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Multi-objective optimization techniques in electricity generation planning
The objective of this research is to develop a framework of multi-objective optimization (MOO) models that are better capable of providing decision support on future long-term electricity generation planning (EGP), in the context of insufficient electricity capacity and to apply it to the electricit...
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
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Department of Statistical Sciences
2014
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| _version_ | 1867613163643469824 |
|---|---|
| access_status_str | Open Access |
| author | Tuyiragize, Richard |
| author2 | Stewart, Theodor J |
| author_browse | Stewart, Theodor J Tuyiragize, Richard |
| author_facet | Stewart, Theodor J Tuyiragize, Richard |
| author_sort | Tuyiragize, Richard |
| collection | Thesis |
| description | The objective of this research is to develop a framework of multi-objective optimization (MOO) models that are better capable of providing decision support on future long-term electricity generation planning (EGP), in the context of insufficient electricity capacity and to apply it to the electricity system for a developing country. The problem that motivated this study was a lack of EGP models in developing countries to keep pace with the countries' socio-economic and demographic dynamics. This research focused on two approaches: mathematical programming (MP) and system dynamics (SD). Detailed model descriptions, formulations, and implementation results are presented in the thesis along with the observations and insights obtained during the course of this research. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/10720 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:31:47.142Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2014 |
| publishDateRange | 2014 |
| publishDateSort | 2014 |
| publisher | Department of Statistical Sciences |
| publisherStr | Department of Statistical Sciences |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/10720 Multi-objective optimization techniques in electricity generation planning Tuyiragize, Richard Stewart, Theodor J Luboobi, Livingstone S Statistical Sciences The objective of this research is to develop a framework of multi-objective optimization (MOO) models that are better capable of providing decision support on future long-term electricity generation planning (EGP), in the context of insufficient electricity capacity and to apply it to the electricity system for a developing country. The problem that motivated this study was a lack of EGP models in developing countries to keep pace with the countries' socio-economic and demographic dynamics. This research focused on two approaches: mathematical programming (MP) and system dynamics (SD). Detailed model descriptions, formulations, and implementation results are presented in the thesis along with the observations and insights obtained during the course of this research. 2014-12-31T19:46:13Z 2014-12-31T19:46:13Z 2011 Doctoral Thesis Doctoral PhD http://hdl.handle.net/11427/10720 eng application/pdf Department of Statistical Sciences Faculty of Science University of Cape Town |
| spellingShingle | Statistical Sciences Tuyiragize, Richard Multi-objective optimization techniques in electricity generation planning |
| thesis_degree_str | Doctoral |
| title | Multi-objective optimization techniques in electricity generation planning |
| title_full | Multi-objective optimization techniques in electricity generation planning |
| title_fullStr | Multi-objective optimization techniques in electricity generation planning |
| title_full_unstemmed | Multi-objective optimization techniques in electricity generation planning |
| title_short | Multi-objective optimization techniques in electricity generation planning |
| title_sort | multi objective optimization techniques in electricity generation planning |
| topic | Statistical Sciences |
| url | http://hdl.handle.net/11427/10720 |
| work_keys_str_mv | AT tuyiragizerichard multiobjectiveoptimizationtechniquesinelectricitygenerationplanning |