Review of Load Frequency Control methods, Part-II: Post-deregulation scenario and case studies

Information and communication technology tremendously facilitates the operation efficiency and economy of modern power systems in recent years. However, risks such as bandwidth constraints and malicious attacks threaten the secure load frequency control (LFC) of power systems. To mitigate such risks, this paper proposes distributed observer-based event-triggered LFC schemes for multi-area power systems under cyber attacks. Considering the practical situation that only local system output information may be available, distributed observer-based LFC schemes are designed. Meanwhile, to reduce the communication burden, an event-triggered mechanism is adopted to design control laws, where both static and dynamic event-triggered approaches are taken and the dynamic one is proved to be more economical in terms of control cost. Verifiable sufficient conditions are established to guarantee the stability of the closed-loop system in the presence of cyber attacks and the controller gains are explicitly derived. Finally, validation studies on a three-area interconnected power system are carried out to demonstrate the proposed control schemes. Note to Practitioners—Load frequency is a crucial index for evaluating the quality of electric energy and thus LFC has brought considerable attention in the area of power systems control. Although many achievements have been made on the LFC of multi-area power systems, the risks such as bandwidth constraints and malicious attacks affect the normal operation of LFC due to the interconnection between different power systems. To deal with these risks, this paper focuses on designing event-triggered LFC to guarantee the stability of the frequency deviation while reducing the communication burden and mitigating cyber attacks. More importantly, the proposed event-triggered LFC is designed based on an observer and can be implemented in a distributed manner, which is relatively practical in real applications. The results presented in this paper aim to provide a helpful reference for stable and secure LFC design of multi-area power systems, such that the corresponding application research can be promoted.

AIn this paper, impact of communication delay on distributed load frequency control (dis-LFC) of multi-area interconnected power system (MAIPS) is investigated. Load frequency control (LFC), as one of ancillary services, is aimed at maintaining system frequency and inter-area tie-line power close to the scheduled values, by load reference set-point manipulation and consideration of the system constraints. Centralized LFC (cen-LFC) requires inherent communication bandwidth limitations, stability and computational complexity, as such, it is not a good technique for the control of large-scale and geographically wide power systems. To decrease the system dimensionality and increase performance efficiency, distributed and decentralized control techniques are adopted. In distributed LFC (dis-LFC) of MAIPS, each control area (CA) is equipped with a local controller and are made to exchange their control actions by communication with controllers in the neighboring areas. The delay in this communication can affect the performance of the LFC scheme and in a worst case deteriorates power system stability. To investigate the impact of this delay, model predictive controller (MPC) is employed in the presence of constraints and external disturbances to serve as LFC tracking control. The scheme discretizes the system and solves an on-line optimization at each time sample. The system is subjected to communication delay between the CAs, and the response to the step load perturbation with and without the delay. Time-based simulations were used on a three-area MAIPS in MATLAB/SIMULINK environment to verify the investigations. The overshoot and settling time in the results reveals deterioration of the control performance with delay. Also, the dis-LFC led to zero steady states errors for frequency deviations and enhanced the MAIPS’ performance. With this achievement, MPC proved its constraints handling capability, online rolling optimization and ability to predict future behavior of systems.

A memory output sliding mode load frequency control (MOSMLFC) strategy is proposed for multi-area interconnected power systems under historical-frequency-triggered denial-of-service (DoS) attacks. Due to the use of the open network, the multi-area power system is prone to cyber-attacks. Different types of attack models have been built to describe the actual attack behavior, so that effective strategies can be quickly formulated in the event of an attack. Therefore, a historical-frequency-triggered DoS attacks model is presented from the perspective of attackers, with the aim of destroying the stable state of the multi-area power system. It is assumed that attackers determine the timing of DoS attacks by monitoring the operational status of multi-area power systems and designing the triggering condition with historical frequency. A MOSMLFC strategy is investigated to ensure the security performance of multi-area power systems under historical-frequency-triggered DoS attacks, which applies the memory output information of the power system to realize the controller design. The security condition of multi-area power systems under historical-frequency-triggered DoS attacks is obtained by Lyapunov’s theorem and linear matrix inequality (LMI). Numerical examples are tested over the IEEE 10-generator 39-bus system and the results prove the usefulness and superiority of the proposed method. Note to Practitioners—Load frequency control is widely applied in multi-area power systems to achieve a balance between the load demand and generation. Frequent cyber-attacks are a threat to the normal operation of the power system. It is therefore necessary to develop appropriate strategies to defend against cyber-attacks. So far, there have been many different forms of cyber-attacks. This has prompted defenders to build different types of attack models to describe the actual attack behavior in order to preemptively formulate appropriate defensive strategies. Smart attacker may notice that certain characteristics of the target system are important, such as the power system frequency. This motivates us to propose a historical frequency-triggered DoS attack model that contributes to a deep understanding of the impact of cyber-attacks on the power system. We propose a unique sliding mode control approach to ensure the stable performance of power system state and output simultaneously.

Load frequency control (LFC) requires transmission of remote measurements to the control center and of control signals from the control center to the plant. Constant delays exist in the dedicated communication channel and an open communication network introduces time-varying delays. Those delays would degrade the dynamic performance of LFC and even cause instability. This paper investigates the delay-dependent stability of the LFC scheme by adopting a delay-dependent criterion and linear matrix inequalities (LMIs). The maximal delay time which allows a power system with a LFC scheme embedded to retain stable is defined as the delay margin for stability analysis. A proportional-integral (PI) controller using the area control error (ACE) as input signal is employed in the LFC scheme. Special attention is paid to the relationship between the gains of PI controller and the delay margin. Case studies are carried out based on one-area and two-area LFC schemes to demonstrate the effectiveness of the criterion. Both constant and time-varying delays are considered. Moreover, the accuracy of the criterion used is also verified by simulation studies.

The hybrid power system is a combination of renewable energy power plants and conventional energy power plants. This integration causes power quality issues including poor settling times and higher transient contents. The main issue of such interconnection is the frequency variations caused in the hybrid power system. Load Frequency Controller (LFC) design ensures the reliable and efficient operation of the power system. The main function of LFC is to maintain the system frequency within safe limits, hence keeping power at a specific range. An LFC should be supported with modern and intelligent control structures for providing the adequate power to the system. This paper presents a comprehensive review of several LFC structures in a diverse configuration of a power system. First of all, an overview of a renewable energy-based power system is provided with a need for the development of LFC. The basic operation was studied in single-area, multi-area and multi-stage power system configurations. Types of controllers developed on different techniques studied with an overview of different control techniques were utilized. The comparative analysis of various controllers and strategies was performed graphically. The future scope of work provided lists the potential areas for conducting further research. Finally, the paper concludes by emphasizing the need for better LFC design in complex power system environments.

This article discusses a Whale Optimization (WO) controller for design analysis, stability management, application, and performance analysis of a deregulated two-area multi-source energy system. Within the power grid, the Automatic Generation Control (AGC) maintains the power balance and strengthens the sudden frequency disturbance of the grid. Various researchers are targeted many kinds of fast-acting energy-storing devices to dampen space frequency oscillations and diversion of the tie line because of unexpected load variation. To regulate the power flow between multi-areas, load frequency control (LFC) is used by keeping frequency constant. But, to design a controller for minimizing the issues of LFC remains a challenge within the deregulated atmosphere. The main objective of the proposed methodology is to design a controller for minimizing the issues in LFC within the deregulated atmosphere. A two-area deregulated hydrothermal power system is employed to analyze many LFC problems in the deregulated power grid. During this modeling, the Thyristor-Controlled Phase Shifters (TCPS) and Capacitive Energy Storage unit (CES) are placed in the tie line and its control space. To mitigate the various issues of LFC in a two-area deregulated hydrothermal power system, the CES–TCPS combination is placed between the two control areas and the transient performance of constant is evaluated. The WO controller will increase the system power size to focus on the better performance of low-frequency management tasks. In addition, the effectiveness of the WO algorithm in tuning the proportional integral controller is also compared in a different contract (unilateral, bilateral and contract violation cases) scenarios of the proposed deregulated power system. Finally, the simulation is carried out in MATLAB/Simulink platform and the results obtained for the WO controller is compared with the normal and fuzzy PI controllers.

The load frequency control (LFC) problem has been one of the major subjects in electric power system design and operation. LFC is becoming much more significant today in accordance with increasing size, changing structure and complexity in interconnected power systems. Practice LFC systems use simple proportional-integral (PI) controllers, but parameters of PI controllers are usually tuned based on the trial-and-error approaches and they are incapable to obtain good dynamic performance under a wide range of operating conditions. For this problem, in this paper quantitative feedback theory (QFT) method is used for LFC problem. A multi-area electric power system with a wide range of parametric uncertainties is given to illustrate proposed method. To show effectiveness of proposed method, a classical PI type controller optimized by genetic algorithms (GA) is designed to compare with QFT controller. The simulation results visibly show the validity of QFT method in comparison with traditional method. Key words: Multi-area electric power system, electric power system load frequency control, robust control, quantitative feedback theory method.

Load frequency control (LFC) has recently gained importance due to the increasing integration of wind energy in contemporary power systems. Hence, several power system models, control techniques, and controllers have been developed to improve the efficiency, resilience, flexibility, and economic feasibility of LFC. Critical factors, such as energy systems, resources, optimization approaches, resilience, and transient stability have been studied to demonstrate the uniqueness of the proposed design. This paper examines the most recent advances in LFC techniques for wind-based power systems. Moreover, the use of classical, artificial intelligence, model predictive control, sliding mode control, cascade controllers, and other newly designed and adopted controllers in the LFC area is thoroughly examined. Statistical analysis and a comparison table are used to evaluate the advantages, disadvantages, and applications of various controllers. Finally, this paper presents a comprehensive overview of contemporary and other widely used soft computing tools for the LFC issue. This detailed literature review will assist researchers in overcoming the gap between current progress, application, limitations, and future developments of wind energy in LFC.

H-Infinity Loop-Shaping Controller for Load Frequency Control of a Deregulated Power System

Maintaining frequency stability in modern multi-area interconnected power systems has become increasingly challenging due to the stochastic nature of wind power and reduced effective system inertia. Under these dynamic conditions, traditional fixed-gain PID controllers frequently fail to provide robust regulation. To address this limitation, this study proposes and evaluates a practical model-free secondary control strategy for multi-area Load Frequency Control (LFC). The proposed hybrid MFAC–PID framework integrates an incremental model-free adaptive control (MFAC) law with a low-gain incremental PID damping term. This combination leverages real-time input–output data to determine primary control actions without relying on an explicit plant model, while the PID component supplies supplementary damping based on recent control errors. Furthermore, the controller utilizes online pseudo-gradient estimation to dynamically adapt to stochastic wind fluctuations and ±5% parametric uncertainty. Simulation results demonstrate that the hybrid design substantially enhances Area Control Error (ACE) regulation. Under wind-disturbed conditions, it reduces the aggregated Integral Absolute Error (IAEtotal) from 92.76 to 41.10, representing an improvement of over 50% compared with the fixed-gain PID baseline. Additionally, the controller maintains a low computational overhead of 0.306 milliseconds per control cycle. These findings indicate that the hybrid MFAC–PID structure provides a robust, computationally efficient solution for real-time Automatic Generation Control (AGC) in renewable-integrated multi-area power grids.

Electric vehicles (EVs) can be employed intelligently in Vehicle-to-Grid (V2G) and Grid-to-Vehicle (G2V) modes for Load Frequency Control (LFC) in the power grid. Due to the rapid variation of charging or discharging power, EVs can perform frequency regulation tasks and serve as distributed energy storage devices. In this paper, a linearized model of an interconnected multi-area power system is formulated in the restructured environment to include Electric Vehicle Aggregators (EVA). The DISCO Participation Matrix (DPM) is used to model Poolco and bilateral contracts in restructured multi-area power systems along with the participation of EVs. The faster dynamic response of EVs can effectively control the deviations in area frequencies imposed by the DISCOs load demand. The gains of the integral controller employed in each area are tuned by Real Coded Genetic Algorithm (RGA) by minimizing the integral square error function for area frequency deviations. The efficacy of power support from the EVs for load frequency control is validated by simulating different Poolco and bilateral transactions. It is shown that the EVs have a significant impact on obtaining optimal transient response for area frequencies, tie-line powers and power generation of conventional thermal generating units for any type of transaction in a restructured environment.

Load frequency control is one of the most important issues in multi area power systems. In this context, due to growing development of wind turbines in power systems, this type of renewable power sources can be used efficiently in frequency control. This paper applies doubly-fed induction generators (DFIGs) along with other conventional generation units for frequency performance enhancement after disturbances in multi-area power systems. Proportional integral (PI) controller is the conventional controller which is used in DFIGs to contribute in frequency control. The parameters of PI controller for DFIG are optimized by improved particle swarm optimization (IPSO) method. Simulation results in a three-area power system illustrate the efficiency of the DFIGs for frequency and tie-line power oscillations improvement.

Load frequency control (LFC) continues to be a major problem in multi-area power systems, which is compounded by communication network issues and parametric uncertainties, that degrade controller performance. In this contribution, a fuzzy H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> -iterative learning controller (FILC) is designed for decentralized LFC with little knowledge of the local power area's model and no knowledge of the external power areas' models. Further to this, time-varying communication delays, parametric variations, large disturbances, and non-identical power system area parameters are considered. The FILC strategy comprises a fuzzy strategy that quickly rejects large disturbances and drives the error to a designed tolerable band where an iterative learning control technique that is proven to be asymptotically stable with a prescribed H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance achieves zero-error convergence. The proposed FILC is compared with that of the well-known PI algorithm for a three-area power system. Results indicate that the FILC performs significantly better than the PI controller under practical combinations of network problems, overlapping large disturbances in multiple areas and parameter variations.

For an economic and reliable operation of a power system, electrical power generation-demand balance must be sustained online. In modern power systems with multiple interconnected control areas (CA), altering the generation-demand does not only affect the system frequency but also leads to undesired deviations in power flows between CAs. To avert the catastrophic failure of the entire system, generation must always balance out the load demand so as to maintain frequency and tie-line power within prescribed limit. Thus, load frequency control (LFC), achieved by adjusting the MW outputs of generators, is applied. In this paper, model predictive control (MPC) based LFC in multi-area power system (MAPS) is presented. It is aimed at maintaining frequency of each CA and tie-line power within given limits. The conventional LFC is modified to consider the effect of incremental control action, in addition to the system dynamic constraints like generation rate constraint (GRC). The effectiveness of the proposed scheme is verified through time-based simulations on 8-generator, 4-area MAPS subjected to multiple load disturbances. The responses of the system is compared with traditional PID controller. The results reveal efficacy of the proposed scheme with 26.79% and 25.12% improvement of settling time and overshoot respectively over the PID controller.

Sampled-data based discrete and fast load frequency control for power systems with wind power