Optimal Power Flow Using Atom Search Optimization

Abdel–Rahim, Abdel-Moamen M.; Shaaban, S. A.; Raglend, I. Jacob

doi:10.1109/i-pact44901.2019.8960024

Cited by 10 publications

(2 citation statements)

References 26 publications

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“…The detailed study and methodology and parameters is referred from (Abdel-Rahim et al, 2019;Kamel et al, 2019;Zhao et al, 2019). This algorithm can be incorporated in optimal allocation of DG/s in DSm.…”

Section: Atom Search Optimization and Methodologymentioning

confidence: 99%

Voltage Profile improvement by optimal DG allocation using atom search optimisation in radial and mesh distribution system

Tahiliani¹,

Gupta²

2022

Int. J. Eng. Sci. Tech

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Recent years have seen a considerable increase in the generation of power using renewable energy sources. This paper deals with the allocation of distributed generations (DG) in radial as well as mesh distribution network (RDSm&MDSm, respectively). The allocation of DG is been done through a meta-heuristic technique known as Atom Search Optimisation. In the paper, the power loss is reduced, along with simultaneous improvement of voltage profile of the system. The proposed algorithm has been tested on IEEE 33 & 69 radial and weakly meshed system with 5 tie lines is considered for power loss minimisation using single and multiple DGs. Two power factors are considered for the simulation 0.8 lag and 0.9 pf lag. The simulation results are carried out in MATLAB.

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Section: Atom Search Optimization and Methodologymentioning

confidence: 99%

Voltage Profile improvement by optimal DG allocation using atom search optimisation in radial and mesh distribution system

Tahiliani¹,

Gupta²

2022

Int. J. Eng. Sci. Tech

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show abstract

“…The repulsive forces allow the atoms to exploit the target region adequately, while the attractive force allows the atoms to explore the search region expansively. From Newton's second law, if c i is the constraint force of an atom, and F i is the reaction force, the acceleration with mass is represented as [39]…”

Section: E Asomentioning

confidence: 99%

Novel Manta Rays Foraging Optimization Algorithm Based Optimal Control for Grid-Connected PV Energy System

et al. 2020

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Large-scale photovoltaic system (PV) installation can affect power system operation, stability, and reliability because of the non-linear characteristic of the PV system installation. DC/AC and DC/DC converters are the major devices use in connecting PV into the grid. These converters are liable to power quality problem if the proper control mechanism is not adopted. This study presents an optimal control technique to improve dynamic operation of PV grid-connected system. An optimal control method with use of Manta ray foraging optimization (MRFO), is implemented as a control strategy for tuning the proportionalintegral (PI) controllers of DC/DC and DC/AC converters for the integration of the PV system into the grid. The MRFO is chosen because of its ease of implementation and requirement of less adjusting parameters. The effectiveness of the proposed technique is studied under irradiance variation. The obtained results demonstrate the superior performance of the MRFO over five other metaheuristic algorithms (i.e., grey wolf optimization, whale optimization, grasshopper optimization, atom search optimization, and salp swarm algorithm) in terms of convergence rate and optimal global solution capture. The entire simulation model is established using MATLAB editor and Simulink. The acquired transient result shows the functionality and viability of the MRFO approach. INDEX TERMS Optimal control; power system dynamics; MRFO optimization; PV system. NOMENCLATURE Variables Ideality constant V DC_REF Reference voltage of dc-link a i Acceleration V DC ripple Ripple voltage C Dc-link capacitor V mpp Desired maximum voltage c 1 , c 2 , c 3 , r ⃗ 1 , r ⃗ 2 Random numbers V t Array thermal voltage d Drift factor V pv Photovoltaic voltage D ⃗ ⃗⃗ , A ⃗ ⃗⃗ , C ⃗⃗ Coefficient vectors Synchronous frequency dq0 Direct-quadrature-zero X ⃗ ⃗⃗ p (k) Wolves location E d Phase voltage of direct-axis X p (t) Vector position of the prey F i Reaction force Abbreviations F ij i Interaction force f s Switching frequency

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A New Fusion of ASO with SA Algorithm and Its Applications to MLP Training and DC Motor Speed Control

et al. 2021

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Optimal Power Flow Using Atom Search Optimization

Cited by 10 publications

References 26 publications

Voltage Profile improvement by optimal DG allocation using atom search optimisation in radial and mesh distribution system

Voltage Profile improvement by optimal DG allocation using atom search optimisation in radial and mesh distribution system

Novel Manta Rays Foraging Optimization Algorithm Based Optimal Control for Grid-Connected PV Energy System

A New Fusion of ASO with SA Algorithm and Its Applications to MLP Training and DC Motor Speed Control

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