LAPSE:2023.27310
Published Article

LAPSE:2023.27310
A Novel Application of Improved Marine Predators Algorithm and Particle Swarm Optimization for Solving the ORPD Problem
April 4, 2023
Abstract
The appropriate planning of electric power systems has a significant effect on the economic situation of countries. For the protection and reliability of the power system, the optimal reactive power dispatch (ORPD) problem is an essential issue. The ORPD is a non-linear, non-convex, and continuous or non-continuous optimization problem. Therefore, introducing a reliable optimizer is a challenging task to solve this optimization problem. This study proposes a robust and flexible optimization algorithm with the minimum adjustable parameters named Improved Marine Predators Algorithm and Particle Swarm Optimization (IMPAPSO) algorithm, for dealing with the non-linearity of ORPD. The IMPAPSO is evaluated using various test cases, including IEEE 30 bus, IEEE 57 bus, and IEEE 118 bus systems. An effectiveness of the proposed optimization algorithm was verified through a rigorous comparative study with other optimization methods. There was a noticeable enhancement in the electric power networks behavior when using the IMPAPSO method. Moreover, the IMPAPSO high convergence speed was an observed feature in a comparison with its peers.
The appropriate planning of electric power systems has a significant effect on the economic situation of countries. For the protection and reliability of the power system, the optimal reactive power dispatch (ORPD) problem is an essential issue. The ORPD is a non-linear, non-convex, and continuous or non-continuous optimization problem. Therefore, introducing a reliable optimizer is a challenging task to solve this optimization problem. This study proposes a robust and flexible optimization algorithm with the minimum adjustable parameters named Improved Marine Predators Algorithm and Particle Swarm Optimization (IMPAPSO) algorithm, for dealing with the non-linearity of ORPD. The IMPAPSO is evaluated using various test cases, including IEEE 30 bus, IEEE 57 bus, and IEEE 118 bus systems. An effectiveness of the proposed optimization algorithm was verified through a rigorous comparative study with other optimization methods. There was a noticeable enhancement in the electric power networks behavior when using the IMPAPSO method. Moreover, the IMPAPSO high convergence speed was an observed feature in a comparison with its peers.
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Keywords
marine predator algorithm, optimal reactive power dispatch, power losses, power system operation
Subject
Suggested Citation
Shaheen MAM, Yousri D, Fathy A, Hasanien HM, Alkuhayli A, Muyeen SM. A Novel Application of Improved Marine Predators Algorithm and Particle Swarm Optimization for Solving the ORPD Problem. (2023). LAPSE:2023.27310
Author Affiliations
Shaheen MAM: Electrical Engineering Department, Faculty of Engineering and Technology, Future University in Egypt, Cairo 11835, Egypt [ORCID]
Yousri D: Electrical Engineering Department, Faculty of Engineering, Fayoum University, Fayoum 63514, Egypt [ORCID]
Fathy A: Electrical Engineering Department, Faculty of Engineering, Jouf University, Sakakah 74331, Saudi Arabia; Electrical Power and Machine Department, Faculty of Engineering, Zagazig University, Zagazig 44519, Egypt [ORCID]
Hasanien HM: Electrical Engineering Department, Faculty of Engineering and Technology, Future University in Egypt, Cairo 11835, Egypt [ORCID]
Alkuhayli A: Department of Electrical Engineering, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia [ORCID]
Muyeen SM: School of Electrical Engineering Computing and Mathematical Sciences, Curtin University, Perth 6102, Australia
Yousri D: Electrical Engineering Department, Faculty of Engineering, Fayoum University, Fayoum 63514, Egypt [ORCID]
Fathy A: Electrical Engineering Department, Faculty of Engineering, Jouf University, Sakakah 74331, Saudi Arabia; Electrical Power and Machine Department, Faculty of Engineering, Zagazig University, Zagazig 44519, Egypt [ORCID]
Hasanien HM: Electrical Engineering Department, Faculty of Engineering and Technology, Future University in Egypt, Cairo 11835, Egypt [ORCID]
Alkuhayli A: Department of Electrical Engineering, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia [ORCID]
Muyeen SM: School of Electrical Engineering Computing and Mathematical Sciences, Curtin University, Perth 6102, Australia
Journal Name
Energies
Volume
13
Issue
21
Article Number
E5679
Year
2020
Publication Date
2020-10-30
ISSN
1996-1073
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Original Submission
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PII: en13215679, Publication Type: Journal Article
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LAPSE:2023.27310
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https://doi.org/10.3390/en13215679
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