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Contributions to Long-Term Electricity System Expansion Planning Through the Systematic Treatment of Data Uncertainty and Operational Assumptions
Thesis (PhD)--Stellenbosch University, 2026.
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| Format: | Thesis |
| Language: | English |
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Stellenbosch : Stellenbosch University
2026
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| _version_ | 1867613933148307456 |
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| access_status_str | Open Access |
| author | Auret, Christina |
| author2 | Bekker, Bernard |
| author_browse | Auret, Christina Bekker, Bernard |
| author_facet | Bekker, Bernard Auret, Christina |
| author_sort | Auret, Christina |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (PhD)--Stellenbosch University, 2026. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/135572 |
| institution | Stellenbosch University (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:44:01Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2026 |
| publishDateRange | 2026 |
| publishDateSort | 2026 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/135572 Contributions to Long-Term Electricity System Expansion Planning Through the Systematic Treatment of Data Uncertainty and Operational Assumptions Auret, Christina Bekker, Bernard Stellenbosch University. Faculty of Engineering. Dept. of Electrical & Electronic Engineering. Thesis (PhD)--Stellenbosch University, 2026. Auret, C. 2026. Contributions to Long-Term Electricity System Expansion Planning Through the Systematic Treatment of Data Uncertainty and Operational Assumptions. Unpublished doctoral dissertation. Stellenbosch: Stellenbosch University [online]. Available: https://scholar.sun.ac.za/items/7e3aaedd-1fd6-4c02-9e6b-9704e7c2786c The focus of this PhD dissertation is to investigate shortfalls and uncertainties in the validation of the long-term electricity system planning process, particularly as they pertain to electricity system planning in South Africa. Validation of the electricity system planning process can only occur in a piecemeal manner, as its outputs are forward-looking. While a broad framework can be built from the international literature, many pertinent details depend on the underlying characteristics of the electricity system that is being planned and thus vary based on specific localised system characteristics. The dissertation investigates and resolves issues related to three validation problems: determining the accuracy of input data and assumptions, the limitations of historical validation, and uncertainty in parameter requirements for unit commitment models used for validation. Two aspects of the first problem are explored. The first concerns the uncertainty surrounding the number of years of input data that is required to accurately represent electricity production from wind and PV in the planning process. The second aspect relates to accurately representing embedded storage in South African electricity system planning. The representation of embedded storage also ties into the second problem because of the difficulty that exists when using historical validation to validate the electricity system planning process in a system with rapidly changing characteristics. The third problem is considered in the context of how partial outages should be represented in short-term unit commitment models used to validate outputs from capacity expansion planning models. The uncertainty surrounding the number of years of input data required to accurately represent production from variable resources was addressed by the development of a methodology that allows the accuracy of a renewable production projection to be estimated based on the number of years of input data that is used when creating the projection. Projection error ranges were calculated for locations across South Africa, and a method was developed by which they can be combined. This will allow planners and researchers to estimate the accuracy of production projections for a fleet of wind and PV generators based on the number of years of input data that is used to make the projections. They would thus be able to easily evaluate the degree of uncertainty they are introducing into the planning process when selecting their renewable production input data set. This represents a significant shift from attempts to provide planners with prescriptive guidelines on dataset size to a more versatile approach that facilitates informed decision-making. The impact of omitting embedded storage from South African electricity system planning models is investigated through unit commitment modelling. While existing South African electricity system models exclude embedded storage, it is clearly shown here that this omission already distorts model outcomes even when the potential redeployment of security of supply infrastructure is not accounted for. The potential for the storage infrastructure acquired during a period of constrained electricity supply to be redeployed as the electricity system becomes more reliable creates an additional risk of overinvestment in storage if the existing capacity is not considered when modelling electricity system expansion. The implications of this are important, not only to the planning of the South African electricity system, but also to long-term planning in countries with constrained electricity systems that are moving towards reliability. Unit commitment modelling is also used to investigate the impact that representation of partial outages has when modelling the South African electricity system for long-term planning. While representation of partial outages is typically omitted in international studies, it is shown that this cannot be safely done when modelling the South African system or systems similar to it. In electricity systems where high unplanned outage rates are combined with generators that experience a high proportion of partial outages, model results can be skewed in terms of the deployment of peakers and storage, and in terms of reliability metrics when the representation of partial outages is omitted. Thus, it is shown that partial outages must be represented in unit commitment models that are used to validate the results of capacity expansion planning models in South Africa and in electricity systems similar to it. Doctoral 2026-04-02T05:40:28Z 2026-04-02T05:40:28Z 2026-03 Thesis https://scholar.sun.ac.za/handle/10019.1/135572 en Stellenbosch University 121 pages : ill. application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Auret, Christina Contributions to Long-Term Electricity System Expansion Planning Through the Systematic Treatment of Data Uncertainty and Operational Assumptions |
| title | Contributions to Long-Term Electricity System Expansion Planning Through the Systematic Treatment of Data Uncertainty and Operational Assumptions |
| title_full | Contributions to Long-Term Electricity System Expansion Planning Through the Systematic Treatment of Data Uncertainty and Operational Assumptions |
| title_fullStr | Contributions to Long-Term Electricity System Expansion Planning Through the Systematic Treatment of Data Uncertainty and Operational Assumptions |
| title_full_unstemmed | Contributions to Long-Term Electricity System Expansion Planning Through the Systematic Treatment of Data Uncertainty and Operational Assumptions |
| title_short | Contributions to Long-Term Electricity System Expansion Planning Through the Systematic Treatment of Data Uncertainty and Operational Assumptions |
| title_sort | contributions to long term electricity system expansion planning through the systematic treatment of data uncertainty and operational assumptions |
| url | https://scholar.sun.ac.za/handle/10019.1/135572 |
| work_keys_str_mv | AT auretchristina contributionstolongtermelectricitysystemexpansionplanningthroughthesystematictreatmentofdatauncertaintyandoperationalassumptions |