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Modelling Decarbonisation Pathways in the Power Sector: The Case of South Africa

Authors: Nosrati Ghods, Nosaibeh; de Kock, Savanha; Gogela, Usisipho; Gongxeka, Jacqueline Siphokazi;

Modelling Decarbonisation Pathways in the Power Sector: The Case of South Africa

Abstract

This report presents a comprehensive analysis of decarbonization pathways for South Africa's power sector using the OSeMOSYS modeling framework. It evaluates three scenarios: Business as Usual (BAU), Integrated Resource Plan 2023 (IRP 2023), and Net Zero 2050 (NZ2050). South Africa's energy landscape is characterized by significant challenges, including electricity supply constraints, high electricity costs, widespread energy poverty, and a heavy reliance on coal. The study reveals that continuing on the current trajectory (BAU) will exacerbate health risks and contribute significantly to climate change. In contrast, both the IRP 2023 and NZ2050 scenarios show substantial reductions in CO2 emissions, driven by decreased reliance on coal and increased adoption of renewable energy sources. The NZ2050 scenario, in particular, envisions a complete phase-out of coal by 2050, supplemented by biomass and nuclear energy to provide base load power. The findings underscore the necessity of significant investments. This research highlights the importance of strategic energy planning and the potential benefits of implementing more ambitious renewable energy targets and infrastructure investments to ensure a sustainable and resilient energy future for South Africa.

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Keywords

Energy Planning, Climate-Related Pressures, Renewable Energy, Energy System Modeling, GHG Emissions Reduction, OSeMOSYS

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green