Browsing by Author "Stone, Adrian"
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- ItemOpen AccessEnergy futures modelling for African cities: selecting a modelling tool for the SAMSET project(Energy Research Centre, University of Cape Town., 2014) Tait, Louise; McCall, Bryce; Stone, AdrianUrbanisation is occurring fastest in developing countries, with the least developed countries expected to have the highest population growth rates between 2010 and 2050 (Madlener and Sunak, 2011). Cities in these countries are going to increasingly be important sites of energy demand and associated emissions. Much of the literature about sustainable urban energy transitions has to date focussed on developed country contexts; as the current sources of greatest emissions, this makes sense. In looking forward, however, if the energy demand and emissions of developing country cities increase to that equivalent of many western cities today, we may be unable to avoid catastrophic climate change. Transitioning energy infrastructures and associated urban systems is a long-term process. In the absence of forward planning, developing country cities run risks of infrastructural and urban planning lock-in to systems that are unsustainable (Olazabal and Pascual, 2013).
- ItemOpen AccessIs nuclear power a cost optimal solution for Kenya's electricity generation mix?(2016) Odera, Sarah; Stone, Adrian; Merven, BrunoIn 2010, the adoption of nuclear power was declared a national priority in Kenya. Thereafter, a target of obtaining 4000 MW of nuclear power by the year 2030 was documented in Kenya's Least Cost Power Development Plan (LCPDP) 2010-2031. The nuclear target has drawn a lot of opposition from some Kenyans whose concerns are centered on the cost and safety risks incurred by nuclear power. The government however states that nuclear power is necessary for the diversification of the electricity generation mix and satisfaction of future electricity demand. The aim of this thesis was therefore to determine whether electricity demand in Kenya could be met without nuclear power and whether it was more economical to utilize nuclear power in Kenya's electricity generation mix rather than increase the generation capacity of other sources of electricity available to Kenya. To answer these questions, two capacity expansion models were developed. These models like the LCPDP studied the period between 2010 and 2031. The aim of the first model was to replicate LCPDP, and in doing so verify the necessity of nuclear power for meeting Kenya's future electricity demand. As far as was possible, the validation model utilized the same assumptions, including the same demand forecast that was used to develop the LCPDP 2010-2031. The validation was done to verify the necessity of nuclear power from the LCPDP's set of assumptions. The second model was developed with the aim of obtaining an updated capacity expansion plan. This plan utilized recent assumptions including an updated demand forecast. The demand was forecasted using regression of historical electricity demand against GDP in the commercial and industrial category. In the domestic category historical demand was regressed against GDP per capita and population. Based on recent data and economic forecasts, a GDP growth rate of 6% was used to forecast the electricity demand instead of 9% used in the LCPDP's demand forecast. [Please note: this thesis file has been deferred until June 2018]
- ItemOpen AccessQuantifying the energy needs of the transport sector for South Africa: a bottom-up model(Energy Research Centre, University of Cape Town., 2012) Merven, Bruno; Stone, Adrian; Hughes, Alison; Cohen, BrettTransport is a large consumer of energy in South Africa and vital for economic development. Currently the transport sector consumes 28% of final energy, the bulk of which, 97%, is in the form of liquid fuels. As the population grows and becomes wealthier, so the demand for passenger transport and private vehicles increases; similarly, rising GDP drives the demand for freight transport. Supply interruptions are costly to the economy and careful longāterm planning is required to ensure that there is sufficient infrastructure to support the efficient functioning and growth of the transport sector in the future.
- ItemOpen AccessReliability evaluation of solar power in South Africa's power system(2014) Bailey, Nicolas; Stone, Adrian; Merven, BrunoGlobal utilisation of renewable energy sources such as solar photovoltaics (PV) in electric power systems is growing rapidly due to government incentives, and negative environmental impacts associated with conventional generators. Many consider solar PV as a promising alternative source of energy due to its apparent environmental, social and economic benefits. This together with government incentives and programmes such as the renewable energy independent power procurement program (REIPPPP) has allowed for investment in PV in South Africa (SA). Solar irradiation is a variable energy source and thus serious consideration needs to be given to the effect that PV might have on the reliability of the system. As a result traditional methods of evaluating power system reliability cannot be used when utility-scale PV is introduced to the system. Thus probabilistic methods are commonly employed to evaluate reliability. In this thesis time series data was used to simulate the yield from 27 PV plants, as defined by round 1 and round 2 of the REIPPP process, through a yield model developed for this investigation.
- ItemOpen AccessSocio-economic implications of mitigation in the power sector including carbon taxes in South Africa(Energy Research Centre, University of Cape Town., 2014) Merven, Bruno; Moyo, Alfred; Stone, Adrian; Dane, Anthony; Winkler, HaraldThe structure of this paper is as follows. The first section provides a discussion of recent developments within South Africa aimed at increasing the contribution of renewable energy. The second section gives a brief description of the carbon tax that National Treasury plans to implement and also provides an overview of previous studies on the implications of a carbon tax in South Africa. The linked model that we use for our analysis is described in section 3. This is then followed in section 4 by a description of the scenarios that we modelled, with results presented in section 5. The last section presents the conclusions and recommendations for further research.