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LCOE estimation in aggregated wind/PV study

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dc.contributor.author Bofinger, S
dc.contributor.author Stander, Johan N
dc.date.accessioned 2018-09-25T12:47:11Z
dc.date.available 2018-09-25T12:47:11Z
dc.date.issued 2017-11
dc.identifier.citation Bofinger, S. and Stander, J.N. 2017. LCOE estimation in aggregated wind/PV study. WINDABA 2017, 15-16 November 2017, Cape Town, South Africa en_US
dc.identifier.uri http://hdl.handle.net/10204/10421
dc.description Presentation delivered during WINDABA 2017, 15-16 November 2017, Cape Town, South Africa en_US
dc.description.abstract CSIR, SANEDI, Eskom and Fraunhofer IWES conducted a study to holistically quantify the wind-power potential in South Africa, and the portfolio effects of widespread spatial wind and solar power aggregation in South Africa. Wind Atlas South Africa (WASA) data was used to simulate wind power across South Africa. Key results showed that South Africa exhibits world-class conditions to introduce very large amounts of variable renewables into the electricity system. en_US
dc.language.iso en en_US
dc.relation.ispartofseries Worklist;21326
dc.subject Wind power en_US
dc.subject Solar PV en_US
dc.subject Wind Atlas South Africa en_US
dc.title LCOE estimation in aggregated wind/PV study en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Bofinger, S., & Stander, J. N. (2017). LCOE estimation in aggregated wind/PV study. http://hdl.handle.net/10204/10421 en_ZA
dc.identifier.chicagocitation Bofinger, S, and Johan N Stander. "LCOE estimation in aggregated wind/PV study." (2017): http://hdl.handle.net/10204/10421 en_ZA
dc.identifier.vancouvercitation Bofinger S, Stander JN, LCOE estimation in aggregated wind/PV study; 2017. http://hdl.handle.net/10204/10421 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Bofinger, S AU - Stander, Johan N AB - CSIR, SANEDI, Eskom and Fraunhofer IWES conducted a study to holistically quantify the wind-power potential in South Africa, and the portfolio effects of widespread spatial wind and solar power aggregation in South Africa. Wind Atlas South Africa (WASA) data was used to simulate wind power across South Africa. Key results showed that South Africa exhibits world-class conditions to introduce very large amounts of variable renewables into the electricity system. DA - 2017-11 DB - ResearchSpace DP - CSIR KW - Wind power KW - Solar PV KW - Wind Atlas South Africa LK - https://researchspace.csir.co.za PY - 2017 T1 - LCOE estimation in aggregated wind/PV study TI - LCOE estimation in aggregated wind/PV study UR - http://hdl.handle.net/10204/10421 ER - en_ZA


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