A Swarm Intelligent Metaheuristic Approach for Efficient Series Compensation Resulting in System Loadability Enhancement.
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| Title: | A Swarm Intelligent Metaheuristic Approach for Efficient Series Compensation Resulting in System Loadability Enhancement. |
|---|---|
| Authors: | Mukherjee, Debanjan1 (AUTHOR) phee170005@nitsikkim.ac.in, Mallick, Sourav2 (AUTHOR) |
| Source: | Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ). Apr2025, Vol. 50 Issue 8, p5795-5823. 29p. |
| Subjects: | Synchronous capacitors, Statistics, Self-pollination, Dynamic models, Topology |
| Abstract: | Real-life engineering issues requiring optimization are quite often discontinuous, non-linear, and non-convex in nature. For such practical problems, most of the derivative-based traditional optimization methods either fall short of providing the desired solution or do so only after easing the nonlinearities. Therefore, population-based meta-heuristic methods have been well-liked recently in handling such issues because of their derivative free nature. Although they are insensitive to problem-complexity, they may not be completely free from the local optima trapping limitation. Hence, appropriate tactic must be adopted to develop any new metaheuristic algorithm capable of addressing such issues with noticeable accuracy. In view of this, the recently developed Levy Flight motivated Adaptive Particle Swarm Optimization (APSOLF) algorithm is further modified by incorporating the Self-Pollination (SP) strategy; thereby, the SP aided APSOLF (SPAPSOLF) algorithm is proposed. This SPAPSOLF is particularly developed to apply and test in an intricate engineering problem like Firing Angle Optimization (FAO) issue. The SPAPSOLF-based-FAO aided 11-level Multilevel Inverter has been implemented in designing dynamic model of Static Synchronous Series Compensator (SSSC) and the efficacy of the SPAPSOLF is observed to be noteworthy in comparison to other state-of-the-art swarm-based metaheuristics and associated statistical analyses help to infer from this comparative investigation. Moreover, the dynamic model of SSSC using 11-level inverter is applied on model of IEEE-5-bus-system. Furthermore, remarkable enhancement in system's Maximum Loadability Limit, owing to reduced switching losses, has been noted in FAO-aided-Reduced Switch 11 level inverter-based-SSSC than SSSCs with other existing topologies. [ABSTRACT FROM AUTHOR] |
| Copyright of Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ) is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 184626564 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A Swarm Intelligent Metaheuristic Approach for Efficient Series Compensation Resulting in System Loadability Enhancement. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Mukherjee%2C+Debanjan%22">Mukherjee, Debanjan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> phee170005@nitsikkim.ac.in</i><br /><searchLink fieldCode="AR" term="%22Mallick%2C+Sourav%22">Mallick, Sourav</searchLink><relatesTo>2</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Arabian+Journal+for+Science+%26+Engineering+%28Springer+Science+%26+Business+Media+B%2EV%2E+%29%22">Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. )</searchLink>. Apr2025, Vol. 50 Issue 8, p5795-5823. 29p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Synchronous+capacitors%22">Synchronous capacitors</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Self-pollination%22">Self-pollination</searchLink><br /><searchLink fieldCode="DE" term="%22Dynamic+models%22">Dynamic models</searchLink><br /><searchLink fieldCode="DE" term="%22Topology%22">Topology</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Real-life engineering issues requiring optimization are quite often discontinuous, non-linear, and non-convex in nature. For such practical problems, most of the derivative-based traditional optimization methods either fall short of providing the desired solution or do so only after easing the nonlinearities. Therefore, population-based meta-heuristic methods have been well-liked recently in handling such issues because of their derivative free nature. Although they are insensitive to problem-complexity, they may not be completely free from the local optima trapping limitation. Hence, appropriate tactic must be adopted to develop any new metaheuristic algorithm capable of addressing such issues with noticeable accuracy. In view of this, the recently developed Levy Flight motivated Adaptive Particle Swarm Optimization (APSOLF) algorithm is further modified by incorporating the Self-Pollination (SP) strategy; thereby, the SP aided APSOLF (SPAPSOLF) algorithm is proposed. This SPAPSOLF is particularly developed to apply and test in an intricate engineering problem like Firing Angle Optimization (FAO) issue. The SPAPSOLF-based-FAO aided 11-level Multilevel Inverter has been implemented in designing dynamic model of Static Synchronous Series Compensator (SSSC) and the efficacy of the SPAPSOLF is observed to be noteworthy in comparison to other state-of-the-art swarm-based metaheuristics and associated statistical analyses help to infer from this comparative investigation. Moreover, the dynamic model of SSSC using 11-level inverter is applied on model of IEEE-5-bus-system. Furthermore, remarkable enhancement in system's Maximum Loadability Limit, owing to reduced switching losses, has been noted in FAO-aided-Reduced Switch 11 level inverter-based-SSSC than SSSCs with other existing topologies. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ) is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s13369-024-09672-5 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 29 StartPage: 5795 Subjects: – SubjectFull: Synchronous capacitors Type: general – SubjectFull: Statistics Type: general – SubjectFull: Self-pollination Type: general – SubjectFull: Dynamic models Type: general – SubjectFull: Topology Type: general Titles: – TitleFull: A Swarm Intelligent Metaheuristic Approach for Efficient Series Compensation Resulting in System Loadability Enhancement. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Mukherjee, Debanjan – PersonEntity: Name: NameFull: Mallick, Sourav IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 04 Text: Apr2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 2193567X Numbering: – Type: volume Value: 50 – Type: issue Value: 8 Titles: – TitleFull: Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ) Type: main |
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