This document summarizes the key findings of a study that used linked energy-economy models to analyze the economy-wide implications of different power sector policies and uncertainties in South Africa. The study found that building new nuclear power was generally more expensive than renewable energy or maintaining coal, and increased electricity prices and GDP losses. Scenarios with a renewable target or lower nuclear costs had lower costs and smaller economic impacts. Imposing an early nuclear program reduced economic growth more than allowing nuclear to develop freely based on its own economics.

1. Economy-wide Implications of Policy and
Uncertainty in the Power Sector of South
Africa: A Linked Modelling Approach
June 2014
Tara Caetano, Britta Rennkamp and Bruno Merven
Energy Research Centre, University of Cape Town
in Collaboration with UNU-WIDER

2. Overview
Background on South Africa and policy/uncertainty landscape
Description of modelling framework
Nuclear case study
Future work

3. Background
Electricity in South Africa
 90% generation from coal
 large emitter of greenhouse gases, particularly CO2 (± 80% of total)
 Improving access instead of increasing capacity - constrained supply
 Low real price - rising by about 300% over last 5 years
Consideration of energy policy: Integrated Resource Plan/Integrated Energy Plan
 environmental sustainability
 depleting low cost coal reserves
 cost competitive alternatives
Important element of growth strategy → growth, employment and welfare
 Price impact
 Investment
 Other: e.g. ability to localise (how does this fit in with other policies)

4. Policy Options
Policy Options and Uncertainty
Uncertainty
Commitment to a Nuclear
Program
CO2 Price/tax level
Commitment to support a Gas
Infrastructure program
Commitment to support
Renewable Program
Open economy to electricity
imports from the region
(generated from hydro/gas)
Cost of Nuclear (R/kW) and risk of
delays and overruns
Economic growth (and demand for
electricity)
CO2 Price/tax level
Global energy commodity prices
Availability and cost of shale and
other gas resource (still under
exploration)
Future cost reductions on RE
Whether regional projects
materialise

5. Motivation for Linked Energy-
Economy-wide Models
 Need tool that can measure the macro- and socio-economic impacts of Energy
Policy
 Available tools:
 Detailed bottom-up energy sector models
 Economic models
 But existing models approaches are inadequate
 Economic Model (CGE type): over-simplification of the energy system
 Optimization Energy System Models: no/little economy and energy system feed-back
 We choose the linked iterative approach over full integration:
 Full inter-temporal integration constrains the level of detail
 Stakeholders like to see detail they can relate to

6. Electricity Sector Model: SATIM-el
 Inter-temporal bottom-up partial equilibrium optimisation model of South Africa’s
energy sector (Energy Research Centre)
 SATIM-el: South African TIMES Model - Electricity Sector
 Optimisation problem
 Minimize the sum of all discounted costs over the planning horizon subject to constraints
and system parameters
 Costs include capital costs, operating costs and taxes (e.g. CO2 tax)
 Constraints: electricity demand, resource limits, reserve margin, policy targets
 System Parameters: load curves, existing stock of power plants, new power plant options, fuel
price and availability
 Other: discount rate, taxes, etc.
 SATIM-el:
 SATIM Calibrated and parameterised in line with recent Integrated Resource Planning Report
(update 2013)
 20 time-slices, annual periods to 2040

7. Economy-wide Model: e-SAGE
 General equilibrium model of South African economy (SAGE, UNU-WIDER)
 Recursive dynamic country-level economy-wide model
 eSAGE: detailed electricity sector
 Comprehensive representation
 62 industries
 49 products
 9 factors of production
 14 representative households
 Energy treated as an intermediate input (Leontief)
 Simplified energy-saving investment behaviour, which allow sectors of production to reduce
energy intensity in response to increasing energy prices constrained by the rate of investment
in the sector
 Upward sloping labor supply curves for less-educated workers
 “Putty clay” capital and endogenous capital accumulation
 Fixed current account with flexible real exchange rate
 Savings-driven investment

8. e-SAGE-SATIM-el Iteration Process
e-SAGE
SATIM-el
• Electricity demand • Electricity production mix by technology/fuel
• Electricity price
• Power plant construction expenditure schedule
SAGE
2010 2020 2030 2050
SATIM
2007
SAGE
SATIM
SAGE
Iterativecoupledruns
Committed Forecast
SATIM
TC
TT (IRP)
2010
2020
2030
Emulating the Planning (IRP) process

9. Nuclear Case Study
Initial work done for the IAEA
South Africa has a clear commitment to nuclear power
Risk of cost and delay
Overnight costs range between US$ 5800 and US$7000 per kW
Hickley Point currently estimated around US$8000 per kW
Lead time between 7 and 12 years (although there are outliers)
Availability of renewable energy, gas and regional imports
REIPPPP coming in under budget and ahead of schedule
Shale gas potential in SA and gas fields in the region
Hydropower developments
What are some of the socio-economic implications of nuclear power?

10. Scenarios
Base remains heavily-reliant on coal
3 Nuclear scenarios
Optimistic case: overnight cost of US$5800
Higher cost: overnight cost US$7000
Nuclear delays: simulated delay of 5 years (lead time 12 years)
Renewable target of 50% renewables by 2040
0
100
200
300
400
500
600
2010 2030 2040 2010 2030 2040 2010 2030 2040 2010 2030 2040 2010 2030 2040
Base Optimistic
Nuclear
Nuclear Higher
Cost
Nuclear Delays Renewable
Target
ElectricitySupply(TWh)
Electricity Supply Breakdown for Scenarios
Imported
Diesel
Gas
Waste
Wind
Solar
Hydro
Nuclear
Coal
Electricity supply around 500 to
530 TWh in 2040
Some demand response from
CGE
Impose a reserve margin of
15%
Dispatch model needed to
account for the transmission
cost for nuclear versus
renewables

11. Investment and Prices
The total investment cost of the base case is just over R1 trillion for the period until 2040
Nuclear scenarios:
- Optimistic costs R2 trillion
- Higher cost R2,25 trillion
- Delays actually the least because of 180 TWh of nuclear supply opposed to 245 TWh
The renewable target scenario totals at R1,4 trillion, substantially less than the nuclear scenarios
attributed to the high reliance on gas generation options.
Electricity price
Lowest under the base case at 72 cents/kWh; Highest under nuclear delays at 98 cents/kWh in 2040
The under-supply of electricity is driving up the price
0
20
40
60
80
100
120
2007 2012 2017 2022 2027 2032 2037
Electricityprice
(cents/KWh)
Average Electricity Price Projection
Base Case
Optimistic
Nuclear
Nuclear
Higher Cost
Nuclear
Delays
Renewable
Target
0
50
100
150
2007 2012 2017 2022 2027 2032 2037
Annualcosts(Randbil.)
Annual Electricity Investment Cost (after interest on
debt payments)
Base Case
Optimistic
Nuclear
Nuclear
Higher Cost
Nuclear
Delays
Renewable
Target

12. Emissions
Base case emissions from the electricity sector more than double from
429 Mt of CO2 in 2010 to 856 Mt of CO2 in 2040.
Nuclear scenarios reduce emissions by around 300 Mt in 2040.
Slightly less for the renewable energy target scenario (625 Mt in 2040)
Larger share of coal-fired generation in the 2040 capacity mix
Room for more
0
100
200
300
400
500
600
700
800
900
2007 2012 2017 2022 2027 2032 2037
TotalCO2emissions(Mt)
Total Co2 Emissions to 2040
Base Case
Optimistic Nuclear
Nuclear Higher Cost
Nuclear Delays
Renewable Target

13. Jobs and Welfare
Trade-off between high
investment cost and economic
growth (savings-driven
investment)
Even burden on households
Expected more of a price effect
Electricity employment increased
by similar amounts for nuclear
and renewables (18000 and
17000)
Nuclear delays = decreased
investment demand for electricity
and increased employment

14. Conclusions
The higher cost scenario increased total investment demand by about
US$25 bn
Nuclear delays caused an escalated electricity price
Burden experienced by both households and firms
Employment increased by the same margin for the electricity sector in the
renewables case as well as the nuclear case
The indirect job loss was substantially lower for renewables
Around 100 000 more jobs were created
All scenarios take South Africa closer to its Copenhagen pledge
There is more room for reductions in the renewable energy scenario

15. Future Work
Unbundling the household price effect
Further work on labour markets
The issue of financing has to be addressed
How will this be financed? Pressure on the fiscus?
Implications of electricity supply shortages
Quantifying the risk
Expansion of the transmission network for nuclear versus renewables
Decommissioning of nuclear power
Costs and process
Nuclear waste
Sites, process and cost

16. Thank you
tara.caetano@gmail.com
http://www.erc.uct.ac.za

17. Sectoral growth
Given the savings-driven investment closure we know
that an increase in the investment allocated to the
electricity sector will have a slightly contractionary effect
on the rest of the economy.
Overall annual GDP growth remains at around 3% for all
scenarios, with the renewable target scenario having the
least contractionary effect on the economy (3,1% annual
GDP growth compared to the 3,14% in the base case).
The nuclear higher cost scenario has the largest effect
on GDP
The effect of nuclear investment on sectoral growth tells
an interesting story by changing the structure of the
economy.
The impact on the mining sector is the most
pronounced, The move away from coal-fired generation
is shown by the mining sector shinking slightly, in
realation to the base.
Metals, water distribution and construction are also
bear a higher burden due to the investment in nuclear
power.
This picture could change if there were a localisation
plan modelled along with the investment in nuclear
power. However, until the details of the localisation plan
are know, we are unable to simulate it.

18. Analysis 1: Impact of CO2 Prices
Two sets of scenarios tested at three CO2 concentration levels:
650, 550 and 450 ppm
1. Optimistic 2. Pessimistic
Nuclear Overnight Cost ($/kW)
Lead time (years)
5800
7
7000
12
RE cost reductions Optimistic Pessimistic
Domestic Natural Gas yes no
New Hydro Imports from the
region
yes no

19. Global Prices from Paltsev (2012)
650: CO2 Price -> ~$10/ton
550: CO2 Price -> ~$20/ton
450: CO2 Price -> increasing: ~$70/ton in 2030 and >$100/ton in 2050
Data set from: Sergey Palstev data set on global commodity prices for a no policy and 3 global stabilisation targets (Paltsev, S. (2012)
'Implications of Alternative Mitigation Policies on World Prices for Fossil Fuels and Agricultural Products', UNU-WIDER Working Paper
No. 2012/65, www.wider.unu.edu)
0
20
40
60
80
100
120
140
160
180
2010
2015
2020
2025
2030
2035
2040
2045
2050
OilPrice$/bbl
Oil Price
No Policy
650
550
450
0
2
4
6
8
10
12
14
16
18
20
2010
2015
2020
2025
2030
2035
2040
2045
2050
GasPrice$/tcf
Gas Price
No Policy
650
550
450
0
20
40
60
80
100
120
140
2010
2015
2020
2025
2030
2035
2040
2045
2050
CoalPrice$/ton
Coal Price
No Policy
650
550
450
0
20
40
60
80
100
120
2010
2015
2020
2025
2030
2035
2040
2045
2050
CO2Price$/ton
CO2 Price
650
550
450

20. Results: Electricity Production in Optimistic and Pessimistic
0
100
200
300
400
500
600
2010 2030 -
650
2030 -
550
2030 -
450
2040 -
650
2040 -
550
2040 -
450
ElectricityProduction(TWh)
Optimistic
Imported
Gas
Wind
Solar
Nuclear
Coal
0
100
200
300
400
500
600
2010 2030 -
650
2030 -
550
2030 -
450
2040 -
650
2040 -
550
2040 -
450
ElectricityProduction(TWh)
Pessimistic
Imported
Gas
Wind
Solar
Nuclear
Coal
0
10
20
30
40
50
60
70
80
90
100
2007
2012
2017
2022
2027
2032
2037
Electricityprice(cents/KWh)
Electricity Price
No Policy
650
550
450
Optimistic
0
20
40
60
80
100
120
140
2007 2012 2017 2022 2027 2032
Annualcosts(Randbil.)
Investment in Power Sector
No Policy
650
550
450

21. Results: Socio-Economic Impacts (optimistic)
-1.0%
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
GDPLossRelativetoReference
GDP Loss Relative to Reference
650
550
450
0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70
AGRICULTURE
INDUSTRY
Mining
Manufacturing
Food processing
Textiles and clothing
Wood and paper products and…
Petroleum products
Chemicals
Non-metal minerals
Metals
Machinery
Vehicles and transport equipment
Other manufacturing
Other industry
Electricity
Water distribution
Construction
SERVICES
Trade and hotels
Transport and communication
Financial services
Business services
Government services
Other services
Average Sectoral GDP loss 2010-2030 for 450 case (Optimistic)
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
JobLossRelativetoBase(million)
Job Losses Relative to Reference
(million)
650
550
450
0.225 0.230 0.235 0.240 0.245 0.250
Poor (0-50)
Non-poor (50-100)
Middle (50-90)
Top (90-100)
Drop in per capira consumption growth (%)
Drop in per capita consumption
growth (2010-2030)

22. Analysis 2: Nuclear Program: 10GW by 2030?
Green Barley Cases
4 Cases:
Case Nuclear
Cost/Lead
Time
RE Costs Domestic Gas Regional Hydro
1. Worst case for Nuclear –
no early program (free)
High
(pessimistic)
Low Yes Yes
2. Best case for Nuclear –
no early program (free)
Low
(optimistic)
High No No
3. Worst case for Nuclear –
imposed early program
(forced)
High
(pessimistic)
Low Yes Yes
4. Best case for Nuclear –
imposed early program
(forced)
Low
(optimistic)
High No No
(pessimistic)
(optimistic)
(pessimistic)
(optimistic)

23. GDP Loss Relative to Unforced Nuclear (Free)
-0.2%
0.0%
0.2%
0.4%
0.6%
0.8%
1.0%
1.2%
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
GDPLossrelativeto"Free"
GDP Loss relative to "Free"
worst
best
550 - Scenario
-0.2%
0.0%
0.2%
0.4%
0.6%
0.8%
1.0%
1.2%
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
GDPLossrelativeto"Free"
Worst
Best
450 - Scenario
-10
10
30
50
70
90
110
130
150
2015 2020 2025 2030
AnnualExpenditure(Randbil.)
Worst - Free
Best - Free
Worst - Forced
Best - Forced
Annual Expenditure on Power Plants
-10
10
30
50
70
90
110
130
150
2015 2020 2025 2030
AnnualExpenditure(Randbil.)
Worst - Free
Best - Free
Worst - Forced
Best - Forced
Annual Expenditure on Power Plants

24. Outstanding Issues and other Current
and Future Work
Improve integration:
i/o coefficients in eSAGE better aligned to SATIM
SATIM to take account of changes in Capital and Labour costs
Linking the full sector model: to improve energy consumption behaviour
of sectors other than electricity
More comprehensive analysis of uncertainty via Expert-Elicitation, Monte
Carlo and Stochastic Programming
Other considerations: Water constraints, spatial aspects of demand and
resource, non-dispatchability of RE techs

25. More detail on Renewables Cost Reductions
Source: IRP update 2013, department of energy, government of South Africa

26. Exports Imports
Total supply
LaborCapital
Inputs (incl.
Energy)
Sector
output
Factory
Supplier 1 Supplier n
Output 1 Output n
Domestic
supply
Warehouse
Households
Government
Investment
Intermediates
Supermarket
Traders
Freight transport
Consumption linkages
Production linkages
Overview of e-SAGE
CES
LEO
LEO
CES
CET
CES
LES LEO LEO

27. Energy as an intermediate input
LaborCapital
Inputs
Sector output
LEO
Inputs
Input 1
Energy
Input n
LEO
CES

28. Energy-saving investment behavior
Change in energy inputs per unit of output based on energy
prices
Energy product input coefficient (ioij) falls when…
Energy prices (pi) rise (provided there is some new investment)
New investment share (sj) is positive (provided the price rises)
Governed by a response elasticity (ρ)
𝑖𝑜𝑖𝑗,𝑡+1
𝑖𝑜𝑖𝑗𝑡
= 1 − 1 −
𝑃𝑗𝑡
𝑃𝑗,𝑡−1
−𝜌
∙ 𝑠𝑖

29. Macro closure rules
Upward sloping labor supply curves for less-educated workers
“Putty clay” capital and endogenous capital accumulation
Fixed current account with flexible real exchange rate
Savings-driven investment
Distinguish between electricity and non-electricity sector investment
Electricity investment differentiated by subsector (esp. import content and job
creation)
Government borrows abroad to pay for investment (gradual interest and principal
repayment)