Enhancing power system stability through intelligent STATCOM control strategies in torsional oscillation environments.
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| Title: | Enhancing power system stability through intelligent STATCOM control strategies in torsional oscillation environments. |
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| Authors: | BAMBA, Sangeeta1 20001902005sangeetabamba@dcrustm.org, GUPTA, Sushil Kumar1 |
| Source: | Sigma: Journal of Engineering & Natural Sciences / Mühendislik ve Fen Bilimleri Dergisi. Dec2024, Vol. 42 Issue 6, p1933-1953. 21p. |
| Subjects: | Grey Wolf Optimizer algorithm, Synchronous capacitors, Rotor dynamics, Particle swarm optimization, Induction generators |
| Abstract: | This research develops a new control method for the IEEE Second benchmark model (SBM) that uses an intelligent optimization-based static synchronous compensator to reduce low-frequency torsional oscillations. This low-frequency oscillation caused by mainly shunt and series compensation produces torsional oscillation and induction generator effect in a synchronous generator that may lead to fatigue in the shaft and continuation of low-frequency oscillations for a long duration. To minimize this effect, various techniques have been applied. The Static Synchronous Compensator›s gate signal is managed by the control strategy using two distinct proportional-integral (PI) controllers in accordance with system voltage. The test system is subjected to a three-phase LLL-G fault with zero inherent dampening considered to simulate the most severe situation, with natural damping for comparative analysis. The time-domain outcomes of the rotor dynamics for different test scenarios with and without the Static Synchronous Compensator and with the proposed PSO (Particle swarm optimization), FF (Firefly algorithm), and GWO (Grey Wolf Optimizer) Optimization-based Static Synchronous Compensator (STATCOM). The efficiency of the proposed controller in reducing overall power system oscillations is demonstrated using optimization-based STATCOM. The proposed study demonstrates the superiority of the GWO optimization technique over FF, PSO, and standard STATCOM in terms of settling time. This is evidenced by comparing the simulation results, including the performance index. [ABSTRACT FROM AUTHOR] |
| Copyright of Sigma: Journal of Engineering & Natural Sciences / Mühendislik ve Fen Bilimleri Dergisi is the property of Sigma: Journal of Engineering & Natural Sciences / Mühendislik ve Fen Bilimleri Dergisi 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 |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 181637427 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Enhancing power system stability through intelligent STATCOM control strategies in torsional oscillation environments. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22BAMBA%2C+Sangeeta%22">BAMBA, Sangeeta</searchLink><relatesTo>1</relatesTo><i> 20001902005sangeetabamba@dcrustm.org</i><br /><searchLink fieldCode="AR" term="%22GUPTA%2C+Sushil+Kumar%22">GUPTA, Sushil Kumar</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Sigma%3A+Journal+of+Engineering+%26+Natural+Sciences+%2F+Mühendislik+ve+Fen+Bilimleri+Dergisi%22">Sigma: Journal of Engineering & Natural Sciences / Mühendislik ve Fen Bilimleri Dergisi</searchLink>. Dec2024, Vol. 42 Issue 6, p1933-1953. 21p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Grey+Wolf+Optimizer+algorithm%22">Grey Wolf Optimizer algorithm</searchLink><br /><searchLink fieldCode="DE" term="%22Synchronous+capacitors%22">Synchronous capacitors</searchLink><br /><searchLink fieldCode="DE" term="%22Rotor+dynamics%22">Rotor dynamics</searchLink><br /><searchLink fieldCode="DE" term="%22Particle+swarm+optimization%22">Particle swarm optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Induction+generators%22">Induction generators</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This research develops a new control method for the IEEE Second benchmark model (SBM) that uses an intelligent optimization-based static synchronous compensator to reduce low-frequency torsional oscillations. This low-frequency oscillation caused by mainly shunt and series compensation produces torsional oscillation and induction generator effect in a synchronous generator that may lead to fatigue in the shaft and continuation of low-frequency oscillations for a long duration. To minimize this effect, various techniques have been applied. The Static Synchronous Compensator›s gate signal is managed by the control strategy using two distinct proportional-integral (PI) controllers in accordance with system voltage. The test system is subjected to a three-phase LLL-G fault with zero inherent dampening considered to simulate the most severe situation, with natural damping for comparative analysis. The time-domain outcomes of the rotor dynamics for different test scenarios with and without the Static Synchronous Compensator and with the proposed PSO (Particle swarm optimization), FF (Firefly algorithm), and GWO (Grey Wolf Optimizer) Optimization-based Static Synchronous Compensator (STATCOM). The efficiency of the proposed controller in reducing overall power system oscillations is demonstrated using optimization-based STATCOM. The proposed study demonstrates the superiority of the GWO optimization technique over FF, PSO, and standard STATCOM in terms of settling time. This is evidenced by comparing the simulation results, including the performance index. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Sigma: Journal of Engineering & Natural Sciences / Mühendislik ve Fen Bilimleri Dergisi is the property of Sigma: Journal of Engineering & Natural Sciences / Mühendislik ve Fen Bilimleri Dergisi 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: 10.14744/sigma.2024.00102 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 21 StartPage: 1933 Subjects: – SubjectFull: Grey Wolf Optimizer algorithm Type: general – SubjectFull: Synchronous capacitors Type: general – SubjectFull: Rotor dynamics Type: general – SubjectFull: Particle swarm optimization Type: general – SubjectFull: Induction generators Type: general Titles: – TitleFull: Enhancing power system stability through intelligent STATCOM control strategies in torsional oscillation environments. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: BAMBA, Sangeeta – PersonEntity: Name: NameFull: GUPTA, Sushil Kumar IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 13047191 Numbering: – Type: volume Value: 42 – Type: issue Value: 6 Titles: – TitleFull: Sigma: Journal of Engineering & Natural Sciences / Mühendislik ve Fen Bilimleri Dergisi Type: main |
| ResultId | 1 |
