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http://hdl.handle.net/10603/423173
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DC Field | Value | Language |
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dc.coverage.spatial | ||
dc.date.accessioned | 2022-12-08T12:15:27Z | - |
dc.date.available | 2022-12-08T12:15:27Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/423173 | - |
dc.description.abstract | A microgrid is equipped with variants of distributed energy resources offering a challenging situation to power engineers to maintain the power quality during its operation. So, monitoring and maintaining power quality is a critical issue for healthy operation of microgrid system up to consumer satisfaction. From the outcome of comprehensive literature review, it has been found that a decision-making methodology is required to assess the power quality of an AC microgrid through assessment of power quality-related electrical parameters such as voltage, frequency, power factor, total harmonic distortion (THD) etc. Hence, a decision making methodology is proposed to quantify the fuzziness in random variation of power quality. In this context, one of the major contributions of this research work is introduction of a power quality monitoring index (PQMI) which has been proposed using 256 rule-based fuzzy inference system (FIS) tested single-phase, as well as three-phase AC microgrid model. The results show the effectiveness of the proposed methodology to assess the status of PQMI, depending upon the acceptable limits of above mentioned electrical parameters, operating in grid-connected or islanded mode. The proposed methodology is verified through Mamdani and Sugeno type FIS using MATLAB-Simulink software. It is also found that the proposed PQMI is significant to define the status of microgrid even during transition from grid-connected to islanded mode and vice-versa. In this research work, it has been found that the battery energy storage (BES), intelligent protection and power quality are considered as independent issues, but these three factors can be interlinked effectively for control of microgrid through automated demand side management (ADSM). In this context, the proposed approach may change the conventional way for microgrid operation and control giving priority to the power quality issues considering protection and BES systems. | |
dc.format.extent | xvii, 148p. | |
dc.language | English | |
dc.relation | ||
dc.rights | university | |
dc.title | Design and Control of Microgrid System for Optimum Operation | |
dc.title.alternative | ||
dc.creator.researcher | Jitender | |
dc.subject.keyword | Engineering | |
dc.subject.keyword | Engineering and Technology | |
dc.subject.keyword | Engineering Electrical and Electronic | |
dc.subject.keyword | Neural networks (Computer science) | |
dc.description.note | ||
dc.contributor.guide | Basak, Prasenjit | |
dc.publisher.place | Patiala | |
dc.publisher.university | Thapar Institute of Engineering and Technology | |
dc.publisher.institution | Department of Electrical and Instrumentation Engineering | |
dc.date.registered | ||
dc.date.completed | 2021 | |
dc.date.awarded | 2021 | |
dc.format.dimensions | ||
dc.format.accompanyingmaterial | None | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Department of Electrical and Instrumentation Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 34.18 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 478.56 kB | Adobe PDF | View/Open | |
03_content.pdf | 31.18 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 23.3 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 60.61 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 89.38 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 1.05 MB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 3.44 MB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 2.55 MB | Adobe PDF | View/Open | |
10_chapter 6.pdf | 2.43 MB | Adobe PDF | View/Open | |
11_chapter 7.pdf | 35.73 kB | Adobe PDF | View/Open | |
12_annexures.pdf | 162.28 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 65.27 kB | Adobe PDF | View/Open |
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