control
2
2023-2025
85, 108
Energy-Storage-Based Control
2
2023-2026
91, 119
Blockchain-Based Control
1
2024
105
In Table 3 narrows in on detection specifically, since not every study that proposes a control strategy also
proposes a way to detect the attack in the first place; here the studies fall into eight detection-technique families,
among them Kalman-filter-based, set-theoretic, observer-based, and intrusion-detection methods.
Table 3: Cyber-attack detection methods reported in lfc research (2015-2026).
Detection method
No. of studies
Year range
Ref.
Attack Detection Technique
(General)
4
2015-2023
3, 34, 84, 86
State/Input Estimation-Based
Detection
3
2018-2023
36, 47, 82
Detection Algorithm (General)
2
2016-2017
15, 24
Detection Scheme (General)
2
2017-2021
21, 65
Intrusion Detection
2
2021
66, 69
Set-Theoretic Detection
1
2018
35
Observer-Based Detection
1
2019
46
Kalman-Filter-Based Detection
1
2021
64
Finally, Table 4 steps back from cataloguing individual studies and instead distils seven open research gaps that
emerge once the field is viewed as a whole, covering coordinated multi-vector attacks, the growing complexity
of renewable and EV-integrated grids, the disconnect between detection and control design, scalability to large
distributed systems, the generalizability of AI-based methods, the still-nascent use of blockchain and quantum-
based security, and the lack of standardized testbeds for comparing approaches; each of these gaps is linked
back to the specific studies that motivate it.
Table 4: Future challenges and open research directions for Cyber-Resilient LFC.
Challenge / Research gap
Description
Multi-vector and coordinated
attacks
Most studies address a single attack type in isolation; robust detection/control
under simultaneous FDI, DoS and time-delay attacks remains largely open (only 9
hybrid studies, e.g. refs 43, 74, 79, 112, 116).
Renewable- and EV-integrated
grids
Low-inertia, high-penetration renewable and EV-aggregator systems introduce
new attack surfaces; only a small, recent subset of studies (e.g. refs 109, 119, 123,
124) addresses this explicitly.
Real-time detection-control
co-design
Detection methods (16 studies) and control strategies (79 studies) are largely
developed separately; tightly-coupled, real-time detection-and-mitigation
frameworks are comparatively rare.
Scalability to large,
distributed/multi-area
systems
Event-triggered and distributed MPC approaches (e.g. refs 40, 51, 69, 120) show
promise but scalability to large multi-area, multi-agent grids needs further
validation.
Data-driven / AI-based
generalization
AI and data-driven control (7 studies) is emerging but often validated on limited
test systems; generalization, explainability and adversarial robustness remain
open questions.
Blockchain- and quantum-
based security
Only isolated studies (e.g. refs 87, 105) explore blockchain- or quantum-based
protection; practical, standardized implementations for LFC remain unexplored.
Standardized cybersecurity
testbeds and benchmarks
Testbed/case-study work (e.g. refs 5, 18, 25) is limited; the field lacks common,
openly available benchmark platforms for comparing detection and control
strategies.
2. Critical analysis, research gaps, limitations, and future research directions
2.1 Critical analysis of the reviewed literature
The literature reviewed in this study demonstrates that considerable progress has been made in developing
cyber-resilient LFC strategies for interconnected power systems. Initial research mainly concentrated on
maintaining frequency stability under conventional operating conditions using classical controllers such as PI
and PID controllers. As power systems evolved into highly interconnected cyber-physical systems, researchers
increasingly focused on addressing cyber threats that could compromise the reliability and stability of
frequency control. In recent years, significant attention has been given to developing resilient control
techniques capable of detecting and mitigating cyber attackssuch as FDI, DoS, replay attacks, communication
delays, deception attacks, and coordinated hybrid attacks. Advanced control approaches, including model
predictive control, adaptive control, observer-based methods, sliding mode control, event-triggered control,
distributed control, and artificial intelligence-based techniques, have shown improved performance compared
with conventional controllers, particularly under uncertain operating conditions. Similarly, nature-inspired
optimization algorithms have been widely adopted to enhance controller tuning and improve dynamic
performance.
Although these developments have contributed significantly to the field, the existing literature remains
fragmented. Most studies investigate only a specific attack scenario or a particular control strategy without
considering the combined influence of multiple cyber-attacks, renewable energy uncertainty, communication
network limitations, and practical implementation issues. Consequently, the available research provides only a
partial understanding of cyber resilience in modern interconnected power systems.
2.2 Research gaps
The comprehensive review of the literature has revealed several research gaps that require further
investigation. The majority of existing studies examine individual cyber attacks independently, whereas real-
world power systems are more likely to experience coordinated attacks involving multiple attack vectors. The
interaction between hybrid cyber attacks and renewable energy uncertainties has received comparatively little
attention. Another important limitation is the lack of experimental validation. Most published works evaluate
their proposed methods using simulation platforms, while only a limited number of studies demonstrate their
effectiveness through Hardware-in-the-Loop (HIL) testing, Real-Time Digital Simulator (RTDS), OPAL-RT
platforms, or industrial-scale implementations. As a result, the practical feasibility of many proposed
techniques remains uncertain.
Artificial intelligence has emerged as a promising solution for cyber-attack detection and resilient control.
However, many AI-based approaches rely on complex deep learning models whose decision-making process is
difficult to interpret. The absence of explainable AI limits their acceptance in safety-critical power system
applications. The increasing integration of renewable energy sources introduces additional operational
uncertainties, including intermittent generation, reduced system inertia, and rapidly changing operating
conditions. Many existing cyber-resilient control strategies do not adequately account for these challenges,
particularly when combined with cyber-attacks. Communication issues also remain insufficiently addressed.
Factors such as communication delays, packet losses, synchronization errors, bandwidth limitations, and
network congestion can significantly influence controller performance but are often simplified or neglected in
current studies. Furthermore, many proposed control strategies have been validated only for small-scale two-
area or three-area interconnected systems. Their scalability and computational performance in large-scale
interconnected smart grids with numerous distributed energy resources require further investigation.
Finally, relatively few studies consider compliance with practical cybersecurity standards and industrial
communication protocols. Bridging the gap between academic research and real-world deployment remains an
important challenge.
2.3 Limitations of existing approaches
The review indicates that every resilient control strategy possesses certain advantages as well as inherent
limitations. Conventional PI and PID controllers are simple to implement but generally provide limited
resilience against sophisticated cyber-attacks. Robust and adaptive controllers improve disturbance rejection
but often require accurate system models and involve higher design complexity. MPC offers excellent dynamic
performance; however, its computational requirements may restrict real-time implementation in large-scale
systems. Observer-based techniques depend heavily on estimation accuracy and may become sensitive under
severe model uncertainties. AI-based methods achieve high detection accuracy but often require large training
datasets and lack transparency in their decision-making process. Likewise, blockchain-based communication
frameworks enhance data integrity and security but introduce additional communication overhead and latency
that must be carefully managed.
2.4 Novelty statement
Unlike existing review articles that primarily focus on conventional LFC techniques, optimization algorithms,
or individual cyber-attack scenarios, this study presents a comprehensive and systematic review of intelligent
and cyber-resilient LFC strategies for modern interconnected power systems. The review synthesizes evidence
from 124 peer-reviewed publications (2015–2026) and integrates developments in resilient control, cyber-
attack detection, secure communication, artificial intelligence, and distributed control into a unified analytical
framework. It provides a structured classification of control methodologies according to controller design,
cyber threats, defense mechanisms, optimization techniques, communication architectures, and renewable
energy integration. This work identifies emerging research trends, highlights unresolved technical challenges,
and establishes future research directions involving AI-enabled adaptive control, event-triggered
communication, observer-based estimation, blockchain-supported security, and decentralized frequency
regulation. By connecting control theory with cybersecurity and intelligent energy management, this review
offers a holistic perspective that is currently lacking in the existing LFC literature.
2.5 Future research directions
The findings of this review suggest several promising directions for future research. Explainable artificial
intelligence should be explored to improve the transparency and reliability of AI-assisted cyber-attack
detection and resilient control. The integration of digital twin technology with LFC may enable continuous
monitoring, predictive analysis, and proactive mitigation of cyber threats. Blockchain and distributed ledger
technologies also offer significant potential for secure communication and data authentication, although their
scalability and computational efficiency require further improvement.
Future studies should investigate resilient control strategies capable of handling coordinated hybrid cyber
attacks under highly uncertain operating conditions associated with renewable energy integration, electric
vehicles, energy storage systems, and distributed generation. Greater emphasis should also be placed on
developing scalable distributed control architectures suitable for large interconnected power systems.
Experimental validation should become an integral part of future research. Hardware-in-the-Loop testing, real-
time digital simulation, FPGA implementation, and pilot-scale demonstrations would provide stronger evidence
of practical applicability. In addition, the development of standardized benchmark systems, publicly available
datasets, and common performance evaluation metrics would facilitate objective comparison among different
cyber-resilient control techniques and accelerate progress in this research area.
3. Cyber-attack themes and resilient control strategies
The Fig. 3 presents a thematic classification of modern, interconnected power systems in cyber-resilient LFC
research; this is evidenced from [32]. Some cybersecurity risks at the LFC level are also illustrated, with time
manipulation attacks, malicious data insertion, denial, deception, and hybrid coordinated threats given germane
mention.
[61]
These threats then spread across various coordinated regions, communication links, control loops,
and, in some cases, to frequency. Among the means to counter these challenges include various resilient control
strategies like observer-based control, triggers of event-based control, and completion control systems.
[75]
Fig. 3: Diagrammatic representation of major cyber-attack themes and resilient control strategies.
Renewable integration and microgrid environments increase the uncertainty of the system considerably-the
boiling points of which are cyber vulnerability. Intelligent and data-driven methods are portrayed as advanced
mitigation tools with artificial intelligence, reinforcement learning, and neural networks. Blockchain-enabled
exposure to security features of communication architectures increasingly demands data integrity. This
exposition shows how the conventional robust control changes to an adaptive and intelligent system of cyber-
resilient LFC. It further goes further inside the basic layers such that it combines detection, estimation, and
mitigation into a single organized viewpoint. In general, this figure provides a well-rounded concept of all
characteristics nurturing cyber-resilient LFC themes and emerging trends in future smart grids.
3.1. Time-delay and communication delay attacks
Time-delay and communication delay attacks represent one of the earliest and most extensively investigated
cyber security threats in LFC systems. These attacks intentionally introduce delays into sensor measurements,
control commands, or communication channels linking interconnected control areas, thereby disrupting the
timely exchange of frequency and tie-line power information. Since LFC relies on continuous feedback to
maintain the balance between power generation and demand, even small communication delays can degrade
dynamic performance, increase frequency oscillations, and prolong settling time under disturbed operating
conditions.
[1,31]
Early studies primarily focused on analysing the impact of communication delays on AGC
performance and assessing their influence on overall system stability. As research progressed, greater attention
was directed towards identifying abnormal communication delays using delay estimation techniques,
timestamp verification, residual monitoring, and communication health assessment. These detection
mechanisms enable the control system to distinguish malicious delays from normal network latency, allowing
appropriate corrective actions to be initiated before system performance deteriorates.
To reduce the adverse effects of delay attacks, several mitigation strategies have been proposed. Delay
compensation algorithms, predictive estimation methods, redundant communication paths, and packet
recovery techniques help maintain reliable information exchange during network disturbances. In parallel,
resilient control approaches have evolved from conventional robust controllers to more advanced techniques,
including sliding-mode observer-based control, H∞ control, memory-based control, and event-triggered
control. These methods reduce the dependence on continuous communication while maintaining frequency
stability despite uncertain network conditions. More recently, distributed and quantized control frameworks
have demonstrated improved robustness against random and stochastic communication delays in large-scale
interconnected power systems.
[59]
Overall, research on time-delay attacks has progressed from impact
assessment to the development of integrated detection, mitigation, and resilient control strategies, significantly
improving the cyber security and operational reliability of modern cyber-physical power systems.
3.2 False data injection attacks
FDI attacks are among the most extensively studied cyber security threats in LFC systems because they directly
compromise the integrity of measurement data used for frequency regulation. In these attacks, an adversary
deliberately manipulates critical signals, such as frequency deviation, tie-line power, and Area Control Error
(ACE), with the objective of misleading the controller while remaining undetected.
[58]
Unlike conventional
disturbances, FDI attacks are particularly dangerous because the manipulated data often appear legitimate,
allowing the attack to gradually degrade system performance without triggering immediate alarms.
[60]
Initial
research in this area primarily focused on state estimation and anomaly detection techniques to identify
inconsistencies between measured and estimated system states. As the field advanced, observer-based
methods, unknown-input observers, and Kalman filter-based algorithms were introduced to improve attack
detection accuracy and reconstruct compromised signals. Adaptive estimation techniques further enhanced the
ability to detect stealthy attacks under varying operating conditions.
Several mitigation strategies have been developed to minimize the impact of compromised measurements on
system performance. Secure state estimation, adaptive filtering, measurement validation, and sensor
redundancy are widely adopted to isolate corrupted data and recover reliable system information before control
actions are executed. More recently, credibility-based distributed LFC frameworks have been proposed to
evaluate the trustworthiness of information exchanged among interconnected control areas, thereby reducing
the influence of compromised communication channels.
[102]
In parallel, resilient control strategies have evolved
to include observer-based controllers, adaptive control schemes, fuzzy logic, neural networks, and deep learning
techniques capable of maintaining stable frequency regulation even in the presence of manipulated data. These
intelligent approaches continuously update system models, improve attack identification, and support real-time
corrective actions. Overall, research on FDI attacks has progressed from basic detection methods to integrated
frameworks that combine attack detection, data validation, mitigation, and resilient control, thereby enhancing
the cyber security and operational reliability of modern interconnected power systems.
3.3 Denial-of-service attacks
DoS attacks primarily target the communication infrastructure of interconnected power systems by
interrupting, delaying, or blocking the transmission of control signals between sensors, controllers, and control
centres. As a result, critical information such as frequency deviation, tie-line power, and ACE may not reach the
controller within the required time, leading to poor coordination among control areas, increased frequency
deviations, and reduced system reliability. Early studies mainly investigated the impact of packet losses,
communication interruptions, and signal blocking on AGC, demonstrating that prolonged communication
failures can significantly degrade transient performance and even threaten system stability. To detect such
attacks, researchers have proposed communication health monitoring, packet-loss analysis, network traffic
monitoring, watchdog timers, and anomaly detection techniques that continuously assess the availability and
integrity of communication links.
Following attack detection, several mitigation strategies have been introduced to maintain reliable frequency
regulation during communication disruptions. These include redundant communication networks, packet
retransmission mechanisms, adaptive communication scheduling, and coordinated defense strategies that
reduce the impact of large-scale network attacks. At the control level, resilient solutions such as event-triggered
control, switching-based control, observer-based control, and predictive control have been developed to
maintain acceptable performance even when communication links are temporarily unavailable. Decentralized
and distributed LFC architectures further improve system resilience by reducing dependence on a centralized
communication network and enabling local controllers to operate independently during communication
failures. More recent studies have integrated adaptive secure observers, robust control techniques, and
distributed resilient control frameworks to enhance the ability of cyber-physical power systems to withstand
DoS attacks while preserving frequency stability. Overall, research on DoS attacks has evolved from analysing
communication failures to developing comprehensive frameworks that combine attack detection, mitigation,
and resilient control, thereby improving the security and reliability of modern interconnected power systems.
3.4 Deception and bias injection attacks
Deception and bias injection attacks are stealthy cyber threats that manipulate control inputs or measurement
signals without interrupting communication between system components. Instead of blocking data
transmission, these attacks introduce carefully crafted false information into frequency deviation, ACE, or tie-
line power measurements, making the manipulated signals appear similar to normal operating disturbances.
As a result, the controller may generate incorrect control actions, leading to gradual deterioration of frequency
regulation performance while the attack remains difficult to detect. Early research mainly focused on analysing
the impact of deception attacks on interconnected power systems and developing mathematical models to
understand their influence on system dynamics. To identify these stealthy attacks, researchers introduced set-
theoretic methods, residual-based monitoring, observer-based estimation, and adaptive state estimation
techniques capable of detecting subtle deviations between measured and expected system behaviour.
[35]
These
approaches significantly improved the detection of malicious signal manipulation under uncertain operating
conditions.
To minimize the impact of compromised measurements such as observer-based signal reconstruction, adaptive
bias compensation, secure state estimation, and measurement validation methods are widely used to recover
reliable system information before it is utilized by the controller. In addition, active fault-tolerant control
strategies have been developed to simultaneously address both physical component faults and cyber intrusions,
thereby improving overall system resilience. Memory-based H∞ controllers, intelligent observers, and adaptive
estimation algorithms further enhance the capability of LFC systems to compensate for hidden malicious inputs
while maintaining stable frequency regulation.
[57]
Recent research has also incorporated artificial intelligence-
based observers and real-time bias compensation techniques to improve detection accuracy and accelerate
system recovery. Overall, the development of secure LFC frameworks for deception and bias injection attacks
has evolved from impact analysis to integrated detection, mitigation, and resilient control strategies, providing
improved protection against stealthy cyber threats in modern interconnected power systems.
3.5 Hybrid and coordinated cyber attacks
Hybrid cyber attacks combine multiple attack strategies, such as FDI, DoS, deception, and communication delay
attacks, to simultaneously compromise different components of interconnected power systems. These
coordinated attacks are considerably more challenging to identify and mitigate because they exploit multiple
vulnerabilities at the same time, resulting in severe degradation of LFC performance and overall grid stability.
The initial indication of a hybrid attack is often the simultaneous occurrence of abnormal communication
behaviour and inconsistent measurement data, making conventional single-layer detection methods
insufficient. Consequently, recent research has focused on developing integrated detection frameworks that
combine anomaly detection, observer-based estimation, machine learning algorithms, and multi-source data
fusion techniques to identify complex attack patterns more accurately. Attacker-defender game-theoretic
models have also been introduced to analyse the interaction between attackers and system operators, enabling
more effective cyber security planning and risk assessment.
[80]
Once a hybrid attack is detected, mitigation strategies aim to isolate compromised communication channels,
validate measurement data, and maintain reliable information exchange across interconnected control areas.
Adaptive communication management, secure data validation, coordinated recovery mechanisms, and
redundant network architectures have been widely investigated to reduce the impact of simultaneous attacks.
In parallel, resilient control strategies have evolved from conventional robust controllers to adaptive and
intelligent control frameworks capable of maintaining frequency stability under multiple cyber threats. Deep
learning-based predictive models have recently been employed to anticipate attack behaviour and support
proactive mitigation before system performance is significantly affected. Block chain-assisted secure
communication has also emerged as a promising solution for preserving data integrity and preventing
unauthorized data manipulation. Furthermore, cooperative multi-agent defense frameworks enable distributed
controllers to exchange trusted information and coordinate control actions, thereby enhancing the overall
resilience of interconnected power systems against sophisticated cyber attacks.
[79]
Overall, current research on
hybrid cyber attacks highlights the growing need for integrated detection, mitigation, and resilient control
mechanisms to ensure the secure and reliable operation of future cyber-physical power grids.
3.6 Renewable-integrated and microgrid cyber themes
The increasing penetration of renewable energy resources and microgrids has introduced new cyber security
challenges for LFC, particularly in low-inertia power systems. Unlike conventional power networks, renewable-
rich systems exhibit higher operational uncertainty and reduced inertia, making them more vulnerable to cyber
attacks that target communication networks, distributed controllers, and measurement devices. Such attacks
can amplify frequency deviations, disrupt power sharing among distributed energy resources, and degrade the
overall stability of interconnected microgrids. Consequently, recent research has focused on identifying
abnormal operating conditions through distributed monitoring, phasor measurement unit (PMU)-based state
estimation, anomaly detection algorithms, and data-driven analytics capable of distinguishing cyber attacks
from normal renewable power fluctuations. These detection techniques provide early warning of malicious
activities while reducing false alarms caused by the intermittent nature of renewable generation.
Following attack detection, several mitigation strategies have been developed to improve the resilience of
renewable-integrated power systems. Secure communication protocols, distributed state estimation, adaptive
energy management, and coordinated control of distributed energy resources help maintain reliable operation
even when parts of the communication network are compromised. Energy storage systems, including battery
energy storage and hybrid storage technologies, further enhance frequency support by compensating for power
imbalances during cyber disturbances. In addition, resilient control strategies based on adaptive control,
stochastic control, model predictive control, and distributed secondary frequency control have been widely
investigated to maintain frequency stability under uncertain operating conditions. More recently, artificial
intelligence and data-driven approaches have been incorporated into LFC frameworks to improve attack
detection, predictive decision-making and real-time disturbance rejection.
[119]
Emerging concepts such as
hydrogen-integrated power systems and hybrid energy systems are also being explored to enhance the cyber
resilience of future smart grids. Overall, current research demonstrates that combining advanced detection
methods, effective mitigation techniques, and intelligent resilient control is essential for ensuring secure and
reliable frequency regulation in renewable-rich interconnected power systems.
3.7. Intelligent and data-driven security themes
Intelligent and data-driven cyber security has become one of the most promising research directions for
improving the resilience of LFC systems against evolving cyber threats. The rapid advancement of artificial
intelligence, machine learning, deep learning, and reinforcement learning has enabled LFC systems to move
beyond conventional rule-based security mechanisms towards adaptive and predictive cyber defense. These
techniques continuously analyse large volumes of operational data to detect abnormal system behaviour,
identify attack patterns, and distinguish cyber attacks from normal operating disturbances with higher
accuracy than traditional model-based approaches.
[101,106]
Deep learning algorithms, intelligent state observers,
and data-driven anomaly detection models have demonstrated significant improvements in identifying stealthy
attacks, estimating compromised system states, and providing early warning of potential cyber intrusions, even
under highly uncertain operating conditions.
The intelligent mitigation strategies employ adaptive learning, online model updating, and predictive decision-
making to minimize the impact of malicious activities before they propagate through the control system. Data
validation, secure information fusion, trust evaluation, and block chain-assisted communication further
enhance the integrity and reliability of data exchanged among interconnected control areas. At the resilient
control level, AI-assisted adaptive controllers, reinforcement learning-based control, self-triggered control, and
intelligent decentralized control frameworks enable rapid recovery from cyber disturbances while maintaining
stable frequency regulation. Hybrid AI-observer architectures further improve estimation accuracy and support
real-time compensation for compromised measurements, thereby strengthening the overall resilience of
interconnected power systems.
[116]
As future smart grids become increasingly digitalized and renewable-
intensive, the integration of intelligent detection, adaptive mitigation, and AI-enabled resilient control is
expected to play a key role in achieving autonomous, secure, and reliable frequency regulation under dynamic
cyber-physical environments.
4. Conclusion
The summary is a hidden place with cyber-robust LFC built to keep varying weather pumps in an unsafe
position at a modern, synchronized electrical power output insertion where it binds substantial portions of
inject-into from the side of increasing renewable penetration, communication delays, and cyber-physical
vulnerabilities. Having studied research contributions conducted in a wide genre, it is shown that much
research progresses through self-assorted and combined recovery southeast productions in cyber-attack
modelling, detection, and resilient control designs, gathering together conventional, robust, observer-based,
and in-depth event-triggered and AI driven approaches. Cyber attacks will cause serious disturbances in
frequency stability, disturb tie-line power regulation, and threaten the secure operation of multi-area power
systems if the system is attacked with FDI, denial-of-service, replay, and time delay attacks. The first takes into
account traditional PI/PID-based LFC methods from the study. Through all documented articles, it is clear that
the traditional LFC with PI/PID control is ineffectual for the contingencies of low-inertia renewable-
incorporated grids as well as cyber combined threats. Advanced control strategies show enhancement of
robustness in comparison to conventional methods. Advanced control strategies include using edge methods,
for example, H∞ control, model-area model-based control, or sliding mode control and distributed observer-
based techniques to attack and the approach with adaptive robust control for the design of novel LFC
algorithms. Also, the intelligent robot is put into action with the flexibility of the brain network used as
reinforcement learning and hybrid optimization algorithms, bolstered by fuzzy logic to help the system shrug
off any attack and attempt any real-time recovery in cyber-physical environments. It is clear that the review
also demonstrates the growing trend towards integrated frameworks combining intrusion detection systems,
secure communication protocols, and data-driven control to enable reliable frequency regulation. Increasing
use of event-triggered and decentralized control architectures can lead to reduced communication overhead
and prevent system instability even when deprived from network constraints and cyber disruptions. Moreover,
inclusion of energy storage systems and renewable deployment force multipliers their dynamic frequency
response and operational flexibility. However, advances being made, several research gaps are yet to be fully
addressed such as accuracy of real-time implementations, scalability in large interconnected grids, the
coordination of defense against hybrid cyber-attacks, and the necessity of standardizing security-aware LFC
frameworks. Future research shall tackle AI-based explainable controller developments, security using block
chain communication and adaptive and resilient control strategies viable for a highly digitalized smart grid.
Potentially, it focuses on cyber-resilient and intelligent LFC design to ensure a secure, stable, and sustainable
operational mode of interconnected next-generation power systems.
CRediT Author Contribution Statement
Satheeshkumar R: Conceptualization, Writing - Original draft, Writing-Review & editing. Jagatheesan K.:
Formal analysis, Writing - Review & editing. Lenin V R: Supervision. Kanendra Naidu: Investigation, Validation.
Anand B: Investigation, Validation. All authors have read and agreed to the published version of the manuscript.
Funding Declaration
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-
profit sectors.
Data Availability Statement
No data were generated or analyzed during the current study. Therefore, data sharing is not applicable to this
article.
Conflict of Interest
There is no conflict of interest.
Artificial Intelligence (AI) Use Disclosure
The authors declare that artificial intelligence (AI)-assisted tools were used only for language refinement,
grammar improvement, and manuscript structuring purposes during the preparation of this work. All technical
content, experimental implementation, results, and interpretations were independently developed and verified
by the authors.
Supporting Information
Not applicable
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