The long-term viability of coal for power generation in ...meridianeconomics.co.za/.../2017/...Report-FINAL.pdf · Figure 6. Existing Eskom fleet plant performance. Source: Draft

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REPORT The long-term viability of coal for power generation in

South Africa

Jarrad G. Wright1, Joanne Calitz2,

Tobias Bischof-Niemz3, Crescent Mushwana4

November 2017

Document Reference Number:

20171013-CSIR-EC-ES-REP-SACOAL-0.1

[email protected], [email protected], [email protected],

[email protected]

Copyright © CSIR 2017. This document is issued subject to contract conditions and parties rights and

obligations under which this document is being issued. In the absence of such contract conditions all rights to

the intellectual property and/or contents of this document remain vested in the CSIR; this document is issued

for the sole purpose for which it is supplied; no part of this publication may be reproduced, stored in a retrieval

system or transmitted, in any form or by means electronic, mechanical, photocopying, recording or otherwise

without the express written permission of the CSIR; it may also not be lent, resold, hired out or otherwise

disposed of by way of trade in any form of binding or cover than that in which it is published

mailto:[email protected]




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Table of Contents

1 BACKGROUND .........................................................................................................................................7

2 METHODOLOGY AND APPROACH ............................................................................................................8

2.1 THE GENERAL METHODOLOGY AND APPROACH ................................................................................................. 8

2.2 APPLICATION TO SOUTH AFRICA .................................................................................................................... 9

3 DATA ASSUMPTIONS ............................................................................................................................. 11

3.1 ECONOMIC PARAMETERS ........................................................................................................................... 11

3.2 ELECTRICITY DEMAND FORECAST ................................................................................................................. 11

3.3 EXISTING AND COMMITTED CAPACITY ........................................................................................................... 11

3.4 EXISTING ESKOM FLEET PERFORMANCE ......................................................................................................... 14

3.5 SUPPLY TECHNOLOGY COST STRUCTURES ....................................................................................................... 14

3.5.1 Conventional and renewable technologies ..................................................................................... 14

3.5.2 Stationary storage technologies ..................................................................................................... 19

3.5.3 Demand shaping – electric water heaters ...................................................................................... 20

3.5.4 Demand flexibility – electric vehicles .............................................................................................. 20

3.6 ELECTRICITY SECTOR EMISSIONS AND WATER CONSUMPTION ............................................................................. 21

3.7 SYSTEM ADEQUACY................................................................................................................................... 21

4 RESULTS ................................................................................................................................................ 23

4.1 BASE CASE .............................................................................................................................................. 24

4.2 KUSILE ................................................................................................................................................... 29

4.3 ARNOT ................................................................................................................................................... 32

4.4 CAMDEN ................................................................................................................................................ 35

4.5 GROOTVLEI ............................................................................................................................................. 38

4.6 HENDRINA .............................................................................................................................................. 41

4.7 KOMATI ................................................................................................................................................. 44

4.8 GROOTVLEI, HENDRINA AND KOMATI........................................................................................................... 47

4.9 SUMMARY .............................................................................................................................................. 50

REFERENCES ................................................................................................................................................... 51

APPENDIX – BASE CASE RESULTS ................................................................................................................... 52

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List of Figures

Figure 1. Methodology for calculating the System Alternative Value of a power station ...................................... 9

Figure 2. Electrical energy demand forecast from the IRP 2016 (CSIR) and the EIUG .......................................... 11

Figure 3. South African generation capacity decommissioning schedule. Source: CSIR ...................................... 12

Figure 4. South African coal generation capacity decommissioning schedule. Source: CSIR ............................... 13

Figure 5. Technical characteristics specified in the model for all generators ....................................................... 13

Figure 6. Existing Eskom fleet plant performance. Source: Draft IRP 2016 .......................................................... 14

Figure 7. Equivalent cost assumption for solar PV based on cost structure of the technology. Source: CSIR ..... 15

Figure 8. Equivalent cost assumption for wind based on cost structure of the technology. Source: CSIR .......... 15

Figure 9. Equivalent cost assumption for CSP based on cost structure of the technology. Source: CSIR ............ 16

Figure 10. CO2 electricity sector emissions trajectories for South Africa ............................................................. 21

Figure 11. Assumptions used for system reserve requirements .......................................................................... 22

Figure 12. Base Case - High demand: Total annual installed capacity and energy ............................................... 24

Figure 13. Base Case - Low demand: Total annual installed capacity and energy................................................ 24

Figure 14. Base Case - High demand: Annual capacity factors of existing coal fleet ............................................ 25

Figure 15. Base Case - Low demand: Annual capacity factors of existing coal fleet ............................................ 25

Figure 16. Base Case - High demand: Total system cost ....................................................................................... 26

Figure 17. Base Case - High demand: Average tariff............................................................................................. 26

Figure 18. Base Case - Low demand: Total system cost ....................................................................................... 27

Figure 19. Base Case - Low demand: Average tariff ............................................................................................. 27

Figure 20. Base Case - High demand: Annual CO2 emissions and water usage .................................................... 28

Figure 21. Base Case - Low demand: Annual CO2 emissions and water usage ..................................................... 28

Figure 22. Scenario Kusile - High demand: Installed capacity and energy from Kusile with 4 units vs. 6 units ... 29

Figure 23. Scenario Kusile – Low demand: Installed capacity and energy from Kusile with 4 units vs. 6 units.... 29

Figure 24. Scenario Kusile – High demand: Additional capacity and energy required to replace last 2 Kusile units

.............................................................................................................................................................................. 30

Figure 25. Scenario Kusile – Low demand: Additional capacity and energy required to replace last 2 Kusile units

.............................................................................................................................................................................. 30

Figure 26. Scenario Kusile - High demand: System Alternative Value for Kusile .................................................. 31

Figure 27. Scenario Kusile - Low demand: System Alternative Value for Kusile ................................................... 31

Figure 28. Scenario Arnot - High demand: Installed capacity and energy from Arnot for planned and early

retirement ............................................................................................................................................................ 32

Figure 29. Scenario Arnot - Low demand: Installed capacity and energy from Arnot for planned and early

retirement ............................................................................................................................................................ 32

Figure 30. Scenario Arnot – High demand: Additional capacity and energy required to replace Arnot .............. 33

Figure 31. Scenario Arnot – Low demand: Additional capacity and energy required to replace Arnot ............... 33

Figure 32. Scenario Arnot - High demand: System Alternative Value for Arnot................................................... 34

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Figure 33. Scenario Arnot - Low demand: System Alternative Value for Arnot ................................................... 34

Figure 34. Scenario Camden - High demand: Installed capacity and energy from Camden for planned and early

retirement ............................................................................................................................................................ 35

Figure 35. Scenario Camden - Low demand: Installed capacity and energy from Camden for planned and early

retirement ............................................................................................................................................................ 35

Figure 36. Scenario Camden – High demand: Additional capacity and energy required to replace Camden ...... 36

Figure 37. Scenario Camden – Low demand: Additional capacity and energy required to replace Camden ....... 36

Figure 38. Scenario Camden - High demand: System Alternative Value for Camden .......................................... 37

Figure 39. Scenario Camden - Low demand: System Alternative Value for Camden ........................................... 37

Figure 40. Scenario Grootvlei - High demand: Installed capacity and energy from Grootvlei for planned and

early retirement .................................................................................................................................................... 38

Figure 41. Scenario Grootvlei - Low demand: Installed capacity and energy from Grootvlei for planned and


Figure 42. Scenario Grootvlei – High demand: Additional capacity and energy required to replace Grootvlei ... 39

Figure 43. Scenario Grootvlei – Low demand: Additional capacity and energy required to replace Grootvlei ... 39

Figure 44. Scenario Grootvlei - High demand: System Alternative Value for Grootvlei ....................................... 40

Figure 45. Scenario Grootvlei - Low demand: System Alternative Value for Grootvlei ........................................ 40

Figure 46. Scenario Hendrina - High demand: Installed capacity and energy from Hendrina for planned and


Figure 47. Scenario Hendrina - Low demand: Installed capacity and energy from Hendrina for planned and


Figure 48. Scenario Hendrina – High demand: Additional capacity and energy required to replace Hendrina ... 42

Figure 49. Scenario Hendrina – Low demand: Additional capacity and energy required to replace Hendrina ... 42

Figure 50. Scenario Hendrina - High demand: System Alternative Value for Hendrina ....................................... 43

Figure 51. Scenario Hendrina - Low demand: System Alternative Value for Hendrina ........................................ 43

Figure 52. Scenario Komati - High demand: Installed capacity and energy from Komati for planned and early

retirement ............................................................................................................................................................ 44

Figure 53. Scenario Komati - Low demand: Installed capacity and energy from Komati for planned and early

retirement ............................................................................................................................................................ 44

Figure 54. Scenario Komati – High demand: Additional capacity and energy required to replace Komati .......... 45

Figure 55. Scenario Komati – Low demand: Additional capacity and energy required to replace Komati .......... 45

Figure 56. Scenario Komati - High demand: System Alternative Value for Komati .............................................. 46

Figure 57. Scenario Komati - Low demand: System Alternative Value for Komati ............................................... 46

Figure 58. Scenario Gr,He,Ko - High demand: Installed capacity and energy from Grootvlei, Hendrina and

Komati for planned and early retirement ............................................................................................................. 47

Figure 59. Scenario Gr,He,Ko - Low demand: Installed capacity and energy from Grootvlei, Hendrina and

Komati for planned and early retirement ............................................................................................................. 47

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Figure 60. Scenario Gr,He,Ko – High demand: Additional capacity and energy required to replace Grootvlei,

Hendrina and Komati ............................................................................................................................................ 48

Figure 61. Scenario Gr,He,Ko – Low demand: Additional capacity and energy required to replace Grootvlei,

Hendrina and Komati ............................................................................................................................................ 48

Figure 62. Scenario Gr,He,Ko - High demand: System Alternative Value for combined Grootvlei, Hendrina and

Komati .................................................................................................................................................................. 49

Figure 63. Scenario Gr,He,Ko - Low demand: System Alternative Value for combined Grootvlei, Hendrina and

Komati .................................................................................................................................................................. 49

Figure 64. SAV for each power station studied for high and low demand forecasts ........................................... 50

List of Tables

Table 1. List of power stations which System Alternative Value was calculated for ............................................ 10

Table 2. Technology cost structures: conventional power plants ........................................................................ 17

Table 3. Technology cost structures: renewables ................................................................................................ 18

Table 4. Cost and input assumptions for stationary storage ................................................................................ 19

Table 5. Input assumptions for electric water heaters ......................................................................................... 20

Table 6. Input assumptions for electric vehicles .................................................................................................. 20

Table 7. Base Case: Existing installed capacity in MW .......................................................................................... 52

Table 8. Base Case: Committed/under construction installed capacity in MW ................................................... 53

Table 9. Base Case - High demand: New build capacity in MW (including decommissioning) ............................. 54

Table 10. Base Case - High demand: Total annual installed capacity in MW ....................................................... 55

Table 11. Base Case - High demand: Existing annual energy in GWh/yr .............................................................. 56

Table 12. Base Case - High demand: Committed/under construction annual energy in GWh/yr ........................ 57

Table 13. Base Case - High demand: New build annual energy in GWh/yr (including decommissioning) ........... 58

Table 14. Base Case - High demand: Total annual energy in GWh/yr .................................................................. 59

Table 15. Base Case - Low demand: Total annual installed capacity in MW ........................................................ 60

Table 16. Base Case - Low demand: Existing annual energy in GWh/yr ............................................................... 61

Table 17. Base Case - Low demand: Committed/under construction annual energy in GWh/yr......................... 62

Table 18. Base Case - Low demand: New build annual energy in GWh/yr (including decommissioning) ............ 63

Table 19. Base Case - Low demand: Total annual energy in GWh/yr ................................................................... 64

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List of Abbreviations CCGT Combined cycle gas turbine CO2 Carbon Dioxide COUE Cost of Unserved Energy CSP Concentrated Solar Power DoE Department of Energy ECF European Climate Foundation EIUG Energy Intensive User Group EPRI Electric Power Research Institute EWH Electric water heaters FFB Fabric filter bag IPP Independent Power Producer IRP Integrated Resource Plan LCOE Levelized Cost of Electricty LNB Low-NOx burner NERSA National Energy Regulator of South Africa NOx Nitrogen Oxides OCGT Open cycle gas turbine PM Particulate Matter PPA Power Purchase Agreement PV Photovoltaic REIPPPP Renewable Energy Independent Power Producer Procurement Programme SAV System Alternative Value SOx Sulphur Oxides

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1 Background

The CSIR was contracted by IEEFA via the European Climate Foundation (ECF) to conduct

power system analysis on the current and future South African power system as will be

discussed.

In this context, analysis was conducted on the “system alternative value” (SAV) of running

particular existing or under construction coal-fired power stations (or set of power stations) in

South Africa. In essence the SAV is the long-term absolute value which a particular power

stations’ optimised energy profile provides to the power system. This can also be expressed

as an equivalent unitised value (R/MWh). This value to the power system is clearly

dependent on the timing of energy provided by the power station, which in turn affects the

dispatch of other existing and new power generators to meet the residual load. Additionally,

the presence of particular types of generators in the power system influences the structure

of the supply mix in the long-term and thus triggers different investment decisions and

associated costs.

Once the SAV of running a particular power station (or set of power stations) is determined,

it can be compared to the expected fixed and variable operating costs as well as capital

costs of that power station (or set of power stations). In order for a new power station (or set

of power stations) to be more valuable to the power system than existing and alternative

power stations, the total cost of building and operating those power stations (or set of power

stations) should be less than the SAV. The SAV thus becomes a ceiling for the cost of any

power station (or set of power stations) considered. Similarly, for an existing power station,

the cost of operating the power station throughout its lifetime should be less than its SAV to

continue providing the most benefit to the power system. If the costs of building and

operating a power station are greater than its SAV, then it would be more economical to shut

it down (if existing) or not build it (if new) and meet the energy (and capacity) requirements

through other supply or demand side options.

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2 Methodology and approach

2.1 The general methodology and approach

The methodology determines the SAV of a particular power station (or set of power stations)

from a power system perspective. The methodology can be applied to any type of electricity

generation technology but is specifically applied in this analysis to a range of coal power

stations in South Africa.

In order to calculate the SAV, two key cost components resulting from the presence of a

particular power station (or set of power stations) are measured; namely:

(i) the effect on the investment required for additional power generators needed to

supply the residual load (when the power station or set of power generators under

study are removed); and

(ii) the effect on the dispatch of existing and possible new power generators to supply

the residual load i.e. their fixed and variable operations costs as well as fuel costs.

The steps listed below are followed for each power station (or set of power stations) under

study to calculate their respective SAV (also represented graphically in Figure 1):

(i) A least-cost capacity expansion plan is run to determine a Base Case power system

over the planning horizon. From this, the total present-value of all capital, fixed and

variable costs for the system are calculated along with the present-value of the

energy generated from the power station (or set of power stations) under study;

(ii) Step (i) is repeated with the power station (or set of power stations) under study

removed at a particular date. This can take the form of an early retirement of a

power station (relative to the expected decommissioning date) or discontinued

construction of a committed/new power station. The difference in energy as well as

capacity from removal of this power station (or set of power stations) will be replaced

by a least-cost optimal supply mix including existing power stations as well as new-

build supply options;

(iii) All costs associated with the power station (or set of power stations) under study are

entirely removed from the total system cost of both (i) and (ii). This isolates the

relative value difference provided by the power station (or set of power stations) and

the set of existing and new-build supply options;

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(iv) The absolute difference in total discounted system costs (the value difference) and

the energy difference determined previously are then used to determine the

equivalent System Alternative Value (SAV).

2.2 Application to South Africa

In this study, the methodology is applied to the South African power system only. The tool

used to implement the methodology is the energy system modelling software package

PLEXOS® [1]. The methodology is applied with hourly temporal resolution and a study

horizon of 2017-2050. Transmission constraints are excluded from the implementation i.e.

only generation costs are modelled. Broader socio-economic dimensions like existing/new

employment opportunities in the energy sector were also excluded from the analysis.

The power stations which were tested in this study are listed in Table 1.

Figure 1. Methodology for calculating the System Alternative Value of a power station

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Table 1. List of power stations which System Alternative Value was calculated for

Station name(s) Case study

Kusile The last 2 units of Kusile power station which are still under

construction.

Arnot Arnot power station being decommissioned earlier by end

financial year (FY) 2020 versus end FY 2029

Camden Camden power station being decommissioned earlier by end FY

2018 versus end FY 2023

Grootvlei Grootvlei power station being decommissioned earlier by end FY


Hendrina Hendrina power station being decommissioned earlier by end FY


Komati Komati power station being decommissioned earlier by end FY


Grootvlei, Hendrina,

Komati combined

A combination of early retirement of Grootvlei, Hendrina and

Komati as per dates above

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3 Data Assumptions

3.1 Economic parameters

The economic input parameters used in this analysis were based on the Draft IRP 2016 [2]

and includes a discount rate of 8.2% and a Cost of Unserved Energy (COUE) of

77.30 R/kWh. All costs in this study are in April 2016 Rands.

3.2 Electricity demand forecast

Two electricity demand forecasts were used in this study and are referred to as the “high”

and “low” demand forecasts. The high demand forecast was taken from the Draft IRP 2016

Base Case [2] while the low demand forecast from [3] was used which was developed by the

Energy Intensive User Group (EIUG). Figure 2 shows the historical electrical demand and

forecasted demand from the Draft IRP 2016 (“High”) and EIUG (“Low”).

Figure 2. Electrical energy demand forecast from the IRP 2016 (CSIR) and the EIUG

3.3 Existing and committed capacity

The existing and committed utility-scale generation capacity in South Africa was modelled

using publically available data. Where available, the technical, cost characteristics and

commissioning and decommissioning schedules of the existing Eskom fleet were obtained

from the Eskom website, Eskom integrated reports [4], [5] and the Draft IRP 2016 [2]. This

study assumes that all renewable capacity from the REIPPPP Bid Window 1, 2, 3, 3.5 and 4

are committed and excludes Bid Window 4 Additional, Expedited and new-build coal IPPs.

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The “P80 commissioning dates” from [2] were used for the Eskom committed plant (Medupi,

Kusile and Ingula).

Almost all existing generation capacity in South Africa will be decommissioned by 2050 as

shown in Figure 3 [3]. Figure 4 shows a more detailed breakdown of how the existing coal

fleet in South Africa is planned to decommission to 2050. As can be seen, South Africa

currently has just less than 50 GW of installed generation capacity. The Eskom coal fleet

starts to decommission from the mid-2020s onwards with 9.6 GW decommissioning between

2020-2030, 14.8 GW between 2030-2040 and 7 GW between 2040-2050. By 2050, only

Medupi, Kusile, and one unit at Majuba are still in operation. Most existing peaking capacity

decommissions just before 2040 while the only existing nuclear capacity (Koeberg)

decommissions in the mid-2040s. The capacity that comes online as part of the REIPPPP

starts to decommission in the mid-2030s until the late 2040s while the 2.2 GW hydro and

2.9 GW pumped storage capacity is still in operation by 2050.

Figure 3. South African generation capacity decommissioning schedule. Source: CSIR

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Figure 4. South African coal generation capacity decommissioning schedule. Source: CSIR

The technical characteristics shown in Figure 5 were specified for all generators in the model

implementation. Most importantly, the Eskom coal fleet was modelled with the constraint of

not being allowed to two-shift (with the exception of Majuba). The Eskom coal fleet therefore

cannot be started and shutdown (except during maintenance or unplanned outages). This

modelling constraint was added to avoid heavy cycling of the coal fleet which may be

technically infeasible in reality.

Figure 5. Technical characteristics specified in the model for all generators

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3.4 Existing Eskom fleet performance

As mentioned, the existing fleet of power generators in South Africa is predominantly made

up of the Eskom coal fleet. As defined in the Draft IRP 2016, the performance of this fleet is

as summarised in Figure 6 via the Energy Availability Factor (EAF). This study adopted the

Moderate fleet performance profile which has an average fleet availability of 80% from 2020

onwards as used in the Draft IRP 2016 Base Case.

Figure 6. Existing Eskom fleet plant performance. Source: Draft IRP 2016

3.5 Supply technology cost structures

3.5.1 Conventional and renewable technologies

The supply technology cost structures used in this study for conventional and renewable

energy technologies are summarized in Table 2 and Table 3 respectively. The costs for

conventional technologies are aligned to [2] and [6] and were inflated to April 2016 Rands

using Consumer Price Inflation (CPI).

Technologies with high expected learning rates in future are focussed on in the discussion

that follows. The starting point in 2016 for the costs of wind, solar photovoltaics (PV) and

Concentrated Solar Power (CSP) were based on the latest Renewable Independent Power

Producer Purchaser Programme (REIPPPP) Bid Window 4 (Expedited) tariffs. CSP was

assumed to follow a similar learning curve shape to that of the IRP 2010-2030 [7] until 2030

following which costs remain constant. Learning for wind was based on the latest

Bloomberg Energy Outlook report [8], which expects wind costs to decline by ~25% by 2030

and ~50% by 2040 and remain constant thereafter. Similarly, learning for solar PV was also

based on [8], whereby solar PV costs decline by ~35% by 2030 and ~70% by 2040 and

15

remain constant thereafter. The wind, solar PV and CSP cost assumptions are shown in

figures 7-9.

Figure 7. Equivalent cost assumption for solar PV based on cost structure of the technology. Source: CSIR

Figure 8. Equivalent cost assumption for wind based on cost structure of the technology. Source: CSIR

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Figure 9. Equivalent cost assumption for CSP based on cost structure of the technology. Source: CSIR

17

Table 2. Technology cost structures: conventional power plants

Coal (PF) Coal (FBC)Coal

(PF with CCS)Coal (IGCC) Nuclear (DoE) OCGT CCGT ICE (2 MW) ICE (10 MW)

Demand

responseInga

Rated capacity (net) [MW] 4 500 250 4 500 644 1 400 132 732 2 9 500 2 500

Overnight cost per capacity 2016 [ZAR/kW] 35 463 42 806 68 598 55 051 60 447 8 173 8 975 12 751 13 667 0 45 372

2030-2050 [ZAR/kW] 35 463 42 806 53 771 66 436 58 816 8 173 8 975 12 751 13 667 0 45 372

Construction time [a] 9 4 9 4 8 2 3 1 1 1 8

Capital cost (calculated)1 2016 [ZAR/kW] 39 328 47 354 76 074 60 900 78 023 8 777 9 956 12 751 13 667 0 67 249

2030-2050 [ZAR/kW] 39 328 47 354 59 631 73 495 75 917 8 777 9 956 12 751 13 667 0 67 249

Fuel cost [ZAR/GJ] 27 14 27 27 8 126 126 126 126 0 0

Heat rate [GJ/MWh] 9 812 10 788 14 106 9 758 10 657 11 519 7 395 9 477 8 780 4 0

Fixed O&M [ZAR/kW/a] 924 621 1 576 1 423 968 161 165 422 475 9 907

Variable O&M [ZAR/MWh] 80 173 148 75 37 2 22 70 120 1 441 0

Load factor (typical) [./.] 82% 82% 82% 82% 90% 6% 36% 36% 36% 2% 70%

Economic lifetime [a] 30 30 30 30 60 30 30 30 30 1 60

2% 2%

6% 6% 5% 20%

13% 13% 5% 25%

17% 17% 15% 25%

Capital phasing [%/a] 17% 17% 15% 10%

16% 10% 16% 10% 20% 5%

15% 25% 15% 25% 20% 40% 5%

11% 45% 11% 45% 10% 90% 50% 5%

3% 20% 3% 20% 10% 10% 10% 100% 100% 100% 5%

Property

Conventionals

1 From capital phasing, discount rate and economic lifetime.

All costs in Apr-2016 Rands

18

Table 3. Technology cost structures: renewables

WindSolar PV

(fixed)CPV

CSP

(tower, 3h)

CSP

(tower, 12h)

Biomass

(forestry)

Biomass

(MSW)Landfill Gas Biogas

Bagasse

(Felixton)

Bagasse

(gen)

Rated capacity (net) [MW] 100 10 10 125 125 25 25 5 5 49 53

Overnight cost per capacity 2016 [ZAR/kW] 13 250 9 243 50 375 62 564 93 168 43 893 143 004 31 048 12 751 17 821 34 165

2030 - 2040 9 780 5 486 50 375 29 013 32 495 43 893 143 004 31 048 12 751 17 821 34 165

2040 - 2050 [ZAR/kW] 7 480 2 982 50 375 29 013 32 495 43 893 143 004 31 048 12 751 17 821 34 165

Construction time [a] 4 1 1 4 4 4 4 1 1 2 3

Fuel cost [ZAR/GJ] 0 0 0 0 0 32 0 0 0 81 81

Heat rate [GJ/MWh] 0 0 0 0 0 14 243 18 991 12 302 11 999 26 874 19 327

Fixed O&M [ZAR/kW/a] 606 327 314 941 1 009 1 655 6 470 2 373 1 941 172 390

Variable O&M [ZAR/MWh] 0 0 0 1 1 66 114 62 52 9 27

Load factor (typical) [./.] 36% 24% 30% 38% 60% 85% 85% 85% 85% 55% 50%

Economic lifetime [a] 20 25 25 30 30 30 30 30 30 30 30

Capital phasing [%/a]

5% 10% 10% 10% 10%

5% 25% 25% 25% 25% 10%

10% 45% 45% 45% 45% 33% 30%

80% 100% 100% 20% 20% 20% 20% 100% 100% 67% 60%

Renewables

1 From capital phasing, discount rate and economic lifetime All costs in Apr-2016 Rands

Property

19

3.5.2 Stationary storage technologies

Stationary storage technologies modelled in this work include Lithium-ion batteries (1 hour

and 3 hour) and Compressed Air Energy Storage (CAES). The starting cost assumptions in

2016 for these technologies were based on [2] and learning was assumed for Lithium-ion

batteries based on [8] and [9] and are summarized in Table 4. Costs for CAES are assumed

to remain constant into the future.

Table 4. Cost and input assumptions for stationary storage

Pumped

Storage

Battery

(Li-Ion, 1h)

Battery

(Li-Ion, 3h)

CAES

(8h)

Rated capacity (net) [MW] 333 3 3 180

Overnight cost per capacity 2016 [ZAR/kW] 22 326 8 100 9 891 24 492

2030 - 2040 [ZAR/kW] 22 326 2 293 2 800 24 492

2040 - 2050 [ZAR/kW] 22 326 1 719 2 100 24 492

2050 [ZAR/kW] 22 326 1 147 1 400 24 492

Construction time [a] 8 1 1 4

Fuel cost [ZAR/GJ] 0 0 0 164

Heat rate [GJ/MWh] 0 4 045 4 045 4 444

Round-trip efficiency [%] 78% 89% 89% 81%

Fixed O&M [ZAR/kW/a] 201 618 618 212

Variable O&M [ZAR/MWh] 0 3 3 2

Load factor (typical) [./.] 33% 4% 12% 22%

Economic lifetime [a] 50 20 20 40

1%

1%

2%

9%

Capital phasing [%/a] 16%

22% 25%

24% 25%

20% 25%

5% 100% 100% 25%

Property

Storage technologies

All costs in Apr-2016 Rands1 From capital phasing, discount rate and economic lifetime.

20

3.5.3 Demand shaping – electric water heaters

Demand shaping in the form of residential electric water heaters (EWH) was included in this

study and was based on [10]. The input assumptions for the EWHs are summarized in Table

5. The EWH’s are assumed to have intraday controllability (can be dispatched as needed on

any given day) based on power system needs but must have a net-zero energy balance on

a daily basis (no substitution effect).

Table 5. Input assumptions for electric water heaters

3.5.4 Demand flexibility – electric vehicles

Similar to the modelling of a demand shaping resource for EWHs, electric vehicles (e-

vehicles) were included as a flexible demand side option in the model. The e-vehicle fleet

assumptions were adapted from [10] and are summarized in Table 6. The e-vehicle fleet

was modelled similarly to the EWH demand shaping resource in that it also has intraday

controllability based on power system needs but needs to have a net-zero energy balance

on a daily basis.

Table 6. Input assumptions for electric vehicles

Property Unit 2016-2019 2020 2030 2040 2050

Population [mln] 55.7 - 57.5 58.0 61.7 64.9 68.2

Number of HHs [mln] 16.9 - 18.1 18.5 22.4 26.0 27.3

Residents per HH [ppl/HH] 3.29 - 3.17 3.13 2.75 2.50 2.50

HHs with EWH [%] 28 - 33 34 50 75 100

HHs with EWH [mln] 4.7 - 5.9 6.3 11.2 19.5 27.3

Demand shaping adoption [%] - 2 25 100 100

Demand shaping [TWh/a] - 0.4 5.4 28.3 26.4

Demand shaping [GWh/d] - 1.1 14.9 77.4 72.3

Demand shaping (demand increase) [MW] - 371 4 991 25 970 24 265

Demand shaping (demand decrease) [MW] - 46 620 3 226 3 015

Property Unit 2016-2019 2020 2030 2040 2050

Population [mln] 0 - 0 58.0 61.7 64.9 68.2

Number of motor vehicles [mln] 7 - 8.2 8.5 12.3 16.2 20.5

EVs adoption [%] 0 - 0 1.5 8.1 28.5 48.9

Number of EVs [mln] 0 - 0 0.1 1.0 4.6 10.0

EVs energy requirement [TWh/a] - 0.5 3.7 17.1 37.0

EVs energy requirement [GWh/d] 3.7 3.7 3.7 3.7 3.7

EVs (demand increase) [MW] - 100 4 600 44 300 95 800

EVs (demand decrease) [MW] - 100 400 2 000 4 200

21

3.6 Electricity sector emissions and water consumption

Relative power station emission rates for CO2, SOx, NOx, and particulate matter (PM) for all

technologies were modelled and aligned with the Draft IRP 2016. Water consumption rates

were also modelled for each power station and also aligned with the Draft IRP 2016. The

results in this study focus on the resulting electricity sector CO2 emissions trajectories as the

IRP 2016 Moderate Decline CO2 trajectory constraint was assumed across all scenarios as

shown in Figure 10.

Figure 10. CO2 electricity sector emissions trajectories for South Africa

3.7 System adequacy

As described in the approach, this study entailed least-cost capacity expansion planning

which was solved by the co-optimisation between existing resource utilisation (which

decommission over time) and new technology investments while ensuring the energy

balance is maintained in every period in the least-cost manner, subject to adequacy

requirements. System adequacy can be measured using a number of metrics, including the

use of deterministic planning reserve margins or probabilistic metrics such as the Loss of

Load Probability (LOLP)/Loss of Load Expectation (LOLE). In this work all capacity

expansion scenarios were optimized to the same level of system adequacy (via the use of a

deterministic reserve requirement) and Unserved Energy being priced very high (thus

inherently minimized). System operational reserve requirements as specified by Eskom up

22

to 2022 are extrapolated forward thereafter towards 2050 for all scenarios as shown in

Figure 11.

Figure 11. Assumptions used for system reserve requirements

23

4 Results

As specified in Section 2, a least cost electricity expansion was conducted in PLEXOS from

2017-2050 to meet the low and high forecasted electricity demand scenarios. A Base Case

scenario was run to provide a reference case from which all other scenarios are compared.

In this Base Case, the Eskom coal-fleet is decommissioned as per their 50 year life or as

stated previously. Additionally, all 6 units at Kusile power station are commissioned.

Following this, 7 scenarios were modelled whereby the power stations being studied were

either decommissioned earlier than planned or in the case of Kusile, the last 2 units were not

completed. By comparing each scenario to the Base Case, the SAV of the corresponding

power stations were calculated.

The 7 scenarios are listed below:

Kusile (2 units);

Arnot;

Camden;

Grootvlei;

Hendrina;

Komati; and

A combination of Grootvlei, Hendrina and Komati.

Results from these scenarios are provided in the sections that follow.

24

4.1 Base Case

The capacity expansion results of the Base Case are shown in Figure 12 and Figure 13 for

the high and low demand forecasts respectively. These results are also tabled in Appendix

A.

Figure 12. Base Case - High demand: Total annual installed capacity and energy

Figure 13. Base Case - Low demand: Total annual installed capacity and energy

As can be seen in Figure 12 and Figure 13, for both the high and low demand forecasts new

capacity in the form of wind, solar PV and flexible technology options (peaking (OCGTs) and

batteries) are deployed up to 2050 with the earliest new build starting around 2023. Mid-

merit gas options (CCGTs) are deployed beyond 2040 in the high demand scenario. There

is some curtailment of wind and solar PV evident from 2030 onwards as the renewable

energy share increases. Curtailed energy is costed in the model as a result of the

investment in capacity being fully captured (whether the energy is used or not) and thus the

decision to build more wind and/or solar PV with some curtailment is made on a purely

25

economic basis. The potential additional value of this curtailed energy being used in other

applications was not considered in this research.

The annual capacity factors of the existing coal fleet in the Base Case are shown in Figure

14 and Figure 15 for the high and low demand forecasts respectively. As can be seen,

capacity factors remain relatively constant between the two demand forecast scenarios due

to the commitment (must-run) constraint of the coal fleet and the dispatch merit order of coal

in the South African power system i.e. it is cheap to run. Majuba was modelled with the

ability to cycle freely, resulting in a very low capacity factor in the early years where excess

capacity is present (Medupi and Kusile commissioning). Majuba’s load factor increases

towards 2030 as the existing coal fleet decommissions but reduces again as more

economical solar PV and wind are deployed thereafter.

Figure 14. Base Case - High demand: Annual capacity factors of existing coal fleet

Figure 15. Base Case - Low demand: Annual capacity factors of existing coal fleet

26

The annual total system cost and average tariff trajectories for the high and low demand

forecasts are shown in Figures 16 – 19. The average tariff (in real-terms) is expected to

peak in the early 2020s and remain constant for some time thereafter following which an

absolute reduction is expected as a result of relatively cheap new-build solar PV and wind

being deployed into the future.

Figure 16. Base Case - High demand: Total system cost

Figure 17. Base Case - High demand: Average tariff

27

Figure 18. Base Case - Low demand: Total system cost

Figure 19. Base Case - Low demand: Average tariff

The resulting annual CO2 emissions and water usage for the Base Case are shown in Figure

20 and Figure 21 for the high and low demand scenarios respectively. It can be seen for

both demand forecasts that annual CO2 emissions and water usage from the electricity

sector decline sharply after 2025 as the coal fleet decommissions and no new coal capacity

is built. The PPD (Moderate) CO2 emissions trajectory is also never binding, i.e. the least

cost expansion build consists of zero/low CO2 emitting technologies. The least-cost build-

out results in a CO2 emissions trajectory below the PPD (Moderate) trajectory for all years

into the future.

28

Figure 20. Base Case - High demand: Annual CO2 emissions and water usage

Figure 21. Base Case - Low demand: Annual CO2 emissions and water usage

29

4.2 Kusile

In this scenario the last 2 units of Kusile are not built and the least-cost expansion model is

re-run. The purpose of this scenario is to identify the SAV of the last two Kusile units. Figure

22 and Figure 23 show the capacity and energy of Kusile with 4 units and 6 units as well as

the stations annual capacity factor for the high and low demand forecasts respectively. The

average annual energy output of Kusile is similar for both forecasts, indicating that Kusile’s

output is relatively robust to changes in electricity demand. The average annual energy

output with 6 units and 4 units is ~30 TWh/yr and ~20 TWh/yr respectively. The changes in

energy output and new capacity built to supply the ~10 TWh//yr energy “gap” from not

building the last 2 Kusile units is shown in Figure 24 and Figure 25 for the high and low

demand forecast scenarios respectively.

Figure 22. Scenario Kusile - High demand: Installed capacity and energy from Kusile with 4 units vs. 6 units

Figure 23. Scenario Kusile – Low demand: Installed capacity and energy from Kusile with 4 units vs. 6 units

30

Figure 24. Scenario Kusile – High demand: Additional capacity and energy required to replace last 2 Kusile units

Figure 25. Scenario Kusile – Low demand: Additional capacity and energy required to replace last 2 Kusile units

The energy from the last 2 Kusile units is primarily replaced by additional energy from the

existing coal fleet in the first 4 years, followed by new wind, solar PV, peaking, batteries and

gas capacity in the high demand forecast scenario. Similarly, in the low demand forecast

scenario the initial energy gap is supplied by the existing coal fleet (but for a longer period),

followed by the deployment of new wind, solar PV, peaking and battery capacity.

The SAV for the last 2 units of Kusile was found to be between 0.57 - 0.61 R/kWh for the

low and high demand forecast scenarios respectively as shown in Figure 26 and Figure 27.

31

The total discounted system costs with and without all costs associated with the power

station under study (Kusile) are shown for the Base Case (Kusile 6 units) and the scenario

with Kusile having only 4 units. The SAV is then the value difference divided by the energy

difference.

Figure 26. Scenario Kusile - High demand: System Alternative Value for Kusile

Figure 27. Scenario Kusile - Low demand: System Alternative Value for Kusile

32

4.3 Arnot

In this scenario Arnot is decommissioned early in FY 2020 instead of the planned

decommissioning date in FY 2029. The purpose of this scenario is to calculate the SAV of

Arnot providing energy for its full 50 year life as opposed to being decommissioned earlier.

Figure 28 and Figure 29 show the capacity and energy of Arnot for the scheduled and early

retirement scenarios for the high and low demand forecasts respectively. The changes in

energy output and new capacity built to supply the energy gap from retiring Arnot early are

shown in Figure 30 and Figure 31 for the high and low demand forecast scenarios

respectively.

Figure 28. Scenario Arnot - High demand: Installed capacity and energy from Arnot for planned and early

retirement

Figure 29. Scenario Arnot - Low demand: Installed capacity and energy from Arnot for planned and early

retirement

33

Figure 30. Scenario Arnot – High demand: Additional capacity and energy required to replace Arnot

Figure 31. Scenario Arnot – Low demand: Additional capacity and energy required to replace Arnot

The energy gap from the early retirement of Arnot is primarily replaced by additional energy

from the existing coal fleet in the first few years. Some additional capacity is also built in the

form of OCGTs and batteries for the purpose of providing capacity to the system. From FY

2025 onwards additional wind, solar PV, peaking and battery capacity is built in the high and

low demand forecast scenarios.

The SAV for Arnot was found to between 0.34 – 0.50 R/kWh for the low and high demand

forecast scenarios respectively as shown in Figure 32 and Figure 33.

34

Figure 32. Scenario Arnot - High demand: System Alternative Value for Arnot

Figure 33. Scenario Arnot - Low demand: System Alternative Value for Arnot

35

4.4 Camden

In this scenario Camden is decommissioned early in FY 2018 instead of the planned


Camden providing energy for its planned life as opposed to being decommissioned earlier.

The least-cost expansion model was re-run and Figure 34 and Figure 35 show the capacity

and energy of Camden for the scheduled and early retirement scenarios for the high and low

demand forecasts respectively. The changes in energy output and new capacity built to

supply the energy gap from retiring Camden early is shown in Figure 36 and Figure 37 for

the high and low demand forecast scenarios respectively.

Figure 34. Scenario Camden - High demand: Installed capacity and energy from Camden for planned and early

retirement

Figure 35. Scenario Camden - Low demand: Installed capacity and energy from Camden for planned and early

retirement

36

Figure 36. Scenario Camden – High demand: Additional capacity and energy required to replace Camden

Figure 37. Scenario Camden – Low demand: Additional capacity and energy required to replace Camden

The energy gap from the early retirement of Camden is primarily replaced by additional

energy from the existing coal fleet. New capacity is not built before FY 2023 in both the high

and low demand forecast scenarios. Small differences in capacity and energy following the

decommissioning of the station are a result of conditions inherently changing early on in the

time horizon which then perpetuate into the future as a result of the early decommissioning

of the station under study.

The SAV for Camden was found to between 0.22 – 0.36 R/kWh for the low and high

demand forecast scenarios respectively as shown in Figure 38 and Figure 39.

37

Figure 38. Scenario Camden - High demand: System Alternative Value for Camden

Figure 39. Scenario Camden - Low demand: System Alternative Value for Camden

38

4.5 Grootvlei

In this scenario Grootvlei is decommissioned early in FY 2019 instead of the planned


Grootvlei providing energy for its planned life as opposed to being decommissioned earlier.

Figure 40 and Figure 41 show the capacity and energy of Grootvlei for the scheduled and

early retirement scenarios for the high and low demand forecasts respectively. The changes

in energy output and new capacity built to supply the energy gap from retiring Grootvlei early

is shown in Figure 42 and Figure 43 for the high and low demand forecast scenarios

respectively.

Figure 40. Scenario Grootvlei - High demand: Installed capacity and energy from Grootvlei for planned and early

retirement

Figure 41. Scenario Grootvlei - Low demand: Installed capacity and energy from Grootvlei for planned and early

retirement

39

Figure 42. Scenario Grootvlei – High demand: Additional capacity and energy required to replace Grootvlei

Figure 43. Scenario Grootvlei – Low demand: Additional capacity and energy required to replace Grootvlei

The energy gap from the early retirement of Grootvlei is primarily replaced by additional

energy from the existing coal fleet, with relatively small capacity additions of wind, solar PV,

peaking and batteries for both the high and low demand forecast scenarios.

The SAV for Grootvlei was found to between 0.31 – 0.47 R/kWh for the low and high


40

Figure 44. Scenario Grootvlei - High demand: System Alternative Value for Grootvlei

Figure 45. Scenario Grootvlei - Low demand: System Alternative Value for Grootvlei

41

4.6 Hendrina

In this scenario Hendrina is decommissioned early in FY 2018 instead of the planned


Hendrina providing energy for its planned life as opposed to being decommissioned earlier.

Figure 46 and Figure 47 show the capacity and energy of Hendrina for the scheduled and


in energy output and new capacity built to supply the energy gap from retiring Hendrina early

is shown in Figure 48 and Figure 49 for the high and low demand forecast scenarios

respectively.

Figure 46. Scenario Hendrina - High demand: Installed capacity and energy from Hendrina for planned and early

retirement

Figure 47. Scenario Hendrina - Low demand: Installed capacity and energy from Hendrina for planned and early

retirement

42

Figure 48. Scenario Hendrina – High demand: Additional capacity and energy required to replace Hendrina

Figure 49. Scenario Hendrina – Low demand: Additional capacity and energy required to replace Hendrina

The energy gap from the early retirement of Hendrina is primarily replaced by additional

energy from the existing coal fleet, with relatively small capacity additions of wind, solar PV,

peaking and batteries for both the high and low demand forecast scenarios.

The SAV for Hendrina was found to between 0.23 – 0.41 R/kWh for the low and high


43

Figure 50. Scenario Hendrina - High demand: System Alternative Value for Hendrina

Figure 51. Scenario Hendrina - Low demand: System Alternative Value for Hendrina

44

4.7 Komati

In this scenario Komati is decommissioned early in FY 2020 instead of the planned


Komati providing energy for its planned life as opposed to being decommissioned earlier.

Figure 52 and Figure 53 show the capacity and energy of Komati for the scheduled and


in energy output and new capacity built to supply the energy gap from retiring Komati early is

shown in Figure 54 and Figure 55 for the high and low demand forecast scenarios

respectively.

Figure 52. Scenario Komati - High demand: Installed capacity and energy from Komati for planned and early

retirement

Figure 53. Scenario Komati - Low demand: Installed capacity and energy from Komati for planned and early

retirement

45

Figure 54. Scenario Komati – High demand: Additional capacity and energy required to replace Komati

Figure 55. Scenario Komati – Low demand: Additional capacity and energy required to replace Komati

The energy gap from the early retirement of Komati is initially primarily replaced by

additional energy from the existing coal fleet, as well as relatively small additional wind, solar

PV, peaking and battery capacity in the high and low demand forecast scenarios.

The SAV for Komati was found to between 0.31 – 0.48 R/kWh for the low and high demand

forecast scenarios respectively as shown in Figure 56 and Figure 57.

46

Figure 56. Scenario Komati - High demand: System Alternative Value for Komati

Figure 57. Scenario Komati - Low demand: System Alternative Value for Komati

47

4.8 Grootvlei, Hendrina and Komati

In this scenario Grootvlei, Hendrina and Komati (Gr,He,Ko) are decommissioned early as

per the dates in section 4.5, 4.6 and 4.7. The purpose of this scenario is to calculate the

SAV of the combination of Grootvlei, Hendrina and Komati providing energy for their planned

lives as opposed to being decommissioned earlier. Figure 58 and Figure 59 show the

capacity and energy of Komati for the scheduled and early retirement scenarios for the high

and low demand forecasts respectively. The changes in energy output and new capacity

built to supply the energy gap from retiring Komati early is shown in Figure 60 and Figure 61

for the high and low demand forecast scenarios respectively.

Figure 58. Scenario Gr,He,Ko - High demand: Installed capacity and energy from Grootvlei, Hendrina and Komati

for planned and early retirement

Figure 59. Scenario Gr,He,Ko - Low demand: Installed capacity and energy from Grootvlei, Hendrina and Komati

for planned and early retirement

48

Figure 60. Scenario Gr,He,Ko – High demand: Additional capacity and energy required to replace Grootvlei,

Hendrina and Komati

Figure 61. Scenario Gr,He,Ko – Low demand: Additional capacity and energy required to replace Grootvlei,

Hendrina and Komati

The energy gap from the early retirement of Grootvlei, Hendrina and Komati is initially

primarily replaced by additional energy from the existing coal fleet. Additional peaking,

battery and solar PV capacity is also built initially, followed by additional wind capacity from

FY 2023, in the high and low demand forecast scenarios.

The SAV for the combined stations was found to between 0.31 – 0.47 R/kWh for the low and

high demand forecast scenarios respectively as shown in Figure 62 and Figure 63.

49

Figure 62. Scenario Gr,He,Ko - High demand: System Alternative Value for combined Grootvlei, Hendrina and

Komati

Figure 63. Scenario Gr,He,Ko - Low demand: System Alternative Value for combined Grootvlei, Hendrina and

Komati

50

4.9 Summary

The SAVs for all scenarios considered are shown in Figure 64 below. As expected, the SAV

of a power station is generally higher for higher demand forecasts i.e. more valuable to the

system. Additionally, the SAV of the oldest power stations which do not have many years

left and are generating in a period of “over-capacity”, are lower than Kusile which generates

throughout the study horizon beyond the period of excess capacity.

Figure 64. SAV for each power station studied for high and low demand forecasts

51

References

[1] Energy Exemplar, “PLEXOS Integrated Energy Model.” 2017.

[2] Republic of South Africa Department of Energy, “Integrated Resource Plan Update:

Assumptions, Base Case Results and Observations.,” 2016.

[3] J. G. Wright, T. Bischof-Niemz, J. Calitz, C. Mushwana, R. Van Heerden, and M.

Senatla, “Presentation: Formal comments on the Integrated Resource Plan (IRP)

Update Assumptions, Base Case and Observations 2016,” 2017.

[4] Eskom Holdings SOC Ltd, “Annual financial statements 2015,” no. March, pp. 1–25,

2015.

[5] Eskom Holdings SOC Ltd, “Integrated Annual Financial Report 31 March 2016,” 2016.

[6] EPRI, “Power Generation Technology Data for Integrated Resource Plan of South

Africa,” no. August, 2015.

[7] Department of Energy, “Integrated Resource Plan for Electricity 2010-2030,” 2011.

[8] Bloomberg, “New Energy Outlook 2017,” 2017.

[9] IRENA, Electricity Storage and Renewables : Costs and Markets To 2030, no.

October. 2017.

[10] J. G. Wright, T. Bischof-Niemz, J. Calitz, C. Mushwana, R. Van Heerden, and M.

Senatla, “Report: Formal comments on the Integrated Resource Plan (IRP) Update

Assumptions, Base Case and Observations 2016,” 2017.

52

Appendix – Base Case results

Table 7. Base Case: Existing installed capacity in MW

Coal Nuclear Gas Peaking Hydro Wind CSP Solar PV

Biomass/-

gas

Pumped

storage

Li-Ion

(1hr + 3 hr)

Demand

Response

2016 36 060 1 860 425 3 419 2 179 1 306 200 1 479 264 1 580 0 0

2017 36 060 1 860 425 3 419 2 179 1 306 200 1 479 264 1 580 0 0

2018 35 900 1 860 425 3 419 2 179 1 306 200 1 479 264 1 580 0 0

2019 35 900 1 860 425 3 419 2 179 1 306 200 1 479 264 1 580 0 0

2020 35 140 1 860 425 3 419 2 179 1 306 200 1 479 264 1 580 0 0

2021 34 780 1 860 425 3 419 2 179 1 306 200 1 479 264 1 580 0 0

2022 34 020 1 860 425 3 419 2 179 1 306 200 1 479 264 1 580 0 0

2023 33 450 1 860 425 3 419 2 179 1 306 200 1 479 264 1 580 0 0

2024 33 060 1 860 425 3 419 2 179 1 306 200 1 479 264 1 580 0 0

2025 32 220 1 860 425 3 419 2 179 1 306 200 1 479 264 1 580 0 0

2026 30 530 1 860 425 3 077 2 179 1 306 200 1 479 264 1 580 0 0

2027 29 200 1 860 425 3 077 2 179 1 306 200 1 479 264 1 580 0 0

2028 27 310 1 860 425 3 077 2 179 1 306 200 1 479 264 1 580 0 0

2029 25 400 1 860 425 3 077 2 179 1 306 200 1 479 264 1 580 0 0

2030 23 080 1 860 425 3 077 2 179 1 306 200 1 479 264 1 580 0 0

2031 21 320 1 860 425 3 077 2 179 1 306 200 1 479 264 1 580 0 0

2032 20 160 1 860 425 3 077 2 179 1 306 200 1 479 264 1 580 0 0

2033 19 000 1 860 425 3 077 2 179 1 306 200 1 479 264 1 580 0 0

2034 18 420 1 860 425 3 077 2 179 370 200 1 479 264 1 580 0 0

2035 17 250 1 860 425 3 077 2 179 0 200 1 479 264 1 580 0 0

2036 15 500 1 860 425 3 077 2 179 0 200 1 479 264 1 580 0 0

2037 13 680 1 860 425 1 005 2 179 0 200 1 479 264 1 580 0 0

2038 10 660 1 860 425 1 005 2 179 0 200 1 479 264 1 580 0 0

2039 9 450 1 860 425 1 005 2 179 0 200 1 479 264 1 580 0 0

2040 7 660 1 860 425 1 005 2 179 0 200 435 264 1 580 0 0

2041 5 120 1 860 425 1 005 2 179 0 200 435 264 1 580 0 0

2042 4 480 1 860 425 1 005 2 179 0 200 0 264 1 580 0 0

2043 3 840 1 860 425 1 005 2 179 0 200 0 264 1 580 0 0

2044 3 840 0 425 1 005 2 179 0 200 0 264 1 580 0 0

2045 3 840 0 425 0 2 179 0 100 0 264 1 580 0 0

2046 3 230 0 425 0 2 179 0 0 0 264 1 580 0 0

2047 2 620 0 425 0 2 179 0 0 0 264 1 580 0 0

2048 2 010 0 425 0 2 179 0 0 0 264 1 580 0 0

2049 1 340 0 425 0 2 179 0 0 0 264 1 580 0 0

2050 670 0 425 0 2 179 0 0 0 264 1 580 0 0

53

Table 8. Base Case: Committed/under construction installed capacity in MW


Biomass/-

gas

Pumped

storage

Li-Ion

(1hr + 3 hr)

Demand

Response

2016 722 0 0 0 0 154 0 0 0 0 0 0

2017 722 0 0 0 5 928 400 115 41 1 332 0 0

2018 2 889 0 0 0 5 1 464 400 340 41 1 332 0 0

2019 4 334 0 0 0 5 1 464 400 415 91 1 332 0 0

2020 6 501 0 0 0 5 1 464 400 415 91 1 332 0 0

2021 7 224 0 0 0 5 1 464 400 415 91 1 332 0 0

2022 7 947 0 0 0 5 1 464 400 415 91 1 332 0 0

2023 8 670 0 0 0 5 1 464 400 415 91 1 332 0 0

2024 8 670 0 0 0 5 1 464 400 415 91 1 332 0 0

2025 8 670 0 0 0 5 1 464 400 415 91 1 332 0 0

2026 8 670 0 0 0 5 1 464 400 415 91 1 332 0 0

2027 8 670 0 0 0 5 1 464 400 415 91 1 332 0 0

2028 8 670 0 0 0 5 1 464 400 415 91 1 332 0 0

2029 8 670 0 0 0 5 1 464 400 415 91 1 332 0 0

2030 8 670 0 0 0 5 1 464 400 415 91 1 332 0 0

2031 8 670 0 0 0 5 1 464 400 415 91 1 332 0 0

2032 8 670 0 0 0 5 1 464 400 415 91 1 332 0 0

2033 8 670 0 0 0 5 1 464 400 415 91 1 332 0 0

2034 8 670 0 0 0 5 676 400 415 91 1 332 0 0

2035 8 670 0 0 0 5 676 400 415 91 1 332 0 0

2036 8 670 0 0 0 5 676 400 415 91 1 332 0 0

2037 8 670 0 0 0 5 540 400 415 91 1 332 0 0

2038 8 670 0 0 0 5 0 400 415 91 1 332 0 0

2039 8 670 0 0 0 5 0 400 415 91 1 332 0 0

2040 8 670 0 0 0 5 0 400 415 91 1 332 0 0

2041 8 670 0 0 0 5 0 400 415 91 1 332 0 0

2042 8 670 0 0 0 5 0 400 415 91 1 332 0 0

2043 8 670 0 0 0 5 0 400 415 91 1 332 0 0

2044 8 670 0 0 0 5 0 400 0 91 1 332 0 0

2045 8 670 0 0 0 5 0 400 0 91 1 332 0 0

2046 8 670 0 0 0 5 0 400 0 91 1 332 0 0

2047 8 670 0 0 0 5 0 100 0 67 1 332 0 0

2048 8 670 0 0 0 5 0 0 0 50 1 332 0 0

2049 8 670 0 0 0 5 0 0 0 0 1 332 0 0

2050 8 670 0 0 0 5 0 0 0 0 1 332 0 0

54

Table 9. Base Case - High demand: New build capacity in MW (including decommissioning)


Biomass/-

gas

Pumped

storage

Li-Ion

(1hr + 3 hr)

Demand

Response

2016 0 0 0 0 0 0 0 0 0 0 0 0

2017 0 0 0 0 0 0 0 0 0 0 0 0

2018 0 0 0 0 0 0 0 0 0 0 0 0

2019 0 0 0 0 0 0 0 0 0 0 0 0

2020 0 0 0 0 0 0 0 0 0 0 331 101

2021 0 0 0 0 0 0 0 0 0 0 331 163

2022 0 0 0 0 0 0 0 0 0 0 1 217 233

2023 0 0 0 1 089 0 0 0 644 0 0 1 488 307

2024 0 0 0 1 943 0 0 0 759 0 0 2 450 388

2025 0 0 0 1 943 0 2 432 0 3 327 0 332 2 450 477

2026 0 0 0 3 123 0 5 809 0 5 311 0 332 3 090 573

2027 0 0 0 4 066 0 10 470 0 8 713 0 332 3 492 676

2028 0 0 0 6 290 0 12 897 0 17 035 0 332 5 671 788

2029 0 0 0 6 290 0 14 368 0 20 814 0 332 8 957 910

2030 0 0 0 6 290 0 20 357 0 24 234 0 332 8 957 1 042

2031 0 0 0 11 851 0 24 418 0 36 830 0 332 9 463 1 280

2032 0 0 0 11 851 0 27 938 0 36 830 0 332 8 783 1 539

2033 0 0 0 11 851 0 34 613 0 38 604 0 332 10 077 1 820

2034 0 0 0 12 809 0 39 947 0 40 650 0 332 10 455 2 125

2035 0 0 0 13 388 0 45 593 0 45 765 0 332 14 161 2 451

2036 0 0 0 17 774 0 47 389 0 51 485 0 359 13 521 2 800

2037 0 0 0 17 774 0 53 310 0 52 645 0 359 13 521 3 168

2038 0 0 0 17 774 0 68 104 0 61 459 0 359 14 035 3 555

2039 0 0 0 17 774 0 69 459 0 71 077 0 359 18 580 3 957

2040 0 0 2 717 18 528 0 70 914 0 77 650 0 359 18 257 4 372

2041 0 0 2 717 27 851 0 70 914 0 79 410 0 2 201 18 311 4 692

2042 0 0 2 717 28 244 0 75 937 0 85 875 0 2 494 18 110 5 014

2043 0 0 2 717 28 244 0 80 365 0 87 667 0 2 494 16 544 5 334

2044 0 0 2 717 28 244 0 94 856 0 91 570 0 2 494 15 204 5 647

2045 0 0 2 717 28 244 0 93 218 0 91 570 0 2 494 15 204 5 951

2046 0 0 2 717 28 244 0 98 301 0 91 570 0 2 494 20 521 6 243

2047 0 0 2 717 35 795 0 93 640 0 95 298 0 3 042 21 160 6 518

2048 0 0 2 717 35 795 0 94 782 0 112 033 0 3 346 24 835 6 777

2049 0 0 2 717 35 795 0 102 968 0 111 918 0 3 346 21 435 7 018

2050 0 0 2 717 35 795 0 108 901 0 112 566 0 3 346 21 427 7 239

55

Table 10. Base Case - High demand: Total annual installed capacity in MW1

1 Total annual installed capacity = existing capacity + committed/under construction capacity + new build capacity

– decommissioned capacity


Biomass/-

gas

Pumped

storage

Li-Ion

(1hr + 3 hr)

Demand

Response

2016 36 782 1 860 425 3 419 2 179 1 460 200 1 479 264 1 580 0 0

2017 36 782 1 860 425 3 419 2 184 2 234 600 1 594 305 2 912 0 0

2018 38 789 1 860 425 3 419 2 184 2 770 600 1 819 305 2 912 0 0

2019 40 234 1 860 425 3 419 2 184 2 770 600 1 894 355 2 912 0 0

2020 41 641 1 860 425 3 419 2 184 2 770 600 1 894 355 2 912 331 101

2021 42 004 1 860 425 3 419 2 184 2 770 600 1 894 355 2 912 331 163

2022 41 967 1 860 425 3 419 2 184 2 770 600 1 894 355 2 912 1 217 233

2023 42 120 1 860 425 4 508 2 184 2 770 600 2 538 355 2 912 1 488 307

2024 41 730 1 860 425 5 362 2 184 2 770 600 2 653 355 2 912 2 450 388

2025 40 890 1 860 425 5 362 2 184 5 202 600 5 221 355 3 244 2 450 477

2026 39 200 1 860 425 6 200 2 184 8 579 600 7 205 355 3 244 3 090 573

2027 37 870 1 860 425 7 143 2 184 13 240 600 10 607 355 3 244 3 492 676

2028 35 980 1 860 425 9 367 2 184 15 667 600 18 929 355 3 244 5 671 788

2029 34 070 1 860 425 9 367 2 184 17 138 600 22 708 355 3 244 8 957 910

2030 31 750 1 860 425 9 367 2 184 23 127 600 26 128 355 3 244 8 957 1 042

2031 29 990 1 860 425 14 928 2 184 27 188 600 38 724 355 3 244 9 463 1 280

2032 28 830 1 860 425 14 928 2 184 30 708 600 38 724 355 3 244 8 783 1 539

2033 27 670 1 860 425 14 928 2 184 37 383 600 40 498 355 3 244 10 077 1 820

2034 27 090 1 860 425 15 886 2 184 40 993 600 42 544 355 3 244 10 455 2 125

2035 25 920 1 860 425 16 465 2 184 46 269 600 47 659 355 3 244 14 161 2 451

2036 24 170 1 860 425 20 851 2 184 48 065 600 53 379 355 3 271 13 521 2 800

2037 22 350 1 860 425 18 779 2 184 53 850 600 54 539 355 3 271 13 521 3 168

2038 19 330 1 860 425 18 779 2 184 68 104 600 63 353 355 3 271 14 035 3 555

2039 18 120 1 860 425 18 779 2 184 69 459 600 72 971 355 3 271 18 580 3 957

2040 16 330 1 860 3 142 19 533 2 184 70 914 600 78 500 355 3 271 18 257 4 372

2041 13 790 1 860 3 142 28 856 2 184 70 914 600 80 260 355 5 113 18 311 4 692

2042 13 150 1 860 3 142 29 249 2 184 75 937 600 86 290 355 5 406 18 110 5 014

2043 12 510 1 860 3 142 29 249 2 184 80 365 600 88 082 355 5 406 16 544 5 334

2044 12 510 0 3 142 29 249 2 184 94 856 600 91 570 355 5 406 15 204 5 647

2045 12 510 0 3 142 28 244 2 184 93 218 500 91 570 355 5 406 15 204 5 951

2046 11 900 0 3 142 28 244 2 184 98 301 400 91 570 355 5 406 20 521 6 243

2047 11 290 0 3 142 35 795 2 184 93 640 100 95 298 331 5 954 21 160 6 518

2048 10 680 0 3 142 35 795 2 184 94 782 0 112 033 314 6 258 24 835 6 777

2049 10 010 0 3 142 35 795 2 184 102 968 0 111 918 264 6 258 21 435 7 018

2050 9 340 0 3 142 35 795 2 184 108 901 0 112 566 264 6 258 21 427 7 239

56

Table 11. Base Case - High demand: Existing annual energy in GWh/yr


Biomass/-

gas

Pumped

storage

Li-Ion

(1hr + 3 hr)

Demand

Response

2016 200 108 14 677 2 238 88 10 492 3 988 838 2 735 1 623 2 337 0 0

2017 201 774 14 380 2 232 88 10 714 3 860 853 2 656 1 619 2 279 0 0

2018 198 244 13 196 2 233 123 9 587 4 063 824 2 781 1 623 2 979 0 0

2019 196 020 13 294 2 234 104 8 807 4 170 855 2 667 1 621 3 328 0 0

2020 192 777 12 928 2 239 120 8 610 3 931 846 2 587 1 626 3 356 0 0

2021 190 380 13 290 2 233 111 8 305 3 811 843 2 753 1 624 3 297 0 0

2022 187 921 13 219 2 233 106 9 048 3 965 828 2 688 1 628 3 314 0 0

2023 188 161 13 713 2 236 179 9 116 3 774 852 2 703 1 621 3 249 0 0

2024 191 386 14 239 2 245 182 9 996 4 013 849 2 777 1 624 3 162 0 0

2025 187 077 13 819 2 243 260 9 537 4 274 826 2 583 1 624 3 275 0 0

2026 179 031 14 058 2 233 185 10 327 3 905 846 2 717 1 619 3 080 0 0

2027 168 188 13 985 2 237 200 9 822 3 985 849 2 757 1 620 2 780 0 0

2028 153 154 13 413 2 250 267 9 576 4 008 843 2 697 1 637 2 815 0 0

2029 147 126 13 688 2 268 191 9 987 3 983 824 2 772 1 625 2 431 0 0

2030 132 580 13 806 2 246 133 9 968 3 959 847 2 696 1 619 2 248 0 0

2031 117 031 12 857 2 353 149 9 737 3 942 837 2 581 1 635 3 213 0 0

2032 109 009 14 460 2 248 92 9 530 3 997 860 2 730 1 638 3 077 0 0

2033 100 115 12 988 2 287 276 9 324 3 965 840 2 688 1 647 2 738 0 0

2034 96 314 13 445 2 293 218 9 361 1 556 829 2 690 1 641 3 003 0 0

2035 89 529 13 756 2 314 199 8 780 0 823 2 794 1 642 2 929 0 0

2036 77 261 12 368 2 324 156 8 708 0 845 2 731 1 650 3 485 0 0

2037 65 883 13 511 2 273 92 8 643 0 856 2 715 1 639 3 308 0 0

2038 47 185 12 996 2 298 113 8 969 0 857 2 754 1 637 2 821 0 0

2039 38 248 12 364 2 330 136 8 765 0 857 2 208 1 640 3 353 0 0

2040 29 455 12 931 2 326 144 8 662 0 850 793 1 636 3 456 0 0

2041 12 137 11 771 2 277 105 8 775 0 840 802 1 628 3 071 0 0

2042 10 235 12 547 2 307 106 8 679 0 853 0 1 645 3 134 0 0

2043 5 453 12 206 2 320 89 8 646 0 848 0 1 647 3 356 0 0

2044 6 104 0 2 357 90 8 769 0 853 0 1 648 3 102 0 0

2045 5 313 0 2 301 78 8 139 0 523 0 1 648 3 596 0 0

2046 4 303 0 2 306 0 8 328 0 31 0 1 638 3 078 0 0

2047 2 904 0 2 292 0 8 329 0 0 0 1 633 3 064 0 0

2048 2 127 0 2 328 0 8 616 0 0 0 1 650 3 362 0 0

2049 1 462 0 2 290 0 8 622 0 0 0 1 629 3 373 0 0

2050 0 0 2 286 0 8 733 0 0 0 1 632 3 093 0 0

57

Table 12. Base Case - High demand: Committed/under construction annual energy in GWh/yr


Biomass/-

gas

Pumped

storage

Li-Ion

(1hr + 3 hr)

Demand

Response

2016 5 470 0 0 0 0 470 81 0 58 29 0 0

2017 5 588 0 0 0 21 2 636 1 646 174 188 2 260 0 0

2018 15 550 0 0 0 22 4 441 1 976 548 270 3 426 0 0

2019 26 471 0 0 0 22 4 674 1 982 748 560 3 700 0 0

2020 40 816 0 0 0 22 4 407 2 003 726 561 3 739 0 0

2021 49 372 0 0 0 22 4 272 1 947 772 559 3 712 0 0

2022 57 163 0 0 0 22 4 445 1 974 754 560 3 558 0 0

2023 61 083 0 0 0 22 4 231 2 009 759 562 3 591 0 0

2024 62 580 0 0 0 22 4 499 1 973 779 561 3 343 0 0

2025 62 179 0 0 0 22 4 791 1 974 725 560 3 323 0 0

2026 64 010 0 0 0 22 4 377 1 975 762 561 3 213 0 0

2027 62 233 0 0 0 22 4 467 1 981 773 561 3 266 0 0

2028 62 820 0 0 0 22 4 492 1 965 757 562 3 395 0 0

2029 64 010 0 0 0 22 4 464 1 987 778 559 2 837 0 0

2030 65 033 0 0 0 22 4 438 2 010 757 560 2 500 0 0

2031 61 560 0 0 0 24 4 419 1 986 724 562 3 390 0 0

2032 62 020 0 0 0 22 4 480 1 998 766 563 3 208 0 0

2033 59 055 0 0 0 23 4 445 1 963 754 560 3 007 0 0

2034 61 562 0 0 0 22 2 360 1 954 755 562 3 281 0 0

2035 60 202 0 0 0 23 2 055 1 955 784 561 3 084 0 0

2036 58 438 0 0 0 23 2 232 1 985 766 562 3 414 0 0

2037 59 907 0 0 0 23 1 638 1 975 762 561 3 411 0 0

2038 58 507 0 0 0 23 104 1 994 773 562 3 045 0 0

2039 57 745 0 0 0 23 0 1 964 758 562 3 484 0 0

2040 58 796 0 0 0 23 0 1 991 756 562 3 568 0 0

2041 58 796 0 0 0 22 0 1 989 765 562 3 163 0 0

2042 58 311 0 0 0 23 0 2 004 730 561 3 255 0 0

2043 58 085 0 0 0 23 0 2 000 663 562 3 318 0 0

2044 57 931 0 0 0 23 0 2 027 0 563 3 455 0 0

2045 56 304 0 0 0 23 0 1 954 0 564 3 673 0 0

2046 57 127 0 0 0 23 0 1 902 0 561 3 157 0 0

2047 56 880 0 0 0 23 0 582 0 469 3 181 0 0

2048 57 040 0 0 0 23 0 0 0 352 3 609 0 0

2049 57 359 0 0 0 22 0 0 0 0 3 548 0 0

2050 57 626 0 0 0 22 0 0 0 0 3 235 0 0

58

Table 13. Base Case - High demand: New build annual energy in GWh/yr (including decommissioning)


Biomass/-

gas

Pumped

storage

Li-Ion

(1hr + 3 hr)

Demand

Response

2016 0 0 0 0 0 0 0 0 0 0 0 0

2017 0 0 0 0 0 0 0 0 67 0 0 0

2018 0 0 0 0 0 0 0 0 68 0 0 0

2019 0 0 0 0 0 0 0 0 67 0 0 0

2020 0 0 0 0 0 0 0 0 68 0 758 0

2021 0 0 0 0 0 0 0 0 68 0 479 0

2022 0 0 0 0 0 0 0 0 67 0 2 346 0

2023 0 0 0 236 0 0 0 1 175 68 0 1 794 0

2024 0 0 0 699 0 0 0 1 345 68 0 2 322 0

2025 0 0 0 699 0 7 474 0 5 615 67 972 1 868 0

2026 0 0 0 941 0 17 231 0 9 804 67 950 1 751 0

2027 0 0 0 1 344 0 31 386 0 16 048 67 868 2 179 0

2028 0 0 0 2 247 0 38 311 0 29 929 68 879 5 620 0

2029 0 0 0 2 284 0 42 344 0 38 491 67 798 10 313 0

2030 0 0 0 2 497 0 60 798 0 42 402 67 694 10 600 0

2031 0 0 0 5 012 0 66 264 0 62 679 69 948 11 202 0

2032 0 0 0 3 925 0 81 535 0 63 651 68 853 11 196 0

2033 0 0 0 4 386 0 95 922 0 71 434 67 766 12 676 0

2034 0 0 0 3 994 0 110 408 0 70 952 67 865 14 331 0

2035 0 0 0 4 908 0 123 473 0 76 805 67 873 15 425 0

2036 0 0 0 5 508 0 135 839 0 88 076 68 1 026 15 104 0

2037 0 0 0 6 072 0 148 775 0 92 582 67 959 17 758 0

2038 0 0 0 5 155 0 167 735 0 105 264 67 852 16 007 0

2039 0 0 0 8 487 0 169 662 0 118 564 67 926 18 357 0

2040 0 0 6 126 5 241 0 169 673 0 133 183 68 994 20 163 0

2041 0 0 4 963 6 015 0 190 613 0 140 434 68 5 317 17 787 0

2042 0 0 5 473 9 218 0 184 868 0 154 773 67 6 061 17 662 0

2043 0 0 5 492 12 807 0 200 868 0 148 583 67 6 060 16 011 0

2044 0 0 5 250 7 513 0 222 808 0 154 001 68 6 002 15 082 0

2045 0 0 5 395 11 167 0 220 711 0 165 792 67 6 640 16 596 0

2046 0 0 5 160 8 920 0 237 447 0 162 056 67 5 710 20 601 0

2047 0 0 5 260 9 656 0 239 281 0 172 155 0 6 962 18 272 0

2048 0 0 5 707 13 250 0 224 682 0 192 394 0 8 799 25 358 0

2049 0 0 5 249 9 403 0 233 346 0 199 268 0 8 590 20 543 0

2050 0 0 5 969 9 287 0 252 150 0 192 268 0 8 036 20 373 0

59

Table 14. Base Case - High demand: Total annual energy in GWh/yr


Biomass/-

gas

Pumped

storage

Li-Ion

(1hr + 3 hr)

Demand

Response

2016 205 578 14 677 2 238 88 10 492 4 458 919 2 735 1 681 2 366 0 0

2017 207 362 14 380 2 232 88 10 735 6 495 2 499 2 830 1 945 4 539 0 0

2018 213 794 13 196 2 233 123 9 609 8 504 2 800 3 329 2 053 6 404 0 0

2019 222 492 13 294 2 234 104 8 829 8 844 2 837 3 415 2 515 7 028 0 0

2020 233 592 12 928 2 239 120 8 632 8 338 2 849 3 313 2 521 7 095 758 0

2021 239 752 13 290 2 233 111 8 327 8 083 2 790 3 525 2 517 7 009 479 0

2022 245 083 13 219 2 233 106 9 070 8 411 2 802 3 442 2 520 6 872 2 346 0

2023 249 244 13 713 2 236 414 9 138 8 005 2 862 4 636 2 517 6 840 1 794 0

2024 253 966 14 239 2 245 881 10 018 8 512 2 823 4 901 2 518 6 505 2 322 0

2025 249 256 13 819 2 243 959 9 559 16 540 2 800 8 922 2 517 7 571 1 868 0

2026 243 041 14 058 2 233 1 127 10 349 25 514 2 821 13 284 2 514 7 244 1 751 0

2027 230 421 13 985 2 237 1 544 9 844 39 839 2 830 19 578 2 514 6 915 2 179 0

2028 215 975 13 413 2 250 2 514 9 598 46 811 2 808 33 382 2 534 7 090 5 620 0

2029 211 136 13 688 2 268 2 474 10 009 50 791 2 811 42 041 2 517 6 066 10 313 0

2030 197 613 13 806 2 246 2 630 9 990 69 195 2 858 45 855 2 514 5 441 10 600 0

2031 178 591 12 857 2 353 5 161 9 760 74 624 2 824 65 984 2 532 7 551 11 202 0

2032 171 029 14 460 2 248 4 018 9 553 90 012 2 858 67 148 2 535 7 138 11 196 0

2033 159 170 12 988 2 287 4 661 9 346 104 333 2 803 74 877 2 541 6 511 12 676 0

2034 157 877 13 445 2 293 4 213 9 383 114 325 2 783 74 397 2 537 7 149 14 331 0

2035 149 731 13 756 2 314 5 107 8 802 125 528 2 778 80 383 2 537 6 886 15 425 0

2036 135 699 12 368 2 324 5 664 8 731 138 072 2 830 91 574 2 546 7 925 15 104 0

2037 125 790 13 511 2 273 6 164 8 665 150 413 2 832 96 058 2 535 7 678 17 758 0

2038 105 693 12 996 2 298 5 268 8 991 167 839 2 852 108 790 2 534 6 718 16 007 0

2039 95 993 12 364 2 330 8 623 8 788 169 662 2 821 121 531 2 536 7 763 18 357 0

2040 88 250 12 931 8 451 5 385 8 686 169 673 2 841 134 732 2 532 8 018 20 163 0

2041 70 934 11 771 7 240 6 120 8 797 190 613 2 829 142 001 2 525 11 551 17 787 0

2042 68 547 12 547 7 780 9 324 8 702 184 868 2 857 155 503 2 540 12 450 17 662 0

2043 63 538 12 206 7 812 12 896 8 669 200 868 2 849 149 246 2 544 12 734 16 011 0

2044 64 035 0 7 607 7 603 8 792 222 808 2 880 154 001 2 545 12 559 15 082 0

2045 61 616 0 7 696 11 245 8 162 220 711 2 477 165 792 2 546 13 909 16 596 0

2046 61 430 0 7 466 8 920 8 351 237 447 1 934 162 056 2 532 11 945 20 601 0

2047 59 784 0 7 553 9 656 8 352 239 281 583 172 155 2 278 13 207 18 272 0

2048 59 167 0 8 036 13 250 8 640 224 682 0 192 394 2 177 15 771 25 358 0

2049 58 821 0 7 538 9 403 8 645 233 346 0 199 268 1 629 15 511 20 543 0

2050 57 626 0 8 255 9 287 8 755 252 150 0 192 268 1 632 14 364 20 373 0

60

Table 15. Base Case - Low demand: Total annual installed capacity in MW


Biomass/-

gas

Pumped

storage

Li-Ion

(1hr + 3 hr)

Demand

Response

2016 36 782 1 860 425 3 419 2 179 1 460 200 1 479 264 1 580 0 0

2017 36 782 1 860 425 3 419 2 184 2 234 600 1 594 305 2 912 0 0

2018 38 789 1 860 425 3 419 2 184 2 770 600 1 819 305 2 912 0 0

2019 40 234 1 860 425 3 419 2 184 2 770 600 1 894 355 2 912 0 0

2020 41 641 1 860 425 3 419 2 184 2 770 600 1 894 355 2 912 6 101

2021 42 004 1 860 425 3 419 2 184 2 770 600 1 894 355 2 912 7 163

2022 41 967 1 860 425 3 419 2 184 2 770 600 1 894 355 2 912 9 233

2023 42 120 1 860 425 3 419 2 184 2 770 600 1 894 355 2 912 187 307

2024 41 730 1 860 425 3 419 2 184 2 770 600 1 894 355 2 912 1 301 388

2025 40 890 1 860 425 3 419 2 184 2 770 600 1 894 355 3 187 1 597 477

2026 39 200 1 860 425 5 609 2 184 3 333 600 2 372 355 3 187 1 597 573

2027 37 870 1 860 425 5 745 2 184 6 840 600 6 227 355 3 187 2 720 676

2028 35 980 1 860 425 6 746 2 184 9 271 600 12 621 355 3 187 4 438 788

2029 34 070 1 860 425 6 840 2 184 10 065 600 16 500 355 3 187 7 219 910

2030 31 750 1 860 425 6 840 2 184 16 507 600 17 048 355 3 187 7 219 1 042

2031 29 990 1 860 425 10 517 2 184 17 545 600 29 038 355 3 187 8 187 1 280

2032 28 830 1 860 425 10 517 2 184 21 254 600 29 038 355 3 187 8 184 1 539

2033 27 670 1 860 425 10 517 2 184 23 861 600 33 520 355 3 187 10 028 1 820

2034 27 090 1 860 425 10 517 2 184 24 429 600 33 524 355 3 187 10 028 2 125

2035 25 920 1 860 425 11 642 2 184 31 335 600 37 309 355 3 187 11 496 2 451

2036 24 170 1 860 425 14 623 2 184 33 317 600 39 454 355 3 187 11 496 2 800

2037 22 350 1 860 425 12 551 2 184 37 952 600 42 847 355 3 187 11 861 3 168

2038 19 330 1 860 425 12 551 2 184 46 507 600 48 682 355 3 187 12 601 3 555

2039 18 120 1 860 425 17 208 2 184 50 964 600 54 946 355 3 187 12 938 3 957

2040 16 330 1 860 425 17 208 2 184 52 981 600 59 032 355 3 187 12 932 4 372

2041 13 790 1 860 425 23 760 2 184 55 021 600 59 931 355 4 042 12 932 4 692

2042 13 150 1 860 425 23 760 2 184 57 578 600 66 256 355 4 042 13 009 5 014

2043 12 510 1 860 425 23 760 2 184 61 036 600 66 256 355 4 042 12 258 5 334

2044 12 510 0 425 23 760 2 184 71 272 600 68 267 355 4 042 11 152 5 647

2045 12 510 0 425 22 755 2 184 71 272 500 68 267 355 4 042 11 140 5 951

2046 11 900 0 425 22 755 2 184 72 359 400 68 267 355 4 042 13 669 6 243

2047 11 290 0 425 26 446 2 184 68 851 100 70 530 331 4 166 15 857 6 518

2048 10 680 0 425 26 446 2 184 67 223 0 81 259 314 4 166 18 901 6 777

2049 10 010 0 425 26 446 2 184 72 012 0 81 259 264 4 166 16 856 7 018

2050 9 340 0 425 26 446 2 184 71 931 0 81 259 264 4 166 16 856 7 239

61

Table 16. Base Case - Low demand: Existing annual energy in GWh/yr


Biomass/-

gas

Pumped

storage

Li-Ion

(1hr + 3 hr)

Demand

Response

2016 198 694 14 671 2 238 88 10 260 3 986 839 2 724 1 627 2 268 0 0

2017 198 146 14 301 2 232 88 9 832 3 832 847 2 673 1 619 2 796 0 0

2018 192 684 12 709 2 246 89 8 711 4 063 824 2 781 1 625 3 252 0 0

2019 189 991 12 887 2 233 89 7 608 4 170 855 2 667 1 619 3 081 0 0

2020 186 486 12 659 2 243 90 7 559 3 931 846 2 587 1 628 3 787 0 0

2021 183 665 12 712 2 234 89 7 152 3 811 843 2 753 1 625 3 535 0 0

2022 180 422 12 596 2 237 88 7 427 3 965 828 2 688 1 627 3 732 0 0

2023 179 457 12 932 2 239 102 8 063 3 774 852 2 703 1 620 3 307 0 0

2024 180 361 13 740 2 240 106 8 658 4 013 849 2 777 1 621 3 372 0 0

2025 181 934 13 536 2 235 162 9 070 4 274 826 2 583 1 623 3 058 0 0

2026 178 421 14 070 2 235 131 10 453 3 905 846 2 717 1 620 3 136 0 0

2027 167 718 14 012 2 237 108 9 766 3 985 849 2 757 1 619 2 773 0 0

2028 153 942 13 432 2 250 227 9 650 4 008 843 2 697 1 633 2 836 0 0

2029 146 516 13 826 2 266 185 9 915 3 983 824 2 772 1 621 2 303 0 0

2030 132 184 14 186 2 232 127 9 995 3 959 847 2 696 1 619 1 992 0 0

2031 118 087 13 138 2 311 145 9 790 3 942 837 2 581 1 637 2 535 0 0

2032 109 343 14 512 2 278 93 9 446 3 997 860 2 730 1 639 2 326 0 0

2033 100 129 13 228 2 269 274 9 652 3 965 840 2 688 1 641 2 751 0 0

2034 101 561 13 864 2 249 271 9 996 1 570 827 2 703 1 626 2 789 0 0

2035 88 843 14 189 2 300 219 8 821 0 823 2 794 1 638 2 554 0 0

2036 77 784 13 027 2 305 157 9 171 0 845 2 731 1 645 3 135 0 0

2037 65 973 13 435 2 272 103 8 909 0 856 2 715 1 639 2 903 0 0

2038 47 947 13 338 2 310 129 9 483 0 857 2 754 1 640 2 943 0 0

2039 37 306 12 389 2 329 125 8 344 0 857 2 208 1 637 2 998 0 0

2040 28 834 13 132 2 323 99 8 806 0 850 793 1 638 3 070 0 0

2041 12 604 11 501 2 290 105 8 427 0 840 802 1 629 3 382 0 0

2042 10 195 12 399 2 307 106 8 761 0 853 0 1 640 3 408 0 0

2043 5 215 12 117 2 320 91 8 706 0 848 0 1 640 3 207 0 0

2044 5 893 0 2 338 88 8 647 0 853 0 1 642 2 893 0 0

2045 4 965 0 2 294 56 8 120 0 523 0 1 640 3 276 0 0

2046 4 451 0 2 302 0 8 442 0 31 0 1 635 3 175 0 0

2047 2 679 0 2 306 0 7 806 0 0 0 1 634 3 241 0 0

2048 2 157 0 2 324 0 8 646 0 0 0 1 637 3 428 0 0

2049 1 353 0 2 279 0 8 511 0 0 0 1 628 3 498 0 0

2050 0 0 2 277 0 8 520 0 0 0 1 632 3 642 0 0

62

Table 17. Base Case - Low demand: Committed/under construction annual energy in GWh/yr


Biomass/-

gas

Pumped

storage

Li-Ion

(1hr + 3 hr)

Demand

Response

2016 5 407 0 0 0 0 470 79 0 55 31 0 0

2017 5 408 0 0 0 21 2 630 1 641 175 189 2 439 0 0

2018 14 961 0 0 0 22 4 441 1 976 548 270 3 477 0 0

2019 25 128 0 0 0 22 4 674 1 982 748 560 3 508 0 0

2020 38 891 0 0 0 22 4 407 2 003 726 561 4 169 0 0

2021 47 124 0 0 0 22 4 272 1 947 772 559 3 893 0 0

2022 54 655 0 0 0 22 4 445 1 974 754 559 3 984 0 0

2023 58 386 0 0 0 22 4 231 2 009 759 561 3 657 0 0

2024 59 217 0 0 0 22 4 499 1 973 779 560 3 750 0 0

2025 60 757 0 0 0 22 4 791 1 974 725 559 3 403 0 0

2026 63 789 0 0 0 22 4 377 1 975 762 561 3 370 0 0

2027 62 672 0 0 0 22 4 467 1 981 773 561 3 169 0 0

2028 62 755 0 0 0 22 4 492 1 965 757 562 3 083 0 0

2029 64 932 0 0 0 22 4 464 1 987 778 559 2 776 0 0

2030 64 192 0 0 0 22 4 438 2 010 757 560 2 446 0 0

2031 62 495 0 0 0 23 4 419 1 986 724 562 3 322 0 0

2032 63 263 0 0 0 22 4 480 1 998 766 563 2 838 0 0

2033 60 486 0 0 0 22 4 445 1 963 754 560 3 062 0 0

2034 64 447 0 0 0 22 2 361 1 947 759 561 3 229 0 0

2035 61 133 0 0 0 22 2 055 1 955 784 560 3 046 0 0

2036 59 278 0 0 0 22 2 232 1 985 766 562 3 127 0 0

2037 61 136 0 0 0 23 1 638 1 975 762 562 2 925 0 0

2038 59 797 0 0 0 23 104 1 994 773 562 2 991 0 0

2039 58 032 0 0 0 23 0 1 964 758 562 3 273 0 0

2040 60 296 0 0 0 23 0 1 991 756 562 3 039 0 0

2041 57 006 0 0 0 23 0 1 989 765 562 3 370 0 0

2042 58 150 0 0 0 23 0 2 004 730 561 3 390 0 0

2043 58 276 0 0 0 23 0 2 000 663 562 3 241 0 0

2044 58 207 0 0 0 23 0 2 027 0 563 3 070 0 0

2045 56 554 0 0 0 23 0 1 954 0 564 3 466 0 0

2046 57 046 0 0 0 23 0 1 902 0 561 3 263 0 0

2047 55 994 0 0 0 23 0 582 0 469 3 196 0 0

2048 57 219 0 0 0 23 0 0 0 351 3 522 0 0

2049 57 317 0 0 0 23 0 0 0 0 3 650 0 0

2050 57 933 0 0 0 22 0 0 0 0 3 900 0 0

63

Table 18. Base Case - Low demand: New build annual energy in GWh/yr (including decommissioning)


Biomass/-

gas

Pumped

storage

Li-Ion

(1hr + 3 hr)

Demand

Response

2016 0 0 0 0 0 0 0 0 0 0 0 0

2017 0 0 0 0 0 0 0 0 67 0 0 0

2018 0 0 0 0 0 0 0 0 67 0 0 0

2019 0 0 0 0 0 0 0 0 67 0 0 0

2020 0 0 0 0 0 0 0 0 68 0 20 0

2021 0 0 0 0 0 0 0 0 68 0 18 0

2022 0 0 0 0 0 0 0 0 67 0 26 0

2023 0 0 0 0 0 0 0 0 67 0 482 0

2024 0 0 0 0 0 0 0 0 68 0 2 546 0

2025 0 0 0 0 0 0 0 0 67 778 1 713 0

2026 0 0 0 383 0 1 669 0 882 67 807 849 0

2027 0 0 0 531 0 12 327 0 7 980 67 676 1 660 0

2028 0 0 0 1 458 0 19 448 0 18 709 68 734 3 022 0

2029 0 0 0 1 184 0 21 246 0 26 959 67 609 7 093 0

2030 0 0 0 1 391 0 41 017 0 26 534 67 558 7 358 0

2031 0 0 0 2 849 0 42 242 0 46 366 68 718 9 454 0

2032 0 0 0 2 108 0 54 702 0 47 077 68 622 9 031 0

2033 0 0 0 2 309 0 60 523 0 58 430 67 662 11 468 0

2034 0 0 0 2 183 0 66 352 0 55 101 67 722 11 749 0

2035 0 0 0 2 612 0 86 060 0 59 578 67 651 12 747 0

2036 0 0 0 2 920 0 98 505 0 64 906 68 800 12 681 0

2037 0 0 0 2 816 0 105 849 0 71 986 67 708 14 329 0

2038 0 0 0 3 225 0 121 975 0 80 326 68 749 14 271 0

2039 0 0 0 5 958 0 128 970 0 89 472 67 726 13 317 0

2040 0 0 0 5 341 0 129 783 0 100 292 68 673 15 158 0

2041 0 0 0 6 147 0 148 679 0 105 157 68 2 842 13 270 0

2042 0 0 0 8 125 0 140 118 0 117 800 67 2 979 13 069 0

2043 0 0 0 10 849 0 152 621 0 110 695 67 2 856 11 898 0

2044 0 0 0 6 493 0 168 537 0 114 459 68 2 664 10 854 0

2045 0 0 0 8 344 0 165 652 0 123 401 68 2 925 12 255 0

2046 0 0 0 7 229 0 173 428 0 119 936 67 2 706 14 170 0

2047 0 0 0 7 255 0 173 299 0 127 451 0 3 077 13 980 0

2048 0 0 0 11 255 0 159 834 0 137 267 0 3 361 17 996 0

2049 0 0 0 6 865 0 163 248 0 143 385 0 3 261 15 097 0

2050 0 0 0 8 714 0 171 291 0 137 721 0 3 598 16 412 0

64

Table 19. Base Case - Low demand: Total annual energy in GWh/yr


Biomass/-

gas

Pumped

storage

Li-Ion

(1hr + 3 hr)

Demand

Response

2016 204 100 14 671 2 238 88 10 260 4 456 918 2 724 1 682 2 299 0 0

2017 203 553 14 301 2 232 88 9 853 6 462 2 488 2 848 1 875 5 234 0 0

2018 207 644 12 709 2 246 89 8 733 8 504 2 800 3 329 1 962 6 730 0 0

2019 215 119 12 887 2 233 89 7 630 8 844 2 837 3 415 2 247 6 589 0 0

2020 225 377 12 659 2 243 90 7 581 8 338 2 849 3 313 2 256 7 956 20 0

2021 230 789 12 712 2 234 89 7 174 8 083 2 790 3 525 2 252 7 428 18 0

2022 235 077 12 596 2 237 88 7 448 8 411 2 802 3 442 2 254 7 716 26 0

2023 237 843 12 932 2 239 102 8 085 8 005 2 862 3 462 2 249 6 964 482 0

2024 239 579 13 740 2 240 106 8 680 8 512 2 822 3 556 2 248 7 121 2 546 0

2025 242 690 13 536 2 235 162 9 092 9 065 2 800 3 308 2 250 7 239 1 713 0

2026 242 210 14 070 2 235 513 10 475 9 951 2 821 4 362 2 248 7 313 849 0

2027 230 390 14 012 2 237 639 9 788 20 779 2 830 11 510 2 247 6 619 1 660 0

2028 216 697 13 432 2 250 1 685 9 672 27 948 2 808 22 162 2 263 6 653 3 022 0

2029 211 448 13 826 2 266 1 369 9 937 29 693 2 811 30 509 2 247 5 688 7 093 0

2030 196 376 14 186 2 232 1 517 10 017 49 414 2 858 29 987 2 247 4 995 7 358 0

2031 180 582 13 138 2 311 2 994 9 813 50 603 2 824 49 672 2 267 6 575 9 454 0

2032 172 606 14 512 2 278 2 201 9 468 63 179 2 858 50 573 2 270 5 786 9 031 0

2033 160 616 13 228 2 269 2 583 9 674 68 934 2 803 61 873 2 269 6 475 11 468 0

2034 166 008 13 864 2 249 2 454 10 018 70 283 2 774 58 563 2 255 6 740 11 749 0

2035 149 975 14 189 2 300 2 831 8 843 88 116 2 778 63 156 2 265 6 251 12 747 0

2036 137 062 13 027 2 305 3 077 9 194 100 737 2 830 68 404 2 275 7 062 12 681 0

2037 127 109 13 435 2 272 2 919 8 931 107 487 2 832 75 463 2 268 6 536 14 329 0

2038 107 744 13 338 2 310 3 354 9 506 122 079 2 852 83 852 2 269 6 683 14 271 0

2039 95 337 12 389 2 329 6 083 8 367 128 970 2 821 92 439 2 267 6 997 13 317 0

2040 89 130 13 132 2 323 5 440 8 829 129 783 2 841 101 841 2 267 6 782 15 158 0

2041 69 610 11 501 2 290 6 252 8 450 148 679 2 829 106 724 2 260 9 594 13 270 0

2042 68 345 12 399 2 307 8 230 8 784 140 118 2 857 118 530 2 268 9 777 13 069 0

2043 63 491 12 117 2 320 10 940 8 729 152 621 2 849 111 357 2 269 9 304 11 898 0

2044 64 100 0 2 338 6 582 8 669 168 537 2 880 114 459 2 272 8 627 10 854 0

2045 61 519 0 2 294 8 400 8 143 165 652 2 477 123 401 2 271 9 667 12 255 0

2046 61 498 0 2 302 7 229 8 465 173 428 1 934 119 936 2 263 9 144 14 170 0

2047 58 673 0 2 306 7 255 7 829 173 299 583 127 451 2 103 9 514 13 980 0

2048 59 376 0 2 324 11 255 8 669 159 834 0 137 267 1 988 10 311 17 996 0

2049 58 670 0 2 279 6 865 8 534 163 248 0 143 385 1 628 10 409 15 097 0

2050 57 933 0 2 277 8 714 8 542 171 291 0 137 721 1 632 11 140 16 412 0

Documents

The long-term viability of coal for power generation in ...meridianeconomics.co.za/.../2017/...Report-FINAL.pdf · Figure 6. Existing Eskom fleet plant performance. Source: Draft