Equilibrium optimization algorithm for automatic generation control of interconnected power systems

Agwa, Ahmed M.

doi:10.15199/48.2020.09.30

Cited by 6 publications

(6 citation statements)

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“…The peak undershoots (PeUn), settling time (t sett ), and steady-state error are the descriptions of f and P t in the time-domain study to be enhanced. It was discovered that the finest criterion for all stated descriptions is the integral-time-absolute errors (ITAE) of f and P t , so Fun Obj is suggested to minimize the ITAE [22][23][24][25][26][27]:…”

Section: Swooping Phasementioning

confidence: 99%

“…Tab. 2 lists the controllers parameters constraints that are the same utilized in the compared algorithm that exists in [22][23][24][25][26][27] for fairly comparing among optimizers. The parameters of the PID and FOPID controllers based-BEO algorithm are listed in Tab.…”

Section: Case 1: System Performance Under Increasing Loadmentioning

confidence: 99%

“…In [21,22], the bacterial foraging optimizer (BFO) was implemented to fine-tune the PID controller parameters. Multiple techniques were utilized to obtain the ideal settings of PID controllers such as GA [23], grey wolf optimizer (GWO) [24], sine-cosine approach (SCA) [25], Jaya approach [26], equilibrium optimization algorithm (EOA) [27], improved Rao algorithm [28], the linear-quadratic-Gaussian technique [29]. The optimized fractional-order PID (FOPID) controller for LFC possesses excellent disturbance rejection capability and high robustness during system parameter variations [30][31][32][33].…”

Section: Introductionmentioning

confidence: 99%

“…The power rating of each zone is 2000 MW, with the nominal load being 1000 MW. This model was adopted in many studies for the design and analysis of LFC of interlinked zones [15,[22][23][24][25][26][27]. The load disturbances ( P d1 ), tie-line power error ( P t ), and the controller's output ( P ref ) are the inputs of each zone.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Optimal FOPID Controllers for LFC Including Renewables by Bald Eagle Optimizer

Agwa¹,

Abdeen²,

Shaaban³

2022

Computers, Materials &Amp; Continua

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In this study, a bald eagle optimizer (BEO) is used to get optimal parameters of the fractional-order proportional-integral-derivative (FOPID) controller for load frequency control (LFC). Since BEO takes only a very short time in finding the optimal solution, it is selected for designing the FOPID controller that improves the system stability and maintains the frequency within a satisfactory range at different loads. Simulations and demonstrations are carried out using MATLAB-R2020b. The performance of the BEO-FOPID controller is evaluated using a two-zone interlinked power system at different loads and under uncertainty of wind and solar energies. The robustness of the BEO-FOPID controller is examined by testing its performance under varying system time constants. The results obtained by the BEO-FOPID controller are compared with those obtained by BEO-PID and PID controllers based on recent metaheuristics optimization algorithms, namely the sine-cosine approach, Jaya approach, grey wolf optimizer, genetic algorithm, bacteria foraging optimizer, and equilibrium optimization algorithm. The results confirm that the BEO-FOPID controller obtains the finest result, with the lowest frequency deviation. The results also confirm that the BEO-FOPID controller is stable and robust at different loads, under varying system time constants, and under uncertainty of wind and solar energies.

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Section: Swooping Phasementioning

confidence: 99%

Section: Case 1: System Performance Under Increasing Loadmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimal FOPID Controllers for LFC Including Renewables by Bald Eagle Optimizer

Agwa¹,

Abdeen²,

Shaaban³

2022

Computers, Materials &Amp; Continua

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“…It is clear that the EO algorithm outperformed commonly used algorithms such as GA and PSO and outperformed the more recently introduced algorithms such as GSA, SSA, GWO and CMA-ES. The effectiveness and capability of EO algorithm is evaluated for various optimization problems, such as tuning of PID controller parameters for direct current (DC) motor control (Mamta and Singh, 2020), automatic generation control of interconnected power system (Agwa, 2020) and tuning PID parameters for AVR system . As EO is a newly proposed algorithm, it has been used in a limited number of studies.…”

Section: Equilibrium Optimizermentioning

confidence: 99%

A novel fractional order PID plus derivative (PI^λD^µD^µ²) controller for AVR system using equilibrium optimizer

Tabak

2021

COMPEL

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Purpose The purpose of this paper is to improve transient response and dynamic performance of automatic voltage regulator (AVR). Design/methodology/approach This paper proposes a novel fractional order proportional–integral–derivative plus derivative (PIλDµDµ2) controller called FOPIDD for AVR system. The FOPIDD controller has seven optimization parameters and the equilibrium optimizer algorithm is used for tuning of controller parameters. The utilized objective function is widely preferred in AVR systems and consists of transient response characteristics. Findings In this study, results of AVR system controlled by FOPIDD is compared with results of proportional–integral–derivative (PID), proportional–integral–derivative acceleration, PID plus second order derivative and fractional order PID controllers. FOPIDD outperforms compared controllers in terms of transient response criteria such as settling time, rise time and overshoot. Then, the frequency domain analysis is performed for the AVR system with FOPIDD controller, and the results are found satisfactory. In addition, robustness test is realized for evaluating performance of FOPIDD controller in perturbed system parameters. In robustness test, FOPIDD controller shows superior control performance. Originality/value The FOPIDD controller is introduced for the first time to improve the control performance of the AVR system. The proposed FOPIDD controller has shown superior performance on AVR systems because of having seven optimization parameters and being fractional order based.

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Gorilla troops optimization-based load frequency control in PV-thermal power system

Can,

Ayas

2023

Neural Comput & Applic

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Equilibrium optimization algorithm for automatic generation control of interconnected power systems

Cited by 6 publications

References 0 publications

Optimal FOPID Controllers for LFC Including Renewables by Bald Eagle Optimizer

Optimal FOPID Controllers for LFC Including Renewables by Bald Eagle Optimizer

A novel fractional order PID plus derivative (PI^λD^µD^µ²) controller for AVR system using equilibrium optimizer

Gorilla troops optimization-based load frequency control in PV-thermal power system

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Equilibrium optimization algorithm for automatic generation control of interconnected power systems

Cited by 6 publications

References 0 publications

Optimal FOPID Controllers for LFC Including Renewables by Bald Eagle Optimizer

Optimal FOPID Controllers for LFC Including Renewables by Bald Eagle Optimizer

A novel fractional order PID plus derivative (PIλDµDµ2) controller for AVR system using equilibrium optimizer

Gorilla troops optimization-based load frequency control in PV-thermal power system

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A novel fractional order PID plus derivative (PI^λD^µD^µ²) controller for AVR system using equilibrium optimizer