A new method for optimization of Load Frequency Control parameters in multi-area power systems using Genetic Algorithms

Rasolomampionona, Désiré; Kłos, M.; Cirit, Can; Montegiglio, Pasquale; Tuglie, E. De

doi:10.1109/eeeic/icpseurope54979.2022.9854535

Cited by 7 publications

(7 citation statements)

References 26 publications

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“…However, it is necessary to consider other parameters to create the models as precisely as possible. For this purpose, physical constraints such as the GDB, the GRC, and the delay in the communication links must be imposed to demonstrate these constraints' effect on the AGC performance [283]. Using this procedure, one can evaluate the model most accurately.…”

Section: Genetic Algorithms (Gas)mentioning

confidence: 99%

“…Thus, one must use intelligent data-driven methods such as GAs, fuzzy logic controllers, and neural networks to solve optimization problems. Therefore, the authors of [283] used GA as an optimization technique to tune the controller gains in this paper. The results showed that to stabilize the performance of LFC, using GA as an additional tool to optimize LFC parameters is a valuable method [283].…”

Section: Genetic Algorithms (Gas)mentioning

confidence: 99%

“…Therefore, the authors of [283] used GA as an optimization technique to tune the controller gains in this paper. The results showed that to stabilize the performance of LFC, using GA as an additional tool to optimize LFC parameters is a valuable method [283].…”

Section: Genetic Algorithms (Gas)mentioning

confidence: 99%

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A Comprehensive Review of Load Frequency Control Technologies

Rasolomampionona,

Połecki,

Zagrajek

et al. 2024

Energies

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Load frequency control (LFC) is one of the most important tools in power system control. LFC is an auxiliary service related to the short-term balance of energy and frequency of power systems. As such, it allows the acquisition of a central role in enabling electricity exchanges and providing better conditions. The classification of LFC can be carried out from different angles: we can enumerate, among others, the type of control used. The following types of control are presented in this review: classical, optimal, and robust control. More advanced controls can also be used for classification: fuzzy logic control, ANN control, genetic algorithms, PSO control, etc. The influence of renewables and power control tools like FACTS is also considered as a category to be analyzed. The last classifications are related to two important subjects—the influence of DC links on LFC efficiency and the dangers of cyberattacks on the LFC.

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Section: Genetic Algorithms (Gas)mentioning

confidence: 99%

Section: Genetic Algorithms (Gas)mentioning

confidence: 99%

See 1 more Smart Citation

A Comprehensive Review of Load Frequency Control Technologies

Rasolomampionona,

Połecki,

Zagrajek

et al. 2024

Energies

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“…The GA is an intelligent optimization algorithm that is used to find an optimal solution for a given problem by maximizing or minimizing a particular cost function. At every iteration, GA calculates the best f (x) value and the mean f (x) value of the specified fitness function, and these values are targeted to be minimized in each successive generation [47,48]. In this paper, GA optimization is performed offline to find the optimal parameters of the delay-based ADRC shown in Figure 2.…”

Section: Optimizing the Controller Parameters Using Gamentioning

confidence: 99%

Predictive Extended State Observer-Based Active Disturbance Rejection Control for Systems with Time Delay

Nahri

Wyk

2023

Machines

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The latest research on disturbance rejection mechanisms has shown active disturbance rejection control (ADRC) to be an effective controller for uncertainties and nonlinear dynamics em-bedded in systems to be controlled. The significance of the ADRC controller is its model-free nature, as it requires minimal knowledge of the system model. In addition, it can actively estimate and compensate for the impact of internal and external disturbances present, with the aid of its crucial subsystem called the extended state observer (ESO). However, ADRC controller design becomes more challenging owing to different system disturbances, such as output disturbances, measure-ment noise, and varying time-delays persistent in the system’s communication channels. Most dis-turbance rejection techniques aim to reduce internal perturbations and external disturbances (input and output disturbance). However, output disturbance rejection with measurement noise under time-delay control is still a challenging problem. This paper presents a novel predictive ESO-based ADRC controller for time-delay systems by employing predictive methods to compensate for the disturbances originating from time delay. The prediction mechanism of the novel (proposed) con-troller design is greatly attributed to the extended state predictor observer (ESPO) integrated with the delay-based ADRC inside the proposed controller method. Thus, the proposed controller can predict the unknown system dynamics generated during the delay and compensate for these dy-namics via disturbance rejection under time-delay control. This approach uses the optimization mechanism to determine controller parameters, where the genetic algorithm (GA) is employed with the integral of time-weighted absolute error (ITAE) as the fitness function. The proposed controller is validated by controlling second-order systems with time delay. Type 0, Type 1, and Type 2 sys-tems are considered as the controlled plants, with disturbances (unknown dynamics due to delay and external disturbance), along with measurement noise present. The proposed controller method is compared with state-of-the-art methods, such as the modified time-delay-based ADRC method and the ESPO-based controller method. The findings indicate that the method proposed in this pa-per outperforms its existing competitors by compensating for the dynamics during the time delay and shows robust behaviour, improved disturbance rejection, and a fair extent of resilience to noise.

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“…However, it is essential for understanding the system's behavior and designing effective control strategies. Fuzzy logic controllers can be used to approximate and simplify the control logic required for AGC/LFC without relying on a highly detailed mathematical model (Rasolomampionona et al, 2022). Load Frequency Control (LFC) plays a critical role in maintaining the stability and reliability of electric power systems by ensuring that the system frequency remains close to the desired nominal value .…”

Section: Introductionmentioning

confidence: 99%

Analysis of Load Frequency Control of Two Area Power System using Different Control Techniques

Kaisher,

Rahman,

Md Moniruzzaman

et al. 2024

IUBAT Rev.

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To maintain stability is a mandatory requirement of any kind of power network. Interconnected power systems have significant advantages in maintaining stability and frequency at their nominal values. The control of the interconnected power systems is performed by Automatic Generation Control (AGC), which has two parts: the Automatic Voltage Regulator (AVR) and Load Frequency Control (LFC). When a disturbance occurs in the system, Load Frequency Control (LFC) acts to re-establish the system into its steady state with zero error as well as the desired transient response characteristics. This paper exhibits the design and implementation of a PID and Fuzzy Logic Controller for two area power systems, taking the steady state error and percentage of overshoot, undershoot, and pre-shoot as comparison parameters. MATLAB/Simulink software was used to bring out the implementation and obtain results. System dynamic performance is observed for PID and Fuzzy Logic Controllers in Simulink. The comparison study indicated that the proposed Fuzzy Logic controller has better performance than the PID controller. IUBAT Review—A Multidisciplinary Academic Journal, 7(1): 62-79

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A new method for optimization of Load Frequency Control parameters in multi-area power systems using Genetic Algorithms

Cited by 7 publications

References 26 publications

A Comprehensive Review of Load Frequency Control Technologies

A Comprehensive Review of Load Frequency Control Technologies

Predictive Extended State Observer-Based Active Disturbance Rejection Control for Systems with Time Delay

Analysis of Load Frequency Control of Two Area Power System using Different Control Techniques

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