Improved Salp Swarm Optimization Algorithm for Damping Controller Design for Multimachine Power System
This paper proposes an improved salp swarm algorithm (ISSA) as an effective metaheuristic method for tackling global optimization issues and damping power system oscillations. In the suggested ISSA, new equations are introduced to update the location of the leader and followers. This modification im...
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9851660/ |
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| author | Ehsan Akbari Morteza Mollajafari Hamza Mohammed Ridha Al-Khafaji Hussein Alkattan Mostafa Abotaleb Mahdiyeh Eslami Sivaprakasam Palani |
| author_facet | Ehsan Akbari Morteza Mollajafari Hamza Mohammed Ridha Al-Khafaji Hussein Alkattan Mostafa Abotaleb Mahdiyeh Eslami Sivaprakasam Palani |
| author_sort | Ehsan Akbari |
| collection | DOAJ |
| description | This paper proposes an improved salp swarm algorithm (ISSA) as an effective metaheuristic method for tackling global optimization issues and damping power system oscillations. In the suggested ISSA, new equations are introduced to update the location of the leader and followers. This modification improves the method’s exploration possibilities while also preventing it from converging prematurely. Benchmark test functions are used to confirm the proposed algorithm’s performance, and the results are compared to SSA and other effective optimization algorithms. According to the extensive comparisons, the enhanced ISSA algorithm has higher convergence accuracy and stability than the original SSA and other researched algorithms. Furthermore, the feasibility and efficiency of the proposed method were demonstrated by the simultaneous coordinated design of UPFC based damping controllers. For the two-area, four-machine system, the experimental findings are provided. Simulation experiments reveal that ISSA designed controllers outperform those created using other methods. |
| first_indexed | 2024-12-10T16:25:51Z |
| format | Article |
| id | doaj.art-717824c381cf448697118a077109b2d7 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-10T16:25:51Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-717824c381cf448697118a077109b2d72022-12-22T01:41:40ZengIEEEIEEE Access2169-35362022-01-0110829108292210.1109/ACCESS.2022.31968519851660Improved Salp Swarm Optimization Algorithm for Damping Controller Design for Multimachine Power SystemEhsan Akbari0https://orcid.org/0000-0002-5318-5673Morteza Mollajafari1https://orcid.org/0000-0002-2717-6335Hamza Mohammed Ridha Al-Khafaji2https://orcid.org/0000-0003-3620-581XHussein Alkattan3Mostafa Abotaleb4Mahdiyeh Eslami5https://orcid.org/0000-0003-1174-1595Sivaprakasam Palani6https://orcid.org/0000-0001-8082-8649Department of Electrical Engineering, Mazandaran University of Science and Technology, Babol, IranSchool of Automotive Engineering, Iran University of Science and Technology, Tehran, IranBiomedical Engineering Department, Al-Mustaqbal University College, Hillah, IraqDepartment of System Programming, South Ural State University, Chelyabinsk, RussiaDepartment of System Programming, South Ural State University, Chelyabinsk, RussiaDepartment of Electrical Engineering, Kerman Branch, Islamic Azad University, Kerman, IranCollege of Electrical and Mechanical Engineering, Addis Ababa Science and Technology University, Addis Ababa, EthiopiaThis paper proposes an improved salp swarm algorithm (ISSA) as an effective metaheuristic method for tackling global optimization issues and damping power system oscillations. In the suggested ISSA, new equations are introduced to update the location of the leader and followers. This modification improves the method’s exploration possibilities while also preventing it from converging prematurely. Benchmark test functions are used to confirm the proposed algorithm’s performance, and the results are compared to SSA and other effective optimization algorithms. According to the extensive comparisons, the enhanced ISSA algorithm has higher convergence accuracy and stability than the original SSA and other researched algorithms. Furthermore, the feasibility and efficiency of the proposed method were demonstrated by the simultaneous coordinated design of UPFC based damping controllers. For the two-area, four-machine system, the experimental findings are provided. Simulation experiments reveal that ISSA designed controllers outperform those created using other methods.https://ieeexplore.ieee.org/document/9851660/DampingUPFCsalp swarm optimizerstability |
| spellingShingle | Ehsan Akbari Morteza Mollajafari Hamza Mohammed Ridha Al-Khafaji Hussein Alkattan Mostafa Abotaleb Mahdiyeh Eslami Sivaprakasam Palani Improved Salp Swarm Optimization Algorithm for Damping Controller Design for Multimachine Power System IEEE Access Damping UPFC salp swarm optimizer stability |
| title | Improved Salp Swarm Optimization Algorithm for Damping Controller Design for Multimachine Power System |
| title_full | Improved Salp Swarm Optimization Algorithm for Damping Controller Design for Multimachine Power System |
| title_fullStr | Improved Salp Swarm Optimization Algorithm for Damping Controller Design for Multimachine Power System |
| title_full_unstemmed | Improved Salp Swarm Optimization Algorithm for Damping Controller Design for Multimachine Power System |
| title_short | Improved Salp Swarm Optimization Algorithm for Damping Controller Design for Multimachine Power System |
| title_sort | improved salp swarm optimization algorithm for damping controller design for multimachine power system |
| topic | Damping UPFC salp swarm optimizer stability |
| url | https://ieeexplore.ieee.org/document/9851660/ |
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