National Intergrated Resource Plan 2 - PBMR

Contents 

Page 

FOREWORD 2 

ACKNOWLEDGEMENTS 3 

NIRP2 Reference Case Report 4 

NIRP2 Stage 2: Risk and Sensitivity Analyses Report 37 

NIRP2 Stage 2 Appendix A: 

Summary of Comments on NIRP2 Reference Case 65 

NIRP2 Stage 2 Appendix D: 

Summary of ARC Comments on NIRP2 Stage 2 report 76 

Information provided on CD ROM 

inside back cover 

NIRP2 Reference Case Appendix 1: Supply-side data, 

NIRP2 Reference Case Appendix 2: Results, 

NIRP2 Reference Case Appendix 3: Background supply-side data. 

NIRP2 Stage 2 Appendix B: Summary of Plans 

NIRP2 Stage 2 Appendix C: NIRP2 Stage 2 Database

Foreword 

Background 

In the light of the Energy Policy White Paper for South Africa and the recent government initiatives for 

restructuring of the ESI, the NER introduced the development of a National Integrated Resource Plan (NIRP) 

as an independent information source to stakeholders and decision-makers for insuring security of the supply. 

The first National IRP (NIRP1) was completed and published in March 2002. 

At the beginning of the year 2003, the NER established the NIRP Advisory and Review Committee (ARC) with 

the function to provide wide stakeholders' guidance and contribution to the NIRP development process. 

Unlike its predecessor the NIRP 2003/4 (NIRP2) relies on average international data (modified to reflect South 

African labor and exchange rates) for the cost and performance of new generation plants. Other important 

change from NIRP1 is the inclusion of sensitivity analysis and scenarios to address risk factors and 

uncertainties. Further the NIRP2 takes into account the transmission integration costs and losses associated 

with the location of the new generation plants. 

NIRP2 Studies 

2 

The NIRP2 has been generated under the guidance of the NER NIRP Advisory and Review Committee (ARC) 

by a NIRP team comprising Eskom Resources and Strategy Group, Energy Research Institute of UCT and the 

NER. The work carried out for NIRP2 is divided into two stages: 

& Stage 1: Development of a reference case 

& Stage 2: Development of risk and sensitivity analyses 

The NIRP2 reference case was completed and published on the NER Web site on 3 March 2004 while NIRP2 

Stage 2: Risk and Sensitivity Analysis - on 22 September 2004. 

This publication consists of NIRP2 Stage 1 and 2 reports. Some of the Appendices associated with the main 

reports are provided in an electronic format (CD). 

The NIRP 2 Reference Case publication contains the following parts: 

& NIRP2 Reference Case Report 

& Appendix 1: Supply-side data 

& Appendix 2: Results 

& Appendix 3: Background supply-side data. 

The NIRP 2 Stage 2: Risk and Sensitivity analysis includes the following five parts: 

& NIRP2 Stage 2 Report, 

& Appendix A: Summary of comments on NIRP2 Reference Case 

& Appendix B: Summary of Plans 

& Appendix C: NIRP2 Stage 2 Data Base Summary 

& Appendix D: Summary of ARC Comments on NIRP2 Stage 2 report.

Acknowledgements 

The NER acknowledge the guidance, contribution and 

valuable suggestions of: 

NER NIRP Advisory and Review Committee (ARC): 

Project Team: 

Chairman: Prof A Eberhard, NER Board 

Dr Bianka Belinska, NER 

Members: Smunda Mokoena, CEO NER Steve McFadzean, Eskom ISEP 

Naresh Singh, EM NER 

Johan Prinsloo, Eskom ISEP 

Andre Otto, DME 

Zaheer Khan, Eskom ISEP 

Dr Elsa Du Toit, DME 

Andrew Etzinger, Eskom ISEP 

Robert Maake, DME 

Mavo Solomon, Eskom ISEP 

Tseliso Magubela, DME 

Moonlight Mbatha, Eskom ISEP 

Chris Gadsden, NT 

Mark Howells, ERI UCT 

Justice Mavhungu, DPE 

Glen Heinrich, ERI UCT 

Arnot Hepburn, EIUG 

Thomas Alfstadt, ERI UCT 

Piet van Staden, EIUG 

Andrew Kenny, ERI UCT 

Dick Kruger, Chamber of Mines 

Alison Hughes, ERI UCT 

Danny Vengedasamy, SACOB 

Rizia Buckas, NER 

Manfred Kuster, AMEU 

Willie Boeije, NER 

Mandla Tshabalala, AMEF 

Lambert du Plessis, NER 

Gerhard Loedolff, Eskom Generation 

Lynette Vajeth, Eskom Generation 

WEB Publisher: 

June Willis, Eskom Transmission 

Michael Barry, Eskom Transmission 

Correy Sutherland, NER 

Segomoco Scheppers, Eskom Transmission 

Erica Johnson, Eskom Transmission 

NIRP Contact Person: 

Jean Louis Pabot, Eskom KSACS 

Hermann FW Oelsner, Darling Windfarm IPP 

Dr Bianka Belinska, NER 

Robert Siemers, Kelvin IPP Tel: 012-4014650 

Donald Bennett, Kelvin IPP Fax: 012-4014687 

Prof K Bennett, ERI UCT 

Email: bianka.belinska@ner.org.za 

3 

ARC Management Officer: 

Dr Bianka Belinska, NER

National Integrated Resource Plan 2 

Reference Case 

4 

COMPILED BY 

ISEP Eskom (Resources and Strategy) 

AND 

Energy Research Institute 

University Of Cape Town 

AND 

The National Electricity Regulator 

27 February 2004


Executive Summary 

INTRODUCTION 

In the light of the Energy Policy White Paper for South Africa and the recent government initiatives for 

restructuring of the ESI, the NER introduced the development of a National Integrated Resource Plan (NIRP) 

as an independent information source to stakeholders and decision-makers for insuring security of the supply. 

The first National IRP (NIRP1) was completed and published in March 2002. 

At the beginning of the year 2003, the NER established an IRP Advisory and Review Committee (ARC) to 

provide wide stakeholders' contribution to the NIRP process. The main functions of the ARC are to approve the 

primary assumptions (technical, economical, environmental and social), evaluate the supply- and demand 

options for inclusion in the plan and oversee the development process. 

This NIRP is a revision of the first NIRP issued in March 2002 and published on the NER Web site. For the 

purposes of these analyses the first NIRP is referred as NIRP1 and the current study as NIRP2. 

The NIRP2 has been generated under the guidance and approval of the NER NIRP Advisory and Review 

Committee (ARC) by a NIRP team comprising Eskom Resources and Strategy Group, Energy Research 

Institute of UCT and the NER. 

Unlike its predecessor the NIRP2 relies on average international data (modified to reflect South African labor 

and exchange rates) for the cost and performance of new generation plants. 

Other important change from NIRP1 is the inclusion of sensitivity analysis and scenarios to address risk 

factors and uncertainties such as performance of existing generation plants (Eskom and non-Eskom), 

sustainability and delivery of Demand-side Management (DSM) options (including Interruptible load supplies 

(ILS)) and changes in the electricity demand load shape. Further the NIRP2 takes into account Transmission 

integration costs and credit for regional location of new capacity not included previously. 

5 

The growth in demand for electricity over the next twenty-year planning horizon is consistent with that 

predicted in NIRP1 and follows a moderate forecast with moderate weather conditions. 

OBJECTIVE AND PRIMARY ASSUMPTIONS 

The objective of the National Integrated Resource Plan (NIRP) is to determine the least cost supply options to 

the country, provide information to market participants on opportunities for investment in new power stations 

and evaluate the security of the supply. 

The NIRP2 reference case is based on the following primary assumptions approved by the ARC: 

& The net discount rate (before tax) agreed for the studies is 10 % internal to South Africa; 

& Options are compared on the basis of 1 January 2003 prices. Foreign capital is converted to South African 

Rand at the exchange rate of R9/$ reflective of a long-term planning approach; 

& Plant availabilities for new plants are based on the World Energy Council (WEC) best quartile results for 

2002. For existing plants the studies use the current targets in Eskom adjusted independently for each 

individual station to give a weighted average for base-load capacity of 88% EAF; (7% PCLF: 3% UCLF with a 

provision of 2% for OCLF to cater for risk). 

& The planning horizon for the study is 20 years from 2003 to 2022; 

& Moderate electricity consumption and demand growth; 

& Low DSM penetration; 

& Inflation for all fuels and new technologies was at South African PPI.


CAPACITY OUTLOOK FOR NIRP2 REFERENCE PLAN 

The capacity outlook for the NIRP Reference plan developed in Stage 1 is illustrated graphically in Figure 1. 

Reference capacity plan (10% Reserve margin) 2004 to 2022 

Capacity (MW) 

58000 

56000 

54000 

52000 

50000 

48000 

46000 

44000 

42000 

40000 

38000 

Greenfield PBMR (Base) - Earliest end 2013 

Greenfield PF (Base) - Earliest end 2013 

Greenfield Pumped Storage - Earliest 2013 

FBC (Base) - Earliest end 2009 

CCGT (Base) - Earliest end 2008 

Komati PF - Earliest 2010 

OCGT - Earliest 2008 

Grootvlei PF - 2007 

Camden 

36000 

Eskom Existing Capacity with Decommissioning Non-Eskom Existing Capacity with Decommissioning 

34000 

Imports-Cahora Bassa Hydro 

Simunye Eskom mothballed plants 

Pumped Storage capacity 

Peaking capacity 

32000 

Base load capacity Peak Demand before DSM 

Peak Demand after DSM 

Required capacity 

30000 

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 

6 

Figure 1: Capacity Outlook for NIRP2 Reference Plan 

CONCLUSIONS 

The main conclusions drawn from the NIRP2 reference case study could be summarised as follows: 

1) Options for diversification are insufficient to meet all of the forecast demand for electricity over the next 20- 

year planning horizon. Coal-fired options are still required for expansion during this period. For 

environmental benefit it is imperative to continue with efforts to reduce the costs of implementing clean 

coal technologies and improve the efficiency of coal-fired plants; 

2) Base load plants are required for commercial operation from 2010. Base load options competing, include; 

Pulverised Fuel Coal-fired (PF); Fluidised Bed Combustion (FBC); Combined Cycle Gas Turbine (CCGT). 

Given the cost and performance data used in the plan these options are broadly comparable, at 10% net 

discount rate, if regional siting and transmission benefits are included; 

3) At the current assumed cost of capital (10% net discount rate) and after returning the Eskom mothballed 

plant to service, fluidised bed combustion technologies are South Africa's most economic option, followed 

by investment in coal-fired plant. This in turn is followed by importing gas / LNG for CCGT plant in the 

Cape; 

4) It will be difficult to justify diversification on an economic basis, unless penalties for not doing so are 

included in future analyses. As the cost for diversification is becoming increasingly more expensive these 

penalties (or opportunities for emissions trading) will need to be substantial to offset the economic benefits 

of remaining with coal; 

5) The NIRP plans are based on attainment and sustainability of the DSM targets , power plants availability, 

imports and interruptible loads; 

6) The NIRP plans indicate that 920 MW OCGT peak load plants must begin commissioning from 2008;


7) Maintaining a higher reserve margin of 15% over the planning period will require acceleration of the RTS of 

the mothballed plants and coal-fired options together with commissioning of additional base load capacity 

(CCGT); 

8) Diversified options are new technologies to South Africa. If these options for whatever reason are not able 

to be implemented it will mean a return to a dependency on new pulverised coal-fired plants earlier than 

shown in these plans; 

9) There are supply options that have not been considered such as co-generation in industry, converting 

OCGT to CCGT, adding units onto existing power stations and new imports resulting from the 

development of Electricity Supply in the Southern African region; 

10) Should interruptible supply and / or OCGT capacity not be implemented this will significantly advance new 

base-load capacity; 

7


Table of Contents 

EXECUTIVE SUMMARY 5 

TABLE OF CONTENTS 8 

LIST OF TABLES 9 

LIST OF FIGURES 9 

ABBREVIATIONS 10 

1.INTRODUCTION - THE INTEGRATED RESOURCE PLANNING PROCESS 11 

2.STRATEGIC FRAMEWORK AND PRIMARY ASSUMPTIONS 11 

2.1 STRATEGIC POSITION (DEFINED BY THE ADVISORY AND REVIEW COMMITTEE (ARC) 

OF THE NER) 12 

2.2 PRIMARY ASSUMPTIONS 12 

2.3 RISKS AND UNCERTAINTIES 12 

2.4 OPTIMISATION PARAMETERS 13 

2.5 CRITERIA FOR INCLUSION OF SUPPLY-SIDE AND DEMAND-SIDE OPTIONS 13 

8 

3.NATIONAL ELECTRICITY FORECAST 13 

3.1 ECONOMIC GROWTH 16 

3.2 LARGE INDUSTRIAL PROJECTS 16 

3.3 ELECTRIFICATION 16 

3.4 ELECTRICITY INTENSITY 17 

3.5 NATURAL GAS 17 

3.6 FOREIGN FORECAST COMPONENT 17 

3.7 DEMAND PROFILES 18 

4.DEMAND-SIDE OPTIONS (DSM) 18 

4.1 THE DEMAND SIDE PLANNING BASIS FOR NIRP2 20 

4.2 INTRODUCTION TO THE DEMAND-SIDE SCREENING RESULTS 20 

4.2.1 Residential Energy Efficiency - REE 21 

4.2.2 Industrial, Mining and Commercial Energy Efficiency 22 

4.2.3 Residential Load Management (RLM) 23 

4.2.4 Industrial and Mining Load Management (IMLM) 23 

4.3 UNCERTAINTY AND RISK ASSOCIATED WITH DSM 23 

4.4 PRIORITIES FOR THE DEVELOPMENT OF DEMAND-SIDE RESOURCES 24 

5.SUPPLY-SIDE OPTIONS 25 

5.1 ESKOM SYSTEM - EXISTING AND COMMITTED CAPACITY 25 

5.2 NON-ESKOM SYSTEM - EXISTING CAPACITY 25 

5.3 RETURN TO SERVICE OF ESKOM MOTHBALLED PLANT (SIMUNYE) 25


5.4 NEW SUPPLY-SIDE OPTIONS 26 

5.4.1 New Pulverised Fuel (PF) Coal-Fired Stations 26 

5.4.2 New Gas-Fired Plant 26 

5.4.3 New Pumped Storage Schemes 27 

5.4.4 Greenfield Fluidised Bed Combustion 27 

5.4.5 Conventional Nuclear (Advanced Light Water Reactor (ALWR)) 29 

5.4.6 Research projects/programs 29 

5.4.7 Imported Hydro 29 

5.5 SCREENING CURVES 29 

5.6 OTHER: ENVIRONMENTAL, EXTERNALITIES, TRANSMISSION EXPANSION 31 

6.INTEGRATION AND SENSITIVITY ANALYSIS 31 

6.1 REFERENCE PLAN 32 

6.2 ALTERNATIVE PLAN 1 TO REFERENCE PLAN 33 

6.3 ALTERNATIVE PLAN 2 (SENSITIVITY STUDY) 33 

6.4 ALTERNATIVE PLAN 3 (OPTIMAL RESERVE MARGIN) 34 

7.SYSTEM ANNUAL AVERAGE LONG RUN MARGINAL COST 35 

8.CONCLUSIONS 36 

LIST OF TABLES 

Table 1: Average demand growth intervals 14 

Table 2: DSM aggregate megawatts displaced 19 

Table 3: Residential Energy Efficiency 21 

Table 4: Commercial energy efficiency 22 

Table 5: Industrial and Mining Energy Efficiency 22 

Table 6: Residential load management programmes 23 

Table 7: Industrial and mining load management 23 

Table 8: Summary of cost and performance data of new supply-side options 28 

9 

LIST OF FIGURES 

Figure 1: Electricity sales forecast range - National plus foreign 14 

Figure 2: Increase in annual peak demand and system losses (national plus foreign) 15 

Figure 3: Eskom track record 16 

Figure 4: RSA electricity intensity 17 

Figure 5: Typical hourly peak demand summer profile 18 

Figure 6: Typical hourly peak demand winter profile 18 

Figure 7: Life cycle levelised costs to build and operate base load plants 30 

Figure 8: Life cycle levelised costs to build and operate peaking plants 30 

Figure 9: Reference plan (10% Reserve Margin) 32 

Figure 10: Alternative 1 to reference plan (15% Reserve Margin) 33 

Figure 11: Alternative 2 - sensitivity to reference plan (excludes interruptible supply options) 34 

Figure 12: Annual average long run marginal costs of plans 35 

APPENDIX 1: SUPPLY SIDE MODELLING DATA SUMMARY 

APPENDIX 2: RESULTS 

APPENDIX 3: BACKGROUND SUPPLY SIDE DATA


Abbreviations 

10 

ALWR 

ARC 

CEE 

CCGT 

CF 

CF (DSM) 

CV 

CUE 

DEAT 

DME 

DSM 

DWAF 

EAF 

EIA 

EPC 

ESI 

FBC 

FOR 

GT 

HELM 

HHV 

HTF 

ICLM 

IMEE 

IMLM 

IEA 

IRP 

ISEP 

LF 

LOLE 

LOLP 

LNG 

LPG 

MCR 

MEUL 

NDR 

MOU 

NER 

O&M 

OCGT 

OCLF 

PCLF 

PBMR 

PF 

POR 

PPI 

PV 

PWR 

REE 

Advanced Light Water Reactor 

Advisory Review Committee 

Commercial Energy Efficiency 

Combined Cycle Gas Turbine 

Coal Fired 

Capacity Factor for DSM 

Calorific Value 

Cost of Unserved Energy 

Department of Environmental Affairs and Tourism 

Department of Minerals and Energy 

Demand Side Management 

Department of Water Affairs and Forestry 

Energy Availability Factor 

Energy Information Administration 

Engineering, Procurement and Construction 

Electricity Supply Industry 

Fluidised Bed Combustion 

Forced Outage Rate 

Gas Turbine 

Hourly Electricity Load Model 

High Heating Value 

Heat Transfer Fluid 

Industrial and Commercial Load Management 

Industrial and Mining Energy Efficiency 

Industrial and Mining Load Management 

International Energy Agency 

Integrated Resource Plan 

Integrated Strategic Electricity Planning 

Load Factor 

Loss of load expectation 

Loss of load probability 

Liquefied Natural Gas 

Liquefied Petroleum Gas 

Maximum Continuous Rating 

Minimum Energy Utilization Level 

Net Discount Rate 

Memorandum of Understanding 

National Electricity Regulator 

Operation and Maintenance 

Open Cycle Gas Turbine 

Other Capability Loss Factor 

Planned Capability Loss Factor 

Pebble Bed Modular Reactor 

Pulverised Fuel 

Planned Outage Rate 

Producer Price Index 

Present Value 

Pressurised Water Reactor 

Residential Energy Efficiency 

RLM 

ROD 

UE 

UCLF 

WEC 

Residential Load Management 

Record of Decision 

Unserved energy 

Unplanned Capability Loss Factor 

World Energy Council


1.INTRODUCTION THE INTEGRATED RESOURCE PLANNING PROCESS 

The prime objective of the National Integrated Resources Plan (NIRP) is to provide a long-term least-cost 

resource plan for meeting the electricity demand consistent with the reliability of the electricity supply, 

environmental, social and economic policies. The NIRP also serves as an information tool for potential project 

developers and decision-makers. 

The NIRP provides an assessment of the system adequacy and also addresses other public policies such as 

environmental impacts and Demand Side Management (DSM). 

The NIRP also takes into account the “The New Partnership for African Development (NEPAD)” by 

incorporating committed contracts for imports and exports to South Africa from neighbouring States. 

This is the second NIRP carried out under the auspices of the NER. The first NIRP was carried out during 2001- 

2002 and published on the NER Web site. For the purposes of these analyses the first NIRP is referred as 

NIRP1 and the current study as NIRP2. This analysis follows the steps already defined in the NIRP 1 as 

follows: 

& Develop the primary assumptions and selection criteria; 

& Produce an electricity consumption and demand forecasts; 

& Investigate a full array of demand- and supply-side options and identify those that meet the strategic 

selection criteria for inclusion in the plan; 

& Determine an optimal combination of demand- and supply-side options from those selected for inclusion in 

the resource plan; 

& Evaluate the risk factors associated with uncertainties such as load growth, plant availability, weather 

conditions, DSM penetration level, level of interruptible loads etc; 

& Analyse the environmental, external and financial consequences; 

& Select a preferred plan. 

11 

The IRP studies carried out in this process use several computer software models. A major model is the RP 

Workstation, which consists of a suite of computer software programs, developed by the American Electricity 

Power Research Institute (EPRI) and specifically the optimisation module, Electric Generation Expansion 

Analysis System (EGEAS). 

Due to time constraints, the work carried out for this NIRP is divided into two stages as agreed within the terms 

of the National Electricity Regulator (NER) Advisory and Review Committee (ARC). These two stages consist: 

& Stage 1: Determine a reference plan for analysis and as basis for recommendation on capacity planning 

issues in the short-term; 

& Stage 2: Develop sensitivity studies and scenarios in order to address targeted risk factors and 

uncertainties. 

The first stage is intended for completion by Feb 2004, which constitutes this report, and the second for 

completion by April 2004. 

2.STRATEGIC FRAMEWORK AND PRIMARY ASSUMPTIONS 

This serves as the strategic basis for the planning assumptions for the NIRP. The NIRP2 was based on the 

planning assumptions approved by the ARC. These studies are based on January 2003 as its primary 

reference date for cost parameters and for the start of the twenty- year planning horizon. The NIRP is a longterm 

planning process and it is undertaken on an annual basis. The assumptions defined in this document 

need to be considered in that context.


2.1 Strategic position (defined by the Advisory and Review Committee (ARC) of the NER) 

The following key points are worth highlighting: 

& The aim of the modelling is to determine the long-term least-cost electricity supply options to the country, 

independent of ESI structure and subject to the primary assumptions and constraints; 

& The NIRP includes the electricity market within and external to South Africa (imports to and exports from 

South Africa); 

& The NIRP may be used as a basis for identifying investment opportunities for suppliers in the ESI; 

& The NIRP's objective is to optimise the supply-side and demand-side mix to keep the price of electricity to the 

consumers as low as possible. 

2.2 Primary Assumptions 

The NIRP2 reference case is based on the following primary assumptions approved by the ARC: 

12 

& The net discount rate (before tax) agreed for the study is 10 % internal to South Africa; 

& Options are compared on the basis of 1 January 2003 prices. Foreign capital is converted to South African 

rands at the exchange rate of R9/$ reflective of a long-term planning approach; 

& Plant availabilities for new plants are based on the World Energy Council (WEC) best quartile results for 

2002. For existing plants the studies use the current targets in Eskom adjusted independently for each 


provision of 2% for OCLF to cater for risk). 

& The planning horizon for the study is 20 years, from 2003 until 2022; 

& National moderate electricity consumption and demand growth; 

& Low DSM penetration; 

& Inflation for O&M and fuel resources at South African PPI unless stated otherwise; 

& New technologies costs are adjusted for Transmission integration or where applicable the avoided 

Transmission costs (and losses) according to regional site selection; 

& The NIRP2 does not make any assumptions on the ownership of the plants. 

2.3 Risks and Uncertainties 

This Report does not address risk rigorously but rather addresses it through imposing a minimum reserve 

margin on the plan of 10%. Imposing a deterministic reliability index (reserve margin of 10%) as a constraint 

does not directly reflect specific risk factors such as FOR, generation mix and unit size. However, it does 

provide a reasonable estimate of reliability performance when other parameters remain constant over the 

planning period. 

Due to time constraints, it was agreed at the ARC as a first pass, to develop a reference plan using a 10% 

reserve margin constraint as proxy for risk. The 10% reserve margin is reflective of current inter utility 

agreements in the Southern African Power Pool (SAPP). In addition, a second plan is developed based on a 

15% reserve margin constraint reflective of international practise. 

There are a large number of risks confronting the ESI in the future. These risks are both short-term and longterm. 

For example in terms of the load forecast a short-term risk could consist of an unexpected cold weather 

snap, whereas a long-term risk could be unexpected sustained increase in demand for electricity. Some of 

these risks include: 

& Plant failure leading to longer than expected plant outage; 

& Unavailability of municipal / Eskom / imported generating capacity; 

& Degree of market penetration of DSM and maintaining current level of interruptible loads;


& Unexpected decrease / increase, spurious or sustained, of electricity demand; 

& Changes to the load shape associated with the forecast electricity demand; 

& Unexpected decommissioning / de-rating of existing generating capacity 

& Uncertain and prolonged lead times for building new plant; 

& Project slippage 

& Inclusion of co-generation options; 

& Embargoes on nuclear energy; 

& Shortage of skills to maintain and grow the system; 

& Other energy forms displacing electricity in the energy market; 

& Revolutionary technologies coming on the scene and stranding existing assets; 

& Internalisation of externalities, such as Introduction of a carbon tax and environmental levy; 

& Plant life expectations not met; 

& Retail choice; 

& Deterioration in credit rating, exchange rates etc. resulting in a higher cost of capital; 

& Electricity supply and sales contracts (import and export contracts) being reneged upon; 

& Effect of AIDS on the electricity market. 

& Drought and Floods 

2.4 Optimisation parameters 

The basis for the optimisation of this NIRP is the least cost of electricity for the supply life cycle. This takes into 

consideration the cost of un-served energy (CUE) to the consumer. For this NIRP2, the CUE is assumed to be 

R20 666/MWh (Eskom 2003). 

This CUE was derived from a customer survey of the market sectors of the electricity supply industry (ESI). 

Because of an expected marketing drive for DSM, mainly in the residential sector, but also in the commercial 

and industrial sectors, the high CUE associated with the industrial sector was chosen as representative. This is 

because DSM initiatives that could change the load profile may become exhausted over the 20-year planning 

horizon. Previous NIRP1 used CUE of R 19000/MWh associated with the industrial sector. 

13 

2.5 Criteria for inclusion of Supply-side and Demand-side options 

The criteria listed below have been approved by the NER's Advisory and Review Committee (ARC) and are 

intended to give guidance in determining whether an option is formally included in the base case. 

Technologies that are not included in the base case will be evaluated in sensitivity studies. For technologies to 

be included in the reference case they should: 

& Be technologically feasible; 

& Be economically viable; 

& Have adequate accuracy of costs; 

& Be under national control either via equity participation, ownership or secure contracts; 

& Be socially, politically and environmentally acceptable; 

& Be dispatchable; 

& In line with World Bank emission standards. 

3.NATIONAL ELECTRICITY FORECAST 

The load forecast is the foundation upon which resources planning is based. It is an endeavour to forecast the 

most likely futures based on selected long-term Southern African economic forecasts. The forecast takes as its 

starting point the current position in the electricity supply market but in projecting the future, it excludes any 

further demand-side interventions. 

A detailed sectoral approach has been used over the last ten years to develop the long-term energy (GWh)


forecast. This method has been improved and refined over time. Using a sectoral approach, which considers 

about 110 sectors or major customers individually, is one of the ways to lower the forecast risk. The forecast 

has also been updated on average more than once per year during the past ten years. 

The national plus foreign electricity forecast used in these studies is based on an average annual economic 

growth rate of 2.8%, over the planning horizon and moderate temperatures throughout the year. The foreign 

portion includes normal sales to traditional neighbouring states plus the Scorpion zinc project in Namibia and 

the aluminium smelters Mozal 1 & 2 in Mozambique. 

To address the major inherent uncertainty in the environment, a cone of uncertainty approach is used to 

develop low, moderate and high-energy forecasts. The electricity database consists of the best quality of data 

for all the 110 individual sectors, going back as far as 1980. The load forecast has been developed by Eskom 

together with contributions from major sectors/customers and wide consultations inside and outside Eskom. 

The National forecast range is illustrated in Figure 1 below. 

Electricity sales forecasts - national plus foreign 

400000 

350000 

High 

Moderate 

Low 

14 

GWh 

300000 

250000 

200000 

150000 

2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 

Figure 1: Electricity sales forecast range - National plus foreign 

The average growth in energy in intervals over a five-year period within the planning horizon is given in Table 1: 

Table 1: Average demand growth intervals 

High (%) Moderate (%) Low (%) 

2003 - 2008 4.3 3.2 1.6 

2008 - 2013 3.1 2.3 1.0 

2013 - 2018 2.6 1.8 0.9 

2018 - 2022 2.5 1.8 0.8 

The electricity growth in the early years until 2006 is high (4% pa) due in part to cater for major expansions in 

platinum mining and high demand for ferrochrome as experienced in 2002 and 2003 and one further 850MW 

aluminium smelter at Coega. However this high growth is not sustained after 2006. Eskom sales growth has 

been high in 2002 and 2003 but the average sales growth is only 2.2% per annum over the last six years. The 

long-term forecast allows for a growth in fixed investment but there are currently no new major projects, which 

have been officially approved, other than the platinum mine expansions.


An hourly electricity load model (HELM) is used to develop the maximum demand forecast where the annual 

energy forecast has been converted to an annual maximum demand forecast using updated sectoral 

customer usage profiles. It is expected that system energy utilisation with respect to annual peak demand will 

deteriorate slightly over time and the system annual load factor worsen from a current average of 74% to about 

73% by 2017. 

Of specific importance is the impact of system losses on the forecast demand. The Eskom system losses have 

been increasing over the last number of years from 5% in 1990 to 7.7% in 2002. The system losses for the 

National forecast are estimated to be currently 9% increasing to in excess of 10% over the planning horizon. 

Details of the moderate annual forecast (energy and demand) are shown in the Tables given in Appendix 2 to 

this report. The demand forecast is illustrated in Figure 2: Increase in annual peak demand and system losses 

(national plus foreign) below. 

Increase in forecast annual peak demand (National + Foreign) and losses 

12.0% 

10.0% 

(%) Increase 

8.0% 

6.0% 

4.0% 

National + Foreign annual 

system losses (%) 

Annual Increase in peak 

Demand (National + Foreign) (%) 

Forecast Annual Peak Demand in 

2022 = 53256MW 

I e. Growth from 2004 to 2022 = 

19611MW 

15 

2.0% 

Forecast Annual 

Peak Demand in 

2004 = 33645MW 

0.0% 

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 

Figure 2: Increase in annual peak demand and system losses (national plus foreign) 

The short-term accuracy of the forecast and the track record of the long-term forecast are being monitored on 

an annual basis. The short-term variance is around the zero line and is not always positive or always negative. 

Figure 3 below tracks Eskom's (as opposed to national plus foreign) forecast predictions over the last ten years 

within a cone of 1.5% to 4% growth per annum. Actual sales are shown in the thick black line. 

Over the last few years these results show that the actual values achieved were slightly lower than the forecast 

values but in the last two years actual values were slightly higher. It is also important to note that the forecast 

value for the year 2007, as seen at this stage is very close to the value forecasted for the same year in 1996.


Eskom long term sales forecast track record 

GWh 

370000 

320000 

270000 

220000 

1994 

1995 

1996 

1997 

1998 

1999 

2000 

2001 

2002 

2003 

Actual 

High 4% 

Low 1.5% 

170000 

120000 

1990 1995 2000 2005 2010 2015 

16 

Figure 3: Eskom track record 

The following is a brief summary of the main assumptions of the long-term forecast (national plus foreign). 

3.1 Economic Growth 

Long term economic growth rate for the moderate forecast is 2.8% average annual growth over the planning 

horizon. This economic growth rate takes into account the impact of HIV / AIDS. 

3.2 Large Industrial Projects 

New large industrial projects, such as the proposed Pechiney aluminium smelter, Billiton Hillside aluminium 

smelter expansions, Columbus Stainless Steel expansions, Sasol new projects and expansions and Mozal 2, 

have been included in the forecast. Further expansions to ferrochrome plants are also provided for. Current 

platinum mining expansions have been included, with provision for limited expansions after 2007/8. It was 

assumed that new gold mining projects would replace old ones. Gold production in South Africa is assumed to 

continue to decrease slightly over the long term. With regard to the longer term, allowance had also been made 

in the energy forecast for unknown new projects, based on past experience. A list is regularly revised for all 

possible new electricity intensive projects, including projects with a very low probability of occurrence. 

3.3 Electrification 

The forecast makes provision for the electrification of homes by Eskom and the municipalities. Electrification 

carried out by Eskom forms the bulk of its prepaid sales category. The number of connections obtained from 

planners and an estimated consumption per connection are used as a guide. It is assumed that the 

electrification rate will level off over time. The prepaid category only formed about 2.5% of total 2002 electricity 

sales in the country.


3.4 Electricity Intensity 

The growth in the long term forecast is high in the near term due to major expansions of some electricity 

intensive industries. However, the growth is expected to reduce in the latter period of the planning horizon due 

to the fact that the electricity intensity of the South African economy is expected to decrease over time. This is 

characteristic of an economy, which is moving towards a more service based structure as is the case in South 

Africa and implies that the GDP growth rate in future will be consistently higher on average than the electricity 

growth rate. This has already been experienced in South Africa during the four-year period 1998 to 2001. 

The electricity intensity of the South African economy is shown in Figure 4. The current major expansions of 

electricity intensive industries are expected to decline and platinum mining is not expected to continue to 

maintain the current high growth rates after 2007/8. With more beneficiation of minerals, less energy will be 

required per unit of production. Once there is no more excess generating capacity, electricity prices will have to 

increase in real terms. Although it is assumed that this increase will not be extraordinary, it is expected that it 

will marginally affect electricity consumption. 

0.35 

RSA electricity intensity 

0.30 

0.25 

kWh / rand 

0.20 

0.15 

17 

0.10 

0.05 

0.00 

1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 

Figure 4: RSA electricity intensity 

3.5 Natural Gas 

Allowance is made for the loss in electricity sales due to consumers switching from the use of electricity to the 

use of natural gas. 

3.6 Foreign Forecast component 

This part of the forecast includes sales that are currently in place - mostly under contract. Also included are the 

Mozal aluminium smelter in Mozambique and the Skorpion zinc project in Namibia. Provision had also been 

made for the Corridor heavy mineral sands project in Mozambique over the longer term.


3.7 Demand Profiles 

Figure 5 shows a typical demand profile for the total Eskom system for a summer week. 

27000 

25000 

Eskom integrated system typical summer week hourly demand profile 

January/February 

2002 

2001 

2000 

23000 

MW 

21000 

19000 

17000 

15000 

Mon Tue Wed Thu Fri Sat Sun 

Figure 5: Typical hourly peak demand summer profile 

Figure 6 and shows a typical demand profile for the total Eskom system for a winter week. 

18 

33000 

31000 

29000 

27000 

Eskom integrated system typical winter week hourly peak demand 

July 

2002 

2001 

2000 

MW 

25000 

23000 

21000 

19000 

17000 

15000 

Mon Tue Wed Thu Fri Sat Sun 

Figure 6: Typical hourly peak demand winter profile 

4.DEMAND-SIDE OPTIONS (DSM) 

This NIRP2 assumes a significantly (approximately 50%) lower penetration of DSM programmes than the 

previously in NIRP1. Previous estimates were based on desktop studies. Pilots and experience in the field 

now indicate that a more conservative approach should be followed in the estimates for DSM programmes 

both in terms of capacity and cost. Five DSM programmes are targeted:


& Residential Energy Efficiency (REE) 

& Commercial Energy Efficiency (CEE) 

& Industrial and Mining Efficiency (IMEE) 

& Residential Load Management (RLM) 

& Industrial and Mining Load Management (IMLM) 

Each programme has been modelled on a basis that capital will be expended over a nine-year period to ensure 

increasing annual displacements of aggregate Megawatts will be deducted from the load associated with a 

specified energy usage profile as indicated in the Table 2. 

Table 2: DSM aggregate megawatts displaced 

Programme Annual MW Displacements Annual Energy Displaced GWh 

Residential Energy Efficiency 32 129 

Commercial Energy Efficiency 14 69 

Industrial and Mining Efficiency 16 101 

Residential Load Management 49 

Industrial and Mining Load Management 41 

Each aggregate annual displacement is maintained over a period of twenty years to ensure no deterioration of 

displacement takes place. (I.e. maintenance will continue for a further 11 years beyond the nine-year 

investment period). 

Interruptible supply options are modelled separately to the above DSM programmes. Eskom has several 

interruptible supply agreements with key customers. These agreements are severely energy constrained and 

their capacity impact in the long-term has been reduced. There have been several comments by various ARC 

members to consider these interruptible supply agreements as emergency capacity only. This issue will be 

addressed in the next round of the NIRP in terms of the uncertainty inherent in this assumption. 

19 

The DSM team of Eskom in their endeavours to continually improve decision-making on the role of DSM in 

resources planning have taken several actions one of which is to improve information on DSM before its 

inclusion. 

In terms of residential DSM, Eskom has good statistics on device populations and unit gains in the residential 

markets. The homogeneity in residential markets provides confidence in DSM planning data, because enduse 

devices are generally characterised within narrow ranges of diversity. 

The need to upgrade confidence for this NIRP was in the commercial and industrial market segments, 

because previously there was no sound strategy to deal with the diversity of information. Fortunately since the 

previous National Integrated Resources Plan, NIRP1, the DSM team has had access to a document on market 

assessment for electric motors prepared for the Department of Energy (DOE) in the USA. This document 

clearly spells out the opportunities for energy efficiency in the majority of the commercial and industrial enduse 

sectors. Electric motors make up nearly 50% of Eskom's total sales, or more than 65% of the sales to 

industrial and commercial clients. 

A major task in preparation of DSM data for NIRP2 has been the mapping of the DOE information on DSM 

opportunities in the USA into the South African context. This has now been done, and together with other desk 

research it has been revealed that the situation in SA is very different to the USA. South Africa needs to devise 

its own strategy to contend with issues that do not exist in the case of the USA. 

There has been a major focus on the industrial and commercial sectors, providing a better insight into the CEE, 

IMEE and IMLM strategies to be adopted in the future. A further improvement in this NIRP is in the provision of


an aggregated summary for the ICEE and ICLM programmes compared with the previous industrial and 

commercial components. 

The NIRP1 placed more emphasis on energy efficiency as opposed to load management programmes. Better 

experience has now shown this emphasis to be misplaced, in that energy efficiency programmes are difficult to 

implement and to achieve performance targets due to the many barriers involved, and are turning out more 

costly than previously estimated. 

4.1 The Demand Side Planning Basis for NIRP2 

The basis for end-use load forecasting adopted for DSM planning in this NIRP is the “moderate forecast” as 

detailed above. The amount of DSM resources to be developed over a planning period is very sensitive to the 

load forecast. For sensitivity studies there is also the facility to use a “high load growth” and a “low load growth” 

forecast. A high growth forecast would imply higher targets for DSM, and a low load forecast would suggest 

lower targets than required for the moderate forecast. This issue will also be addressed in the next round of the 

NIRP in terms of the uncertainty in DSM penetration. 

4.2 Introduction to the Demand-Side Screening Results 

The following summarises the DSM resources submitted for inclusion in the NIRP2. Resources that are not 

currently included may qualify for inclusion in future version if further investigation provides the information 

needed to obtain positive screening results. The screening results for energy efficiency options are given in 

Table 1 to 3 below. For comparison, separate columns give the NIRP1 and NIRP2 assumed market 

penetration. 

20 

In Tables 6 and 7, pertaining to the load management resources, there are high and low capacity factor (CF) 

resource capacities, given in MW, and the balance, which is the difference between the two. 

Capacity factor is defined as the percentage of time that the capacity of the load management resource can be 

fully utilised. “Hi CF MW” means that control algorithms are utilised to achieve a high capacity factor. There is a 

maximum percentage of time that the residential load management (RLM) resource can be utilised. In the 

maximum percentage mode the system peak MW can only be reduced by the amount reflected in the “Hi CF 

MW” column. 

The system peak can be further reduced by the amount in the “Balance of MW” column, when operated in the 

low capacity mode. The “Lo CF MW” column indicates the total reduction of the system peak if the entire load 

management resource is only operated in low capacity factor mode.


4.2.1 Residential Energy Efficiency - REE 

Table 3 gives the results of screening Residential Energy Efficiency. 

Table 3: Residential Energy Efficiency 

OPTION No of units Assumed Market 

Penetration 

MW/a GWh/a IN NIRP2 NIRP1 NIRP2 

INTEGRAL CFL'S 25.20 91.97 YES 33% 20% 

HOT WATER SYS. EFFICIENCY 2.93 10.13 YES 28% 10% 

LOW FLOW SHOWERHEADS 2.38 8.22 YES 34% 10% 

HOTWATER CONSERVATION 0.47 1.63 YES 30% 10% 

COOKING AWARENESS 1.34 3.44 YES 30% 10% 

EFFICIENT COOL STORAGE NO 30% 10% 

THERMAL EFFICIENCY NO 30% 10% 

DEMARKETING TO GAS NO 30% 15% 

MODULAR CFL'S NO 33% 20% 

Total 32.39 129.0 

The REE resources submitted for NIRP are predominated by integral CFL's. 

The energy efficiency measures related to hot water systems have also been included but it was decided not to 

include efficient cool storage appliances, thermally efficient building practices and de-marketing to gas. Also 

included are integral CFL's and energy efficiency measures on storage water heaters. The integral version of 

the CFL costs less to sustain this technology over the planning period. The major problem associated with 

targeting integral CFL's for the efficient residential lighting initiatives is the risk of sustainability (i.e. conversion 

back to inefficient incandescent light bulbs in the future). 

21 

The strategy with respect to electrical water heating is to encourage storage water heating. Indications are that 

residential load management is a lower cost resource than building peaking plant. Instant water heaters have 

not found favour, because they do not lend themselves to load shifting. For storage water heating to hold its 

ground in SA it is important to demonstrate that these systems can be energy efficient, and that the per capita 

water consumption can be contained, especially in the event of water shortages at a future time. For waterheater 

system efficiency measures like hot water conservation, low flow showerheads and thermal insulation 

are included. 

Other DSM options that have been included in residential energy efficiency strategies in other countries have 

yet to be developed to a stage where they are mature enough to include in the REE strategy with some 

confidence. For example energy-efficient fridges and freezers will only be included in the strategy at a later 

stage when there is more clarification on appliance labelling policy. Information is required on how appliance 

labelling would help to create demand and to make the program economically more attractive. The strategy on 

fridges and freezers is therefore to closely monitor the DME initiatives regarding appliance labelling. 

Residential space-heating loads are not included but should be targeted as a demand-side measure, because 

they are one of the main reasons for poor utilization of supply capacity, and therefore not very economical to 

supply. Previous work by the DSM team has indicated that gas heating is likely to be more expensive to the 

consumer, yet electrical space heating is losing market share to gas space heating. With rising oil prices, and 

therefore LPG prices, it is uncertain, whether there will be a significant shift to gas for space heating. Better 

information is needed on how thermal efficiency measures impact on space heating demand before deciding 

on a relevant strategy. In particular, there is a need to know what the most marketable measures are to desensitise 

system space-heating demand to weather-related events like falling temperatures and cloud cover 

during winter months.


4.2.2 Industrial, Mining and Commercial Energy Efficiency 

Table 4 gives the results of screening CEE programmes. For CEE, the assumptions on market penetration 

remain more or less the same as with the NIRP1 

Table 4: Commercial energy efficiency 


Penetration 

MW/a GWh/a IN NIRP2 NIRP1 NIRP2 

SUPERVISION 2.05 10.60 YES 14.1% 15% 

FANS/PUMPS 0.64 4.68 YES 26.0% 26.0% 

COMP AIR 

LIGHTING 9.53 43.54 YES 27.0% 27.0% 

VSD's 0.26 1.90 YES 3.0% 3.0% 

REPLACE 0.68 3.50 YES 15.0% 10.0% 

UPGRADE 0.66 3.40 YES 13.0% 10.0% 

DOWNSIZE NO 

COOLING SYSTEM EFF NO 

HEAT RECOVERY NO 

INSULATION NO 

Total 13.82 69.38 

22 

Table 5 gives the results of screening of Industrial and Mining energy efficiency programmes 

Table 5: Industrial and Mining Energy Efficiency 


Penetration 

MW/a GWh/a IN NIRP NIRP1 NIRP2 

SUPERVISION 2.24 15.33 YES 14.1% 2.0% 

FANS/PUMPS 1.31 9.26 YES 26.0% 5.0% 

COMP AIR 2.26 16.54 5.0% 

LIGHTING 3.77 23.44 YES 27.0% 10.0% 

VSD's 4.40 29.3 YES 3.0% 3.0% 

REPLACE 1.13 7.72 YES 15.0% 2.0% 

UPGRADE 1.06 7.02 YES 13.0% 2.0% 

DOWNSIZE NO 

COOLING SYSTEM EFF NO 

HEAT RECOVERY NO 

INSULATION NO 

Total 16.15 100.93 

These results suggest that most of the drive-power programs qualify for submission. The demand-side plan 

assumes that ESCO's will be enabled that specialize in the delivery of CEE and IMEE resources to the 

industrial market, and that they are competitive and operational in SA in the future. Under these assumptions it 

is possible that this target can be achieved within 10 years. 

This assumption assumes support from 

governance authorities in terms of policy. 

Additional energy efficiency resources would become available were commercial and industrial participants to


focus their attention on heating and cooling systems that derive their energy from an electricity supply. These 

are indicated in the demand-side plan as a requirement for further investigation. 

The most viable area for industrial and commercial energy efficiency is motor supervision and control. 

Maintenance and supervision of compressed air or gas compressor systems is another area for potentially 

very cost-effective energy efficiency measures. Companies that employ the practice of re-winding motors 

rated lower than 45kW may require advice on the economics of re-winding versus replacing. In some cases it 

may even pay to upgrade motors to premium efficiency motors. 

It is most important to transform the market for new construction to energy efficient lighting, especially in 

commercial buildings. Lighting controls should be installed to avoid unnecessary lighting usage. Retrofits 

typically do not offer very short paybacks, but are in the range where respectable rates of return can be 

guaranteed. Lighting retrofits that would also reduce air-conditioning load should be targeted first. It is a matter 

of major concern that the majority of industrial and commercial lighting sales into the new construction market 

still conform to old and outdated standards for energy efficiency. 

Every effort should be made to apply best practices in the design of systems employing fluid or airflow. In 

particular excessive throttling of flow should give way to variable speed drives or staged switching of drives, 

and pipes and ducts should be sized to minimise total resource costs. Every effort should be made to promote 

the adherence to best practices on systems with pumps, fans and compressors. CEE and IMEE retrofits 

should initially target systems of large drives, i.e. 200 kW and larger. 

4.2.3 Residential Load Management (RLM) 

In the case of RLM, the screening criteria have led the DSM Team to firm conclusions on the RLM strategy. Up 

until now too many conflicting DSM strategies were considered. Table 6 gives the results of screening the 

various RLM strategies and options. 

23 

Table 6: Residential load management programmes 

SUMMARY OF RLM SCREENING RESULTS 

Options Hi CF MW/a Balance of MW/a Lo CF MW/a 

Ripple Control 49 49 98 

4.2.4 Industrial and Mining Load Management (IMLM) 

The pre-integration study data shows that for IMLM there is a potential 600 MW of controllable load that can be 

developed, assuming the resource is operated at high capacity factor. 

A summary of the first-round screening results for ICLM is given in Table 7 

Table 7: Industrial and mining load management 

Options Hi CF MW/a Balance of MW/a Lo CF MW/a 

INDUSTRIAL/ MINING LOAD 40.9 40.9 82 

Under system emergencies the resource can be operated at low capacity factor. The low capacity factor 

figures assume that the resource is required for 2 hours per day. 

4.3 Uncertainty and Risk Associated with DSM 

The DSM team has had to come to grips with the reality that it is developing DSM plans for a fast-changing 

energy market. Many of the decisions about the future structures of the Electricity Supply Industry (ESI) in


South Africa, which have yet to be made, may impact on DSM. Utilities will have no control over the way the 

industry will develop in future. 

To deal with uncertainty about the future, the DSM team has to make certain assumptions regarding the 

conditions for sustainable demand-side resources to exist. The DSM programmes assume that the 

governance authorities in consensus will set up the specified conditions for a DSM resource market with key 

stakeholders and energy consumers. 

Risk is closely linked to a lack of dependable information. The Demand-side plans make many assumptions on 

important factors that affect market penetration. The DSM assumptions and resource plans are based on 

targets that are believed to be realistic. The demand-side plan is exposed to risk if any of the assumptions are 

proven to be unrealistic. It is prudent to firm up on much needed information about the market potential for 

demand-side resources. 

4.4 Priorities for the Development of Demand-Side Resources 

24 

These demand-side plans are based on the assumption that the SA market will be willing and able to transform 

towards a preference for the development of demand-side resources. Historically the preference has been to 

develop supply-side resources, so the SA market is currently not richly endowed with the resources and skills 

required to deliver demand-side resources on a large scale. A prime issue of concern is the fact that DSM is 

often seen from a utility perspective as a loss leader in that their core business is in selling electricity. This is 

especially relevant to energy efficiency programmes and it is imperative that policy and legislation be adopted 

in future to address this problem. Another major problem is in sustainability. For example in the Table View load 

management pilot study, previously about 8-10MW could be achieved through geyser control. Recent tests 

show only 4MW can currently be switched off. Customers are bypassing the system because they see no 

personal benefit as no time-of-use tariff is in place for individual residential customers.


5.SUPPLY-SIDE OPTIONS 

Technology options are compared on the basis of discounted cash flows (total capital & operating costs) over 

the option lifetime using 10% net discount rate as dictated by the ARC of the NER. The levelised cost per unit 

output of the option is obtained by dividing the present value by the total discounted lifetime generation. 

Levelised costs are calculated as a function of plant load factors (screening curves) to illustrate the relation 

between the levelised cost and plant load factor. 

5.1 Eskom System - Existing and Committed Capacity 

The current (2003) total net base load capacity in operation of the Eskom system is given in Appendix 1 to this 

report and is 33 871 MWe. The total net peaking capacity in operation is 2319 MWe. This includes Acacia and 

Port Rex gas turbines, Drakensberg and Palmiet pumped storage, Gariep and Vanderkloof hydro plants. 

Eskom has a long-term contract to purchase power from Cahora Bassa hydro plant in Mozambique. Available 

net capacity from Cahora Bassa is at present 912 MWe (after losses). A further 369 MWe (after losses) is 

committed from 2004. Eskom is importing about 100 MWe of peaking capacity from Zesco (Zambia) via 

Zimbabwe and about 110 MWe from the DRC. These latter are excluded from the study as Eskom has been a 

net exporter of similar proportions to neighbouring states. (I.e. as these imports and exports are effectively 

equivalent the exports are not included in the load forecast nor are the imports included in the capacity plan). 

5.2 Non-Eskom System - Existing Capacity 

The following options are considered in the plan: 

Appendix 1 also gives the net capacity of non-Eskom generating plant. These have been aggregated into 

blocks of similar capacity units for modelling purposes as follows: 

25 

& Munic 1: consisting 12x60 MW sent out coal-fired capacity 

& Munic 2: consisting 21x30 MW sent out coal-fired capacity 

& Sasol: consisting 12x60 MW sent out coal-fired capacity 

& Steenbras pumped storage plant: 3x60 MW sent out 

& Mini Hydro: 1x65 MW sent out 

& Minic OCGT: 6x50 MW sent out 

The details of these plant and capacities are given in Appendix 1. 

In addition to the Eskom and non-Eskom supply capacity there is a total 1510 MW interruptible supply capacity 

included in the plan. The interruptible load accepted for inclusion in the plan, although based on current 

contracts, does not necessarily represent the existing contracts. It is assumed that some level of interruptible 

capacity, either in the form of contracts for reserve or as a demand-side bidding option, will exist in the future. In 

total the existing capacity assumed on the National system in 2003 amounts to 41378 MWe sent out. 

5.3 Return to Service of Eskom Mothballed Plant (Simunye) 

These are the stations that were put into storage during the period of high excess capacity on the Eskom 

system: Camden (1520 MW), Grootvlei (1130 MW) and Komati (909 MW). These capacities are on a sent out 

basis. These stations all use PF coal. When refurbished, Camden is anticipated to run as base load, whereas 

Grootvlei and Komati would most probably be two-shifted i.e. operating at an annual load factor of less than 

30%. 

Results of a pre-feasibility study initiated and carried out by Eskom indicate that repowering some of Eskom's 

old plant with Fluidised Bed Combustion (FBC) technology (such as at Komati) could be an option in


comparison with other future base load plant. The remaining half of Komati (456 MW) could be re-powered 

with FBC technology to operate as base load. 

5.4 New Supply-Side Options 

Table 8 below summarises the data for all the new supply-side technologies considered in the plan. Detailed 

description of the cost and performance of the considered supply-side options is shown in Appendix 3. The 

ARC, applying the approved selection criteria, determined the inclusion of the supply side technologies in the 

plan. The capital costs are averages of the international data evaluated. Operating and Maintenance costs 

shown are averages from the international literature, after they have been adjusted for South African labour 

conditions. Appendix 3 contains additional information about the supply-side technologies, including costs, 

performance parameters, lead times and data statistics. 

A transmission benefit has been given to stations built in the Cape close to the load centres. This is to account 

for the line losses that occur when transmitting electricity from an equivalent station in the Highveld and for 

strengthening the grid along transmission lines. 

PBMR data is given for both the initial multi-module and, after several multi-modules have been deployed, a 

cheaper multi-module (costs are likely to decrease, benefiting from technology learning). 

Adding units to existing coal plants and co-generation options have not been considered in the plan. 

5.4.1 New Pulverised Fuel (PF) Coal-Fired Stations 

26 

In the absence of more cost competitive options, coal-fired plants are likely to remain the backbone of the 

electricity supply industry in South Africa for a long time. Their proven design, the vast operating experience 

gained locally, their wide availability, reliability and relatively low cost make them an attractive option for base 

1 

load generation. This is often the case in other parts of the world, such as China , where low-cost coal is 

available. The future stations considered consist of 6 units, each of 700 MW installed capacity, with drycooling 

(or hybrid) systems. Coal stations can operate with or without flue gas desulphurisation (FGD) to 

reduce emissions but only the option with FGD was considered for the plan because of the decision to adhere 

to World Bank emission standards. Detailed information on the cost and performance of the PF plants is 

shown in Appendix 3.4 

5.4.2 New Gas-Fired Plant 

Potentially Namibia, Mozambique or Angola could supply Gas. New gas-fired plants considered are open 

cycle gas turbines (OCGT) and combined cycle gas turbines (CCGT). Open cycle gas turbines, by virtue of 

their low efficiencies and resultant high cost of fuel when operating at low load factors are considered for 

peaking options only. Combined cycle gas turbines with much improved efficiency levels are regarded as nonpeaking 

technologies due to the likely constraints on gas contracts (take or pay) although they could 

technically follow load. 

The OCGT stations considered have two 120 MW units. The CCGT stations considered have 5 x 400 MW 

units. 

If OCGT turbines were built, and in the future a gas network was developed, it is likely that OCGT plants would 

be converted to CCGT plants, which would increase the capacity and efficiency of the stations. This has not 

been taken into account in the plan. 

1 Future Implications of China’s Energy-Technology Choices, July 2001


Fuels considered for OCGT plants are kerosene, LPG, local syngas and LNG. Fuels considered for CCGT are 

pipeline gas and LNG. Fuel prices for the gas options are given for all the fuels considered for each technology. 

Detailed information on the cost and performance of the OCGT and CCGT plants is shown in Appendix 3.2 and 

3.3 respectively. 

5.4.3 New Pumped Storage Schemes 

Two pumped-storage schemes have been considered in the plan. Braamhoek (which has already received a 

record of decision (ROD)) and a generic scheme which would follow Braamhoek. Braamhoek consists of four 

333 MW units, while the generic option consists of three 333 MW units. It must be noted that the costing of 

pumped storage schemes is site specific. Additional details on the pumped storage plants are provided in 

Appendix 3.8. 

5.4.4 Greenfield Fluidised Bed Combustion 

The fluidised bed combustion (FBC) stations considered have an installed capacity of 500 MW. They are 

comprised of two 250 MW boilers and a 500 MW turbine, and have a 35 year lifetime. The price of duff coal will 

have to be negotiated between the station and the mines. Additional information on the FBC is provided in 

Appendix 3.5. 

27


28 

Table 8: Summary of cost and performance data of new supply-side options


5.4.5 Conventional Nuclear (Advanced Light Water Reactor (ALWR)) 

The new nuclear plant considered is an advanced light water reactor. It consists of two 900 MW units and will 

be built at the Koeberg (existing nuclear) site near Cape Town. 

The ALWRs are based on existing light water reactors but are designed for simplicity and ease of construction 

and maintenance. They have a considerable degree of inherent safety (safety built in to the design rather than 

reliant on active safety mechanisms). Examples of such reactors are the Westinghouse AP1000 and the 

General Electric ABWR. There are currently no ALWR plants in operation. Additional information on the ALWR 

is provided in Appendix 3.6. 

5.4.6 Research projects/programs 

In addition to the “mainstream” supply-side options listed above, the following are amongst the technologies 

that are being researched and are considered in the screening curve analysis: 

5.4.6.1 Wind energy 

There are several areas in South Africa, particularly in the coastal regions, which have been identified as 

having good potential for wind power. The proposed wind farm consists of twenty (1 MW) wind turbines. 

There is little detailed data available for specific sites in South Africa. Additional details on wind turbines are 

provided in Appendix 3.9. 

5.4.6.2 Solar thermal 

The Solar Thermal power station would be built near Upington in the Northern Cape. It would have three 110 

MW units and the capacity for storage. It is therefore regarded as a dispatchable station in the plan. Additional 

details on solar thermal power stations are provided in Appendix 3.10. 

29 

5.4.6.3 PBMR 

If the necessary approvals are given and a commercial decision is taken to build one, the first full-sized 

demonstration unit should be on line by 2008. If successful, further units will be built with the aim of producing 

a power station consisting of eight units, each unit with an installed capacity of 170 MW. Additional details on 

the PBMR plant are provided in Appendix 3.7 

5.4.7 Imported Hydro 

There is a large potential for South Africa to import hydro-electricity from the rest of Africa. A promising site is at 

Mepanda Uncua in Mozambique about 60 km downstream of the existing Cahora Bassa Power Station on the 

Zambezi River. In the first stage of this project the installed capacity at the HV terminals would be 1300 MW. 

The firm power capacity at 95% availability is 827 MWe. Additional details on the imported hydro option are 

provided in Appendix 3.11. 

5.5 Screening Curves 

To evaluate the cost of generation from new options, a screening curve analysis was undertaken. A screening 

curve evaluates the cost of generating electricity at different average levels of production or load factors over 

the life of the plant. This gives an indication of the economics of running the plant at these load factors. 

The following screening curves have been drawn from the levelised capital, O&M and fuel costs for the various 

technologies at different load factors. The analysis has been split into two sections: non-peaking stations 

(plants expected to run at high load factors) and peaking stations (plants expected to run at low load factors). 

Non-peaking plants operate as base load when their operating (including fuel) costs are lower than peaking


stations. There are some exceptions where stations with high operating costs are included as must run plants 

by virtue of fixed price contracts or technical constraints. CCGT options are examples whereby the gas 

contracts are placed on the basis of firm commitments to take minimum quantities by virtue of purchasing 

power agreements. These plants can be considered as inflexible options to system dispatch and construed as 

must run options. 

Peaking stations run at low load factors by virtue of their high operating costs generally have lower capital and 

fixed operating expenses than non-peaking stations. The ranges reported in the screening curves reflect the 

deviation in the data collected from international literature. 

Figure 7 illustrates the life cycle costs to build and operate the base load plants analysed in this report. 

1500.00 

1300.00 

1100.00 

R/MWh 

900.00 

700.00 

CF with FGD 

Conventional Nuclear 

PBMR 

Imported Hydro 

Solar Thermal 

500.00 

CCGT LNG 

CCGT Pipe 

300.00 

30 

Greenfield FBC 

100.00 

30 40 50 60 70 80 90 

Load Factor (%) 

1 

Figure 7: Life cycle levelised costs to build and operate base load plants 

Figure 8 illustrates the life cycle costs to build and operate the peaking plants analysed in this report. 

4000 

3500 

3000 

2500 

Gas Turbine (LNG) 

Gas Turbine (Local Syngas) 

R/MWh 

2000 

1500 

1000 

Wind (Non-dispatchable) 

Pumped Storage (Generic) 

500 

Pumped Storage (Braamhoek) 

0 

0 5 10 15 20 25 30 

Load Factor (%) 

Figure 8: Life cycle levelised costs to build and operate peaking plants


The open cycle gas turbine levelised cost curves cross the Braamhoek Pumped Storage scheme cost curve 

near 6% load factor. They cross the Generic Pumped Storage Scheme near 10% load factor. (Note: Wind 

turbines are considered non-dispatchable options operating at low load factor due to paucity of wind resources 

in South Africa). 

Although some of the technologies overlap in the screening curves shown above, there is a significant 

statistical difference between the capital costs of the various technologies at a 95 % confidence interval (see 

Appendix 3). The screening curves show that, once capital costs are combined with O&M and fuel costs, the 

differences between the total levelised costs of certain technologies are not statistically significant (they 

overlap) at certain load factors. 

5.6 Other: Environmental, Externalities, Transmission Expansion 

Certain sites and technologies will reduce the need to strengthen the electricity grid as they will be built close to 

load centres that are currently far from existing generation. This is taken into account in the levelised cost 

curves and is described further in the detailed descriptions of the technologies. 

All the new coal fired generating options considered meet World Bank emissions standards. Conventional coal 

stations will be equipped with flue gas desulphurisation. Due to the limited water resources all new coal 

stations are dry cooled. 

6.INTEGRATION AND SENSITIVITY ANALYSIS 

Resources Planning has to deal with multiple conflicting objectives, a broad range of options and pervasive 

uncertainty. In this context it has to do with dominance and finding plans representing reasonable trade off 

amongst various conflicting objectives. If, for example, the objective were to minimise cost then those plans 

with higher cost would be considered inferior to those with lower cost. Lower cost plans would therefore 

dominate the higher cost plans. 

31 

The focus of the traditional resources planning approach is to provide a robust (and flexible) plan determined 

on the basis of an analysis of risk from either under or over investment within a range of forecast demand for 

electricity over a specified planning horizon. (A plan that is 100% robust is one which lies in the decision set for 

all futures and would lead to no regret). Flexibility is of equal importance to robustness, if not more important in 

the uncertain planning environment. Flexibility can be defined as the ability to modify a resource plan without 

significantly degrading system reliability and economics, in response to actual data that have deviated from 

the forecast data. 

The objective is therefore to provide long-term strategic projections of supply-side and demand-side options 

added or deducted from the system over a specified planning horizon taking into account investment risk and 

option lead time under a range of different planning scenarios. 

The risks associated with this planning process have been outlined previously but predominantly focus on 

those uncertainties, which will influence decisions on: 

& The timing for new supply-side and demand-side initiatives 

& The plant mix


Due to time constraints, this round of the NIRP focuses on the development of a reference plan only. Elements 

of uncertainty and risk are taken into account by imposing constraints on plant operating reserve. In terms of 

this process two plans have been developed for this round of the NIRP, namely: 

& Reference Plan - constrained to 10% reserve margin 

& Alternative Plan 1 - constrained to 15% reserve margin 

& Alternative Plan 2 - sensitivity study conducted on the reference plan in order to determine the impact of 

excluding Interruptible supply agreements from the plan 

& Alternative Plan 3 (optimum reserve margin) - non-constrained plan providing as an output the optimum RM 

based on trade-off between the cost of reliability of supply and the cost of un-served energy to the 

consumer. 

The details of these plans are given in Appendix 2 to this report. 

6.1 Reference Plan 

The reference plan has a minimum constraint of 10% on the reserve margin as proxy to take account of the risk 

elements detailed above. In addition to the constraint on the reserve margin, two further constraints are 

imposed. 

The first is in terms of the extent of un-served energy that would be allowed. In this case the un-served energy 

is constrained to a maximum of 0.011% of total energy demand in any specific year. This is reflective of 

historical values utilised in Eskom in previous years in order to ensure a loss of load expectation (LOLE) of 22 

hours is not exceeded in any given year. 

32 

The second is in terms of the number and capacities of Open Cycle Gas turbines accommodated in the plan 

because of perceived limitations in the gas supply and the possibility of these options becoming stranded 

assets in the event more interruptible supply options are implemented in the future. It was decided in this 

instance to consider a maximum number of 10 stations limited to 2x120 MW each could be built in the twentyyear 

planning horizon. 

The capacity outlook for this plan is illustrated in Figure 9 below and the detailed results are given in Appendix 

2 to this report. 

Mothballed Coal-Fired FBC GT Pumped Storage Demand-side Options 

YR Cam (PF) Gr'tvlei 

(PF) 

Kom 

(PF) 

PF (1) PF (2) Greenfield 

FBC 

OCGT PS (A) PS (B) PS (C) PS (D) CEE IMEE IMLM REE RLM Syst Res 

Committed Committed CommittedCommittedCommittedCommittedCommitted 

2003 Decide 14 16 41 32 49 24% 

2004 Decide Decide 14 16 41 32 49 21% 

2005 380 Decide Decide 14 16 41 32 49 18% 

2006 380 Decide 14 16 41 32 49 15% 

2007 380 Decide Decide 14 16 41 32 49 14% 

2008 380 Decide 240 14 16 41 32 49 12% 

2009 377 480 14 16 41 32 49 12% 

2010 377 303 480 14 16 41 32 49 12% 

2011 377 303 480 14 16 41 32 49 10% 

2012 303 466 480 333 11% 

2013 240 999 11% 

2014 466 666 11% 

2015 333 333 10% 

2016 466 666 11% 

2017 932 333 11% 

2018 466 333 11% 

2019 642 10% 

2020 642 1284 12% 

2021 1284 1284 12% 

2022 1284 1284 11% 

TOTAL 1520 1130 909 3852 3852 2796 2400 1332 999 999 666 124 145 368 292 441 

Figure 9: Reference plan (10% Reserve Margin)


These results indicate a commitment to ensuring the immediate return to service of Camden power station in 

the suite of Eskom Simunye mothballed plants. In addition an immediate decision is required to build at least 

720 MW of OCGT plant for commissioning and commercial service by 2009. Furthermore, activities 

(monitoring and evaluation) need to be implemented immediately to ensure Braamhoek pumped storage 

remains on track for commercial service in 2012, and also that the DSM programmes achieve their targets over 

the ensuing years. 

6.2 Alternative Plan 1 to Reference Plan 

There is a concern that carrying a 10% reserve margin on the moderate national forecast is too conservative in 

the light that most international utilities are reluctant to carry a RM below 15%. An additional plan has been 

developed which is constrained to a reserve margin of 15%. This plan is detailed in Figure 10 below. 

Mothballed Coal-Fired FBC GAS Pumped Storage Demand-side Options 

YR 

Cam (PF) Gr'tvle 

i (PF) 

Kom 

(PF) 

PF (1) PF (2) Greenfield 

FBC 

CCGT 

(1) 

CCGT (2) OCGT PS (A) PS (B) PS (C) PS (D) CEE IMEE IMLM REE RLM Syst 

Res 

Committed Decide Committed Committed Committed Committed CommittedCommitted 

2003 Decide Decide Decide Decide 14 16 41 32 49 24% 

2004 Decide Decide Decide 14 16 41 32 49 21% 

2005 380 14 16 41 32 49 18% 

2006 380 Decide 14 16 41 32 49 15% 

2007 380 188 Decide 14 16 41 32 49 14% 

2008 380 377 202 Decide 480 14 16 41 32 49 15% 

2009 377 303 480 14 16 41 32 49 15% 

2010 202 466 387 240 14 16 41 32 49 15% 

2011 466 774 14 16 41 32 49 14% 

2012 188 1161 333 15% 

2013 202 999 15% 

2014 932 333 15% 

2015 666 14% 

2016 642 333 15% 

2017 466 666 333 15% 

2018 642 466 15% 

2019 333 13% 

2020 1284 333 15% 

2021 1284 1284 15% 

2022 1284 1284 387 14% 

TOTAL 1520 1130 909 3852 3852 2796 1935 774 1200 1332 999 999 999 124 145 368 292 441 

33 

Figure 10: Alternative Plan 1 to reference plan (15% Reserve Margin) 

Alternative 1 requires additional capacity of 1842 MW over the planning horizon, at the additional cost of 15 

552 million Rand, in order to maintain the higher RM of 15%. The plan also requires acceleration of the return to 

service of the mothballed plants and base load PF plant. 

6.3 Alternative Plan 2 (Sensitivity Study) 

A prime concern of ARC members is the uncertainty surrounding the sustainability of interruptible supply 

options. In order to determine the impact of interruptible supply options, a further plan (Alternative Plan 2) was 

developed based on the primary assumptions and constraints used to develop the reference plan but 

excluding all interruptible supply options from the plan. This plan is detailed in Figure 11 below. 

This plan requires significant acceleration of the return to service programme of the mothballed plants in the 

near term. In this, the plan is at risk, because the return to service programme of the Simunye plant, even with 

the best endeavours, might be unable to be accelerated sufficiently to meet the demand in the near term 

(2006). 

There is a PV increase in costs of this plan when compared to the reference plan of 2 997 Million Rand. The 

higher cost of this plan is largely due to the fact that there is a penalty paid in interrupting customers in the early 

years at a high cost of un-served energy of 20 660 R/MWh.


Mothballed Coal-Fired FBC Gas Pumped Storage Demand-side Options 


(PF) 

Kom (PF) PF (1) PF (2) Greenfield 

FBC 

OCGT PS (A) PS (B) PS (C) PS (D) CEE IMEE IMLM REE RLM Syst 

Res 

Committed Committed Committed Committed Committed Committed Committed 

2003 Decide Decide Decide Decide 14 16 41 32 49 19% 

2004 Decide Decide 14 16 41 32 49 16% 

2005 380 14 16 41 32 49 13% 

2006 380 Decide Decide 14 16 41 32 49 10% 

2007 380 377 101 14 16 41 32 49 10% 

2008 380 101 Decide 480 14 16 41 32 49 11% 

2009 377 202 480 14 16 41 32 49 11% 

2010 377 303 480 14 16 41 32 49 12% 

2011 202 466 480 14 16 41 32 49 11% 

2012 466 480 333 11% 

2013 999 11% 

2014 999 333 11% 

2015 333 10% 

2016 466 333 333 10% 

2017 932 333 11% 

2018 642 333 11% 

2019 466 10% 

2020 642 1284 11% 

2021 1284 1284 11% 

2022 1284 1284 11% 

TOTAL 1520 1130 909 3852 3852 2796 2400 1332 999 999 999 124 145 368 292 441 

Figure 11: Alternative Plan 2 - sensitivity to reference plan (excludes interruptible supply options) 

6.4 Alternative Plan 3 (Optimal reserve margin) 

The issue of determining an optimal reserve margin for electricity generation in South Africa has not been 

addressed formally in any forum in the country to date. In optimal integrated resources planning studies, the 

calculation of the reserve margin is an outcome, based on the primary assumptions underpinning the 

development of the plan. 

34 

It is therefore expedient to determine a reserve margin based on the outcome of the optimisation process, but 

taking into account specified risk(s) associated with key uncertainties in the primary planning assumptions. 

Such a plan will result in a different mix and timing of new plant options compared to one developed to meet a 

deterministic reliability index. 

The development of such a plan is intended as the outcome of the next round of studies aimed at producing a 

recommended set of strategies (plan) for NIRP2 based on an analysis of risk factors associated with the 

primary assumptions. 

As a starting point to this exercise, an optimal plan has been developed, based on the primary assumptions 

listed above without imposing any constraints and in particular on the reserve margin, un-served energy and 

number of peaking (OCGT) plants. 

This plan is detailed in the Appendix 2 to this report. It is intended that this plan will serve as the basis for the 

next round of studies where several different plans will be developed on the basis of meeting a number of risk 

scenarios associated with the uncertainties surrounding several of the key assumptions. In each of the plans, 

the reserve margin will be an outcome as a function of the risk associated with specified uncertainties. 

It is important to state that given certainty in the current primary assumptions, the reserve margin required 

would be of the order 4% in the long-term. This plan would however not be sufficiently flexible to meet any of 

the short or long-term risks detailed above.


7.SYSTEM ANNUAL AVERAGE LONG RUN MARGINAL COST 

In this report, the terms Long Run Marginal Cost (LRMC) and Long Run Incremental Cost (LRIC) are used 

interchangeably. Theoretically the LRMC refers to the incremental cost of providing one additional unit of 

energy to supply the increase in demand; whereas the LRIC refers to the incremental cost of providing an 

additional increment of energy. 

The LRMC curve is calculated by determining the difference in costs between two generation expansion plans 

developed over the twenty-year planning horizon: 

(1) Base case: to meet the forecast demand in electricity and, 

(2) Marginal case: the forecast demand increased by an increment (500 MW in this case) 

The annual difference in optimal cost for building and operating plant to meet these two plans is divided by the 

difference in energy associated with each of these annual forecast demands. (I.e. the base demand and the 

demand increased by the increment of 500 MW at the system annual average load factor). 

The LRMC has been developed using this methodology, for the reference plan and each of the alternative 

plans to the reference plan. The detailed results are given in Appendix 2 attached to this report and illustrated 

graphically in Figure 12. 

280.0 

260.0 

System Marginal Cost of NIRP Ref Plan at 2003 prices (10% NDR) 

240.0 

220.0 

35 

LRMC in R/MWh 

200.0 

180.0 

160.0 

140.0 

120.0 

100.0 

80.0 

Alt Plan 2 (Ref excluding interruptible loads , (R/MWh) 

Alt Plan 1 (15% RM) (R/MWh) 

Ref Plan (R/MWh) 

60.0 

40.0 

20.0 

0.0 

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 

Years 

Figure 12: Annual average long run marginal costs of plans 

Of particular significance in these results are the high values of the LRMC in the early years associated with the 

Alternative 2 excluding interruptible supply options. This is because the Simunye mothballed plant cannot be 

returned to service in time to avoid interrupting customers at a high cost to the economy.


8.CONCLUSIONS 

The main conclusions drawn from the NIRP2 reference case study could be summarised as follows: 

36 

1) Options for diversification are insufficient to meet all of the forecast demand for electricity over the next 20- 

year planning horizon. Coal-fired options are still required for expansion during this period. For 

environmental benefit it is imperative to continue with efforts to reduce the costs of implementing clean 

coal technologies and improve the efficiency of coal-fired plants; 

2) Base load plants are required for commercial operation from 2010. Base load options competing, include; 

Pulverised Fuel Coal-fired (PF); Fluidised Bed Combustion (FBC); Combined Cycle Gas Turbine (CCGT). 

Given the cost and performance data used in the plan these options are broadly comparable, at 10% net 

discount rate, if regional siting and transmission benefits are included. 

3) At the current assumed cost of capital (10% net discount rate) and after returning the Eskom mothballed 

plant to service, fluidised bed combustion technologies are South Africa's most economic option, followed 

by investment in coal-fired plant. This in turn is followed by importing gas / LNG for CCGT plant in the 

Cape. The studies also show that after taking the avoided cost of transmission into account (including 

losses) that is not sufficient to make the CCGT plant competitive with coal; 





5) The NIRP plans are based on attainment and sustainability of the DSM targets , power plants availability, 

imports and interruptible loads; 

6) The NIRP plans indicate that 920 MW OCGT peak load plants must begin commissioning from 2008; 

7) Maintaining a higher reserve margin of 15% over the planning period will require acceleration of the RTS of 

the mothballed plants and coal-fired options together with commissioning of additional base load capacity 

(CCGT); 

8) Diversified options are new technologies to South Africa. If these options for whatever reason are not able 

to be implemented it will mean a return to a dependency on new pulverised coal-fired plants earlier than 

shown in these plans; 




10) Should interruptible supply and / or OCGT capacity not be implemented this will significantly advance 

new base-load capacity;

Risk & Sensitivity Analysis 


Stage 2 


37 

COMPILED BY 

The National Electricity Regulator 

ISEP Eskom (Resources and Strategy) 

Energy Research Institute 

University Of Cape Town


NIRP 2 STAGE 2: 

RISK AND UNCERTAINTY ANALYSIS 

TABLE OF CONTENTS 

1 INTRODUCTION 40 

2 SCOPE OF STUDY 40 

2.1 APPROPRIATE RESERVE MARGIN 40 

2.2 IDENTIFIED RISKS AND UNCERTAINTIES 41 

2.3 IMPACT OF THE SELECTED RISK PORTFOLIOS 42 

38 

3 MODELED UNCERTAINTIES 43 

3.1 FORECAST 43 

3.1.1 Background 43 

3.1.2 Compilation of the energy component of the higher forecast 43 

3.1.3 Compilation of the demand component of the higher forecast 44 

3.1.4 Forecast Data 46 

3.2 AVAILABILITY OF PLANT 47 

3.3 SUSTAINABILITY OF EXISTING INTERRUPTIBLE LOADS 48 

3.4 SUSTAINABILITY OF EXISTING CAPACITY 48 

4 SCENARIO DEVELOPMENT 49 

5 RANKING OF PLANS/CANDIDATE PLANS 51 

5.1 METHODOLOGY 51 

5.2 TOTAL PROBABILITY-WEIGHTED COST 52 

5.3 RELIABILITY ASSESSMENT 53 

5.4 EMISSIONS AND DIVERSIFICATION ASSESSMENT 54 

6 PREFERRED RESOURCE PLAN 56 

6.1 PREFERRED PLAN 14 56 

7 SENSITIVITY ANALYSIS 57 

7.1 COMPARISON OF DATA CHANGES TO NIRP2 REFERENCE PLAN 57 

7.2 THE IMPACT OF NET DISCOUNT RATE ON OPTIMUM CHOICE OF TECHNOLOGY 59 

7.3 RENEWABLE ENERGY TECHNOLOGIES 62 

8 CONCLUSIONS 64 

9 APPENDICES 64


LIST OF FIGURES 

Figure 1. Impact of Modelled Uncertainties 43 

Figure 2. Energy Forecasts 44 

Figure 3. Maximum Demand Forecasts 45 

Figure 4. The proportion of consumption increases over the reference case. 47 

Figure 5. Variability of total cost. 53 

Figure 6. Reserve Margin under own future. 53 

Figure 7. Reserve Margin under A1 future. 54 

Figure 8. Ranking of Plans 56 

Figure 9. Capex Costs for Base Options 58 

Figure 10. O&M Costs for NIRP 2 Reference Plan and NIRP 2 Risk & Sensitivity Plan 58 

Figure 11. Fuel Costs for NIRP 2 Reference Plan and NIRP 2 Risk & Sensitivity Plan 59 

Figure 12. Levelised costs of base-load plants versus Net Discount Rate for the 

NIRP 2 Reference Plan 61 

Figure 13. Levelised costs of base-load plants versus Net Discount Rate for the 

NIRP 2 Risk & Sensitivity analysis 61 

Figure 14. Preferred Plan 14 with Renewables 63 

Figure 15. Reduction in environment emissions in preferred Plan 14 with renewables. 63 

LIST OF TABLES 

Table 1. Forecasting Data 46 

Table 2. Electricity demand in the high growth scenario (GWh) 47 

Table 3. Availabilities of new plant. 48 

Table 4. Probabilities associated with primary assumptions. 49 

Table 5. Scenarios and their probabilities. 50 

Table 6. PWC Ranking of the Plans 52 

Table 7. Comparison of Candidate Plans 55 

Table 8. Preferred Plan 14. 57 

Table 9. Levelised costs of candidates for selection in the NIRP2 Reference Plan 60 

Table 10. Levelised costs of candidates for selection for the NIRP2 Risk and Sensitivity 

analysis 60 

Table 11. Additional Cost of Renewable Technologies 62 

39


1.Introduction 

This Report is an update of the NIRP2 Reference Plan. This work was commissioned following comments 

received from both the Public and the NER Advisory Review Committee (ARC) after the publication of the 

NIRP2 Reference Plan. 

This Report should be read in conjunction with that of the NIRP2 Reference Plan since it uses as basis the 

primary planning assumptions (including the data base) of the reference plan unless stated otherwise. Where 

data revisions have been made to the reference data, these are explained in the Report. The list of 

abbreviations and bibliography of the NIRP2 Reference Plan apply to this Report. 

The objective of this study is to provide a robust plan for NIRP2 based on an appropriate net reserve margin 

above the expected annual maximum demand for electricity assumed in the Reference plan. This reserve 

margin is calculated as an outcome based on an analysis of specified probability weighted risk portfolios. 

A complete listing of comments from the Advisory Review Committee (ARC) of the NER plus comments from 

individual members of the Public concerning the NIRP2 Reference Plan are contained in Appendix A attached 

to this Report. The most important aspects leading to the need to carry out a risk and sensitivity analysis are 

summarized below: 

& The use of deterministic reserve capacity margin as a substitute for risks, without explicitly identifying the 

mitigated risks associated with the planning uncertainties (plant availability, load forecast deviations, fuel 

availability, interruptible supplies etc), is not ideal planning method; 

40 

& The appropriate reserve margin should be an outcome of a risk and uncertainty analyses, characteristics of 

the existing and future plants and costs. The reserve margin should be an outcome of the modeling process 

based on sets of defined assumptions for different scenarios; 

& The impact of the discount rate on the optimum choice of technology should be considered in the analyses; 

& Considerations regarding resource alternatives under high growth scenarios should be included; 

& The costs of some generation sources such as FBC and imported hydro, as well as the cost of the coal are 

underestimated; 

& The Inclusion of Government renewable energy targets. 

2.Scope of study 

The major concern expressed by the ARC and members of the Public were expressed in the many comments 

regarding an appropriate reserve margin to cater for risk. This report therefore focuses on developing a robust 

plan with an appropriate reserve margin accounting for risk. It also takes into account as far as possible 

attributes other than least cost such as environmental emissions, flexibility and a diversified portfolio of 

options. 

2.1 Appropriate Reserve Margin 

The reference plan used two levels of deterministic net reserve margin (10% and 15%) to take account of risk. 

The use of a deterministic net reserve margin to address risk, without explicitly identifying and quantifying the 

risks associated with the primary planning uncertainties (e.g. plant availability, load forecast deviations, fuel 

availability, interruptible supplies etc), is not an ideal planning method.


An appropriate net reserve margin should consist of a plant mix which matches the risk impacting the capacity 

shortage; E.g. If Cahora Bassa units became unavailable , base-load capacity would be required to meet the 

shortfall. If interruptible capacity became unavailable, peaking plant would be required. 

Following discussions at the Advisory Review Committee and resulting from the various comments received, it 

was decided to adopt the following approach to determine a appropriate net reserve margin for stage2 of 

NIRP2. 

& Develop scenarios and assign probabilities 

& Develop plans for each scenario 

& Carry out trade-off analyses (I.e. Test each plan under each scenario and calculate the total probability 

weighted cost (cost of supply plus cost of non-supply) of each plan multiplied by the probability of 

occurrence of the scenario 

& Select the most robust (flexible) plan under agreed attributes 

Evaluate the net reserve margin of this plan in respect of the expected forecast 

2.2 Identified risks and uncertainties 

Following the NIRP2 Reference plan, the following short-term and long-term risks and uncertainties were 

identified for inclusion in the risk and uncertainty analysis. 

& Plant failure leading to longer than expected plant outage; 

& Unavailability of municipal / Eskom / imported generating capacity; 

& Degree of market penetration of DSM and maintaining current level of interruptible loads; 

& Unexpected decrease / increase, spurious or sustained, of electricity demand; 

& Changes to the load shape associated with the forecast electricity demand; 

& Unexpected decommissioning / de-rating of existing generating capacity 

& Uncertain and prolonged lead times for building new plant; 

& Project slippage 

& Inclusion of co-generation options; 

& Embargoes on nuclear energy; 

& Shortage of skills to maintain and grow the system; 

& Other energy forms displacing electricity in the energy market; 

& Revolutionary technologies coming on the scene and stranding existing assets; 

& Internalisation of externalities, such as introduction of a carbon tax and environmental levy; 

& Plant life expectations not met; 

& Deterioration in credit rating, exchange rates etc. resulting in a higher cost of capital; 

& Electricity supply and sales contracts (import and export contracts) being reneged upon; 

& Effect of AIDS on the electricity market. 

& Drought and Floods 

41 

Many of these risks and uncertainties are inter-dependent. By aggregating some risk events into independent 

risk portfolios it is possible to provide a net reserve margin to cater for a number of risk events under the 

umbrella of one independent risk portfolio. This can best be illustrated by the following examples: 

Drought: The impact of drought on Hydro imports (Cahora Bassa) can be taken into account by reducing the 

capacity of this option. The level of capacity reduction from Cahora Bassa can also be increased to cater for 

reduced imports due to increasing capacity withdrawals to neighbouring states (notwithstanding current 

agreements) in the future. Although strictly speaking these two events can be construed as separate events 

each with their own probability of occurrence, for the purposes of this report the level of capacity reduction is 

set to accommodate both with the same probability. 

No account is taken of the impact of drought on existing Hydro capacity because the amount of such Hydro in


this country is very low. Drought also impacts both cooling water supplies of existing and new coal-fired plants. 

This is mitigated to some extent by the fact that all new inland base plants are considered to be dry-cooled (or in 

the least dry-cooled with wet assistance at high ambient temperatures). Those located at the coast use once 

through sea water cooling. 

Flood: This impacts the availability of fuel supplies to the coal-fired plants, mitigated to some extent by those 

stations with open cast mines (these are more likely to be impacted) carrying higher stock levels. From the 

point of view of imported Hydro, a substantial energy loss could be averted in times of flood, through 

implementing a SAPP Zambesi River Authority to ensure for example that where possible water is not let out of 

higher altitude dams (Kafua) whilst lower altitude dams (Cahora Bassa) are spilling. 

Impact of fuel cost / price: The South African Electricity Supply is heavily dependent on coal as feedstock. In 

the event that there was a major price increase in the cost of coal, the economy would be at risk. There are 

proponents to providing a diversified approach to building new generating options which may also be more 

favorable in reducing environmental and greenhouse gas emissions. This aspect is addressed in that three 

new base technologies other than conventional coal-fired plants are considered: Fluidised Bed Combustion 

(FBC), Nuclear Pebble Bed Modular Reactors, Gas Combined Cycle (CCGT) options. 

Following discussions with various experts in their specific fields, it was decided to address the following four 

risk portfolios, considered to be largely independent of each other and as having a major impact on the plant 

mix, timing and requirement for carrying reserve, namely: 

42 

& Level of risk associated with the moderate national forecast being higher and particularly in the near-term to 

medium-term; 

& Level of risk associated with Eskom and non-Eskom generators being able to sustain high levels of plant 

availability once the system becomes stressed and the plants age; 

& Level of risk of Non-Eskom and Import capacity becoming unavailable or unreliable (i.e. being de-rated) and 

particularly in the near-term; 

& Availability of interruptible supply options continuing to serve as reserve capacity. Already these options are 

severely energy constrained and their capacity impact has been reduced. 

2.3 Impact of the selected risk portfolios 

Following discussions with respective experts the following levels of risk were identified for each of the risk 

portfolios: 

& National moderate Load forecast increased by 2570MW in 2007 to 5078MW in 2022 to account for higher 

GDP growth and colder weather (Base-load to Peaking) 

& Plant availability reduced from 88% to 85% due to poorer FOR (Base-load). 

& Contracted Interruptible Supply Excluded: 

> Mozal, Alusaf, Ferrochrome and other industries (Peaking) 

& Capacity Reductions: 

> Cahora Bassa capacity reduced from 1281MW by 250MW in 2004 and 500MW thereafter (Base-load) 

> Non-Eskom OCGT capacity (180MW of 270MW) assumed unavailable over the planning horizon 

(Peaking) 

> Non-Eskom coal-fired capacity (600MW of 1920MW) assumed unavailable over the planning horizon 

(Base-load)


The impact of these levels of uncertainty over the planning horizon is illustrated graphically in Figure 1 below. 

Impact of Modelled Uncertainties 

10000 

9000 

8000 

7000 

Capacity (MW) 

6000 

5000 

4000 

3000 

Capacity impact of excluding Import and Munic capacity (MW) 

Capacity Impact of excluding DSM Interruptible load (MW) 

Capacity impact of increased load forecast (MW) 

Capacity impact of reduced plant availability (89% to 85%) (MW) 

2000 

1000 

0 

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 

Years 

Figure 1: Impact of Modelled Uncertainties 

3.Modelled Uncertainties 

These risk portfolios were generated on the basis of the comments made on the primary assumptions by the 

ARC and in consultations with various experts. Following is a description of the levels or risk associated with 

the primary assumptions as detailed in the NIRP2 Reference Plan. 

43 

3.1 Forecast 

3.1.1 Background 

The NIRP2 reference plan is based on a moderate demand for electricity developed by Eskom. This forecast 

used moderate GDP growth and moderate weather conditions. It was recommended by the ARC to also 

develop a forecast of accelerated demand growth for the risk and uncertainty analysis, reflecting colder 

weather conditions and higher GDP growth (especially in the near-term). It was not considered necessary by 

the ARC to use a lower forecast than the moderate, the moderate being considered to be already reflective of a 

lower than expected scenario. It was agreed that the Energy Research Centre (ERC) would develop the high 

growth forecast independent of Eskom. Eskom resources would be used to transform the energy forecast into 

hourly annual demand values according to Eskom sector profiles. 

3.1.2 Compilation of the energy component of the higher forecast 

The higher energy forecast in demand for electricity was developed by ERC based on energy forecasting 

techniques incorporated in the LEAP model (SEIB 2002; Howells et al 2002; and Hughes et al, 2003), and the 

Integrated Resource Planning manual of the United Nations Environment Program (UNEP 1998). It considers 

a relatively detailed breakdown of electricity consuming sectors. For example, the mining sector was divided 

into nine different sub-sectors, as was the industrial sector. Added to this was the commercial, transport, 

agricultural and residential sectors. A relationship was developed between the outputs of these sectors and the 

future Gross Domestic Product (GDP) (with the exception of the residential sector) as a basis for future 

electricity demand. The relationship between GDP and sector output is time dependant with the proportional 

contribution of each sector changing over time. The sector outputs considered was either value added, or 

physical output.


In line with the assumptions approved by ARC, the ERC developed a high forecast which used higher than 

expected growth in the near- to medium-term in specific sectors. The growth associated with this forecast is 

higher than that of the moderate forecast of the NIRP2 Reference plan by an estimated half a percentage point 

in the short to medium term. 

When the results of the ERC energy forecast are compared to that of the Eskom model they will differ in certain 

respects. A forecast with a higher growth rate will automatically imply a different sectoral energy mix. 

Furthermore, the energy model used by the ERC makes use of sectoral data of a more aggregated nature than 

the Eskom sectoral model. 

A comparison of the energy forecasts for the previous NIRP1, NIRP2 reference case and this analysis is 

shown in the Figure 2 below. 

Energy sent out 

400000 

44 

Annual energy sent out [GWh] 

350000 

300000 

250000 

200000 

NIRP1 Moderate growth and moderate weather 

NIRP2 Moderate growth and moderate weather 

NIRP2 High growth and cold weather 

150000 

2001 

2003 

2005 

2007 

2009 

2011 

2013 

2015 

2017 

2019 

2021 

2023 

2025 

Year 

Figure 2:. Energy Forecasts 

3.1.3 Compilation of the demand component of the higher forecast 

The energy forecast is transformed into an hourly demand forecast (instantaneous demands averaged over 

each hour) with the HELM (Hourly Electric Load Model) computer model. The model uses: 

& Detailed sectoral load profiles developed by Eskom 

& Energy sales forecast and losses as inputs 

& Temperature as an input where the impact is determined through pre-determined formulae (E.g. for 

extremely cold weather). 

& Output is hourly maximum demands in each year over the whole planning horizon 

The following assumptions were used in developing this demand forecast: 

& The ERC energy sales forecast as described above; 

& Updated sectoral demand profiles, which were obtained from recent load research carried out by Eskom 

consultants in 2003; 

& The system load factor was constrained to deteriorate within a narrowband (from 72% in 2004 to 70% in 

2022).


& Based on 1996 weather conditions which is recorded as the coldest weather Nationally over the last 12 years 

& No new demand side management initiatives are included in the forecast from 2003 (I.e. from the beginning 

of the planning horizon) 

It is pertinent to note that the system losses as calculated by the ERC and used in this analysis are marginally 

different to those calculated by Eskom. The annual maximum demands for the various NIRP studies are 

compared in Figure 3below. 

65000 

Maximum demand 

60000 

Maximum demand [MW] 

55000 

50000 

45000 

40000 

35000 

30000 

25000 

NIRP1 Moderate growth with moderate weather 

NIRP2 Moderate growth with moderate weather 

NIRP2 High growth with cold weather 

2001 

2003 

2005 

2007 

2009 

2011 

2013 

2015 

2017 

2019 

2021 

2023 

2025 

Year 

45 

Figure 3:. Maximum Demand Forecasts 

3.1.3.1.1 Weather 

The 1996 National weather pattern was used to estimate weather impact because statistically it was found to 

be the coldest over the last twelve years. The impact of this colder weather is to increase the annual peak 

demand of the moderate forecast by approximately 3% in 1996 and extrapolated for the other years in the 

planning horizon.


3.1.4 Forecast Data 

The relevant data supporting the Figures illustrated above are given in the Table 1 below. 

NIRP1 (Moderate) NIRP2 (Moderate) NIRP2 (High) 

Moderate Growth and moderate 

weather (Forecast energy and losses 

determined by Eskom) 

Moderate Growth and moderate 

weather (Forecast energy and losses 

determined by Eskom) 

Higher Growth and cold weather 

(Forecast energy and losses 

determined by ERC) 

Year 

NIRP1 MW 

Moderate Increase 

per 

Year 

(MW) 

Sales 

GWh 

Losses 

% 

Annual 

Energy 

(GWh) 

NIRP2 

Moderate 

Demand 

(MW) 

MW 

Increase 

per 

Year 

(MW) 

Sales 

GWh 

Losses 

% 

Annual 

Energy 

(GWh) 

NIRP2 MW 

High Increase 

Demand per 

(MW) Year 

(MW) 

Sales 

GWh 

Losses 

% 

Annual 

Energy 

(GWh) 

46 

1999 177689 

2000 181908 

2001 32316 185171 9.88 205476 

2002 33283 967 188747 10.83 211665 

2003 34499 1216 194240 11.63 219794 33645 197189 9.15 217044 34624 197401 9.21 217426 

2004 35684 1185 202858 10.81 227439 34914 1269 205159 9.15 225824 36817 1274 209722 9.33 231303 

2005 36784 1100 212559 9.19 234066 36146 1232 212415 9.15 233805 38394 1238 218274 9.45 241054 

2006 37867 1083 220649 8.24 240457 37632 1486 221593 9.27 244242 39931 1466 227001 9.57 251024 

2007 38811 944 225444 8.22 245623 38528 896 226305 9.27 249423 41098 902 232602 9.69 257560 

2008 39798 987 230669 8.15 251128 39440 912 231064 9.26 254657 42166 919 237671 9.81 263523 

2009 40784 986 235125 8.51 256984 40377 937 236245 9.33 260559 43387 930 243686 9.93 270552 

2010 41835 1051 239711 8.84 262952 41389 1012 241799 9.33 266681 44574 1018 249547 10.05 277429 

2011 42864 1029 244139 9.26 269068 42342 953 247295 9.34 272762 45777 961 255450 10.17 284370 

2012 43894 1030 248886 9.53 275118 43389 1047 253220 9.41 279513 47091 1039 262064 10.29 292123 

2013 44893 999 253810 9.64 280896 44343 954 258581 9.41 285448 48275 962 267718 10.42 298859 

2014 45922 1029 258683 9.83 286883 45271 928 263829 9.42 291258 49423 936 273173 10.54 305358 

2015 46971 1049 263584 10.04 292993 46198 927 268355 9.55 296678 50520 903 278263 10.66 311465 

2016 47980 1009 268586 10.22 299148 47034 836 273055 9.56 301910 51597 844 283176 10.78 317391 

2017 49068 1088 273812 10.37 305500 47939 905 277825 9.56 307194 52692 913 288139 10.90 323388 

2018 50199 1131 278976 10.64 312198 48901 962 282731 9.63 312847 53839 954 293445 11.02 329788 

2019 51350 1151 284268 10.88 318978 49841 940 287716 9.63 318375 54976 948 298636 11.14 336075 

2020 52507 1157 289652 11.10 325802 50790 949 292725 9.63 323929 56118 958 303850 11.26 342405 

2021 53739 1232 295143 11.32 332817 52249 1459 297965 10.64 333445 57101 1072 308905 11.38 348572 

2022 54936 1197 300639 11.55 339879 53256 1007 303304 10.64 339407 58334 1013 314602 11.50 355483 

2023 56182 1246 306176 11.74 346911 

2024 57400 1218 311731 11.96 354066 

2025 58673 1273 317332 12.16 361269 

Average 1098 1032 1013 

Table 1: Forecasting Data 

3.1.4.1 Changes in higher forecast from reference case 

The difference between the NIRP2 Reference case forecast and this high growth forecast is due mostly to an 

increase in industrial demand. This is illustrated in a breakdown of differences in consumption for the year 

2013 as shown in Figure 4.


Transport 

Residential 

Mining 

Agriculture 

Commerce 

Industry 

Figure 4: The proportion of consumption increases over the reference case. 

A detailed breakdown in GWh of demand consumption for the high growth case is given in Table 2 below. 

Table 2: Electricity demand in the high growth scenario (GWh) 

Sector/Year 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 

Transport 3432 3569 3656 3752 3782 3807 3847 3886 3930 3987 4029 

Mining 31923 33204 34079 34987 35228 35326 35528 35678 35966 36398 36694 

Total Industry 91658 97999 101415 105855 108896 111698 115107 118308 121313 124531 127563 

Commerce 18360 19537 20450 21449 22058 22633 23317 23968 24660 25457 26161 

Agriculture 6310 6728 7055 7408 7621 7819 8052 8267 8493 8755 8985 

Residential 32884 34866 36325 37431 38882 40202 41596 42944 44296 45650 46982 

Total domestic 

ex own 

generation 184568 195903 202981 210881 216468 221484 227446 233052 238659 244779 250414 

47 

3.2 Availability of plant 

The plant availabilities of new plants for the NIRP2 Reference Plan are based on the World Energy Council 

(WEC) best quartile results for 2002. For existing plants the NIRP2 Reference Plan uses the current targets in 

Eskom adjusted independently for each individual station to give a weighted average for base-load capacity of 

88% EAF; (7% PCLF: 3% UCLF with a provision of 2% for OCLF to cater for risk). 

The above availability levels were considered too optimistic by the ARC. It was decided to use average results 

rather than best quartile taken from the WEC Report 2001 as being reflective of a lower level of plant 

availability. (Note: Later editions of WEC Reports do not accurately reflect global plant availability levels 

because fewer and fewer utilities are providing input to the WEC database as competition in the Electricity 

Supply Industry increases. Figures are now biased towards a few remaining large utility players still 

contributing). For existing plants this study uses lower Eskom targets adjusted independently for each 


provision of 2% for OCLF). 

A comparison of plant availability levels for this analysis as compared to the NIRP2 Reference Plan is given in 

Table 3 below for all new plant options.


Table 3: Availabilities of new plant. 

48 

Option Expected Low Option Expected Low 

New Coal with FGD 

New Gt Open Cycle (LNG) 

PORg 7.20% 7.20% PORg 7.08% 7.08% 

FORg 5.17% 7.97% FORg 7.31% 13.90% 

Availability 88.00% 85.40% Availability 86.13% 80.00% 

New Coal without FGD 

New Gt Open Cycle (Kerosene) 

PORg 7.20% 7.20% PORg 7.08% 7.08% 

FORg 5.17% 7.97% FORg 7.31% 13.90% 


New Pumped Storage 

Renewables (CSP) 

PORg 1.66% 1.66% PORg 3.85% 

FORg 1.26% 4.82% FORg 1.98% 

Availability 97.10% 93.60% Availability 94.25% 

New Fluidised Bed 

Renewables (Wind) 

PORg 10.20% 7.69% PORg 2.00% 2.00% 

FORg 4.57% 8.89% FORg 1.02% 8.16% 


CCGT Pipeline Excl Trans 

Public PBMR (1st MM) Excl Tran 

PORg 8.73% 8.73% PORg 4.04% 4.04% 

FORg 6.46% 9.61% FORg 4.13% 8.29% 


CCGT LNG Exc Trans 

Public PBMR (1st MM) Inc Tran 

PORg 8.73% 8.73% PORg 4.04% 4.04% 

FORg 6.46% 9.61% FORg 4.13% 8.29% 


CCGT LNG Inc Trans 

Public PBMR Series No Trans 

PORg 8.73% 8.73% PORg 4.04% 4.04% 

FORg 6.46% 9.61% FORg 2.04% 6.21% 


New Gt Open Cycle (Local Syngas) Nuclear 

PORg 7.08% 7.08% PORg 15.00% 

FORg 7.31% 13.90% FORg 7.65% 

Availability 86.13% 80.00% Availability 78.50% 

3.3 Sustainability of existing interruptible loads 

The current contracts entered between customers and Eskom concerning interruptible supply are severely 

constrained in terms of their usage requirements. Studies carried out in Eskom comparing these options with 

equivalent OCGT capacity showed that they should be de-rated to obtain equivalence. In anticipation of future 

Demand Market Participation or other Demand Response mechanisms becoming available, it was considered 

prudent by the ARC to consider the possibility that current interruptible supply contracts may be re-negotiated 

in the future. As such some plans should be developed on the basis of excluding them from the planning base 

in the risk analysis. 

3.4 Sustainability of existing capacity 

As stated previously, some risk events are aggregated into independent risk portfolios. The aggregated 

options in each portfolio are assigned the same probability of occurrence for purposes of this Report. 

The following capacity reductions are included as aggregated options in this analysis. The levels of capacity 

reductions are based on either ARC recommendations or expert opinion:


& Cahora Bassa capacity is reduced by 250MW (from 1281MW) in 2004 and by 500MW thereafter. This is a 

base-load capacity reduction; 

& Non-Eskom OCGT capacity is reduced by 180MW (from 270MW) and assumed unavailable over the 

planning horizon. This is a Peaking capacity reduction; 

& Non-Eskom coal-fired capacity is reduced by 600MW (from 1920MW) and assumed unavailable over the 

planning horizon. This is a base-load capacity reduction. In addition, this latter option targets Municipal 

capacity destined for decommissioning from 2011. 

4.Scenario Development 

It was agreed by the ARC to carry out the risk and uncertainty analysis to develop an appropriate net reserve 

margin using a Resources Planning approach. The focus of this approach is to provide a best (robust and 

flexible) plan developed from an analysis of the risk portfolios and then compare the capacity of the selected 

plan with the expected demand to establish an appropriate net reserve margin. 

(Note: A plan that is 100% robust is one, which lies in the decision set for all futures and would lead to no regret 

whereas flexibility is the ability to modify a resource plan without significantly degrading system reliability and 

economics, in response to actual data that have deviated from the forecast data). 

There are four risk portfolios defined each consisting two alternatives. This results in sixteen scenarios 

incorporating the alternative risk events from each risk portfolio. Optimal plans are then developed for each of 

the sixteen scenarios where the basis for the optimisation is the least cost of electricity for the supply life cycle. 

This considers the least cost of each plan in terms of the cost of supply and the cost of non-supply (CUE) to the 

consumer. For this NIRP2 as explained in the NIRP2 Reference Plan, the CUE is assumed to be 

R20 666/MWh. 

Probabilities were assigned to each of the risk portfolios using a Delphi approach in consultation with the 

various experts in the field associated with developing the portfolios. 

49 

Table 4 below details the probabilities assigned to each of the risk portfolios. 

Table 4: Probabilities associated with primary assumptions. 

Uncertainties: Probability Probability 

Load Forecast Expected (Moderate) (ED) 0.6 High (HD) 0.4 

Plant outage Expected (EF) 0.4 High (HF) 0.6 

Capacity availability Expected (EC) 0.3 Low (LC) 0.7 

DSM Interruptible Load Expected (EI) 0.4 Low (LI) 0.6 

Table 5 below details the sixteen scenarios incorporating the alternative risk events from each risk portfolio 

with the resultant probabilities assigned to each scenario.


Table 5: Scenarios and their probabilities. 

Futures Plan A-1 / Scenario 1 Plan A-2 / Scenario 2 

Load Forecast Expected (ED) High (HD) 

Plant outage Expected (EF) High (HF) 

Capacity availability Expected (EC) Low (LC) 

DSM Interruptible Supply Expected (EI) Low (LI) 

Probability 0.0288 0.1008 



Plant outage High (HF) Expected (EF) 

Capacity availability Low (LC) Expected (EC) 

DSM Interruptible Supply Low (LI) Expected (EI) 




Plant outage High (HF) High (HF) 




50 









Plant outage Expected (EF) Expected (EF) 

Capacity availability Expected (EC) Expected (EC) 

DSM Interruptible Supply Low (LI) Low (LI) 






DSM Interruptible Supply Expected (EI) Expected (EI) 


Futures Plan A-13 / Scenario 13 Plan A-14/ Scenario 14 



Capacity availability Low (LC) Low (LC) 



Futures Plan A-15 / Scenario 15 Plan A-16/ Scenario 16 





Probability 0.0672 0.0432


It is necessary to state that after consultation with the various experts in their fields, that some of the expected 

events (used as basis for developing the NIRP2 Reference Plan) were in fact less realistic than originally 

thought. This resulted in some cases, higher probabilities being assigned to the alternative case than the 

expected case. 

5.Ranking of Plans/Candidate Plans 

The assessment of the plans/scenarios includes the following steps: 

& Development of optimal resource plan for each of the 16 scenarios; 

& Testing each of the plans under the assumptions of the remaining scenarios; 

& Calculation of the total probability weighted cost (PWC) of each plan; 

& Ranking of the plans in terms of the attributes 

& Selection of the most robust plan 

The output of the trade-off analyses would be the most robust optimum plan/strategy for capacity development 

over the planning period. 

The selected attributes (measures of goodness) for evaluation of the plans are: 

& Total probability weighted cost 

& Reliability 

& Emissions; 

& Diversity of fuel sources. 

5.1 Methodology 

51 

The main criteria for measuring the performance of the plans is the total probability-weighted cost (PWC). The 

probability-weighted cost is calculated as the sum of the total cost of the plan for each of the 16 scenarios 

multiplied by the probability of occurrence of the corresponding scenario. 

The 16 plans are ranked in ascending order (minimum cost) in terms of total probability-weighted cost (PWC). 

The first three plans with the lowest probability-weighted total cost are then selected as candidates for the 

preferred plan. 

In order to test the sensitivity of the probability-weighted cost to the length of planning period, these analyses 

were conducted for planning horizon of 8, 12, 16 and 20 years. 

To test the sensitivity of the probability weighted cost to the probability assigned to each of the primary 

uncertainties, i.e. the analyses were conducted for equal probability of each of the primary uncertainties (50% 

probability of occurrence of each of the primary uncertainties), as well as for 60% probability of occurrence of 

the expected uncertainties. 

The second attribute considered is the reliability of the plans measured as the level of the reserve margin 

provided by the plan over the planning horizon. Higher reserve margin will provide higher system adequacy 

and reliability. The candidate plans are ranked in descending order according to the RM they provide. 

The evaluation of the plans in terms of the emissions is conducted by comparing the total emission level (CO2, 

SO2, NO2 and particulate emissions) of the three candidate plans over the planning horizon. 

The fourth attribute for comparison is the diversity of the plans. The diversity of the plans is measured as the 

ratio of non-coal and coal based generation resources.


5.2 Total Probability-Weighted Cost 

The ranking of the plans is conducted in terms of the attribute total probability weighted cost. The first three 

plans are selected as candidates for the most robust plan/strategy for implementation. 

The ranking of the 16 plans and their associated expectation cost over the whole planning period (20 years), 16 

years, 12 years and 8 years is illustrated in Table 6 below. While under the assumed probabilities of the 

primary uncertainties Plan 14 enjoys the least cost or most robust position, Plan 8 and Plan 16 follow closely its 

performance. The ranking of these three plans remains unchanged within a range of planning period from 12 to 

20 years. 

The ranking of the plans for the first 8 years indicates that the Plan 14 and Plan 08 maintain their position as the 

best performers while Plan 3 emerges as the second most robust plan for the first 8 years of the resource plan 

study period. 

Table 6: PWC Ranking of the Plans 

Ranking of Expectation over 

Plans over 8 8 years, mR 

years 

Ranking of Plans 

over 12 years 

Expectation over 

12 years, mR 

Ranking of 

Plans over 16 

years 

Expectation 

over 16 years, 

mR 

Ranking of 

Plans over 

20 years 

Expectation 

over 20 years, 

mR 

52 

Assumed probabilities 

Plan14 102 651 Plan14 145 335 Plan14 181 830 Plan14 212 601 



50% Probabilities of primary uncertainties (Each plan has an equal probabilty of 6.25%) 




60% Probablities of expected primary uncertainties (Plan A1 has the highest probability of 12.96%) 




The above results show that the ranking of Plan 14 is not sensitive to small changes in the assigned 

probabilities and the length of the planning period. 

The difference in the PWC of the first three plans is marginal and less than 1%. 

The actual variability of the plans PV cost under the modeled future conditions is illustrated in Figure 5 below. 

For a comparison the graph also includes plan A2 which is developed for the most pessimistic conditions 

(highest capacity requirements) and therefore carries the least variability of the costs under the remaining 15 

more favorable futures. 

The performance of the first three plans, Plan 14, 08 and 16 is further evaluated in terms of the attributes 

reliability, emissions and diversity.


310 000 

290 000 

Plan 2 NPV 20 





Total cost, mR 

270 000 

250 000 

230 000 

210 000 

190 000 

S01 S02 S03 S04 S05 S06 S07 S08 S09 S10 S11 S12 S13 S14 S15 S16 

Scenario 

Figure 5: Variability of total cost. 

5.3 Reliability Assessment 

The reliability assessment is conducted in terms of the reserve margin carried by the plans under the future 

scenario they were developed for and the reserve margin that the plans would carry had the expected 

conditions (business as usual) prevailed over the planning period. The reserve margin under own future and 

under the expected (A1) future are shown in Figure 6 and Figure 7, respectively. 

25.00% 

53 

RM, % 

20.00% 

15.00% 

A3 

A14 

A16 

A8 

10.00% 

5.00% 

0.00% 

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 

Year 

Figure 6: Reserve Margin under own future.


25.00% 

20.00% 

A3 

A14 

A16 

A8 

RM, % 

15.00% 

10.00% 

5.00% 

0.00% 

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 

Year 

Figure 7: Reserve Margin under A1 future. 

Plan 14 carries a higher than 10% reserve margin (RM) under its own future from 2008 to 2022 and 12% % RM 

under expected future (A1). In comparison Plan 16 carries a better RM under A1 future but under its own future 

scenario its RM is relatively low. 

5.4 Emissions and Diversification Assessment 

54 

A summary of the comparison of the plans in terms of diversity of resources, emissions as well as costs and 

reliability parameters is provided in Table 7 overleaf. 

In terms of emissions the least-cost candidate plans have quite similar performance. This is a result of the large 

share of the coal-fired generation in all 16 plans. For the same reason the diversification of the plans is also low 

and varies between 9 and 12%. However, regardless of the close performance of the plans in terms of 

emissions, Plan 3 ranks marginally as the plan with the lowest emissions level, followed by the remaining three 

plans with almost equal pollution level. 

Higher diversification of resource is achieved in the alternative of the Plan 14, presented hereafter, which 

factors the Government renewable energy (RE) target of 10 000 GWh by 2012 in the capacity mix.


Table 7: Comparison of Candidate Plans 

NIRP 2 STAGE 2 COMPARISON OF CANDIDATE PLANS 

Plan A14 A8 A16 A3 

Probability 0.0672 0.0288 0.0432 0.1512 

Demand High High High E 

FOR E High High high 

Capacity Avail Low E E Low 

DSM IL Low E Low Low 

RM(weighted average 2006-2022) 10.61% 6.85% 6.23% 8.90% 

RM(weighted average 2006-2022) under Ref 

case A1 14.53% 16.57% 17.70% 12.80% 

LOLP (average over 20 yrs) 0.00514 0.0054066 0.007379 0.00568 

USE (over 20yrs), GWh 919 940 1307 888 

Probability weighted PV cost over 20yrs, mR 212 601 214 053 214 546 216 969 

Probability weighted PV cost over 20yrs, % 100.00% 100.68% 100.91% 102.05% 

PV System Cost, mR 209 169 221 189 230 200 202 638 

PV of Capex, mR 61 009 69 261 70 534 58553 

PV of Energy Prod (20 yrs) GWh 2 455 643 2 545 521 2 545 268 2 455 613 

Constant cost, R/KWh 0.0852 0.0869 0.0904 0.0825 

Constant pobability weighted cost, R/KWh 0.0866 0.0841 0.0843 0.0884 

New capacity, MW 

Mothballed plants, MW 3559 3559 3559 3559 

First unit year 2005 2005 2005 2005 

OCGT(peak), MW 2880 2880 3360 1920 

First unit year 2 006 2 006 2 006 2006 

Pump Storage (peak), MW 3330 3330 3330 3330 

First unit year 2 012 2 012 2 012 2012 

CCGT (base load), MW - - - - 

First unit year - - - - 

PF(base load), MW 9630 10914 11556 10272 


FBC (base load), MW 2330 2796 2330 1398 


Total capacity MW 21 729 23 479 24 135 20 479 

PV of Capex, mR 61 009 69 261 70 534 58553 

Coal based, % 86.75% 87.73% 86.08% 90.62% 

Diversity (non-coal), % 13.25% 12.27% 13.92% 9.38% 

55 

CO2 Emissions (Mt) 5397 5340 5336 5180 

SO2 Emissions (Mt) 47 47 46 44 

NO2 Emissions (Mt) 20 20 20 19 

Particulate Emissions (Mt) 1 1 1 1 

Water Usage (Mcub m) 7232 7028 7034 6951 

Total emissions, Mt 5464 5407 5402 5243


6.Preferred Resource Plan 

The overall ranking of the plans is conducted in terms of the attributes PWC, RM own, diversity and emissions 

with a weighting of 40, 40, 10 and 10% respectively. Sensitivity analyses are performed with weightings of 

30/30/20/20 and 50/30/10/10. The results of the ranking of the plans are illustrated in Figure 8 below. 

1.100 

1.000 

0.900 

Best plan =1 

A14 

A3 

A8 

A16 

0.800 

0.700 

0.600 

0.500 

0.400 

RM own Prob Weighted PV Emmissions Diversity Weight 40/40/10/10 Weight 30/30/20/20 Weight 50/30/10/10 

Figure 8: Ranking of Plans 

56 

Plan 14 remains the most robust plan, followed by Plan 3, plan 8 and Plan 16. Therefore in terms of the 

attributes Plan 14 should be selected as the optimum most robust plan/strategy for implementation. It has to be 

highlighted that the four candidate plans are very similar regarding the capacity mix and timing. All plans, 

except Plan 3 are developed for high growth scenario which is the planning uncertainty with the highest impact 

on the future capacity requirements, timing and capacity mix. 

The preferred Plan 14 is developed under high growth demand forecast, expected plant outage rate, low 

import and municipal capacity availability and no interruptible loads. 

6.1 Preferred Plan 14 

The capacity mix and timing of Plan 14 are shown in Table 8. Details about Plan 14 attributes are illustrated in 

Table 5.2. 

Similarly to the remaining 15 plans, Plan 14 is also based on RTS of all mothballed plants by the year 2011. 

In terms of peaking plants, the plan requires construction of 2880 MW of OCGTs starting from the year 2006 to 

meet the medium term requirements for peaking capacity. The peaking requirements in the second half of the 

planning period are satisfied by the commissioning of 3330 MW of pump-storage plants starting from the year 

2012. 

The first FBC base-load capacity is required in 2012 while the first PF coal-fired unit must be commissioned in 

2016. 

The plan provides certain degree of flexibility regarding modification of the timing of the required capacity. 

Depending on deviations of the actual demand from the forecasted, the decisions for resource commissioning 

could be accelerated or delayed.


Table 8: Preferred Plan 14. 

Mothballed Coal-Fired FBC Gas Pumped Storage DSM 


(PF) 

Kom (PF) PF (1) PF (2) PF (3) Green-field 

FBC 

OCGT PS (A) PS (B) PS (C) CEE IMEE 

IMLM REE 

RLM 

Reserve on 

moderate 

forecast 

Committed Committed Committed 

2003 Committed Committed Decide 152 24% 

2004 Decide Decide 152 21% 

2005 380 Decide 152 18% 

2006 380 720 152 17% 

2007 570 188 152 16% 

2008 190 377 101 Decide 480 152 16% 

2009 565 202 Decide 720 Decide 152 17% 

2010 303 720 152 17% 

2011 303 152 13% 

2012 932 333 13% 

2013 466 999 13% 

2014 932 999 15% 

2015 13% 

2016 1284 13% 

2017 1284 14% 

2018 1284 14% 

2019 999 14% 

2020 1284 15% 

2021 1284 642 14% 

2022 1284 1284 240 13% 

TOTAL 1520 1130 909 3852 3852 1926 2330 2880 1332 999 999 1370 

7.Sensitivity Analysis 

The ARC requested the following sensitivities be investigated: 

& The impact of the net discount rate on the optimum choice of technology; 

& The impact of Renewable Energy Technologies on the preferred (robust) plan; 

57 

These sensitivity studies were considered necessary to test the robustness of the conclusions and 

recommendations emanating from the NIRP2 Reference Plan, and their impact on important energy policy 

issues. 

Before discussing the sensitivity analysis it is necessary to highlight data changes made to the demand- and 

supply-side data base of the NIRP2 Reference Plan in this study. 

A summary of the complete data base of new plant capital, O&M, Fuel costs and performance parameters is 

given in Appendix C of this Report 

7.1 Comparison of Data changes to NIRP2 Reference Plan 

No data changes were made to any existing plant options or new demand-side initiatives from the NIRP2 

Reference Plan. Marginal changes were made to some specific new supply-side options. To highlight these 

changes more effectively, the candidate plants are separated into Peaking and Base Load options. 

These options are compared in terms of their levelised costs at their maximum production levels and 

separated into O&M, Fuel and Capex components. It is important to note that the CCGT option in the Cape 

using natural gas was excluded from the analysis in this Report. However this was replaced with a CCGT plant 

(located in Namibia) using natural gas from the Kudu field. 

The results in Figure 9, Figure 10 and Figure 11 below, show that the most significant changes were made to 

the cost of coal. There is an increase in coal costs in the case of the PF plants and an increase in O&M cost for 

new FBC options to account for an increased requirement for sorbent.


Comparison of Change in Cost at 10% NDR between the Reference NIRP2 Plan and the 

Risk & Sensitivity Plan 

400.00 

Reference Plan Plant Capex 

Risk & Sensitivity Plant Capex 

360.00 

320.00 

CAPEX R /MWh 

280.00 

240.00 

200.00 

160.00 

120.00 

80.00 

40.00 

0.00 

CF with FGD 


with FGD 

CCGT Incl Trans 

(LNG) 

CCGT Kudu 

(Offshore nat gas) 


(pipe) 

Mepanda Uncua 

PBMR (1st MM 

Incl trans) 

PWR (Incl trans 

benefits) 

Figure 9: Capex Costs for Base Options 

58 



Reference O & M Cost 

60.00 

Risk & Sensitivity O & M Cost 

CAPEX R /MWh 

40.00 

20.00 

0.00 

CF with FGD 


with FGD 


(LNG) 

CCGT Kudu 



(pipe) 

Mepanda Uncua 


Incl trans) 


benefits) 

Figure 10: O&M Costs for NIRP 2 Reference Plan and NIRP 2 Risk & Sensitivity Plan




Reference Fuel Working Cost 

Risk & Sensitivity Fuel Working Cost 

200.00 

CAPEX R /MWh 

150.00 

100.00 

50.00 

0.00 

CF with FGD 


with FGD 


(LNG) 

CCGT Kudu 



(pipe) 

Mepanda Uncua 


Incl trans) 


benefits) 

Figure 11: Fuel Costs for NIRP 2 Reference Plan and NIRP 2 Risk & Sensitivity Plan 

7.2 The impact of net discount rate on optimum choice of technology 

59 

The timing of building new plant options will not be impacted to any great extent by small changes to the net 

discount rate. However changes to the net discount rate will impact on which base-load and peaking 

technologies are selected in the plant mix. 

Due to time constraints required to prepare sets of plans for different net discount rates, it was agreed by the 

ARC to carry out this analysis, external to the computer modelling process, by studying the impact of different 

net discount rates on the life-cycle levelised costs of building and operating the specific plant options. 

The analysis is carried out on both the data as detailed in the NIRP2 Reference Plan database as well as for the 

updated costs as applied in the database for this study. Where applicable, differences between the two sets of 

data are highlighted.


Table 9 below shows the impact of changes in the net discount rate on the life-cycle levelised costs of all the 

options available to the NIRP2 Reference Plan at their maximum operating levels. 

Table 9: Levelised costs of candidates for selection in the NIRP2 Reference Plan 

NIRP 2 Reference Plan Options Load Factor 


4.0% 6.0% 8.0% 10.0% 12.0% 14.0% 16.0% 

PF with FGD 88% 137.4 160.1 185.6 214.0 244.7 277.7 312.7 

PF without FGD 88% 127.5 148.3 171.7 197.6 225.8 256.0 288.1 

Greenfield FBC without FGD 86% 131.7 153.0 176.9 202.9 230.8 260.5 291.5 

Greenfield FBC with FGD 86% 134.2 155.3 179.0 205.0 232.9 262.5 293.5 

CCGT Incl Trans (LNG) 85% 310.7 318.7 327.6 337.1 347.2 357.8 368.7 

CCGT Excl Trans (LNG) 85% 328.1 337.4 347.6 358.6 370.3 382.5 395.0 

Single cycle GT (kerosine) 13% 1158.3 1199.8 1244.3 1291.3 1340.0 1389.8 1440.2 

Single cycle GT (LNG) 13% 706.9 749.5 795.1 843.0 892.5 943.0 994.2 

Single cycle GT (local syngas) 13% 663.3 706.3 752.3 800.6 850.5 901.4 952.9 

Single cycle GT (LPG) 13% 1005.8 1047.7 1092.6 1139.9 1188.8 1238.9 1289.5 

CCGT Incl Trans (pipe) 85% 219.5 227.7 236.7 246.4 256.5 267.2 278.1 

CCGT Excl Trans (pipe) 85% 234.8 244.3 254.7 265.8 277.5 289.8 302.4 

PS (based on Braamhoek public data) 23% 185.2 225.3 275.2 335.4 406.6 489.5 585.4 

PS (generic) 20% 269.1 348.9 448.2 568.1 710.0 875.5 1066.8 

Mepanda Uncua 58% 242.3 303.9 375.4 456.5 547.4 647.8 758.0 

Wind 33% 256.0 292.6 331.9 373.8 417.9 463.9 511.4 

Concentrating Solar Power 70% 336.6 409.2 486.3 566.0 646.9 728.0 808.3 

PBMR (1st MM incl. trans) 86% 187.7 220.6 258.3 299.9 344.9 392.8 443.4 

PBMR (1st MM excl. trans) 86% 206.6 244.0 286.7 334.0 385.0 439.4 496.7 

PBMR (Series MM excl. trans) 88% 154.7 174.7 197.7 223.1 250.5 279.7 310.4 

PWR (inc trans benefits) 79% 236.9 268.4 303.5 341.2 380.8 421.9 464.1 

PWR (exc trans benefits) 79% 248.6 280.4 315.7 353.8 393.8 435.3 477.9 

60 

Table 10 below shows the impact of changes in the net discount rate on the life-cycle levelised costs of all the 

options available in this study also at their maximum operating levels. 

Table 10: Levelised costs of candidates for selection for the NIRP2 Risk and Sensitivity Analysis 

NIRP 2 Risk and Sensitivity Plan Options Load Factor 


4.0% 6.0% 8.0% 10.0% 12.0% 14.0% 16.0% 

PF with FGD 88% 145.6 167.9 193.2 221.1 251.5 284.1 318.7 

PF without FGD 88% 136.0 156.4 179.6 205.1 233.0 262.8 294.5 

Greenfield FBC without FGD 86% 134.8 156.1 179.9 206.0 233.9 263.6 294.7 

Greenfield FBC with FGD 86% 150.2 171.8 195.9 222.1 250.2 279.9 311.1 

CCGT Incl Trans (LNG) 85% 308.0 315.9 324.6 334.0 343.9 354.3 365.1 

CCGT Excl Trans (LNG) 85% 320.4 329.5 339.5 350.3 361.7 373.6 385.9 

Single cycle GT (kerosine) 13% 1158.3 1199.8 1244.3 1291.3 1340.0 1389.8 1440.2 

Single cycle GT (LNG) 13% 706.9 749.5 795.1 843.0 892.5 943.0 994.2 

Single cycle GT (local syngas) 13% 663.3 706.3 752.3 800.6 850.5 901.4 952.9 

Single cycle GT (LPG) 13% 1005.8 1047.7 1092.6 1139.9 1188.8 1238.9 1289.5 

CCGT Kudu (Offshore nat gas) 85% 228.8 238.4 249.0 260.4 272.5 285.1 298.2 

PS (based on Braamhoek public data) 23% 193.7 233.8 283.7 343.8 415.0 498.0 593.8 

PS (generic) 20% 277.6 357.4 456.7 576.6 718.5 884.0 1075.2 

Mepanda Uncua 58% 216.0 280.6 355.8 440.8 535.1 638.5 751.1 

Wind 33% 251.1 281.9 314.3 347.7 381.9 416.5 451.3 

Concentrating Solar Power 70% 492.6 565.2 642.3 722.1 803.1 884.2 964.5 

PBMR (1st MM incl. trans) 92% 168.6 199.3 233.7 271.0 310.4 351.6 394.2 

PBMR (1st MM excl. trans) 92% 183.8 218.7 257.7 299.9 344.7 391.4 439.7 

PBMR (Series MM excl. trans) 94% 124.3 143.0 163.9 186.7 210.8 235.9 261.8 

PWR (inc trans benefits) 79% 239.3 270.8 305.8 343.6 383.2 424.3 466.4 

PWR (exc trans benefits) 79% 255.4 287.1 322.5 360.6 400.6 442.1 484.6 

Due to the levelised cost being sensitive to the load factor applied, the following analyses focus on the 

candidate base-load technologies taken at their maximum operating levels.


Selected plots for the various options based on type can be revealing. The base-load options with transmission 

credits, referenced against a coal-fired plant are illustrated in Figure 12 and Figure 13 below for both the NIRP2 

Reference Plan and this study. Options with a high capital component become less attractive with the increase 

in net discount rate. The reverse is true at lower discount rates. 

Life cycle levelised cost (R/MWh) to build and operate new plant - NIRP2 Reference plan 

Cost of Supply (R/MWh) 

500.0 

450.0 

400.0 

350.0 

300.0 

250.0 

200.0 

150.0 

PWR (inc trans benefits) 

CCGT Incl Trans (LNG) 

PBMR (1st MM incl. trans) 

CCGT Incl Trans (pipe) 

PF with FGD 

Greenfield FBC with FGD 

100.0 

50.0 

0.0 

4.0% 6.0% 8.0% 10.0% 12.0% 14.0% 16.0% 

Real Discount Rate (%) 

Figure 12: Levelised costs of base-load plants vs Net Discount Rate for the NIRP 2 Reference Plan 

61 

Sensitivity of Levelised Lifecycle costs of Plant to Net Discount Rate - NIRP2 Risk & Sensitivity 

Analysis 

Cost of Supply (R/MWh) 

500.0 

450.0 

400.0 

350.0 

300.0 

250.0 

200.0 

150.0 

PWR (inc trans benefits) 

CCGT Incl Trans (LNG) 

PBMR (1st MM incl. trans) 

CCGT Kudu (Offshore nat gas) 

PF with FGD 

Greenfield FBC with FGD 

100.0 

50.0 

0.0 

4.0% 6.0% 8.0% 10.0% 12.0% 14.0% 16.0% 

Real Discount Rate (%) 

Figure 13: Levelised costs of base-load plants vs Net Discount Rate for the NIRP 2 Risk & 

Sensitivity Analysis


7.3 Renewable Energy Technologies 

The levelised costs of renewable technologies (wind and concentrating solar power) are relatively high when 

compared to other equivalent supply options operating at similar levels of production. Because of this high cost 

in building renewable energy technologies, the computed economic least cost optimisation process excludes 

these options from the planning base. 

However, it is difficult to assess the externality benefits of these options in a purely economic comparison and it 

is stated Government policy to introduce some amount of renewable technologies in the Electricity Supply 

planning base. 

For purposes of this study, and to try and meet the aspirations of Government policy (10000GWh cumulative 

energy supplied by renewable energy sources (RES) wind, solar, biomass, small-scale hydro by 2013), two of 

the technologies; wind and concentrating solar power (CSP), are considered in this analysis only due to the 

lack of reliable data for other RES. It has to be underlined that the selected RES mix is not the least cost mix. A 

number of lower cost RES options have been identified by the White Paper on Renewable Energy (WPRE) 

and currently under investigation for implementation. 

The lead-time required to engineer, design and build these options is stated as 2 years for wind, and 3 years for 

CSP. This excludes EIA's, licensing, financing and other issues. For the purpose of this study and to be able to 

meet Government aspirations, wind turbines (20MW total) are brought into commercial service in 2007, 

expected to achieve a maximum load factor of at least 30% annually. CSP (300MW total), is anticipated to 

operate at a load factor of at least 70% (with battery assistance) are introduced from 2008. 

62 

The additional cost of imposing renewable technologies on the system and the cumulative energy contribution 

can be seen in Table 11 below. 

Table 11: Additional Cost of Renewable Technologies 

Capex (Rm) 

O & M Costs 

Total 

PV Cost (Rm) 

Total Energy SO 

(Rm) 

cost of 

of 

(GWh) 

Wind & 

Renewables 

Solar 

Year Wind Solar Wind Solar (Rm) Total Cum. Annual Cum. 

2003 

2004 

2005 

2006 

2007 155 4 159 109 109 57 57 

2008 10377 4 337 10717 6655 6763 1935 1992 

2009 4 337 341 192 6955 1935 3927 

2010 4 337 341 175 7130 1935 5862 

2011 4 337 341 159 7289 1935 7797 

2012 4 337 341 144 7434 1935 9732 

2013 4 337 341 131 7565 1935 11667 

2014 4 337 341 119 7684 1935 13602 

2015 4 337 341 109 7793 1935 15537 

2016 4 337 341 99 7892 1935 17472 

2017 4 337 341 90 7981 1935 19407 

2018 4 337 341 82 8063 1935 21342 

2019 4 337 341 74 8137 1935 23277 

2020 4 337 341 67 8204 1935 25212 

2021 4 337 341 61 8266 1935 27147 

2022 4 337 341 56 8321 1935 29082 

These results show the high cost of the solar contribution to the total additional cost of these two renewable 

technologies. The overall increase in cost to the system from implementing these options is estimated by 

carrying out a detailed computational analysis on the preferred plan 14.


The power supply profiles of these options will not always be consistent with the system demand profile. These 

options are therefore modelled as non-dispatchable technologies. A power demand profile for the wind option 

was supplied by ERC in consultation and assistance from the Darling Wind Farm IPP in the Western Cape, to 

yield a load factor of 33%. 

The profile for the CSP was assumed to be similar to that of the commercial and industrial energy efficiency 

programmes yielding a load factor of 71%. These profiles were used to simulate the required load factor 

expectations of these renewable options. 

The results of the computational analysis show an increase in PV cost of R4773 Million cumulative over the 

planning horizon compared to the preferred Plan 14 without renewables, as illustrated in Figure 14 below. 

Mothballed Coal-Fired FBC Gas Pumped Storage Renewables DSM 


(PF) 

Kom (PF) PF (1) PF (2) PF (3) Green-field 

FBC 

OCGT PS (A) PS (B) PS (C) Conc. 

Solar 

Panels 

(CSP) 

Wind 

Turbines 

CEE IMEE 

IMLM REE 

RLM 

Committed Committed Committed 

2003 Committed Committed Decide 152 

2004 Decide Decide Decide Decide 152 

2005 380 Decide 152 

2006 380 720 152 

2007 570 188 20 152 

2008 190 377 101 Decide 240 300 152 

2009 565 202 720 152 

2010 303 Decide 720 152 

2011 303 240 Decide 152 

2012 932 333 

2013 999 

2014 932 999 

2015 466 

2016 1284 

2017 1284 

2018 1284 

2019 

2020 1284 

2021 1284 466 999 

2022 1284 1284 

TOTAL 1520 1130 909 3852 3852 1284 2796 2640 1332 999 999 300 20 1370 

63 

Figure 14: Preferred Plan 14 with Renewables 

The renewable options will reduce environmental emissions and water consumption of the preferred Plan14. 

The extent to which the renewables reduce the environmental emissions is illustrated in Figure 15 below. 

CO 2 MTons 

30 

25 

20 

Cum CO2 Reduced Emissions 

Cum SO2 Reduced Emissions 

Cum Reduced NO2 Emissions 

Cum Reduced Part Emissions 

MTons { SO 2 , Particulates 

& NO 2 Emmisions} 

0.3 

0.25 

0.2 

15 

0.15 

10 

0.1 

5 

0.05 

0 

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 

Years 

Figure 15: Reduction in environment emissions in preferred Plan 14 with renewables. 

0


The cumulative total emission reduction of CO2 over the planning horizon is 28.2 Million Tons whereas the 

cumulative constant rand increase in the cost of the plan is R13547 Million. This represents a cost of R481/Ton 

of CO2 saved at 1 January 2003 prices. 

8.Conclusions 

The main conclusions of these studies in comparison with the NIRP2 reference are summarised as follows: 

64 

1) The preferred plan has been developed on the basis of an evaluation of risk profiles and the reserve 

margin is an outcome of the optimisation process. 

2) The reserve margin of the preferred plan is higher than the 10% reserve margin used as a deterministic 

reliability criteria in the reference plan; 

3) The studies show that immediate decisions are required for peaking and base load plants from 2006 and 

2012 respectively; 

4) The base load plants competing for commercial operation from 2012 competing, include; Pulverised Fuel 

Coal-fired (PF); Fluidised Bed Combustion (FBC); Combined Cycle Gas Turbine (CCGT) 

5) In order to meet Government RES targets by 2013 immediate decisions are also required for renewable 

energy options; 

6) Options for diversification are still insufficient to meet all of the forecast demand for electricity over the next 

20-year planning horizon. Coal-fired options are still predominating the capacity during the 20-year 

planning horizon. For environmental benefit it is imperative to continue with efforts to reduce the costs of 

implementing clean coal technologies and improve the efficiency of coal-fired plants; 

7) At the current assumed cost of capital (10% net discount rate before tax) and after returning the Eskom 

mothballed plant to service, fluidised bed combustion technologies are South Africa's most economic 

option, followed by investment in coal-fired plant. This in turn is followed by importing gas / LNG for CCGT 

plant in the Cape; 





9) The NIRP2 Stage 2 plans are based on the accepted RTS program of the mothballed plants; 

10) The preferred plan indicates that 2880 MW OCGT peaking plants are required in the planning horizon in 

service from 2006; 




12) The RES scenario is not fully reflective of the least cost RES mix currently investigated for implementation 

of the WPRE. This will be included in the next round of the NIRP update. 

13) Should interruptible supply and / or OCGT capacity not be implemented this will significantly advance new 

base-load capacity; 

9.Appendices 

Appendix A: Summary of comments on reference case report 

Appendix B: Detailed Plans 

Appendix C: Data Base

ARC and Public Comments on NIRP2 Reference Case 

Appendix A 

ARC AND PUBLIC COMMENTS ON THE NIRP2 REFERENCE CASE 

I. ESKOM SYSTEM OPERATION COMMENTS 66 

II. ESKOM KSACS COMMENT 67 

III. EIUG COMMENT ON NIRP 2003/4 REFERENCE CASE VERSION 18 DECEMBER 2003 70 

IV. ESKOM GENERATION COMMENTS ON NIRP 2003/4 REFERENCE CASE 

VERSION 18 DECEMBER 2003 72 

V. COMMENTS FROM DARLING IPP 74 

VI. COMMENTS FROM KELVIN IPP 75 

65

National Integrated Resource Plan 2 - Appendix A 

I 

I. ESKOM SYSTEM OPERATION COMMENTS 

Provided by Mr. Michael Barry 

1. The method to use pre-defined reserve margins and then derive the generation expansion plan is not 

ideal. As mentioned in the ARC meetings, I believe a set of data assumptions should be defined and used 

in the modeling. The reserve margin is then an outcome of the modeling process. Using this approach, 

one can relate each generation expansion plan to a set of assumptions, for example with x% reduction in 

generation performance, the expansion plan is advanced by y years. This set of assumptions is changed 

for the various sensitivity studies/scenarios. 

2. The NIRP Reference Plan is for the forecast moderate load growth. (The documentation makes mention of 

robust plans, no regret and flexibility, but from my understanding these are not specifically considered in 

deriving the reference plan). The Reference Plan then gives a conservative picture (building too late) 

when one considers the load growth uncertainty and the cost of supplied vs unsupplied electricty. The 

Reference Plan should, as part of the set of assumptions, include an additional plant margin for load 

growth uncertainty. 

3. The NIRP Reference Plan does not make provision for the inherent inertia in changing the "direction" of a 

"ship" the size of the electricity industry in South Africa. The country is used to many years of no significant 

generation capacity expansion. The Reference Plan should, as part of the set of assumptions, include an 

additional plant margin for this inertia. 

66 

4. The Conclusions contain a number of "immediately implement" statements when referring to specific 

capacity additions. Is the NIRP saying a period of capacity shortages is forthcoming (and even more so 

considering the comments above)? If this is the case, should the NIRP not make some clear statement 

about the desirability of any capacity expansion or demand management in the next few years. 

5. From a strategic perspective, I believe a NIRP resulting in a reserve margin of anything less than 12% will 

harm the economy of South Africa. Potential international investors in the industrial arena might think 

"electricity interruptions" when seeing future reserve margins of less than 12%. Should the strategy not 

rather be to establish the capacity thereby stimulating highe growth? 

6. The reserve margin is calculated after the peak demand is reduced by the interruptible load. This implies a 

NIRP planning to interrupt customers. Is this the correct message?


II 

II.ESKOM KSACS COMMENT 

Provided by Dr. Jean Pabot 

With respect to SAPP, I did not find this word in your report, though you mention briefly an option for imported 

hydro (Table 6). This option is not even discussed in the text (e.g. in Section 5). I assume you included the 

transmission costs from the foreign plant to the Eskom network into your capital cost. However this option 

appears not to have been considered in your simulations? If true, why? 

I accept that there are no good recent reliable data for SAPP hydro plants, except maybe for Mepanda Uncua, 

which may be the option mentioned inTable 6. If this is the case, it should be stated. 

You might consider a scenario where both Mepanda Uncua and Inga 3 are built, e.g. in 2014, irrespective of 

their costs, and study the impact thereof on your NIERP. 

There is some confusing wording and apparently an inconsistency about imports-exports in Section 3.6 and 

Section 5.1 (last 3 lines). Were exports included in the load forecast or not? 

It would be useful to include a table showing the MW exports included in the load forecast. It might already be in 

the appendices, but I did not see it. 

With respect to the reserve margins used in the SAPP studies, these are: 

We use: 

& 7,6 % for hydro units, 

& 10,6 % for thermal units, 

67 

There is a problem, even in Eskom, to justify a 10 % capacity reserve criterion to auditors, when many 

utilities have reserve criteria ranging from 15 % to 25 %. 

The minimum (or optimal) reserve margin is utility dependent. It depends on: 

& The risks which the utiity wants to mitigate by adding reserve capacity, e.g risks associated with uncertainties 

on plant availability, load forecast, fuel availability, etc. 

& The characteristics of the existing and future plants, e.g. unit size, plant availability, etc. 

& The costs involved, e.g. plant cost, cost of un-served energy, etc. 

Eskom is a SAPP member. A few years ago, the SAPP reduced its minimum installed capacity reserve 

requirements (not the operating reserve requirements) to about 10 %, based on the results of a simple 

optimization study. The methodology and assumptions are auditable, though auditors might disagree with all. 

With hindsight, I now believe that one of the drought related assumptions is not valid, but this would have little 

impact on thermal plant based utilities. 

Additional minor comments on your report: 

1. Interruptible supplies: 

& In section 5.2, the report states: there is a total 1510 MW interruptible supply capacity included in the plan. 

Does this mean that you have 1510 MW of interruptible load/supplies assumed to be equivalent to 1510 MW


of supply capacity? or is this 2500 MW or 3000 MW of interruptible load/supplies assumed to be equivalent 

to 1510 MW of supply capacity? Table 1 in Appendix 1 mentions it is derated capacity. This should be 

explained in the text. 

& Table 2 in Appendix 2 shows that the existing interruptible load (IL) decreases from 1510 MW to 500 MW in 

2012 and 384 MW and that it is not replaced by new IL. This does not make much sense. 

& IL is a very cost effective way to provide reserve to a system, and if Eskom's IL contracts come to an end, 

Eskom would surely seek new IL contracts. 

2. LRMC 

Table 12 in Appendix 12 shows that the LRMC does not vary significantly with the reserve margin (i.e. with the 

alternative plan) beyond 2015. 

With the methodology presented in Section 7, the LRMC should depend on 

the amount of plant to be built to meet a 500 MW load increase, which depends on the reserve margin criterion. 

3. Wind generator 

Section 9, in Appendix 3, should indicate the fuel/wind availability: when is it available during the day and with 

what probability? 

What capacity credit do you give the wind generator for reserve margin calculations? 

68 

4. Imported hydro 

& The capital cost of imported hydro differs in Table 6 of the main report ( Rm 17044) and in Table 3 of Appendix 

1 (Rm 19366). 

& The life of the imported hydro plant is given as 30 years, much lower that the life of a pumped storage plant or 

a PBMR (40 years). This is not realistic. A dam can last 100 years, and a hydro generating unit 40 or 50 years. 

NIRP2 Reference Case Handling of Risks 

I noticed in your executive summary (Section 6) and in the main report (section 2.3) the way you handle risk: 

"The reference plan uses a constraint of 10% on the reserve margin. In addition the un-served energy is 

constrained to a maximum of 0.11% of total energy demand in any specific year. 

In order to address some risks to some extent and to determine reserve margin exposure to lead time, four 

alternative plans to the NIRP Reference plan were developed for increasing levels of constraint on the reserve 

margin 

As explained previously this Report does not address risk rigorously in this round but rather addresses it 

through imposing a minimum reserve margin on the plan of 10%." 

& Where did you get the 10% on the reserve margin criterion from and the 0.11 % UE criterion from? 

& Why do you need these criteria for planning? Theoretically, your optimization method should yield a plan, 

from which you could derive the planned reserve margin and UE.


& Why do you need to have plans for various reserve margins, from 10 % to 17 %. This is not a random choice. 

Which on is the best and why? 

& The above points should be explained in the report. 

& SAPP uses a reserve margin criterion because this was the only way acceptable to all members to agree on 

what capacity each member should provide. However the reserve margin criterion itself was selected with a 

specific auditable process (see my previous message and attached paper) and was not arbitrary (though 

debatable). 

I just have a few additional theoretical comments. You could find the same comments and additional /better 

ones in the numerous articles available in the literature on this topic. 

& In a generation planning problem, the planner has to handle risk (associated with uncertainties), i.e. he has 

to have a base/reference plan (e.g. over 10 years) and to define risk handling strategies to deviate from the 

plan if uncertainties are realized in a way or another (e.g. if the load forecast increases or decreases, if 

nuclear energy is phased out or encouraged, or if gas becomes very cheap or expensive, or if wind energy 

becomes a must have option). 

& Long ago (20 or 30 or 50 years ago), the planners identified their planning risks, determined a reserve margin 

criterion (e.g peak load + 20 %), planned accordingly, and would revise their plans regularly as uncertainties 

become realized, and new ones develop. 

The problem is that a reserve margin criterion becomes invalid if the load shape changes, or the 

reliability changes, or uncertainties change. 

& Later (25-35 years ago) the planners moved to a reliability criterion (e.g. 1 days in 10 years loss of load, or 

LOLE = 20 hours per year, or UE = .1 % or any similar one). 

69 

& This is better than a reserve margin criterion, but how do you select the reliability criterion? 

& Later (20-30 years ago) the planners moved to a minimum cost to society approach (using the cost of unserved 

energy) 

& Eskom generation planners moved from a reserve margin criterion (long ago, before my time) to a reliability 

criterion (10 % LOLP at the peak of the year) around 1979, but the reliability criterion was derived from the 

minimum cost to society approach (using a 0.5 R/kWh cost of un-served energy). 

& Later around 1995 Eskom generation planners moved to a pure minimum cost to society approach, mainly 

because of the availability of more modern computing tools. 

& I am not involved in Eskom ISEP, and I have not seen the plans ISEP9 and/or 9A. I understand that the 

Eskom ISEP planners are now also using a reserve margin criterion in addition to the minimum cost to 

society approach. 

& I saw various Eskom documents where various people compared the reserve margin in Eskom with the 

reserve margin in other utilities. This is not very meaningful, unless you know well what risks each utility is 

exposed to (i.e. their associated uncertainties), and which risks are mitigated by a reserve margin (i.e. 

building reserve plant) and which risks are mitigated by additional strategies (e.g. plant mix, flexibility, etc), 

strategies which might be cheaper than building additional reserve plant. 

& The problem with handling risk in planning, is that it changes from year to year in future (uncertainties 

increase as you look further in the future), therefore the reserve margin criterion should change every year in


your planning process (e.g. 8 % in 2004, 9 % in 2005, 10 % in 2006, etc...) but there is a limit in future, where it 

is not meaningful to plan to build additional reserve, since there would be time to change the plans (e.g. in 

SAPP, the reserve margin criterion is optimized to mitigate risk over 4 years, e.g. if one notices a load 

forecast increase in year 1, the utility can do something about it in year 4, e.g. install a GT or contract for 

interruptible load). 

III. EIUG COMMENT ON NIRP 2003/4 REFERENCE CASE VERSION 18 DECEMBER 2003 

Provided by Mr Arnot Hepburn, EIUG Sectretariat 

Impressions 

1. The Eskom / ERI-UCT / NER team are to be congratulated on developing the NIRP document from what 

was previously a high level comparison of planning scenario options to a study report making specific 

project recommendations. 

70 

2. EIUG Members welcome the publication of a significantly more comprehensive NIRP than previously 

issued which provides information that is essential to the business planning of energy intensive users. 

3. Although the NER was under the impression that they had given 4 weeks for comment the fact that the 

document was released just before the Christmas recess meant that most recipients were afforded less 

than 2 weeks to review and comment on this critical document. This has negatively impacted on the 

review and comments received. 

General Comments 

4. It is important to note that the optimum choice of technology is very dependent on the selected discount 

rate, with higher discount rates favouring less capital-intensive plant with shorter lead times. This mirrors 

the international trend towards more flexible technology options and away from traditional coal-fired and 

hydro stations. 

5. Due to the high regulatory uncertainty, independent power producers may well require rates of return 

higher than 10%, thereby affecting the appropriate technology choice. This effect should be taken 

into consideration. 

6. It is noted that although a range of demand projections are presented, the alternatives are only considered 

against a single demand forecast. There needs to be consideration of the course of action under the 

high demand scenario at least, or at the very least a qualitative description of the response to that 

scenario. 

7. A load duration curve and a forecast for its evolution over time should be included, so as to provide the 

minimum required information for attracting independent power producers into the ESI in the medium to 

long term. 

8. The full impact of the appropriate reserve margin should be considered - 10% appears low by


1 

international norms, which are around 20% for long-term planning purposes . While the 

appropriate reserve margin differs from market to market, and should be a result of a thorough 

LOLP and VOLL analysis, the specific characteristics of the South African system, i.e. a high 

degree of uncertainty on demand forecasts and the inflexible and long lead-time technologies 

used in SA (coal PF, pump storage) would indicate the need for a higher rather than lower reserve 

margin. 

9. The EIUG have stated at IRP ARC meetings and would again like to place on record that we do not 

agree with interruptible load being considered as 'firm capacity' as this capacity can only be used in 

an emergency and is only 'firm' for a contractually limited time period each week. 

10. We are surprised to find that media sources, such as the Engineering News, serve as references for cost 

estimations (Appendix 3 footnote 64, p25). This creates doubt over the reliability of this information and 

should be avoided in future. 

11. The report has been enhanced by the addition of the appendices however there is very limited reference to 

specific sections in the appendices within the text of the report negating the effective transfer of 

information to the reader. This should be addressed in editing the report. 

12. The opening paragraph of the report mentions taking into account committed contracts for imports and 

exports to South Africa from neighbouring states which is tie-line trading. The NEPAD initiative would 

require South Africa to be the anchor customer for bulk import of new hydropower as envisaged from the 

so-called Western Corridor (DRCANSA Interconnection). Lack of comment on the impact of such 

regional initiates on the NIRP appears to be an omission. 

Specific Comments 

71 

13. In Table 6 of the main report (p18) entitled 'Summary Table of New Supply Side Options Data', the 

efficiency ascribed to the CCGT's appears low. A figure of 50% is routinely quoted in international papers. 

14. In Table 8 of Appendix 1, no fuel costs have been allocated to the pumped storage units i.e. off-peak 

electricity purchases for pumping. It is important to know whether, in the evaluation of the viability of 

pumped storage units, the cost of the additional coal that has to be burnt for the pumping cycle was 

included as a variable pumped storage cost. Table 8 implies that this has not been done and if so, should 

be rectified. 

15. Table 2 of Appendix 2 (p3) shows that 2,400 MW of new build SCGT is to be fired on local syngas. The 

assumption that as much as 2,400 MW of local syngas will actually be available seems quite optimistic. 

The other SCGT fuel source is Kerosene as it is currently cheaper than diesel, although kerosene is a 

government subsidised fuel and it is not certain if it would be appropriate to subsidise a peak power 

station's fuel source. 

16. In paragraph 5 of Appendix 3 the Fluidised Bed Coal Fired Plant is discussed. The lower firing 

temperatures in a fluidised bed boiler certainly limits the formations of NOX's. However the SOX's are 

dependent on the coal characteristics and presumably limestone will be required. It appears as if 

limestone costs are not included in the variable costs of this technology. In addition, the coal 

costs appear to be low and should be confirmed with the owners of the reserves. 

17. The efficiency range quoted (in note 51) of 35.2 to 42.1 presumably refers to pressurised and other 

advanced fluidised bed technologies. We assume that the technology in the NIRP is basic fluidised 

combustion. For this technology an efficiency of 37.36% seems to be very optimistic. 

1 National Grid Company of the UK “Seven Year Statement” www.nationalgrid.com


18. Points 4 to 7 in the Conclusions of the Executive Summary and the Report are welcomed as they are clear 

recommendations to implement specific projects but these should all have the required commissioning 

date (or first to last unit commissioning dates) as has been done with point 5 to stress the need. 

19. The Conclusions need to make a clear statement regarding why the import of bulk hydropower is 

not considered in the report. 

20. The Conclusions need to make a clear statement as to whether the studies identified any 

inadequacies or constraints in the transmission system that could impact on the quality of supply. 

21. Question - are the amounts of dispatched imbedded generation (municipal and industrial) 

included in the load forecast (fig 1 page 5) to give the total consumption since imbedded 

generation is included in the supply side availability figures. 

22. Executive summary text editing: 

Page I para 1 line 4 : ensuring not insuring 

Page IV section 5 line 2 : as dictated by the ARC of the NER 

Page VII fig 5 title : NIRP reference plan and alternatives at 

Page VII conclusion 1 last sentence : (including losses) it is not sufficient. 

Report text editing : 

Page 14 last line : time-of use tariff is available. 

72 

IV 

IV. ESKOM GENERATION COMMENTS ON NIRP 2003/4 REFERENCE CASE VERSION 18 DECEMBER 

2003 

Provided by Mr. Gerhard Loedolff 

1) Is this a report by Eskom, ERI and NER, or is it a report by Eskom & ERI for NER, or is it a report by NER, 

drafted by Eskom and ERI. Depending on the answer, the text needs to be reflective of the position the 

report is written from. 

2) In the Introduction, it is referred in par 1 that the study is conducted to provide information on the 

economics of new electrical generation. Is this really so, or is objective more fold, and directed at 

identifying the appropriate level of new capacity additions to meet future supply; assess the 

appropriateness of various solutions and reflect on the economic outcome of such solutions? 

3) Also in the Introduction, a number of bullets is listed as steps defined and carried forward from NIRP1. 

However, on many of them the objective (to achieve what?) is not specified. Therefore, as an example, 

you are 'Selecting a preferred Plan' to achieve what?; or you are analyzing financial consequences of 

What? 

4) At the top of page 2, the report refers to the "NER agreeing to...." . Surely the NER appointed ARC to 

develop the planning assumptions. 

5) Especially on DSM, the report contains a huge amount of debate and policy and management suggestions 

to NER. To my knowledge this is outside of the scope of this report. I would have expected a good review of 

assumptions, with possible implications of deviation on the study outcomes. Refer pages 14- 16


6) Paragraph 3.3: 2% to 3% represents a movement of 50%. can you not 

7) close the gap somewhat? 

8) Par 3.5: Surely such a statement needs some explanation? 

9) Par 3.7: No indication is provided on the relevance of this information 

10) Par 3.7.2: No indication as to why sales growth is assumed to be higher in earlier than later years. Also 

impact of TOU based WEPS rates not referred to. 

11) Who is DOE? 

12) Wording around Eskom's plant performance is again confusing. Suggest it reflects that it is based on 

90:7:3, with an average long term EAF of 88%, as also discussed at the last ARC meeting, and as used. 

(p27) 

13) In a number of places in the report, restructuring of the text to bullet format will substantially ease reading. 

14) Par 5.4: New Supply Side Options were recognized, BUT not included. Why? 

15) R60/ton for coal to the 6-pack appears underestimated by around R20/ton, while overnight capital appears 

about R100/kW higher that latest used in ISEP 

16) Suggest that the screening curves should focus only on proven technologies, and not on the speculative / 

developing ones in the main report. Can include an annex to give relative position to adopted supply side 

options 

73 

17) Section 6 deals with some issues around reliability of supply. Rather than opening a debate here, which 

could also be based on invalid assumptions like Cost of non supply, should the current regulatory standard 

w.r.t. QoS criteria as applied via licenses not rather serve as the basis? 

18) The plan on p29 indicates OCGT's being decided upon ahead of Komati and Grootvlei. From the 

discussion at the ARC meeting this appears to be the result of artificially constraining the return of 

Grootvlei and Komati. Is this still so; If so, Please correct!


V 

V. COMMENTS FROM DARLING IPP 

Provided by Mr. Herman Oelsner 

I would like to put on record our disappointment that input given in our E-mail dated 2nd of December (copied 

below) has not found its way into the modelling. 

The committee could find itself soon in a very embarrassing situation since Renewable Energy Sources and 

Technologies have largely been ignored. This despite clear government (RE White Paper) policy and targets 

and numerous country-wide spread activities in this sector. 

From the Renewable Sector's view it appears to be "business as usual". 

In order to enable a more valuable contribution from the Renewable Energy Service sector, I would like to 

propose the co-option of two new additional members from RES to the committee which can assist me in 

effectively contributing to the process. 

Since there was only short time to look at the documentation you distributed, I had no opportunity to query 

certain figures in the modelling results. 

For example: 

74 

The lead times for wind are much shorter and should be recorded as: 

a Concept Phase 

one year 

b Feasibility phase 

two years (Darling as first-off is a bad example/ see 

Klipheuwel EIA took less a year) 

c Investment and construction one year maximum for 20 MW 

Extremely short lead times and the possibility of small decentralized plants which can integrate into existing 

national grid are the outstanding advantages of wind electricity generation. 

a.Life (yrs) 25 (not 20) 

b.Maximum Capacity factor 35% (not 19.27) 

c.Minimum Capacity factor 20 %(not 4,85) 

d.Operational Mode is not in base load but generation takes place dominantly during peak and standard times. 

e.Energy Limit per station of 20 MW is 54 GWh/a not 33.5 

There are several abbreviations in the documentation, which I do not recognize. A key would be of great help. 

Renewable Energy generation, solar / wind does not appear at all in the NIRP Plans for Publication projecting 

plans until 2022. 

At last weeks World Wind Energy Conference Honourable Minister Ms Phumzile Mlambo-Ngcuka announced 

that the government will ratify in Cabinet on Wednesday the 3rd of December the Renewable Energy White 

Paper. 

The White Paper sets a 10-years target of 10 000 GWh renewable energy contribution to final energy 

consumption by 2013, from wind, biomass, solar and small hydro. Since wind is arguably at present the most 

economic mode of electricity generation and a well developed technology, wind will play a dominant role in new 

generation plant in South Africa in the near future. Assuming that wind will contribute at least half for this target,


would translate into 10 off 20 MW wind farms, which is very realistic and rather conservative. 

The implementation progress will be evaluated mid-term in order to find out whether it will be necessary to 

revise the White paper. 

Based on the White Paper, the first draft renewable energy strategy is expected to be published in February 

2004. 

I respectfully submit that RE must be included in the NIRP Reference Plan. 

VI 

75 

VI. COMMENTS FROM KELVIN IPP 

Provided by Mr. Donald Bennett 

I have been through the document and do not have any major comments about it in general. The only point 

that I would like to make is that the reference to Kelvin Power Station is incorrect (Appendix 1 page 3 table 2). 

Kelvin (A & B) is grouped with the “Munics 1 & 2”. Kelvin was in fact privatized in November 2001 and operates 

as an IPP (although only serving the City of Johannesburg under a Long Term Agreement at this point in time). 

Reference is also made in point 5.2 (Non-Eskom System Existing Capacity) page 15 of the main document to 

the fact that Kelvin generation is included in the “Munic 1 & 2” blocks.

National Integrated Resource Plan 2 - Appendix D 

Appendix D 

NIRP ARC COMMENTS ON THE NIRP2 STAGE 2 REPORT 

I. ESKOM KSACS COMMENT 77 

Concept of expectation / Definition of the word “expected” 77 

Uncertainties considered (Section 4) 77 

Range of values for uncertain parameters (Section 4) 77 

Definition of scenarios (futures) (Section 4) 78 

Simulation of plans , and cost estimates (Sections 4 and 5) 79 

Renewable technologies (Section 7.3) 80 

Conclusion 80 

II. EIUG COMMENT ON NIRP2 STAGE 2 REPORT 80 

III. DEPARTMENT OF MINERALS AND ENERGY COMMENTS 

ON RENEWABLE ENERGY SCENARIO 81 

76

NIRP ARC Comments on NIRP2 Stage 2 Report 

I 

I. ESKOM KSACS COMMENT 22 August, 2004 

COMMENTS ON NIRP 2003/4 STAGE 2 REPORT 

Personal comments by JL Pabot 

The principle of the methodology used in the report to develop an optimal plan seems reasonable, but I have 

serious doubts on the implementation techniques applied with this methodology to derive the recommended 

plan, which in my opinion invalidates the results. 

Therefore I cannot determine from the report if the recommended plan is truly the best plan. 

Concept of expectation / Definition of the word “expected” 

The word “expected” is mentioned at many places in the document, but It does not seem to have the usual 

meaning, which is confusing for the reader. 

For me, when a parameter (e.g. availability of plant) has a statistical distribution of values over a range (low, 

median, high), the expected value is the probability weighted average over the range, usually close to the 

median value. 

In the whole report, the expected value of a parameter seems to always be at one end of the range, always the 

least favourable (i.e. the best) end for capacity investment (the side requiring the least capacity installed). All 

other values are worse, i.e. lead to higher capacity investment. 

77 

Uncertainties considered (Section 4) 

The report addresses only uncertainties that have a direct impact on the load/capacity balance. 

Other uncertainties that might have a significant impact on the plan, are not considered, e.g. fuel cost or fuel 

availability (except for imported hydro). 

Range of values for uncertain parameters (section 4) 

As mentioned in comment 1 above, the range of values selected for the analysis for the uncertain parameters 

is systematically biased towards the worst end of the range (i.e. the values requiring the highest capacity 

installed). The expected value being the lowest value considered. 

This obviously will lead to an optimal plan requiring more capacity than truly required. 

Examples of parameters that could have more favourable values than expected, i.e. outside the range 

considered in the study: 

& Load growth forecast: Surely there is some probability that there might be an economic crisis due to some 

international event (high petrol price, financial crisis, war in the middle, crisis in a neighbouring country, 

impact of AIDS, etc) which might lead to lower energy consumption growth. Export sales to SAPP might also 

decrease if new stations are built in SAPP.


& Imported energy: Surely there is some probability that Eskom could import more power from SAPP, e.g. from 

Inga 1-2 after refurbishment, from ZESCO in Zambia, when they have finished refurbishing their plant, from 

Kafue Gorge lower, from Kudu in Namibia, if the plant is built primarily for supplying Nampower, and if Eskom 

buys the balance of energy generated, etc… 

& Interruptible load (IL) and DSM: it is quite likely that in future Eskom may contract for more IL capacity, 

possibly with less usage constraints, and for more demand management programmes (DMP) or DSM 

programmes. 

The probabilities allocated to the parameters values on the worst (for MW to be built) end of the range seem 

excessive, e.g. 70 % for available capacity 

Definition of scenarios (futures) (Section 4) 

There is an implicit (not discussed in the text) assumption in the scenarios: the 4 uncertain parameters are of a 

random nature, and are independent. 

At least one parameter, the existing IL MW capacity, is not a random parameter. The IL contracts are to a large 

extent under Eskom's control, i.e. their continued existence cannot be used in a probabilistic analysis. 

The 4 parameters are not independent in the long term, and a few of them are also not independent in the short 

term. 

78 

& IL MW capacity is not independent of the other parameters. Eskom is unlikely to cancel (or renegotiate) 

these contracts if there is a shortage of capacity to replace them (e.g. if there is some indication of a high load 

growth, or if imports are curtailed). 

& The same can be said of the municipal generation (it will not be retired if its capacity is needed) and of the 

plant availability (if low, Eskom will strive to improve it if there is a shortage of capacity, at least within a year or 

two). 

& The MW capacity of DSM programmes contracted by Eskom is not independent of the other parameters: 

Escom will invest more resources in developing these programmes if there is more need for them (e.g. for 

high load growth) 

& The MW capacity of imports is also not independent of the other parameters: Eskom will not give up part of its 

contractual MW allocation form Cahora Bassa at Songo if this capacity is needed in South Africa. Also 

Eskom will import more energy form SAPP if there is a need for it, mainly because Eskom can then offer a 

higher price. 

& The load forecast includes the energy exported to SAPP (about 2100 MW peak power in 2004). Most of 

Eskom's export contracts are expiring soon, part of the existing contract are non-firm (Eskom can decline to 

sell energy at 1 day notice). In future Eskom will reduce exports if there is a prospect of capacity shortage. 

Therefore the definition of the scenarios (by combining all the values of the uncertain parameters), and the 

derivation of their probabilities (by multiplication of the individual probabilities), is not appropriate for this 

expansion planning exercise. 

It would be more appropriate to define a set of 3 values for the uncertain parameters (low, medium, high), 

assess their interdependence, and derive by judgement a set of 4 or 5 realistic futures. 

With reference to my comment 1, it is very odd that the future (scenario 1) with all parameters having their 

expected values has a probability of 3 % and that all the other futures (with a combined probability of 97 %) are


all worse (in terms of capacity requirements), even much worse for many of them. 

This reflects a bias in the study towards the worst cases, requiring higher installed capacity. 

Simulation of plans , and cost estimates (sections 4 and 5) 

The NIERP planners (the authors of the study) design 16 plans for the 16 futures. They then simulate each plan 

for each future, over the study period (8 to 20 years) assuming that the plans remain as designed for the whole 

duration of the study period. 

This does not make sense: a plan designed for a low load growth forecast would not remain unchanged if a 

higher load forecast would occur. Eskom would surely take some action within a year or two, e.g. order OCGTs 

(lead time = 1 or 2 years), contract more IL, etc…The simulation should make some provision for the 

adaptability of the plans to the future under which they are simulated. 

The consequence of this methodology implementation technique is to derive very high costs for the plans 

designed for favourable (i.e. good, as defined in Comment 1) futures when run under unfavourable (bad) 

futures. 

Example: The table below shows the PV cost of plans 1 (designed for future 1, the best) and 2 (designed for 

future 2, the worst) when run under futures 1 and 2. It shows also the expected cost (probability weighted cost, 

PWC) of the plans over the 16 scenarios. These costs were provided by the NIERP planners in a spreadsheet. 

Simulation Scenario Scenario PWC 

20 years future 1 future 2 cost 

79 

Plan 1, cost Rm 182427 746958 403520 

Plan 2, cost Rm 215676 240722 222918 

The high cost of plan 1 (low capacity installed) for future 2 is due to the high amount of unserved energy 

calculated for that case, and to the high cost of unserved energy (20 R/kWh). 

& The cost of unserved energy is unrealistic for that case. This is an outage cost, not a shortage cost. As 

mentioned extensively in the literature, outage costs are incurred by consumers when unexpected outages 

occur, and shortage costs are incurred when outages are expected (e.g. when there is a shortage of capacity 

over long periods, e.g. 6 months). Shortage costs are much lower that the outage costs. Obviously in the 

case of plan 1 run under future 2, outages would be expected, and a shortage cost should have been used 

for unserved energy, not an outage cost. 

& The high amount of unserved energy of plan 1 for future 2 is totally unrealistic. Plan 1 would not remained 

unchanged over 20 years for future 2, nor for any future worst than future 1 (i.e. for all other futures) over 20 

years, nor over 8 years, nor over 4 years. 

The impact of this invalid methodology implementation technique is to weigh all plans designed for the most 

favourable futures with very high unserved energy costs, which leads to very high probability weighted costs 

for these plans, and to their elimination on the basis of high PWC. 

In effect the study is seriously biased towards plans designed for bad futres, i.e. with high capacity installed. 

The study would be more valid if the plans were simulated as adaptable, i.e. if additional gas turbines could be 

installed at short notice when needed, or if plant commissioning could be delayed at short notice (with


additional costs) to cope with changing futures. 

Renewable technologies (Section 7.3) 

Plan 14 with 320 MW of renewable capacity installed over the nest 20 years only pays lip service to the 

government's desire to introduce renewable energy in the generation of electricity. I did not check the white 

paper on energy policy, so maybe the study is realistic in this respect. 

A more visionary scenario would consider a more commendable goal, e.g. 5 % or 10 % of all new installed 

capacity to be based on renewable energy. 

If in future South Africa moves to gas fired plants with expensive gas fuel (e.g. LNG) for electricity generation, 

wind power plants may become economical because of their associated fuel savings, even if they receive no 

capacity credit to meet the peak load: 

Conclusion 

The principle of the methodology used in the report to develop an optimal plan seems reasonable, but the 

planning techniques used in this study for the implementation of this methodology, are in my opinion invalid. 

In my opinion, the shortcomings identified in the above comments invalidate the results, i.e. I cannot determine 

from the report if the recommended plan 14 is truly the best. 

I also cannot determine if the recommendation to build 720 MW of Open cycle gas turbines in 2006 is 

reasonable. 

80 

However since the DME representatives stated at a recent meting at the NER that Eskom and the DME had 

already agreed that these 720 MW of OCGT would be built in 2006, this capacity is in effect committed, and my 

opinion on this point is irrelevant. 

II 

II.EIUG COMMENT ON NIRP2 STAGE 2 REPORT 

Provided by Mr Arnot Hepburn, EIUG Sectretariat 

EIUG members in their review of the NIRP2 Stage 2 report are in agreement that the comments submitted 

previously and the EIUG concerns raised again at the last NIRP ARC meeting are all that need be given for the 

current report. As stated by the EIUG at the last NIRP ARC meeting it is imperative that the release of the report 

should not be delayed in any way as the information is urgently needed by decision makers. It is appreciated 

that it will never be possible to achieve 100% projections but what is known must be published. 

The EIUG gives it's assurance that it will give what ever support possible to future NIRP studies and reports 

and submit to you the following comments for consideration in the preparation of NIRP3: 

Demand- and consumption growth forecasting 

1. There appears to be uncertainty and a lack of agreement on the actual figures in the baselines as used, 

and on the expected demand growth in future. For example, in table 1 in the NIRP HIGH column, the sales


in 2003 is shown as 197 401 GWh. From the Eskom annual report the actual Eskom sales was 196 980 

GWh. The Eskom figures excludes the energy sent out from non-Eskom generation, and therefore it 

appears that we are projecting future demand and consumption figures from a too low base. This may 

have a significant effect on the actual reserve situation in future. 

Further to the above, the 0,5% increase (on top of the NIRP 2 base case) in the demand growth from the 

ERC study to arrive at the high growth scenario, seems modest compared to the actual year on year 

growth of 5% over the last few years, even if we know of large new industrial loads that came on line 

recently. It the actual rate of growth does not taper off to 3% during the remaining months of 2004, we 

should consider another upward adjustment to the forecast next year. 

2. In table 4, the probabilities assigned to the different primary assumptions seem debatable. A probability of 

0.4 is assigned to the high load forecast, while recent history and the current economic outlook seem to 

support a higher probability. Similarly, the 0.6 probability that plant outages will be higher implies that 

Eskom will not be able to maintain their equipment availability, against a history that they never dropped 

below 88%, even in a bad year like 2003. Given the fact that the impact of higher load growth is more 

severe than the rest (figure 1), these assumptions greatly influence the results in the 16 scenarios. If a 0.6 

probability is assigned to the high load growth assumption it will result in lower reserve margins and higher 

PWC in scenarios 2, 6, 8 and 16. If such a relative modest change in a primary assumption can lead to a 

scenario of zero reserve margin, the report should point that out, assign a probability to it and sensitize 

government to such a possible eventuality. 

3. The report is silent on brown fields CF base load options, while it is common knowledge that these 

possibilities have shorter lead times and are cheaper than green fields options. 

4. The inclusion of 300 MW CSP, at R10bn capital does not seem to be well researched. It is unclear why 

wind power cannot contribute more to the 10 000 GWh target of Government. 

81 

III 

III. DEPARTMENT OF MINERALS AND ENERGY COMMENTS ON RENEWABLE ENERGY SCENARIO 

Provided by Mr. Andre Otto 

The levelised cost for wind is for all discount rates as indicated in table 9 lower than that for CSP wind, what was 

then the decision rationale and calculation used to "choose" the significant 300 MW CSP vs only 20 MW wind? 

The GEF South African Wind Energy Programme (GEF council approval of full size project in progress) aimed 

at an installed wind farm capacity of up to 50 MW (5 MW Darling + 45 MW through SAWEP) by December 

2009. 50 MW is regarded as the minimum installed wind farm capacity to attract investment and to start up a 

local manufacturing and exporting capability which should lower further wind farm investment in SA. 

The Eskom CSP demo plant (as far as I know) is based on 100 MW which still have to secure the necessary 

financing and authorisation. 

A macro-economic analysis (see attached) done (in cooperation with National Treasury) in motivating for


Cabinet approval of the White Paper on Renewable Energy (RE WP) and forming the basis of the RE Strategy 

(in progress), indicates a least cost based approached to be followed in implementing the RE WP target of 10 

000 GWh RE contribution to energy consumption by 2013. 

The Renewable Energy Market Transformation project (REMT) which is approved and financed by the SA 

Government, GEF and PCF via the World Bank, investment will start in 2005, aimed at establishing RE 

capacity to produce the 1st 1000 GWh of the 10 000 GWh target by 2008. Pending the success, the project will 

be expanded to an additional 3000 GWh to be introduced the following 4 years. The REMT is based on the 

macro-economic least cost approached of introducing the RE WP. The following RE technologies and 

applications (see table below) have been identified through a DME and World Bank economic and financial 

due diligence of the REMT. 

Recommendation 

The NER NIRP be updated with the RE technologies and applications as identified through the DME and 

World Bank economic and financial due diligence of the REMT, including CSP and wind energy as indicated in 

the attached table. 

Please take note: The REMT envisaged to introduce 744 MW RE capacity over the 1st 8 years of the RE target 

period which is already in excess of 320 MW. 

Footnote in RE WP published in Government Gazette vol 466, 14 May 2004, No 26169: 

82 

"It is estimated that if the cumulative renewable energy capacity by end of 2013 is 

approximately 1667 MW, then 10 000 GWh renewable energy would have been consumed over 

the 10 year period" 

Dec 03 Jan 07 

to Jan to Dec 

07 GWh 11 

GWh 

REMT Phase 1 Phase 2 

Sugar sugar mills spare 

capacity 

reduced process 

MW 

Annual 

load 

factor 

% 

55 55 12 52 

109 109 24 52 

steam 

full scale cogen 551 157 40 

SWH 175 1,000 190 60 

Pulp Ngodwana 65 65 8 90 

&Paper 

Additional projects 20 170 21 90 

Hydro Identified projects 210 210 63 38 

Additional projects 75 1,000 300 38 

LFG Identified projects 240 240 34 80.8 

Additional projects 51 600 85 80.8 

GEF 

SAWEP 

Wind 120 50 28 

Eskom 

CSP 613 100 70 

Total 1000 4733 894 

Total 5733 GWh (57% of 10 000 GWh target) 

Balance 4267 GWh most probably taken up by biofuel

Notes 

83

National Intergrated Resource Plan 2 - PBMR

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