Pathway towards achieving 100% renewable electricity by 2050 for South Africa
Ayobami Solomon Oyewo, Arman Aghahosseini, Manish Ram, Alena Lohrmann, Christian Breyer
LUT University, Yliopistonkatu 34, 53850 Lappeenranta, Finland
E-mail: email@example.com and firstname.lastname@example.org
Transition to a cost effective and fossil carbon-free energy system is imminent for South Africa, so is the
mitigation of issues associated with the ‘water-energy nexus’ and their consequent impacts on the climate.
The country’s key fossil carbon mitigation option lies in the energy sector, especially in shifting away from
the coal-dependent power system. Pathways towards a fully decarbonised and least cost electricity system
are investigated for South Africa. The energy transition is simulated for five scenarios, assessing the impact
of various factors such as sector coupling, with and without greenhouse gas (GHG) emission costs. South
Africa’s energy transition is simulated using an hourly resolved model until 2050. This modelling approach
synthesises and reflects in-depth insights of how the demand from the power sector can be met. The
optimisation for each 5-year time period is carried out based on assumed costs and technological status until
2050. The modelling outcomes reveal that solar PV and wind energy, supplying about 71% and 28% of the
demand respectively in the Best Policy Scenario for 2050, can overcome coal dependency of the power
sector. The levelised cost of electricity increases just slightly from 49.2 €/MWh in 2015 to 50.8 €/MWh in
the Best Policy Scenario, whereas it increases significantly to 104.9 €/MWh in the Current Policy Scenario
by 2050. Further, without considering GHG emissions costs, the cost of electricity slightly increases from
44.1 €/MWh in 2015 to 47.1 €/MWh in the Best Policy Scenario and increases up to 62.8 €/MWh in the
Current Policy Scenario by 2050. The cost of electricity is 25% lower in the Best Policy Scenario than in
the Current Policy Scenario without factoring in GHG emissions costs and further declined to 50% with
GHG emissions costs. The Best Policy Scenario without GHG emissions costs led to 96% renewables and
the remaining 4% is supplied by coal and gas turbines, indicating pure market economics. The results
indicate that a 100% renewable energy system is the least-cost, least-water intensive, least-GHG-emitting
and most job-rich option for the South African energy system in the mid-term future. No new coal and
nuclear power plants are installed in the least-cost pathway, and existing fossil fuel capacities are phased
out based on their technical lifetime.
Keywords: South Africa, Coal, Energy transition, 100% Renewable energy, Decarbonisation
A-CAES adiabatic compressed air energy
BPS(s) Best Policy Scenario(s)
CAPEX capital expenditures
CCGT combined cycle gas turbine
CCS carbon capture and storage
CHP combined heat and power
CPS(s) Current Policy Scenario(s)
CSP concentrating solar thermal power
LCOS levelised cost of storage
LCOT levelised cost of transmission
OCGT open cycle gas turbine
OPEX operational expenditures
PHES pumped hydro energy storage
RE renewable energy
SNG synthetic natural gas
DOE Department of Energy
GT gas turbine
GHG greenhouse gas
HVDC high voltage direct current
IRENA International Renewable Energy
IPPs Independent Power Producers
IRP Integrated Resource Plan
LCOC levelised cost of curtailment
LCOE levelised cost of electricity
ST steam turbine
TES thermal energy storage
VRE variable renewable energy
WACC weighted average cost of capital
ZAR South Africa Rand
South Africa is the fifth most populated country in Africa, with a population of 56.7 million in 2017 and an
annual average population growth rate of 1.2%, occupying an area of 1.219 million km2 (World Bank,
2017). The country’s GDP is 349 b€ with a growth rate of 1.3% in 2017 (World Bank, 2017). The electricity
demand is expected to increase from 245 TWh in 2015 to 522 TWh in 2050, with an annual average growth
rate of 2.3% (Wright et al., 2017). South Africa, like any other coal-abundant country, is susceptible to huge
environmental crises, due to over-reliance on coal-generated electricity (Baker and Sovacool, 2017;
Klausbrucker, 2016). Coal-fired power plants account for over 90% of electricity production in South
Africa (Menyah and Wolde-Rufael, 2010). The country is listed amongst the world’s most fossil carbon-
intensive economies and is ranked as the 7th largest emitter of greenhouse gas (GHG) per capita (Alton et
al., 2014). In Africa, South Africa remains the largest CO2 emitter and accounts for 42% of the continent’s
emissions (Alton et al., 2014). South Africa commits, as defined in national policy, a peak, plateau and
decline GHG emissions trajectory range, with emissions by 2025 and 2030 in a range of between 398 and
614 MtCO2eq, as per the 2015 intended nationally determined contribution (DEA, 2015). The country’s main
fossil carbon mitigation option lies in shifting away from its coal dependence in the power sector (DEA,
2015), which complies with the Paris Agreement on climate change (Delina and Sovacool, 2018).
Transition towards renewable energy is highlighted in the Paris Agreement for mitigating climate change
(Delina and Sovacool, 2018). Figure 1 shows the total active installed capacities, by the end of 2014 in
South Africa, and illustrates the almost complete reliance on fossil fuel (Farfan and Breyer, 2017).
Additional background information on South Africa is available in the Supplementary Material (section 1).
Figure 1. Total installed active power capacities (in GW) by the end of 2014 in South Africa (Farfan and
A brief summary of various studies on the trend of RE share in the South African energy system is presented
in Table 1.
Table 1: Studies on trends of renewable energy shares in the South African energy system
The Advanced Energy [R]evolution scenario projects a renewable electricity share in the
South African energy system of 49% by 2030 and 94% by 2050. The installed capacity of
RE will reach 59 GW in 2030 and 114 GW in 2050. Solar PV, wind energy and CSP
dominate the shares of installed capacity, contributing 40 GW, 27 GW and 35 GW
respectively by 2050.
The South African power system is dominated by coal with 54.2 GW and 42.9 GW in the
Baseline and Efficiency scenarios respectively, by 2030. RE installed capacity is 20.1 GW
(23%) of 86.6 GW in the Baseline scenario, and 23.7 GW (31%) of 77.4 GW in the
The New Policy Scenario assumes RE installed capacity of 35 GW and fossil power plants
of 73 GW by 2040. Coal dominates the installed capacity with 53 GW (49%). Coal and
nuclear contributes 243 TWh (61%) and 47 TWh (12%) respectively of the total electricity
generation at 401 TWh by 2040.
Under the Renewable Promotion Scenario, South Africa’s RE installed capacity reached
37.5 GW (43%) and fossil is 50.2 GW (57%). Coal dominates the installed capacity with
41.5 GW (47%), followed by wind energy and solar PV with 17.3 GW (20%) and 13.9
GW (16%) respectively by 2030.
Wright et al. (2017)
The least cost (‘Expected’ costs) scenario achieves over 70% RE penetration by the year
2050, with a significant investment in solar PV and wind energy as expected, with gas
turbines providing system flexibility and adequacy with hydropower and biomass. Storage
and remaining coal capacity assist in system adequacy. By 2050, energy mix is dominated
by solar PV with 140 GW and followed by wind with 73 GW. Solar PV and wind dominate
in this scenario due to a further cost reduction assumed for PV and wind.
The decarbonised scenario achieves over 90% RE penetration by 2050. Solar PV and wind
energy dominate the total installed capacity, with 84 GW and 83 GW respectively by 2050.
In addition, solar PV and wind energy are complemented by biomass (16 GW), CSP (13
GW), hydro (9 GW) and gas turbines (43 GW).
WWF Vision 2030
RE capacity of 35 GW (37%) and 18 GW (24%) is projected for the high-demand and low-
demand scenarios respectively, by 2030. While, renewable electricity generation is 78
TWh (19%) for the high-demand scenario and 39 TWh (11%) for the low-demand
This article explores the paradigmatic and dynamic pathway to a fully decarbonised and least cost electricity
solution for South Africa in the mid-term future. A 100% RE scenario for South Africa is simulated using
an hourly resolved model, from 2015 to 2050, covering the power sector demand. Furthermore, the water-
energy nexus is explored through analysing the water footprint of the different energy scenarios. In addition,
another crucial aspect for South Africa is the creation of local employment, which is further analysed for
the different energy scenarios in this research. The paper is structured as follows: the research methodology
is described in section 2. Results are presented and analysed in section 3. In section 4, the results are
discussed and compared with related studies. Conclusions and policy implications are presented in section
The South African energy system was modelled with the LUT Energy System Transition Model described
in (Bogdanov and Breyer, 2016; Breyer et al., 2018; Bogdanov et al., 2019). The energy system model is a
linear optimisation tool developed to determine the optimal investment and generation technology mix
required to meet the electricity demand in South Africa from 2015 until 2050. The main objective of this
research is to understand the transition pathways to a fully RE-based power system for South Africa. The
optimisation for each time period (5-year intervals) is carried out on the basis of assumed costs and
technological status until 2050 for all energy technologies involved. The installed capacities of the different
types of power plants from 1960 to 2015 is considered according to Farfan and Breyer (2017). Additionally,
the water footprint analyses are based on Lohrmann et al. (2019) and employment creation is based on Ram
et al. (2017a). After 2015, there are no additional capacities of fossil fuel resources allowed. The existing
fossil power plants are phased out based on their lifetimes. However, gas turbines can be installed after
2015, due to their lower GHG emissions, higher efficiency, and the possibility to accommodate bio-methane
and synthetic natural gas in the power system in a later phase. The RE capacity share increase cannot exceed
4% per year (3% per year from 2015 to 2020), in order to avoid disruptions.
2.2 Model overview
The power system used in this study was developed to match generation and power demand for every hour
of the simulated year. The model is based on linear cost optimisation of energy system parameters under
certain constraints. The model is compiled using MATLAB R2016a (MathWorks, 2016), while the
optimisation is carried out in MOSEK version 8 (Mosek, 2017). The key target function of the model is to
optimise the system, so that the total annual energy system cost is minimised. This cost is calculated as the
addition of the annual costs of the installed capacities of each technology, operational expenditures, and
costs of generation ramping. In addition, the energy system takes into account self-generation and
consumption of electricity for residential, commercial and industrial end-users. Another mini-transition
hourly model describes the PV prosumers systems and optional battery development capacity. The
respective capacities of rooftop PV systems and optional batteries are installed by the prosumers. The target
function for prosumers is the minimisation of cost of consumed electricity, calculated as the sum of self-
generation, annual costs, and the cost of electricity consumed from the grid. Excess electricity is sold to the
grid at 0.02 €/kWh by prosumers, when their own demand is satisfied, but not more than 50% of total self-
generation. The prosumer demand is limited to 20% of the total demand. The prosumer constraints ensure
that the 20% is not reached within the first time step. Thus, the model determines a step-wise progression
from a maximum of 6% in the first time step to 9%, 15%, 18% and 20% in subsequent time steps if the
economic model of prosumers indicates benefits of PV self-generation. PV self-consumption is considered
as an exogenous input into the system optimisation. The energy system is optimised in addition to the
prosumer capacities, which avoid any distortion of the overall system. The model overview is shown in
Figure 2. Detailed model description, equations and applied constraints can be found in (Bogdanov and
Breyer, 2016; Breyer et al., 2018; Bogdanov et al., 2019).
Figure 2. Main inputs and outputs of the LUT Energy System Model (Bogdanov and Breyer, 2016).
South Africa was structured into 9 sub-regions based on the existing provincial structure, namely, Gauteng
(ZA-GT), Mpumalanga (ZA-MP), KwaZulu-Natal (ZA-NL), North West (ZA-NW), Limpopo (ZA-LP),
Western Cape (ZA-WC), Free State (ZA-FS), Eastern Cape (ZA-EC) and Northern Cape (ZA-NC). All the
sub-regions are interconnected with transmission grids as shown in Figure 3.
Figure 3. South African sub-regions and transmission lines configuration.
2.3 Applied technologies
The main technologies applied for the South African energy system modelling include electricity
generation, storage, transmission and energy sector bridging technologies to provide more flexibility to the
complete energy system. Figure 4 shows the block diagram of the energy transition model.
Figure 4. Block diagram of the LUT Energy System Transition model used for South Africa (Breyer et al.,
2018). Abbreviations not introduced elsewhere include PP- power plant, ST- steam turbines, PtH – power-
to-heat, ICE – internal combustion engine, GT gas turbines, A-CAES – adiabatic compressed air storage,
PtG- power-to-gas, PHES – pumped hydro energy storage, TES – thermal-energy-storage, HHB – hot heat
burner, CSP – concentrated solar thermal power.
2.4. Modelling assumptions
2.4.1. Financial and technical assumptions
The financial and technical assumptions for all energy system components are applied in 5-year time steps.
This includes operational expenditures (OPEX), capital expenditures (CAPEX) and technical lifetimes from
2015 to 2050 for the applied technologies, as provided in the Supplementary Material (Table S1). The
technical assumptions concerning storage technologies (efficiency and power to energy ratio), fuels, and
transmission grids can be found in the Supplementary Material (Tables S2-S4).
The weighted average cost of capital (WACC) is set to 7% in this study. However, for residential PV
prosumers WACC is set to 4% due to lower financial return requirements. The cost recovery is mostly
considered for a wider aggregate range of investors, which includes a mix of debt and equity financing. On
this basis, the commercial and industrial investors require higher returns on equity margins than private
investors. Therefore, WACC is split into two categories in this study. The WACC variation does not
substantially alter the cost of the energy system (Breyer et al., 2017). Additionally, the risk profile of nuclear
and coal is much higher than RE, which should result in a higher WACC level for nuclear energy and coal
compared to RE technologies (Ram et al., 2018), however, these higher risks are not taken into account in
The electricity prices for residential, commercial and industrial consumers for the year 2015 were retrieved
from (Eskom, 2015). The electricity price was calculated until 2050 according to Gerlach et al. (2014) and
Breyer and Gerlach (2013). The electricity prices during the transition are calculated according to the
assumptions from Gerlach et al. (2014) that grid electricity prices rise by 5% per annum for <0.15 €/kWh,
by 3% per annum for 0.15–0.30 €/kWh and by 1% per annum for >0.30 €/kWh. The electricity prices for
South Africa are provided in the Supplementary Material (Table S5). An average currency exchange rate
for a period of 5 years from 2013 to 2018 was considered, at 16.67 €/ZAR (equal to 0.06 ZAR/€).
The upper limits for all RE technologies were estimated according to Bogdanov and Breyer (2016) and
lower limits are obtained from Farfan and Breyer (2017). Upper and lower limits of RE and fossil fuels are
provided in the Supplementary Material (Tables S6 and S7). For all other technologies, upper limits are not
specified. However, for solid biomass residues, biogas, and waste-to-energy plants it is assumed, due to
energy efficiency reasons, that the available and specified amount of the fuel is used during the year.
2.4.2. Resource potential for renewable technologies
The feed-in profiles for solar PV optimally tilted and single-axis tracking ground-mounted power plants,
wind energy and CSP are calculated according to Bogdanov and Breyer (2016) and Afanasyeva et al.
(2018), based on resource data of NASA (Stackhouse and Whitlock, 2008; 2009), reprocessed by the
German Aerospace Centre (Stetter, 2012). The obtained NASA dataset is in a temporal resolution of 3 h
for the year 2005 and spatial resolution of 1o x 1o. An Enercon wind turbine (E-101) with a rated power of
3 MW and 150 m hub height is used to compute the wind feed-in profiles. The full load hours (FLH) feed-
in profiles are calculated based on real weather conditions for the year 2005 on a 0.45o x 0.45o spatially and
hourly temporally resolved data using a weighted average formula, this methodology is described in
Bogdanov and Breyer (2016). It is assumed that 0-10% best areas are weighted by 0.3, 10-20% best areas
are weighted by 0.3, 20-30% best areas are weighted by 0.2, 30-40% best areas are weighted by 0.1 and
40-50% best areas are weighted by 0.1%. The hydropower feed-in profiles are computed based on the
monthly resolved precipitation data for the year 2005 as a normalised sum of precipitation in the regions.
Such an estimate leads to a good approximation of the annual generation of hydropower plants (Verzano,
2009). Full load hours of various resources are presented in the Supplementary Material (Tables S11-S13
and Figure S1) and visualised in an hourly resolution in Figure 5. Figure S1 shows the geographic diversity
in wind and solar resources across the country.
Figure 5. Aggregated feed-in profiles for optimally tilted (top left) and single-axis tracking PV (top right),
CSP solar field (bottom left), and wind power plants (bottom right) in South Africa.
The potentials for biomass and waste resources are taken from German Biomass Research Centre (DBFZ,
2010) and are classified according to Bogdanov and Breyer (2016). The costs for biomass are calculated
using data from the International Energy Agency (IEA, 2012) and Intergovernmental Panel on Climate
Change (IPCC, 2011). For solid waste, a 50 €/ton gate fee was assumed for 2015, which increased up to
100 €/ton in 2050.
2.4.3. Electricity demand
The hourly electricity load profile is calculated as a fraction of the total demand for each sub-region based
on synthetic load data weighted by the sub-regions population (Toktarova et al., 2018). Figure 6 shows the
aggregated load curve and long-term electricity demand for South Africa. Electricity demand is taken from
Wright et al. (2017). The population in South Africa is expected to grow from 54 million in 2015 to 66
million in 2050 (UN, 2015), while the average per capita electricity demand rises from 4.9 to 8.2 MWh as
shown in Figure 6 (right). The electricity demand until 2050 is provided in the Supplementary Material
Figure 6. Aggregated load curve for South Africa for 2050 (left) and long-term demand from 2015 to
In this study, five scenarios were studied for the South African energy transition analyses, which are briefly
described in Table 2.
Table 2: Overview on scenarios
Best Policy Scenario (BPS)
This scenario targets 100% RE by 2050. In addition, GHG emissions costs are
considered and only electricity demand is covered. The Best Policy Scenario
naming is considered on basis of 100% RE, zero GHG emissions, most job-
rich and least-water intensive characteristics.
Best Policy Scenario no GHG
emissions costs applied
In this scenario, no GHG emissions costs are assumed.
Current Policy Scenario (CPS)
In this scenario, respective installed capacities according to the Integrated
Resource Plan (IRP) from now until 2050 were taken into account, in
modelling the South African energy transition in the mid-term future (Wright
et al., 2017).
Current Policy Scenario no GHG
emissions costs (CPSnoCC)
In this scenario, no GHG emissions costs are assumed. Thus, only the
financial implications of this scenario are discussed.
3.1. Analysis of financial outcome of the transition for all scenarios
The average financial results for the studied scenarios are expressed as levelised cost of electricity (LCOE),
levelised cost of electricity for primary generation (LCOE primary), levelised cost of curtailment (LCOC),
levelised cost of storage (LCOS), levelised cost of transmission (LCOT), levelised cost of import (LCOI),
fuel costs and CO2eq emission costs, as shown in Figure 7 from 2015 to 2050. The LCOE in the BPSs is
observed as shown in Figure 7 (a-b). The LCOE increase until 2025, due to decommissioning of fossil
power plants and concurrent replacement with RE capacities. From 2025 onwards, the LCOE declines, as
low-cost solar PV and wind energy dominate the system in the BPS. Whereas, the LCOE in the BPSnoCC
increases until 2035 and gradually declines afterwards until 2050. By 2050, the LCOE obtained in the BPS
is 50.8 €/MWh and 47.1 €/MWh in BPSnoCC, as shown in Figure 7 (a and b). The contrary trend is
observed in the CPS, as the LCOE increases throughout the transition. By 2050, the LCOE obtained in the
CPS is 104.9 €/MWh as shown in Figure 7c. Fuel and GHG emissions costs account for more than 50% of
the LCOE in the CPS by 2050. Yet, the LCOE obtained in the CPS without GHG emissions costs
(CPSnoCC) is 62.8 €/MWh as shown in Figure 7d, which is still higher in comparison to the LCOE obtained
in the BPSs by 24% in 2050. Additional results on costs for all scenarios are available in the Supplementary
Material (Table S14 and Figure S2-S4).
Figure 7. Levelised cost of electricity for BPS (a), BPSnoCC (b), CPS (c), and CPSnoCC (d).
3.2. Analysis of required installed capacities and electricity generation mix during the transition
The system architecture changes gradually as the fossil generators leave the system and are replaced by RE
technologies, particularly in the BPSs. Figure 8 presents the installed capacities from 2015 until 2050 and
absolute numbers are available in the Supplementary Material (Tables S8-S10) for all scenarios. By 2050,
the total installed capacity is 321 GW, 295 GW and 134 GW in the BPS, BPSnoCC and CPS, respectively.
In the BPSs, the solar PV and wind energy shares dominate the total installed capacity by 2050. The
installed solar PV capacity is 241.7 GW, 233.4 GW and 15.8 GW in the BPS, BPSnoCC, and CPS
respectively by 2050. While wind energy installed capacity is 51.2 GW, 36.8 GW and 30.4 GW in the BPS,
BPSnoCC and CPS respectively by 2050. By 2050, the total installed capacity of thermal power plants is
26.6 GW, 23.8 GW and 81.3 GW in the BPS, BPSnoCC and CPS, respectively. The application of GHG
emissions costs resulted in a fast and high penetration of RE installed capacities as observed in the BPS in
comparison to BPSnoCC. The total capacity requirement in the BPSnoCC is low, due to the influence of
thermal plants operating on high FLH. Key power capacities required for the energy transition for South
Africa are provided in the Supplementary Material (Tables S8-S10).
Figure 8. Installed generation capacities for BPS (a), BPSnoCC (b) and CPS (c) from 2015 to 2050.
Figure 9 depicts the electricity generation mix in all scenarios from 2015 to 2050. The coal-dependent
power system can be substituted by a mix of solar PV and wind energy, complemented by hydropower and
biomass as observed in BPS and BPSnoCC as shown in Figure 9 (a-b). The results of this research indicate
that from 2035 onwards, solar PV and wind energy can drive the deep decarbonisation of the South African
power system in the BPSs. By 2050, solar PV and wind energy contributes 459 TWh and 181 TWh in the
BPS as shown in Figure 9a. Whereas, the solar PV and wind supply shares decrease to 441 TWh and 131
TWh respectively in the BPSnoCC as shown in Figure 9b, due to the influence of fossil power plants
operating on higher FLH until 2050. Nevertheless, in the BPSnoCC the share of RE generation reaches
95.6% by 2050, which implies a high cost competitiveness of RE technologies, particularly solar PV and
wind energy. Wind energy contribution remains constant from 2030 onwards, which is a consequence of
the continued cost decline of solar PV and battery storage, also observed for the case of Turkey (Kilickaplan
et al., 2017). Figure 9c shows the generation mix in the CPS. Coal, nuclear and wind energy dominate with
155 TWh, 152 TWh and 114 TWh of the total generation respectively by 2050. Coal-based electricity
supply declines from 2030 onwards as the shares of RE capacities and gas turbines increase in the energy
system, while nuclear energy contribution increases from 2040 onwards in the CPS. The share of electricity
imports increases from 2030 onwards, as hydropower imports from Inga is considered according to the IRP
(Wright et al., 2017). Additional graphical results of electricity generation by technology for all scenarios
are presented in the Supplementary Material (Figure S5).
Figure 9. Electricity generation mix for BPS (a), BPSnoCC (b) and CPS (c) from 2015 to 2050.
3.3. Assessments of system flexibility during the transition for all scenarios
The flexibility of the power system due to a high share of variable renewable energy (VRE) and dynamic
load is analysed in this section. The power system flexibility is analysed in context of storage requirement
and utilisation, grid integration and the role of gas turbines for deep decarbonisation of coal-dependent
South African power system.
3.3.1. Analysis of storage utilisation and required capacities during the transition
Storage capacity requirement and utilisation are crucial in the BPSs due to high penetration of RE in these
scenarios. By 2050, the cumulative installed storage capacity is 16.3 TWh, 2.5 TWh and 0.01 TWh in the
BPS, BPSnoCC and CPS, respectively. Gas storage dominates the total storage capacity in the Best Policy
Scenarios by 2050. By 2050, gas storage contributes 15.7 TWh in BPS, 1.9 TWh in BPSnoCC and 0.008
TWh in CPS as shown in Figure 10. The high shares of gas storage in the BPSs are required to smoothen
the synoptic and compensate the seasonal variation of RE resources. The shares of gas storage capacities
increase from 2040 onwards in BPS, as the RE shares increase to about 80%. Gas storage includes the PtG
technology, which allows production of SNG for the power system. The PtG option provides the system
with the highest flexibility and integrates most of the excess electricity generated. The prosumer and utility-
scale battery storage capacities increased from 2030 onwards in the BPSs. In the CPS, PHES provides the
entire storage need for the year 2015 and contributes to the storage mix until 2050. TES dominates the
storage mix from 2020 to 2045, due to CSP installed capacities. The heat generated through CSP and power-
to-heat is stored in the TES. The gas storage capacity increases until 2030 and remains stable afterwards.
The storage capacity in the CPS grows until 2035, and declines afterwards due to an increasing share of
nuclear energy from 2040 onwards.
Figure 10. Cumulative installed capacities of storage technologies for BPS (a), BPSnoCC (b) and CPS (c)
from 2015 to 2050.
Figure 11 shows the storage throughput during the transition and absolute numbers are presented in the
Supplementary Material (Tables S15-S17). Battery storage dominates with respect to storage throughput
during the transition in the BPS and BPSnoCC as shown in Figure 11 (a and b). Hybrid PV-battery systems
evolve to a highly economic option for the energy system. The daily charge and discharge of batteries is
needed due to high solar PV penetration in the system. Utility-scale and prosumer battery storage output
shows huge relevance during the transition, while gas storage, TES and PHES complement depending on
RE variability timescales in the system. Prosumer battery dominates in terms of output until 2030. In the
CPS, PHES and TES dominate the system until 2030 as shown in Figure 11c. Nevertheless, storage capacity
requirement and utilisation in terms of throughput is low in the CPS, due to the dominance of thermal power
plants. The storage requirement in terms of installed capacity and utilisation observed for all scenarios
during the transition is found to be directly proportional to the level of RE penetration. More graphical
results on the state of charge of storage technologies in all examined scenarios are available in
Supplementary Material (Figures S6-S10).
Figure 11. Cumulative storage output for BPS (a), BPSnoCC (b) and CPS (c) from 2015 to 2050.
Battery discharge to PtG is observed in the BPSs. This phenomenon (Battery-to-PtG effect (Gulagi et al.,
2018)) is observed nearly throughout the years. During the night and early hours of the day when demand
is low, energy stored in batteries is discharged to electrolyser units to produce gas, which is stored for long
term. By 2050, battery-to-PtG discharge is around 12 TWh in each of the Best Policy Scenarios as part of
the least cost solution, representing 2% of the electricity demand in 2050. Batteries discharging to PtG is
observed from 2035 onwards, when RE share is around 80% in the BPSs.
3.3.2. Assessment of transmission grid utilisation during the transition
The level of grid utilisation varies from time to time in BPS and BPSnoCC, while it is constant in the CPS
as shown in Figure 12. Grid utilisation in the BPS and BPSnoCC occurs mostly in the summer and spring
periods, and reduces in autumn and winter times as shown in Figure 12 (a and b). The summer and spring
periods, are the best seasons for solar and wind resource availability. During the autumn and winter periods,
gas storage compensates the seasonal variation of RE resources. In the CPS, thermal power plants are site
specific and require maximum grid utilisation in shifting energy across the country. The grid utilisation is
intense during the daytime working hours and at night, but low in the early morning hours in the CPS. The
net grid export between sub-regions ranges from 167 TWh to 197 TWh in the BPSs and 242 TWh in the
CPS by 2050. This implies that sub-regions are more independent in producing their own electricity in the
BPSs than in the CPS. In the BPS, it is observed that sub-regions with best RE resources are net exporters
and others are net importers. The Northern Cape province is the main exporting region due to excellent RE
resources and low demand. Figure 13 shows the direction and amount of electricity transmitted across the
country. The thickness of the flow indicates the amount of electricity transferred between the regions in
TWh. North Cape becomes the main exporting region by 2050 in a fully RE system in comparison to the
current situation in which Mpumalanga province supplies almost the entire country’s electricity demand
due to huge power plants located in the province.
Figure 12. Grid profile for BPS (a), BPSnoCC (b) and CPS (c) for 2050. (Grid profile is the hourly
distribution of electricity demand over the entire year)
Figure 13. Electricity transmission between the sub-regions for 2050 in the BPS
3.3.3. Analysis of gas technology relevance during the transition in the Best Policy Scenarios
The gas turbines usage is observed during low RE resource availability, particularly in the winter period.
By 2050, the capacity of gas turbines is 23 GW each in BPS and 20 GW in BPSnoCC. The average FLH
of gas turbines decline from about 2600 hours in 2015 to 700 hours in BPS and to 800 hours in BPSnoCC
by 2050. In addition, gas turbines are a relevant peaking technology because they are economically and
technically more rampable to produce high amounts of power when required. By 2050, gas turbines
generate approximately 16 TWh in the BPS and 17 TWh in BPSnoCC. Gas turbines are comprised by about
87% OCGT and 13% CCGT in the BPS as the least cost mix, with 482 FLH for OCGT and 2146 FLH for
3.4. Analysis of sub-region optimised fully renewable system structure by 2050
This section presents the sub-regional installed capacity projection for a fully RE system in 2050 as shown
in Figure 14. Solar PV dominates the share of total installed capacities, particularly solar PV single-axis
tracking followed by PV prosumers. Solar PV single-axis tracking installed capacity is 95 GW in BPS,
representing 39.4% of total solar PV capacity. While the installed capacity of PV prosumers is 81 GW in
each of the scenarios. Solar PV installations are observed in all sub-regions due to even distribution of solar
resources across the country. However, the highest share of installed solar PV capacity is found in the
Northern Cape sub-region, due to excellent solar resource in this province. Solar PV emerges as the least
cost option to meet electricity demand by 2050. Nevertheless, there are excellent wind sites in South Africa,
particularly the Eastern Cape, Western Cape and Northern Cape. Beside solar PV, wind energy plays an
important role in the transition. The total wind capacity is approximately 51 GW in BPS. Solar PV and
wind energy drive most of the system in South Africa by 2050. Additional graphical results on sub-regional
electricity generation, installed capacity, regional storage capacities and regional storage annual throughput
in 2050 can be found in the Supplementary Material (Figures S11-S14).
Figure 14. Installed generation capacities for BPS across the nine sub-regions of South Africa for 2050.
3.5. Analysis of GHG emissions under various transition scenarios
The GHG emissions trajectory during the transition for all scenarios is illustrated in Figure 15. The red
curve shows the ratio of CO2 emitted per kWh of electricity. The emissions trend in the BPSs is visualised
as shown in Figure 15 (a and b). The emissions trend in BPS and BPSnoCC shows a similar pattern, as
GHG emissions plateau by 2020 and decline afterwards in both scenarios. From 2025 onwards, emissions
decrease substantially as coal-fired plants are replaced by RE capacities, mainly solar PV and wind energy
in the BPSs. By 2050, a zero emissions system is achieved in the BPS. Deep decarbonisation of 75% to 71
MtCO2eq in 2030 and 98% to 10.2 MtCO2eq in 2040 as shown in Figure 15a for BPS. The BPSnoCC shows a
slower reduction in GHG emissions and zero emissions is not reached by 2050. However, deep
decarbonisation of 70% to 89 MtCO2eq in 2035 and 96% to 16 MtCO2eq is still achieved for the BPSnoCC in
2050, as shown in Figure 15b. The GHG emissions trend in the CPS is visualised in Figure 15c. The annual
GHG emissions reach its peak in 2030 and gradual decline afterwards as coal contribution in terms of
capacity and generation declines in the system. In the CPS, GHG emissions decline from 214 MtCO2eq in
2030 to 151 MtCO2eq in 2050.
Figure 15. The total annual GHG emissions and ratio of GHG emissions to electricity generation during
the transition for BPS (a), BPSnoCC (b) and CPS (c).
3.6. Water demand by power plants and job creation during the transition
3.6.1. Water demand of thermal power plants
Water withdrawal and water consumption of thermal power plants were calculated based on the water use
intensity factors provided by Macknick et al. (2012) and using the methodology of Lohrmann et al. (2019).
For the analysis, the subset of thermal power plants exceeding 50 MW was selected. This corresponds to
47.6 GW and accounts for 0.85% of the total thermal power generation capacity of South Africa. Figure 16
depicts the exact location of the active thermal power plants presented for the analysis.
Figure 16. Active thermal power plants exceeding 50 MW, per fuel type.
In 2015, total water consumption (combined freshwater and saline water) for thermal generation was 0.346
km3, whereas total water withdrawal was 2.72 km3. From the perspective of freshwater extractions, 0.331
km3 of freshwater was consumed (96% of the total water consumption) and 0.399 km3 of freshwater was
withdrawn (15% of the total water withdrawals). Currently, coal-based power plants account for 100% of
the freshwater consumed. The ‘leader’ among regions in freshwater extractions is the Mpumalanga
province constituting for 83% of all freshwater extractions for the power sector of South Africa.
The development of freshwater demand for both scenarios is illustrated in Figure 17. According to the BPS,
both freshwater withdrawal and consumption are estimated to be reduced 87% by the year 2030, and 99%
by 2050, respectively, compared to the 2015 level. In 2050, gas-fired power plants consume 0.0001 km3 of
freshwater, which is expected to constitute for 100% of the country´s annual freshwater consumption related
to the power sector. Opposed to that, the projections of the CPS show a decline of only 38% in freshwater
extractions by 2050. In 2050, thermal power plants consume 0.196 km3 of freshwater, of which 99.7% is
allocated for cooling of newly commissioned coal power plants. More information on the current water
demand of thermal power plants and its’ projected development during 2015-2050 is available in
Supplementary Material (Tables S18-S21 and Figures S15-S18).
Figure 17. Development of freshwater consumption and freshwater withdrawal (median values and min-
max interval): the CPS (a-b) and the BPS (c-d).
3.6.2 Job creation for the Current Policy Scenario and Best Policy Scenario
The annualised direct jobs created in the power sector during the energy transition for the BPS, as well as
the CPS were estimated based on the methodology presented by Ram et al. (2017a, 2019) and the assumed
employment generation factors can be found in the Supplementary Material (Table S22). Solar PV is
observed to be the prime job creator through the transition period, with 67% of the total jobs created by
2050, in the case of BPS as depicted in Figure 17. Whereas, coal-based power generation creates the most
jobs in the CPS, with 45% of the jobs by 2050 as indicated in Figure 18. Overall, number of direct energy
jobs created in the BPS are seen to grow massively from around 210 thousand in 2015 to nearly 408
thousand by 2035, with the massive capacity additions propelled by higher growth rates. Beyond 2035, as
growth rates stabilise, jobs created are observed to steadily reduce to over 278 thousand by 2050. On the
other hand, jobs created in the CPS remain quite stable with a marginal decrease to around 184 thousand
Figure 18. Jobs created by the various power generation and storage technologies (left) and jobs created
based on different categories with the development of electricity demand specific jobs (right) during the
energy transition from 2015 to 2050 in South Africa for the BPS.
Figure 19. Jobs created by the various power generation and storage technologies (left) and jobs created
based on different categories with the development of electricity demand specific jobs (right) during the
energy transition from 2015 to 2050 in South Africa for the CPS.
Figures 18 and 19 also indicate the distribution of jobs across the different categories during the transition
period in the BPS as well as CPS. In the case of BPS, with ramp up of installations up to 2035, bulk of the
jobs are created in the construction and installation of power generation technologies. The electricity
demand specific jobs in the BPS increases substantially from 787 jobs/TWhel in 2015 to 1148 jobs/TWhel
in 2025 with the rapid ramp up in RE installations. Beyond 2025, it stabilises around 1000 jobs/TWhel and
then declines steadily to around 511 jobs/TWhel by 2050, as shown in Figure 17. Whereas, the electricity
demand specific jobs in the case of CPS decline continually from 2020 onwards to 338 jobs/TWhel by 2050,
as indicated in Figure 19. The International Renewable Energy Agency (IRENA) estimated that the RE
sector employed nearly 10 million people worldwide in 2016, with 62,000 jobs in Africa. Nearly half of
these jobs are in South Africa and a quarter in North Africa (IRENA, 2017).
Results of this research indicate that transition towards 100% RE-based system is achievable for South
Africa. A 100% renewable based electricity is found to be the least cost option, consuming less water and
creating more jobs than the current power system, which is mainly driven by coal-fired power plants. An
addition scenario is presented in the Supplementary Material, which describes the integration of the
desalination sector to the power sector (BPS-DES). Additional information on the electricity generation
profile and energy flow diagrams are provided in the Supplementary Material (Figure S19-S24).
4.1 Analysis of key differences in Best Policy Scenarios and Current Policy Scenarios in 2050
This section compares the BPSs and the CPSs. Table 3 highlights the key differences in financial outcomes
and selected electricity parameter for 2050. This research demonstrates that a fully decarbonised power
system is the more cost optimal solution for South Africa by 2050. It reduces GHG emissions by 100%
compared to the CPS. The total annualised cost of system in the CPS is 50% higher than in the BPS as show
in Figure 20. Whereas, the total annualised cost of system obtained for 2050 in the CPSnoCC is 20% higher
than in BPSnoCC as show in Figure 20. The total annualised cost of system required in CPSnoCC and
BPSnoCC are relatively close until 2035, afterwards a disparity occurs as new investments in nuclear power
plants are incurred in the CPSnoCC. Regarding capacity requirements, the BPSs are approximately 59%
higher than required in the CPS. This is due to lower FLH of RE technologies, particularly solar PV and
wind energy that dominate the power system in the BPS. While, the total generation in the BPSs are higher
than the CPS by 16%, approximately. Results for the fully renewable end-point scenarios indicate that there
is no need for high cost and high risk nuclear energy in the future South African electricity mix.
Figure 20. Comparison of total annualised cost of system for all scenarios in 2050.
Table 3: Difference in electricity parameters and financial outcomes in 2050 for all scenarios.
Total annualised cost of
Levelised cost of electricity
The LCOE obtained for the BPSs is comparable to Breyer et al. (2018), which shows a global range of 50-
70 €/MWh. The annualised cost of system obtained for the year 2050 is 27.5 b€, 25.5 b€, 55.8 b€ and 32.9
b€ in the BPS, BPSnoCC, CPS and CPSnoCC, respectively. The financial outcomes of this research show
that RE-based systems are economically feasible in South Africa. Most of the cost reduction can be
attributed to low cost of solar PV, batteries and wind energy. In addition, RE has no fuel costs, which
compensate for the entire system investments in the BPSs. Whereas, investments in fossil power plants in
the CPSs might become a burden on the country’s economy, as newly built coal or nuclear plants are likely
to become stranded assets due to high relative cost, not only for the investment cost, but also the operation
cost. In addition, the profitability of fossil fuel based technologies will be undercut by the increasing
competitiveness of RE technologies (IEEFA, 2016).The 100% RE-based option for South Africa presented
in this study is more cost competitive than the other alternative scenarios, which still have further
disadvantages. South Africa is committed to reducing its GHG emissions, in pursuit of this goal, carbon
capture and storage (CCS) is considered as part of its climate change mitigation strategy (Beck et al., 2013;
Surridge et al., 2009). Energy system options, such as nuclear and fossil-CCS are not cost competitive
(Breyer et al., 2018). According to Ram et al. (2017b; 2018), coal-CCS CAPEX are around 3891 €/kW in
2030, while the LCOE is around 105 €/MWh. For gas-CCS, the CAPEX ranges from 1934 €/kW to 2118
€/kW in 2030, the respective LCOE ranges from 94 €/MWh to 130 €/MWh. The LCOE assumed for new
technologies in South Africa, shows that the tariffs in the year 2015 for solar PV and wind energy are 38%
and 40% lower than LCOE for new baseload coal and nuclear (Wright et al., 2017). Furthermore, based on
South Africa’s decommission plan, another BPS scenario was simulated with coal and nuclear power plant
decommissioning schedule set to 50 and 60 years, respectively. The result shows that by extending the coal
and nuclear decommissioning schedule the power system will incur additional cost from 2030 onwards,
until around 2045, in the range of 0.02 – 1.01 b€/a (0.1 – 3.9% of total annualised system cost).
The high costs observed in the CPS, is due to new investments in thermal power plants, in particular nuclear
power plants from 2040 onwards. In fact, the relative cost difference may be higher in the CPS than the
BPS, if capex assumptions for coal are considered according to IRP 2018 (DOE, 2018). Representatives
from South Africa’s largest utility mentioned, in early 2018, that nuclear would not be at the top of the
agenda and South Africa simply could not afford nuclear (EWN, 2018). In addition, nuclear projects are
susceptible to huge cost overruns (Sovacool et al., 2014). Moreover, new investment in coal power plants
in South Africa should be carefully considered, as recently added coal-based power plants have already
become stranded assets in several countries (Ram et al., 2017b; Farfan and Breyer, 2017; IEEFA, 2016).
The results of the BPSs show that no new coal and nuclear will be required in the least-cost expansion.
Furthermore, nuclear energy violates all sustainability criteria that should form a framework for a resilient
energy system design (Child et al., 2018).
4.2 Role of RE and storage technologies
The power system optimisation shows solar PV followed by wind energy drive the energy system in the
BPS and BPSnoCC. The outstanding role of PV technologies needs to be highlighted in RE dominated
scenarios for the case of South Africa. It is least-cost to supply 71% to 73% of electricity demand from
solar PV alone. PV prosumers contribute 22% to the total electricity generation in 2050. Based on living
standards measure 7 (LSM7) households and 5 kW household installations, embedded generation
residential and commercial PV in South Africa could reach 22.5 GW by 2030 (Tuson, 2014). There are
already developed regulations to guide the implementation of small-scale solar PV embedded generation in
South Africa (Tuson, 2014). In addition, South Africa is recognised to have a huge solar potential, which
is largely untapped. Barasa et al. (2018) reported on the impact of PV prosumers on a 100% RE system for
Sub-Saharan Africa for 2030 cost assumptions and concluded that the total system cost increase slightly by
3.4-3.6%, while the electricity costs of the PV prosumers go down, whereas the peak load is reduced by
5.2%, which may lead to cost reductions beyond the scope of that study. PV prosumers installed capacity
increases during the transition as the retail electricity prices increase. The growth is propelled by continuous
decline in PV battery capex anticipated during the transition. The PV prosumers appear to be an important
enabler of the transition. A study estimates the utility-scale solar PV projects to be equivalent to 220 GW
using existing environmental impact assessment, while a conservative estimation for rooftop solar PV
showed a potential capacity of 72 GW (Knorr et al., 2016). Both the rooftop and utility-scale solar PV
showed a conservative potential of about 292 GW. The plausible reason for a high solar PV penetration is
due to excellent resource conditions, low seasonal variation unlike other countries where solar PV supply
drops in winter months and continuous cost decline of PV (Bischof-Niemz and Creamer, 2018; Breyer et
al., 2018). Wind energy is expected to supply 22% to 28% to the total generation in 2050. However, wind
energy contribution remains constant from 2030 onwards, due to further costs decline of solar PV and
battery storage. In addition, if the wind capex would decline faster, a higher share of wind power generation
could be expected. South Africa has the solar, wind and land resources to technically host a power system
led by a mix of RE technologies (Bischof-Niemz and Creamer, 2018). The specific capacity density limited
in the LUT Energy System Transition model is 75 MW/km2 for optimally tilted PV and 8.4 MW/km2 for
onshore wind (Bogdanov and Breyer, 2016). Hence, an area of 3260 and 6180 km2 is needed for solar PV
and wind capacities in 2050 representing just 0.3% and 0.5% of the total land area of South Africa. The
results of this study show that solar PV and wind energy will emerge as the backbone of a fully RE-based
power system in South Africa, which is comparable to the findings of Barasa et al. (2018) for entire Sub-
Saharan Africa (SSA) based on an overnight scenario approach for 2030. They conclude that SSA countries
can be powered mainly by solar PV and wind energy. The Greenpeace Advance Energy [R]evolution
scenario (Greenpeace, 2011a), projects higher annual RE growth rates, thus achieving a renewable
electricity share of 94% and RE installed capacity of 114 GW by 2050. According to Greenpeace (2011a),
solar PV dominates the installed capacity with 40 GW (35%), followed by CSP with 35 GW (31%), and
wind energy with 27 GW (24%) by 2050. However, in the generation mix CSP dominates with 259 TWh
(54%), complemented by solar PV with 79 TWh (16%) and wind energy with 68 TWh (14%) (Greenpeace,
2011a). The Council of Scientific and Industrial Research (CSIR) demonstrates that solar PV, wind and
flexible power generators are the cheapest energy mix for South African power system (Wright et al., 2017).
The study demonstrates a least cost option for the South African power system with over 70% of RE
penetration by 2050, which uses less water and provides a higher number of job opportunities (Wright et
al., 2017). According to Wright et al. (2017), solar PV and wind energy dominate the total installed capacity
with 140 GW (45%) and 73 GW (23%), while electricity supplied by solar PV is 213 TWh (36%) and wind
is 223 TWh (38%), whereas no CSP generation is expected. The results of the BPSs in this study are
comparable to the findings of Wright et al. (2017; 2019). In the CPS, fossil power plants dominate the
power system accounting for 72% (383 TWh) of the total electricity generation in 2050. Among the RE
technologies, wind energy emerges as a relevant resource in the CPS by 2050, which contributes 114 TWh
(21%) of the total electricity generation by 2050. Upon the completion of Inga 3, 2.5 GW of the capacity is
expected to be supplied by hydropower transmitted to South Africa. Electricity imports increase from 2030
onwards, in the CPS due to imports from Inga 3. The major risks associated with relying on hydropower
imports are delays in the construction of the necessary grid extension as well as the hydropower plant (DOE,
2018). Oyewo et al. (2018) conclude that South Africa and other neighbouring countries can benefit from
the Inga hydropower development. While the host country may bear most of the economic burden, not to
mention the environmental risks. Results of the BPSs indicate that South Africa could independently meet
its electricity demand without any electricity imports.
The results of this research reveal the significant role of PtG for handling high shares of RE, as discussed
in (Gulagi et al., 2018; Ram et al., 2017a; Pleßmann et al., 2014; De Boer et al., 2014). The significance of
battery storage is noticed from 2025 onwards, particularly in the BPSs. Regarding storage outputs, battery
storage dominates due to daily requirements. By 2050, battery total output is 183 TWh (92% of total storage
output) and 186 TWh (92%) in BPS and BPSnoCC, respectively. The role of prosumers and utility-scale
batteries increased significantly from 2030 onwards. PV-battery hybrid systems emerge as the least cost
option in a fully optimised RE system. Further cost reduction of batteries is expected (Schmidt et al., 2017;
Kittner et al., 2017), which will increase PV growth (Breyer et al., 2018). Storage requirement is low in the
CPS due to the dominance of thermal power plants that run on high FLH. Grid utilisation is very high in
the beginning and towards the end of the year, particularly due to balancing demand in power deficit sub-
regions in the BPSs. In the CPS, power plants are site specific and transmission grids are frequently utilised
to supply electricity across the country. This clearly indicates the advantage of a distributed power system
observed in the BPSs, as each region could produce its own electricity and import only when needed. The
role of dispatchable gas technology is observed in the BPSs, as it is required to maintain balance between
demand and supply in the power system. The role of gas turbines in a fully RE system is discussed in
(Greenpeace, 2011a). According to Greenpeace (2011a), gas turbines installed capacity is 10 GW and
generation is 16 TWh. Similarly in the CPS, gas technologies respond in times of high demand. A recent
study on energy transition in South Africa concludes that a power grid with high RE penetration, in
particular solar PV and wind energy requires flexibility that could be provided by using flexible natural gas
fired turbines, if the costs of battery do not decrease (Klein et al., 2018).
4.3 Benefits of 100% RE
Examining the application of a GHG emissions cost during the transition, especially in the BPSs results in
a rapid transition and fast GHG emissions reduction in comparison to no GHG emissions cost scenarios.
However, the no GHG emissions cost scenarios achieved comparable results in terms of capacity,
generation, cost of electricity and GHG emissions trajectory to the BPSs. By 2050, the RE electricity
generation reaches 95.6% (579 TWh) in the no GHG emissions cost scenario, while the remaining 4.4%
(26.9 TWh) is supplied by coal and gas turbines. The BPSnoCC is about 17% lower in total costs than the
BPS, but 7% lower in costs than the CPSnoCC and 42% lower in total GHG emissions for the period 2015
to 2050. This indicates that the South African energy transition is achievable without GHG emissions cost
implementation, if least cost options are chosen.
This study presents a pathway to a fossil carbon-free economy for South Africa on an hourly basis in 5-
year intervals, which makes this study unique and a first of its kind. From an energy security perspective
(Azzuni and Breyer, 2018), analysis of this research reveals that South Africa could achieve a secure power
supply without imports. RE development in the country will foster socio-economic development, the results
show that the BPS could boost employment prospects in South Africa. The direct energy jobs created in the
BPS are seen to grow massively from around 210 thousand in 2015 to nearly 408 thousand by 2035, with
the massive capacity additions propelled by higher growth rates. Beyond 2035, as growth rates stabilise
jobs created are observed to steadily reduce to over 278 thousand by 2050. Whereas, jobs created in the
CPS remain quite stable with a marginal decrease to around 184 thousand by 2050.
The findings of this research align with the perspectives of a recent review on the feasibility of 100% RE
systems (Brown et al., 2018). Results of this research clearly show that a fully decarbonised South African
power system can be achieved between 2040 and 2050. Deep decarbonisation of South Africa’s energy
system is technically and economically feasible by 2050. Owing to the low-cost electricity driven by solar
PV and wind, South Africa can progressively pursue an electrification-of-almost-everything strategy by
coupling the low-cost renewables-led electricity generation to the transport and heat sectors (Bischof-
Niemz and Creamer, 2018). This research presents a detailed transition pathway towards a least cost and
fully decarbonised power system by 2050, which complies with the Paris Agreement target of limiting
temperature rise to 1.5 – 2 oC compared to the pre-industrial age.
The modelling outcomes reveal that a fully RE-based system is cost competitive and reliable as observed
in the BPSs in comparison to the CPSs. The total system LCOE obtained in the BPSs ranged from 47.1
€/MWh to 50.8 €/MWh and from 62.8 €/MWh to 104.9 €/MWh in the CPSs by 2050. Much of the cost
savings can be characterised by realistic ongoing cost decrease of RE technologies expected during the
transition, especially high competitiveness of solar PV-battery hybrid systems and wind energy. Solar PV
and wind dominate all the BPSs by 2050, solar PV contributes the most (75-79%) and wind energy (11-
16%) to the total installed capacities, and (71-73%) and (22-28%) to the total electricity generation,
Storage technologies, transmission grids and gas power plants provide the required flexibility in a fully RE-
based power system. The huge share of solar PV in electricity generation leads to a corresponding share of
battery storage due to daily requirements. Gas storage becomes prominent when the RE share reaches 80%
around 2035 in the BPS, balancing seasonal variation of wind and solar PV in the system. The existing coal
and nuclear plants are expected to be phased out based on their lifetimes. However, new investments in
coal and nuclear power plants may become stranded assets, which may be permanently subsidised. In
addition, they stand the risk of cost overruns as in the case of Medupi and Kusile coal-fired power projects.
Introducing GHG emissions cost would result in a rapid energy transition. Zero GHG emissions energy
system is achieved in the BPS by 2050, when the GHG emissions cost is considered. Although, a similar
emissions trajectory is observed in the BPSnoCC, but zero GHG emissions could not be achieved by 2050.
The results of the BPS without GHG emissions cost indicate that RE electricity generation can reach 95.6%,
while coal and gas turbines cover the remaining 4.4% by 2050
Energy policy in South Africa should place solar PV and wind energy at its core. It is clear that these
technologies are set to play an active role in South Africa’s future energy system as they are the least cost
options for electricity supply. A 100% RE-based system is achievable and a real policy option for South
Africa. The results of this research clearly show that a fully renewable power system consumes less water
and creates more jobs than a fossil dominated system. South Africa’s electricity demand can be met
sustainably with the country’s abundant renewable resources particularly solar and wind. Solar PV-battery
hybrid systems and wind energy drive most of the system from 2030 onwards in a fully RE-based system.
Further research has to be conducted incorporating additional energy sectors, i.e. transport, heat and
industry, for a wider analysis of the South African energy transition in the mid-term future.
The authors gratefully recognise the governmental financing of Tekes (Finnish Funding Agency for
Innovation) for the ‘Neo-Carbon Energy’ projects under the number 40101/14. Ayobami Solomon Oyewo
would like to thank LUT Foundation for the valuable scholarship. The authors thank Tobias Bischof-Niemz
for his valuable advice, which helped in further improving this research paper.
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