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Development and application of a multi-criteria decision-support framework for planning rural energy supply interventions in low-income households in South Africa
Problems in the public policy decision-making environments are typically complex and continuously evolve. In a resource-constrained environment, several alternatives, criteria, and conflicting objectives must be considered. As a result, solutions to these types of problems cannot be modelled solely...
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| Format: | Thesis |
| Language: | English |
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Department of Mechanical Engineering
2022
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| _version_ | 1867614533242060800 |
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| access_status_str | Open Access |
| author | Dzenga, Bruce |
| author2 | Stewart, Theodor J |
| author_browse | Dzenga, Bruce Stewart, Theodor J |
| author_facet | Stewart, Theodor J Dzenga, Bruce |
| author_sort | Dzenga, Bruce |
| collection | Thesis |
| description | Problems in the public policy decision-making environments are typically complex and continuously evolve. In a resource-constrained environment, several alternatives, criteria, and conflicting objectives must be considered. As a result, solutions to these types of problems cannot be modelled solely using single-criteria techniques. It has been observed that most techniques used to shape energy policy and planning either produce sub-optimal solutions or use strong assumptions about the preferences of decision-maker(s). This difficulty creates a compelling need to develop novel techniques that can handle several alternatives, multiple criteria and conflicting objectives to support public sector decision-making processes. First, the study presents a novel scenario-based multi-objective optimisation framework based on the augmented Chebychev goal programming (GP) technique linked to a value function for analysing a decision environment underlying energy choice among low-income households in isolated rural areas and informal urban settlements in South Africa. The framework developed includes a multi-objective optimisation technique that produced an approximation of a Pareto front linked to an a priori aggregation function and a value function to select the best alternatives. Second, the study used this model to demonstrate the benefits of applying the framework to a previously unknown subject in public policy: a dynamic multi-technology decision problem under uncertainty involving multiple stakeholders and conflicting objectives. The results obtained suggest that while it is cost-optimal to pursue electrification in conjunction with other short-term augmentation solutions to meet South Africa's universal electrification target, sustainable energy access rates among low-income households can be achieved by increasing the share of clean energy generation technologies in the energy mix. This study, therefore, challenges the South African government's position on pro-poor energy policies and an emphasis on grid-based electrification to increase energy access. Instead, the study calls for a portfolio-based intervention. The study advances interventions based on micro-grid electrification made up of solar photovoltaics (PV), solar with storage, combined cycle gas turbine (CCGT) and wind technologies combined with either bioethanol fuel or liquid petroleum gas (LPG). The study has demonstrated that the framework developed can benefit public sector decision-makers in providing a balanced regime of technical, financial, social, environmental, public health, political and economic aspects in the decision-making process for planning energy supply interventions for low-income households. The framework can be adapted to a wide range of energy access combinatorial problems and in countries grappling with similar energy access challenges. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/36762 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:53:33.300Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | Department of Mechanical Engineering |
| publisherStr | Department of Mechanical Engineering |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/36762 Development and application of a multi-criteria decision-support framework for planning rural energy supply interventions in low-income households in South Africa Dzenga, Bruce Stewart, Theodor J Hughes, Alison energy access multi-objective linear programming multi-criteria decision analysis augmented Chebychev goal programming multi-attribute value theory low-income households dynamic multi-technology decision problem under uncertainty scenario analysis sensitivity analysis isolated rural areas and informal settlements Problems in the public policy decision-making environments are typically complex and continuously evolve. In a resource-constrained environment, several alternatives, criteria, and conflicting objectives must be considered. As a result, solutions to these types of problems cannot be modelled solely using single-criteria techniques. It has been observed that most techniques used to shape energy policy and planning either produce sub-optimal solutions or use strong assumptions about the preferences of decision-maker(s). This difficulty creates a compelling need to develop novel techniques that can handle several alternatives, multiple criteria and conflicting objectives to support public sector decision-making processes. First, the study presents a novel scenario-based multi-objective optimisation framework based on the augmented Chebychev goal programming (GP) technique linked to a value function for analysing a decision environment underlying energy choice among low-income households in isolated rural areas and informal urban settlements in South Africa. The framework developed includes a multi-objective optimisation technique that produced an approximation of a Pareto front linked to an a priori aggregation function and a value function to select the best alternatives. Second, the study used this model to demonstrate the benefits of applying the framework to a previously unknown subject in public policy: a dynamic multi-technology decision problem under uncertainty involving multiple stakeholders and conflicting objectives. The results obtained suggest that while it is cost-optimal to pursue electrification in conjunction with other short-term augmentation solutions to meet South Africa's universal electrification target, sustainable energy access rates among low-income households can be achieved by increasing the share of clean energy generation technologies in the energy mix. This study, therefore, challenges the South African government's position on pro-poor energy policies and an emphasis on grid-based electrification to increase energy access. Instead, the study calls for a portfolio-based intervention. The study advances interventions based on micro-grid electrification made up of solar photovoltaics (PV), solar with storage, combined cycle gas turbine (CCGT) and wind technologies combined with either bioethanol fuel or liquid petroleum gas (LPG). The study has demonstrated that the framework developed can benefit public sector decision-makers in providing a balanced regime of technical, financial, social, environmental, public health, political and economic aspects in the decision-making process for planning energy supply interventions for low-income households. The framework can be adapted to a wide range of energy access combinatorial problems and in countries grappling with similar energy access challenges. 2022-08-30T08:38:49Z 2022-08-30T08:38:49Z 2022 2022-08-25T11:27:21Z Doctoral Thesis Doctoral PhD http://hdl.handle.net/11427/36762 eng application/pdf Department of Mechanical Engineering Faculty of Engineering and the Built Environment |
| spellingShingle | energy access multi-objective linear programming multi-criteria decision analysis augmented Chebychev goal programming multi-attribute value theory low-income households dynamic multi-technology decision problem under uncertainty scenario analysis sensitivity analysis isolated rural areas and informal settlements Dzenga, Bruce Development and application of a multi-criteria decision-support framework for planning rural energy supply interventions in low-income households in South Africa |
| thesis_degree_str | Doctoral |
| title | Development and application of a multi-criteria decision-support framework for planning rural energy supply interventions in low-income households in South Africa |
| title_full | Development and application of a multi-criteria decision-support framework for planning rural energy supply interventions in low-income households in South Africa |
| title_fullStr | Development and application of a multi-criteria decision-support framework for planning rural energy supply interventions in low-income households in South Africa |
| title_full_unstemmed | Development and application of a multi-criteria decision-support framework for planning rural energy supply interventions in low-income households in South Africa |
| title_short | Development and application of a multi-criteria decision-support framework for planning rural energy supply interventions in low-income households in South Africa |
| title_sort | development and application of a multi criteria decision support framework for planning rural energy supply interventions in low income households in south africa |
| topic | energy access multi-objective linear programming multi-criteria decision analysis augmented Chebychev goal programming multi-attribute value theory low-income households dynamic multi-technology decision problem under uncertainty scenario analysis sensitivity analysis isolated rural areas and informal settlements |
| url | http://hdl.handle.net/11427/36762 |
| work_keys_str_mv | AT dzengabruce developmentandapplicationofamulticriteriadecisionsupportframeworkforplanningruralenergysupplyinterventionsinlowincomehouseholdsinsouthafrica |