Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/519991
Title: | Analysis of reconfigured distribution network with distributed generation integration |
Researcher: | Arun Kumar S |
Guide(s): | Padma S |
Keywords: | Distributed Generation (DG) Engineering Engineering and Technology Engineering Electrical and Electronic Power Generation PSOGA |
University: | Anna University |
Completed Date: | 2023 |
Abstract: | newline The distribution system connects the power system to the consumers. Increased power generation is a result of rising population and growing demand for electricity. When electricity producing capacity is increased, the capital cost rises dramatically, resulting in a complex distribution system. Distribution losses are significant, when compared to power losses in transmission systems. It demands distribution system automation in order to improve reliability, power quality, and efficiency. So Meta-heuristic algorithms are preferred for solving specific optimization issues. As a result, Particle Swarm Optimization Genetic Algorithm (PSOGA) was used as the optimization algorithm in this study. |
Pagination: | xvi, 120 p. |
URI: | http://hdl.handle.net/10603/519991 |
Appears in Departments: | Faculty of Electrical Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 29.04 kB | Adobe PDF | View/Open |
02_prelim_pages.pdf | 2.44 MB | Adobe PDF | View/Open | |
03_contents.pdf | 28.3 kB | Adobe PDF | View/Open | |
04_abstracts.pdf | 76.87 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 476.12 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 128.25 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 479.18 kB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 364.03 kB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 262.82 kB | Adobe PDF | View/Open | |
10_chapter 6.pdf | 420.21 kB | Adobe PDF | View/Open | |
11_annexures.pdf | 108.36 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 90.01 kB | Adobe PDF | View/Open |
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