System dynamics simulation of income distribution and electric vehicle diffusion for electricity planning in South Africa

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dc.contributor.advisorBrent, Alan C.en_ZA
dc.contributor.advisorMusango, J. K.en_ZA
dc.contributor.advisorGrobbelaar, Saraen_ZA
dc.contributor.authorPilay, Nalini Sooknananen_ZA
dc.contributor.otherStellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.en_ZA
dc.date.accessioned2018-10-15T07:30:18Z
dc.date.accessioned2018-12-07T06:47:30Z
dc.date.available2018-10-15T07:30:18Z
dc.date.available2018-12-07T06:47:30Z
dc.date.issued2018-12
dc.descriptionThesis (PhD)--Stellenbosch University, 2018.en_ZA
dc.description.abstractENGLISH ABSTRACT: The electricity generation industry has developed a symbiotic interdependence with the social, environmental, economic and political ecologies in the country, resulting in divergent complexities, which require non-linear model-based planning methodologies. Some of the determinants influencing the power industry include technologies, such as battery electric vehicles (BEVs), which have gained prominence as a possible option to support South Africa’s climate change commitments. This study used an adapted system dynamics modelling process to determine the provincial affordability of BEVs in South Africa so that amended regional forecasts of BEVs could be established to plan for charging infrastructure, environmental impacts in the energy and transport sectors, as well as changes in electricity consumption. Results from the Electricity Strategic Battery Electric Vehicle (E-StratBEV) simulator indicate that aligning BEV market penetration with the current consumer behaviour within deciles on vehicle expenditure, results in significantly lower than the expected market penetration. This means that by 2040, a low growth GDP-based target of 233,700 BEVs could adjust to 44,155 BEVs, while a high growth scenario of 2,389,950 BEVs (based on South Africa’s commitment in the Paris Agreement) could adjust to 451,736 BEVs. The inclusion of BEV drivers, such as reduced purchase price, increased charging infrastructure, reduced “range anxiety”, and improved reputation effect, add a further cumulative total of 270 GWh from 2019 until 2040 for the low growth scenario, and an additional 2,764 GWh for the high growth scenario, to the residential electricity consumption. From 2019 to 2040, a renewables heavy supply mix results in a 7% cumulative decrease in CO2 emissions in the transport sector; however, with a coal heavy supply mix, no gains in carbon emission reduction is achieved. The adapted system dynamics modelling process allowed for the successful development and implementation of the E-StratBEV, however, the process can be further enhanced by establishing preliminary complexity criteria to ensure a project requires this method before commencement.en_ZA
dc.description.abstractAFRIKAANSE OPSOMMING: Geen opsomming beskikbaaraf_ZA
dc.identifier.urihttp://hdl.handle.net/10019.1/104843
dc.language.isoen_ZAen_ZA
dc.publisherStellenbosch : Stellenbosch Universityen_ZA
dc.rights.holderStellenbosch Universityen_ZA
dc.subjectElectric vehicles -- Batteriesen_ZA
dc.subjectElectricity in transportationen_ZA
dc.subjectElectric vehicle supply equipmenten_ZA
dc.subjectElectric power productionen_ZA
dc.subjectElectric vehicles -- South Africaen_ZA
dc.subjectUCTDen_ZA
dc.titleSystem dynamics simulation of income distribution and electric vehicle diffusion for electricity planning in South Africaen_ZA
dc.typeThesisen_ZA
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