Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
Application of differential evolution to power system stabilizer design
Includes synopsis.
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
Department of Electrical Engineering
2015
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
| _version_ | 1867613334442868736 |
|---|---|
| access_status_str | Open Access |
| author | Mulumba, Tshina Fa |
| author2 | Folly, Komla A |
| author_browse | Folly, Komla A Mulumba, Tshina Fa |
| author_facet | Folly, Komla A Mulumba, Tshina Fa |
| author_sort | Mulumba, Tshina Fa |
| collection | Thesis |
| description | Includes synopsis. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/12026 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:34:28.941Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2015 |
| publishDateRange | 2015 |
| publishDateSort | 2015 |
| publisher | Department of Electrical Engineering |
| publisherStr | Department of Electrical Engineering |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/12026 Application of differential evolution to power system stabilizer design Mulumba, Tshina Fa Folly, Komla A Electrical Engineering Includes synopsis. Includes bibliographical references. In recent years, many Evolutionary Algorithms (EAs) such as Genetic Algorithms (GAs) have been proposed to optimally tune the parameters of the PSS. GAs are population based search methods inspired by the mechanism of evolution and natural genetic. Despite the fact that GAs are robust and have given promising results in many applications, they still have some drawbacks. Some of these drawbacks are related to the problem of genetic drift in GA which restricts the diversity in the population. ... To cope with the above mentioned drawbacks, many variants of GAs have been proposed often tailored to a particular problem. Recently, several simpler and yet effective heuristic algorithms such as Population Based Incremental Learning (PBIL) and Differential Evolution (DE), etc., have received increasing attention. 2015-01-11T04:42:40Z 2015-01-11T04:42:40Z 2012 Master Thesis Masters MSc http://hdl.handle.net/11427/12026 eng application/pdf Department of Electrical Engineering Faculty of Engineering and the Built Environment University of Cape Town |
| spellingShingle | Electrical Engineering Mulumba, Tshina Fa Application of differential evolution to power system stabilizer design |
| thesis_degree_str | Master's |
| title | Application of differential evolution to power system stabilizer design |
| title_full | Application of differential evolution to power system stabilizer design |
| title_fullStr | Application of differential evolution to power system stabilizer design |
| title_full_unstemmed | Application of differential evolution to power system stabilizer design |
| title_short | Application of differential evolution to power system stabilizer design |
| title_sort | application of differential evolution to power system stabilizer design |
| topic | Electrical Engineering |
| url | http://hdl.handle.net/11427/12026 |
| work_keys_str_mv | AT mulumbatshinafa applicationofdifferentialevolutiontopowersystemstabilizerdesign |