Journal of Energy in Southern Africa (Mar 2017)

Implications of biofuel production in the Western Cape province, South Africa: A system dynamics modelling approach of South Africa: A system dynamics modelling approach

  • Willem Jonker,
  • Alan Colin Brent,
  • Josephine Kaviti Musango,
  • Imke de Kock

DOI
https://doi.org/10.17159/2413-3051/2017/v28i1a1457
Journal volume & issue
Vol. 28, no. 1
pp. 1 – 12

Abstract

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The national government instated a mandatory blending policy to facilitate the uptake and establishment of a biofuels sector in South Africa. Uncertainty exists, however, regarding the implications and effects of producing biofuels within the Western Cape province, as part of a strategy of the province to transition to a green economy. This investigation was carried out as an effort to simulate the biofuel production within the Western Cape under certain project and policy considerations. A system dynamics model was developed to identify key strategic intervention points that could strengthen the business case of biofuel production. The model showed a feasible business case for bioethanol production, with the best case showing an internal rate of return of 23% (without government subsidy), and an emissions reduction of 63% when compared with coal. It is recommended that special consideration be given to the location of bioethanol production facilities, as operational costs can be minimised by incorporating invasive alien land-clearing schemes as part of the bioethanol production. The model further showed that medium-to-large-scale biodiesel production in the province is not feasible under the given model assumptions, as the positive effects of local biodiesel production do not justify the required government subsidy of ZAR 4.30 per litre. It is recommended that a different approach be investigated, where multiple on-site small-scale biodiesel production facilities are used, thus utilising multiple feedstock options and minimising capital expenditure. Keywords: green economy; transportation; blending; uncertainty; complexity

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