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Decision support for the production and distribution of electricity under load shedding
Every day national power system networks provide thousands of MW of electric power from generating units to consumers. This process requires different operations and planning to ensure the security of the entire system. Part of the daily or weekly operation system is the so called Unit Commitment pr...
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| Format: | Thesis |
| Language: | English |
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Department of Statistical Sciences
2016
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| _version_ | 1867613343318016000 |
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| access_status_str | Open Access |
| author | Rakotonirainy, Rosephine Georgina |
| author2 | Durbach, Ian |
| author_browse | Durbach, Ian Rakotonirainy, Rosephine Georgina |
| author_facet | Durbach, Ian Rakotonirainy, Rosephine Georgina |
| author_sort | Rakotonirainy, Rosephine Georgina |
| collection | Thesis |
| description | Every day national power system networks provide thousands of MW of electric power from generating units to consumers. This process requires different operations and planning to ensure the security of the entire system. Part of the daily or weekly operation system is the so called Unit Commitment problem which consists of scheduling the available resources in order to meet the system demand. But the continuous growth in electricity demand might put pressure on the ability of the generation system to sufficiently provide supply. In such case load shedding (a controlled, enforced reduction in electricity supply) is necessary to prevent the risk to system collapse. In South Africa at the present time, a systematic lack of supply has meant that regular load shedding has taken place, with substantial economic and social costs. In this research project we study two optimization problems related to load shedding. The first is how load shedding can be integrated into the unit commitment problem. The second is how load shedding can be fairly and efficiently allocated across areas. We develop deterministic and stochastic linear and goal programming models for these purposes. Several case studies are conducted to explore the possible solutions that the proposed models can offer. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/20942 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:34:38.153Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2016 |
| publishDateRange | 2016 |
| publishDateSort | 2016 |
| 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:11427/20942 Decision support for the production and distribution of electricity under load shedding Rakotonirainy, Rosephine Georgina Durbach, Ian Nyirenda, Juwa Statistical Sciences Every day national power system networks provide thousands of MW of electric power from generating units to consumers. This process requires different operations and planning to ensure the security of the entire system. Part of the daily or weekly operation system is the so called Unit Commitment problem which consists of scheduling the available resources in order to meet the system demand. But the continuous growth in electricity demand might put pressure on the ability of the generation system to sufficiently provide supply. In such case load shedding (a controlled, enforced reduction in electricity supply) is necessary to prevent the risk to system collapse. In South Africa at the present time, a systematic lack of supply has meant that regular load shedding has taken place, with substantial economic and social costs. In this research project we study two optimization problems related to load shedding. The first is how load shedding can be integrated into the unit commitment problem. The second is how load shedding can be fairly and efficiently allocated across areas. We develop deterministic and stochastic linear and goal programming models for these purposes. Several case studies are conducted to explore the possible solutions that the proposed models can offer. 2016-07-28T12:15:03Z 2016-07-28T12:15:03Z 2016 Master Thesis Masters MSc http://hdl.handle.net/11427/20942 eng application/pdf Department of Statistical Sciences Faculty of Science University of Cape Town |
| spellingShingle | Statistical Sciences Rakotonirainy, Rosephine Georgina Decision support for the production and distribution of electricity under load shedding |
| thesis_degree_str | Master's |
| title | Decision support for the production and distribution of electricity under load shedding |
| title_full | Decision support for the production and distribution of electricity under load shedding |
| title_fullStr | Decision support for the production and distribution of electricity under load shedding |
| title_full_unstemmed | Decision support for the production and distribution of electricity under load shedding |
| title_short | Decision support for the production and distribution of electricity under load shedding |
| title_sort | decision support for the production and distribution of electricity under load shedding |
| topic | Statistical Sciences |
| url | http://hdl.handle.net/11427/20942 |
| work_keys_str_mv | AT rakotonirainyrosephinegeorgina decisionsupportfortheproductionanddistributionofelectricityunderloadshedding |