Application of grey wolf optimization algorithm for load frequency control in multi-source single area power system

Paliwal, Nikhil; Srivastava, Laxmi; Pandit, Manjaree

doi:10.1007/s12065-020-00530-5

Cited by 61 publications

(25 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As a consequence, choosing an appropriate optimization technique in the design procedure of the controller is a basic and crucial challenge. Classical optimization procedures were previously utilized to find the best frequency controller settings [18,33]. Additionally, ref.…”

Section: Literature Reviewmentioning

confidence: 99%

“…These algorithms, however, face several difficulties, including slumps, deathtraps in local minimums, the demand for several iterations, and reliance on initial conditions for selecting the optimal settings. As a result, scholars overcame these obstacles by improving meta-heuristic optimization methods, such as the grey wolf optimizer [33], particle swarm optimization [35], ant lion optimization [36], chimp optimization algorithm [5], teaching-learning-based optimization [37], moth-flame optimization [11], equilibrium optimization [38], and atom search optimization [39]. Substantial emphasis has been placed on the use of various optimization techniques to assist them in tackling technical difficulties, particularly the load frequency control issue.…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Robust Control of Frequency Variations for a Multi-Area Power System in Smart Grid Using a Newly Wild Horse Optimized Combination of PIDD2 and PD Controllers

Khudhair¹,

Ragab

AboRas

et al. 2022

Sustainability

View full text Add to dashboard Cite

This paper proposes a new combined controller, the proportional integral derivative-second derivative with a proportional derivative (PIDD2-PD), to improve the frequency response of a multi-area interconnected power system with multiple generating units linked to it. The optimum gains of the presented controller are well-tuned using a wild horse optimizer (WHO), a modern metaheuristic optimization approach. The main study is a two-area-linked power system with varied conventional and renewable generating units. The physical constraints of the speed turbines and governors are considered. The WHO optimization algorithm is proven to outperform various other optimization approaches, such as the whale optimization algorithms (WOA) and chimp optimization algorithms (ChOA). The efficacy of the proposed WHO-based PIDD2-PD controller is evaluated by comparing its performance to other controllers in the literature (cascaded proportional integral derivative-tilted integral derivative (PID-TID), integral derivative-tilted (ID-T) controller). Multiple and varied scenarios are applied in this work to test the proposed controller’s sturdiness to various load perturbations (step, random, and multi-step), renewable energy source penetration, and system parameter variations. The results are provided as time-domain simulations run using MATLAB/SIMULINK. The simulation results reveal that the suggested controller outperforms other structural controllers in the dynamic response of the system in terms of settling time, maximum overshoot, and undershoot values, with an improvement percentage of 70%, 73%, and 67%, respectively.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Robust Control of Frequency Variations for a Multi-Area Power System in Smart Grid Using a Newly Wild Horse Optimized Combination of PIDD2 and PD Controllers

Khudhair¹,

Ragab

AboRas

et al. 2022

Sustainability

View full text Add to dashboard Cite

show abstract

“…The Friedman test is a nonparametric analogue of the parametric two-way ANOVA. [87][88][89] The original results are converted into ranks as the first step in calculating the test statistic. In this statistical test, the performance of the Rao algorithm has been compared with widely used benchmark Genetic Algorithm, 90,91 Particle Swarm Optimization algorithm 46,64 and sine cosine algorithm.…”

Section: Statistical Test Of the Rao Algorithm In Tuning The Mfopid C...mentioning

confidence: 99%

Rao algorithm based optimal Multi‐term FOPID controller for automatic voltage regulator system

Paliwal¹,

Srivastava²,

Pandit³

2022

Optim Control Appl Methods

View full text Add to dashboard Cite

This article presents a novel application of an optimal Multi‐term Fractional‐Order PID (MFOPID) controller for improving the performance of the automatic voltage regulator (AVR) system. A recently developed Rao algorithm has been used to optimize the proposed Multi‐term FOPID controller. The effectiveness of the Rao algorithm tuned Multi‐term FOPID controller for the AVR system has been proved by performing transient response, robustness, and performance analyses. Statistical analysis of the proposed Multi‐term FOPID controlled AVR system has been carried out to explore the most effective performance index among ITAE, ITSE, ISE, and IAE. The external disturbance rejection capability of the Rao algorithm‐tuned MFOPID controller has been examined by injecting external disturbances into the AVR system of different capacities at different times. The superiority of the proposed Multi‐term FOPID controller is validated by comparing the simulation results with recently employed various PID, PID‐Acceleration (PIDA), and FOPID controllers tuned by different metaheuristic algorithms. In addition, the behavior of the proposed Multi‐term FOPID controller has been examined in a real synchronous generator that is connected to a 10,000 MVA, 230 kV electric power network via a 210 MVA transformer using a MATLAB/Simulink environment. From the various simulation results, it has been concluded that the proposed Rao algorithm tuned optimal and robust Multi‐term FOPID controller has significantly improved the performance, robustness and stability of the AVR system.

show abstract

“…There are four performance indices namely integral of absolute error (IAE), integral of time‐weighted squared error (ITSE), integral of time‐weighted absolute error (ITAE), and integral of square error (ISE) 21,92 . These performance indices may be employed as an objective function in a straight forward manner, and there is no need to set any weighting factors.…”

Section: Formulation Of Objective Functionmentioning

confidence: 99%

Equilibrium optimizer tuned novel FOPID‐DN controller for automatic voltage regulator system

Paliwal

Srivastava

Pandit

2021

Int Trans Electr Energ Syst

Self Cite

View full text Add to dashboard Cite

Summary This paper presents a novel fractional‐order PID plus derivative with filter coefficient (FOPID‐DN) controller for automatic voltage regulator (AVR) system using the MATLAB/Simulink environment. An AVR system is employed in the power system to maintain the terminal voltage at the desired level. Parameters of the proposed FOPID‐DN controller are optimally tuned by the recently developed Equilibrium Optimizer (EO) algorithm. Performance of the designed FOPID‐DN controller for an AVR system is compared with various controllers which are optimally tuned by different optimization algorithms. Comparative transient response analysis of the proposed technique has been carried out by considering vital transient response indicators like maximum overshoot, rise time, and settling time. Performance analysis of the proposed technique for an AVR system has been done by considering several input conditions. Robustness analysis of the EO algorithm tuned FOPID‐DN controller has been performed by varying the time constants of different components in an AVR system. The capability of the FOPID‐DN controller to handle nonlinearities of an AVR system has been investigated. The stability of the FOPID‐DN controlled AVR system has been analyzed. In addition, the disturbance rejection capability of the FOPID‐DN controlled AVR system has also been investigated. From the various simulation results obtained using the MATLAB/Simulink environment, it has been observed that the proposed FOPID‐DN‐based AVR system provided better performance as compared to different existing controllers.

show abstract

Application of grey wolf optimization algorithm for load frequency control in multi-source single area power system

Cited by 61 publications

References 43 publications

Robust Control of Frequency Variations for a Multi-Area Power System in Smart Grid Using a Newly Wild Horse Optimized Combination of PIDD2 and PD Controllers

Robust Control of Frequency Variations for a Multi-Area Power System in Smart Grid Using a Newly Wild Horse Optimized Combination of PIDD2 and PD Controllers

Rao algorithm based optimal Multi‐term FOPID controller for automatic voltage regulator system

Equilibrium optimizer tuned novel FOPID‐DN controller for automatic voltage regulator system

Contact Info

Product

Resources

About