Technology learning for renewable energy: implications for South Africa's long-term mitigation scenarios

 

Show simple item record

dc.contributor.author Winkler, Harald
dc.contributor.author Haw, Mary
dc.contributor.author Hughes, Alison
dc.date.accessioned 2016-02-08T08:16:48Z
dc.date.available 2016-02-08T08:16:48Z
dc.date.issued 2009
dc.identifier.citation Winkler, H.; Hughes, A. & Haw, M. (2009) Technology learning for renewable energy: implications for South Africa's long-term mitigation scenarios. Energy Policy 37:4987–4996. en_ZA
dc.identifier.issn 0301-4215 en_ZA
dc.identifier.uri http://hdl.handle.net/11427/16874
dc.description.abstract Technology learning can make a significant difference to renewable energy as a mitigation option in South Africa’s electricity sector. This article considers scenarios implemented in a Markal energy model used for mitigation analysis. It outlines the empirical evidence that unit costs of renewable energy technologies decline, considers the theoretical background and how this can be implemented in modeling. Two scenarios are modelled, assuming 27% and 50% of renewable electricity by 2050, respectively. The results show a dramatic shift in the mitigation costs. In the less ambitious scenario, instead of imposing a cost of Rand 52/tCO2-eq (at 10% discount rate), reduced costs due to technology learning turn renewables into negative cost option. Our results show that technology learning flips the costs, saving R143. At higher penetration rate, the incremental costs added beyond the base case decline from R92 per ton to R3. Including assumptions about technology learning turns renewable from a higher-cost mitigation option to one close to zero. We conclude that a future world in which global investment in renewables drives down unit costs makes it a much more cost-effective and sustainable mitigation option in South Africa. en_ZA
dc.language eng en_ZA
dc.publisher Elsevier en_ZA
dc.source Energy Policy en_ZA
dc.source.uri http://www.journals.elsevier.com/energy-policy/
dc.subject.other Sustainable development
dc.subject.other Climatic changes
dc.subject.other Greenhouse gas mitigation
dc.title Technology learning for renewable energy: implications for South Africa's long-term mitigation scenarios en_ZA
dc.type Journal Article en_ZA
dc.date.updated 2016-02-03T09:39:37Z
uct.type.publication Research en_ZA
uct.type.resource Article en_ZA
uct.subject.keywords Technology learning en_ZA
uct.subject.keywords Renewable energy en_ZA
uct.subject.keywords Climate change mitigation en_ZA
dc.publisher.institution University of Cape Town
dc.publisher.faculty Faculty of Engineering and the Built Environment
dc.publisher.department Energy Research Centre en_ZA
uct.type.filetype Text
uct.type.filetype Image
dc.identifier.apacitation Winkler, H., Haw, M., & Hughes, A. (2009). Technology learning for renewable energy: implications for South Africa's long-term mitigation scenarios. <i>Energy Policy</i>, http://hdl.handle.net/11427/16874 en_ZA
dc.identifier.chicagocitation Winkler, Harald, Mary Haw, and Alison Hughes "Technology learning for renewable energy: implications for South Africa's long-term mitigation scenarios." <i>Energy Policy</i> (2009) http://hdl.handle.net/11427/16874 en_ZA
dc.identifier.vancouvercitation Winkler H, Haw M, Hughes A. Technology learning for renewable energy: implications for South Africa's long-term mitigation scenarios. Energy Policy. 2009; http://hdl.handle.net/11427/16874. en_ZA
dc.identifier.ris TY - Journal Article AU - Winkler, Harald AU - Haw, Mary AU - Hughes, Alison AB - Technology learning can make a significant difference to renewable energy as a mitigation option in South Africa’s electricity sector. This article considers scenarios implemented in a Markal energy model used for mitigation analysis. It outlines the empirical evidence that unit costs of renewable energy technologies decline, considers the theoretical background and how this can be implemented in modeling. Two scenarios are modelled, assuming 27% and 50% of renewable electricity by 2050, respectively. The results show a dramatic shift in the mitigation costs. In the less ambitious scenario, instead of imposing a cost of Rand 52/tCO2-eq (at 10% discount rate), reduced costs due to technology learning turn renewables into negative cost option. Our results show that technology learning flips the costs, saving R143. At higher penetration rate, the incremental costs added beyond the base case decline from R92 per ton to R3. Including assumptions about technology learning turns renewable from a higher-cost mitigation option to one close to zero. We conclude that a future world in which global investment in renewables drives down unit costs makes it a much more cost-effective and sustainable mitigation option in South Africa. DA - 2009 DB - OpenUCT DP - University of Cape Town J1 - Energy Policy LK - https://open.uct.ac.za PB - University of Cape Town PY - 2009 SM - 0301-4215 T1 - Technology learning for renewable energy: implications for South Africa's long-term mitigation scenarios TI - Technology learning for renewable energy: implications for South Africa's long-term mitigation scenarios UR - http://hdl.handle.net/11427/16874 ER - en_ZA


Files in this item

This item appears in the following Collection(s)

Show simple item record