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http://hdl.handle.net/10603/458484
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DC Field | Value | Language |
---|---|---|
dc.coverage.spatial | Power quality enhancement between two adjacent feeders using ai based interline dynamic voltage restorer | |
dc.date.accessioned | 2023-02-16T05:54:07Z | - |
dc.date.available | 2023-02-16T05:54:07Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/458484 | - |
dc.description.abstract | Enhancing distribution systems execution has turned into a critical newlineissue because of extensive increment in electrical power consumption in recent newlineyears. Voltage fluctuations, frequently as voltage sags, can cause extreme newlineprocess disturbances and result in generous monetary misfortune. Interline newlineDynamic Voltage Restorer (IDVR) is constantly utilized in distribution systems newlineto moderate voltage sag/swell issues. An IDVR generally comprises several newlineDynamic Voltage Restorers (DVRs) sharing a typical DC interface associating newlineautonomous feeders to secure electric power to basic loads. While one of the newlineDVRs makes up for the neighbourhood voltage sag in its feeder, alternate DVRs newlinerecharge the normal DC-connect voltage. This research work proposes a novel newlinecontrol strategy based on interline dynamic voltage restorer to improve the newlinepower quality between the two adjacent feeders in a distribution system. The newlineIDVR is an interconnected form of multi dynamic voltage restorer with a newlinecommon share of DC link. newlineArtificial Intelligence (AI) based control strategy is proposed in this newlinethesis to quickly solve the power quality issues such as voltage sag, voltage newlineswell and harmonics. The Fractional Order PID (FOPID) controller optimized newlineusing Gravitational Search algorithm (GSA) is implemented in IDVR system. As newlinea novelty, Whale Optimization Algorithm (WOA) is proposed here to improve newlinethe performance of the IDVR. The architecture, control strategy and newlineperformance of the whale optimized interline dynamic voltage restorer is newlineanalyzed in the research work. The effectiveness of the proposed whale newlineoptimized IDVR system is verified through the comparative analysis with the newlineconventional optimization algorithms such as Ant Lion Optimizer (ALO) and newlineParticle Swarm Optimization (PSO). The unabridged working of the proposed newlinetechnique has implemented in Mat lab/Simulink and the results are verified. newline | |
dc.format.extent | xiv,150p. | |
dc.language | English | |
dc.relation | p.137-149 | |
dc.rights | university | |
dc.title | Power quality enhancement between two adjacent feeders using ai based interline dynamic voltage restorer | |
dc.title.alternative | ||
dc.creator.researcher | Sarojini Devi M | |
dc.subject.keyword | Power Quality | |
dc.subject.keyword | Dynamic Voltage Restorer | |
dc.subject.keyword | Artificial Intelligence | |
dc.description.note | ||
dc.contributor.guide | Suresh Kumar V | |
dc.publisher.place | Chennai | |
dc.publisher.university | Anna University | |
dc.publisher.institution | Faculty of Electrical Engineering | |
dc.date.registered | ||
dc.date.completed | 2021 | |
dc.date.awarded | 2021 | |
dc.format.dimensions | 21cm | |
dc.format.accompanyingmaterial | None | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Faculty of Electrical Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 32.42 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 1.11 MB | Adobe PDF | View/Open | |
03_content.pdf | 11.8 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 4.3 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 396.2 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 211.58 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 703.81 kB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 728.09 kB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 463.1 kB | Adobe PDF | View/Open | |
10_chapter 6.pdf | 270.53 kB | Adobe PDF | View/Open | |
11_annexures.pdf | 157.57 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 78.64 kB | Adobe PDF | View/Open |
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