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1、Planning and prospectsfor renewable powerCENTRAL AFRICAIRENA 2024Unless otherwise stated,material in this publication may be freely used,shared,copied,reproduced,printed and/or stored,provided that appropriate acknowledgement is given of IRENA as the source and copyright holder.Material in this publ
2、ication that is attributed to third parties may be subject to separate terms of use and restrictions,and appropriate permissions from these third parties may need to be secured before any use of such material.ISBN:978-92-9260-650-3CITATIONIRENA(2024),Planning and prospects for renewable power:Centra
3、l Africa,International Renewable Energy Agency,Abu Dhabi.Available for download:www.irena.org/publications.For further information or to provide feedback,please contact IRENA atinfoirena.org.ABOUT IRENAThe International Renewable Energy Agency(IRENA)is an intergovernmental organisation that supports
4、 countries in their transition to a sustainable energy future,and serves as the principal platform for international co-operation,a centre of excellence,and a repository of policy,technology,resource and financial knowledge on renewable energy.IRENA promotes the widespread adoption and sustainable u
5、se of all forms of renewable energy,including bioenergy,geothermal,hydropower,ocean,solar and wind energy in the pursuit of sustainable development,energy access,energy security and low-carbon economic growth and prosperity.www.irena.orgACKNOWLEDGEMENTSThe report draws upon discussions and inputs de
6、veloped as part of a capacity development programme between 2021-23 organised by IRENA and the Central African Power Pool(CAPP),in collaboration with the International Atomic Energy Agency(IAEA).The programme included participation by over 70 experts from planning offices in ministries,electric util
7、ities and specialised agencies from Angola,Burundi,Cameroon,Central African Republic,Chad,Democratic Republic of the Congo,Equatorial Guinea,Gabon,Republic of the Congo,Rwanda,and So Tom&Prncipe.IRENA is grateful to those experts for permitting the use of their national models in this regional analy
8、sis and for their review of this report.The national models have been altered to some extent by IRENA,so that the results presented here do not necessarily reflect the national experts original analysis.This report was prepared by Daniel Russo(IRENA)under the guidance of Roland Roesch(Director,IRENA
9、 Innovation and Technology Centre),Asami Miketa(IRENA)and Larissa Pinheiro Pupo Nogueira(IRENA).This report benefited from valuable contributions by Mohamed Bassam Ben Ticha(IAEA),Himalaya Bir Shrestha(IRENA),Bilal Hussain(IRENA),Bruno Merven(IRENA consultant),Tatyana Davydenko(IRENA),and Christoph
10、Mehler(IRENA).The report benefited from the reviews and comments provided by Sebastian Sterl(World Resource Institute);George Giannakidis(IEA-ETSAP);Thyrsos Hadjicostas(EU GTAF);Tonderayi Gumunyu(AUDA-NEPAD);Martin Lugmayr(UNIDO);Mamadou Goundiam(IRENA);Kamlesh Dookayka(IRENA);Nolwazi Khumalo(IRENA)
11、;Thierry Odou(IRENA);and Rebecca Bisangwa(IRENA).Publications and editorial support were provided by Francis Field and Stephanie Clarke.The report was edited by Jonathan Gorvett,with design by Phoenix Design Aid.IRENA is grateful for the generous support of the Walloon Government of Belgium which ma
12、de this report possible.DISCLAIMERThis publication and the material herein are provided“as is”.All reasonable precautions have been taken by IRENA to verify the reliability of the material in this publication.However,neither IRENA nor any of itsofficials,agents,data or other third-party content prov
13、iders provides a warranty of any kind,either expressed or implied,and they accept no responsibility or liability for any consequence of use of the publication or material herein.The information contained herein does not necessarily represent the views of all Members of IRENA.The mention of specific
14、companies or certain projects or products does not imply that they are endorsed or recommended by IRENA in preference to others of a similar nature that are not mentioned.The designations employed and the presentation of material herein do not imply the expression of any opinion on the part of IRENA
15、 concerning the legal status of any region,country,territory,city or area or of its authorities,or concerning the delimitation of frontiers or boundaries.CONTENTS ABBREVIATIONS.8 EXECUTIVE SUMMARY.9 Report background.9 Key characteristics of the regional power sector landscape:.9 Key insights from t
16、he results:.101 INTRODUCTION.12 1.1 Background:The IRENA Regional Modelling Analysis&Planning Support Programme.12 1.2 The report in context.132 OVERVIEW OF METHODOLOGY.153 REGIONAL POWER SECTOR OVERVIEW AND KEY SCENARIO ASSUMPTIONS.18 3.1 General definition of scenarios.354 MODELLING RESULTS.36 4.1
17、 Capacity and generation.36 4.2 CO2 emissions.72 4.3 Cross-border electricity trade.74 4.4 System costs.855 CONCLUSIONS.100 REFERENCES.103 APPENDIX:METHODOLOGICAL DETAILS.104 A.1 Overall assumptions.104 A.2 Electricity demand profiles.104 A.3 Electricity generation options.105 A.4 Evolution of capit
18、al expenditure,operating expenditure and fuel costs for power generation.106 A.5 Constraints related to system and unit operation.1084PLANNING AND PROSPECTS FOR RENEWABLE POWERFIGURESFigure 1 Governance structure of the development of the EAPP Master Plan.14Figure2 Schematic overview of the referenc
19、e energy system of each country node in the SPLAT-Africa model.17Figure 3 Electricity access(top)and electricity generation per capita(bottom)in CAPP countries,2000-2022 .19Figure 4 Secondary(sent-out)electricity demand projections,2019-2040,by country .20Figure 5 Total existing capacity per CAPP co
20、untry per technology(as of start of 2023).21Figure 6 Total committed site-specific capacity per CAPP country per technology (as of start of 2023).23Figure 7 Total candidate site-specific capacity per CAPP country per technology (as of start of 2023).24Figure 8 Existing and committed capacity in Cent
21、ral Africa by technology,compared with projected peak load,2020-2040 .25Figure 9 Country-level detail on technical VRE potential(MW)in the SPLAT-Africa model:Example of Angola .29Figure 10 Capacity results in all scenarios .37Figure 11 Difference in capacity results relative to Reference and Full Co
22、ntinental scenarios .38Figure 12 Production results in all scenarios .40Figure 13 Difference in production results relative to Reference and Full Continental scenarios .41Figure 14 Production share across scenarios .43Figure 15 Country-level breakdown of the power capacity mix by 2040,by scenario .4
23、5Figure 16 Country-level breakdown of the power generation mix by 2040,by scenario .47Figure 17 Hydropower capacity in all scenarios .50Figure 18 Difference in hydropower capacity results relative to Reference and Full Continental scenarios .51Figure 19 Grand Inga development across all scenarios .5
24、3Figure 20 Hydropower production in all scenarios .54Figure 21 Results by country for hydropower capacity in scenarios with the lowest(RefHydroDelay),top,and the highest(FullConHighDem),bottom (DR Congo separated).56Figure 22 Solar PV,onshore wind and battery capacity across all scenarios .60Figure
25、23 Difference in solar PV,onshore wind and battery capacity results relative to Reference and Full Continental scenarios .61Figure 24 Results by country for the lowest solar PV,onshore wind and battery capacity(RefInterconDelay),top,and the highest(FullConHighDem),bottom .63Figure 25 Location and am
26、ount of Solar PV MSR capacity(MW)in Angola across scenarios(selected MSRs circled in red).65Figure 26 Fossil fuel capacity across all scenarios .67Figure 27 Difference in fossil fuel capacity results relative to Reference and Full Continental scenarios .695CENTRAL AFRICAFigure 28 Results by country
27、for scenarios with the lowest fossil fuel capacity (RefInterconnDelay),top,and the highest(FullConDelayDryHigh),bottom .70Figure 29 CO2 emissions from CAPP region generation across scenarios .72Figure 30 CO2 emissions from generation in Nigeria and South Africa(combined)in Reference and RefHydroDela
28、y scenarios .73Figure 31 Country-level breakdown of imports and exports in the power generation mix by 2040(GWh,by scenario).75Figure 32 CAPP electricity imports and exports across all scenarios,2040(GWh).78Figure 33 CAPP electricity imports and exports,2040(GWh):Reference scenario(left)and Full Con
29、tinental scenario(right).79Figure 34 Interconnector capacity results(MW):Lowest(top,RefHydroDry)and highest (bottom,Full Continental).80Figure 35 Cameroon sub-annual generation mix,2040(MW):Reference and FullConDelayDryHigh scenarios.82Figure 36 Gabon sub-annual generation mix,2040(MW):Reference and
30、 FullConDelayDryHigh scenarios.83Figure 37 Sub-annual hydropower generation,2040(MW):FullConDelayDryHigh scenarios.84Figure 38 CAPP cumulative total system costs(USD million)by scenario(top)and difference from Reference scenario(bottom).86Figure 39 CAPP annual total system costs(USD million)by scena
31、rio .87Figure 40 CAPP annual total system costs(USD million):Difference from Reference scenario by cost category(top)and technology(bottom).88Figure 41 Cumulative total system costs(USD million)by scenario(top)and difference from Reference scenario(bottom),Africa.91Figure 42 Annual total system cost
32、s(USD million)by scenario,Africa .92Figure 43 Annual Africa total system costs(USD million):Difference from Reference scenario by cost category(top)and technology(bottom).93Figure 44 Capacity and production in the Full Continental scenario with and without Grand Inga .96Figure 45 Total annual(top)an
33、d cumulative(bottom)CAPP system cost difference in the Full Continental scenario with and without Grand Inga.97Figure 46 Country-level capacity difference in the Full Continental scenario with and without Grand Inga by 2040(not including DR Congo).98Figure 47 Country-level breakdown of the power gen
34、eration mix in the Full Continental scenario by 2040,with and without Grand Inga.99Figure 48 Daily time slice aggregation.104Figure 49 Normalised load(MW)on an average day in each season,all years of the modelling period.105Figure 50 Baseline overnight investment cost assumptions for generic technol
35、ogies (USD/kW).107Figure 51 Fuel price projections.1086PLANNING AND PROSPECTS FOR RENEWABLE POWERTABLESTable 1 Existing and identified hydropower projects,as of start of 2023(MW).27Table 2 Total solar and wind capacity potential included in CAPP countries in the SPLAT-Africa model(MW).29Table 3 Exis
36、ting,committed and candidate cross-border transmission infrastructure(MW).32Table 4 Site-specific cross-border transmission infrastructure summary.32Table 5 Capacity expansion scenarios .35Table 6 Electricity trade between CAPP countries,2019(GWh).74Table 7 Overview of reserve margin contributions o
37、f the various technology types used in the SPLAT-Africa model(numbers represent the percentage of the technologys installed capacity that counts towards the installed reserves).1097CENTRAL AFRICABOXESBox 1 Scenarios for the energy transition:The African power pool experience.13Box 2 Location of pote
38、ntial VRE projects in results:Example of IRENA Model Supply Regions in Angola.65Box 3 SPLAT-Africa dispatch results .82Box 4 Grand Inga:Implications on model results .958PLANNING AND PROSPECTS FOR RENEWABLE POWERABBREVIATIONSAC alternating currentAfREP African Renewable Energy Profiles for Energy Mo
39、delling AU African UnionAUDA-NEPAD African Union Development Agency-New Partnership for Africas DevelopmentCAPEX capital expenditureCAPP Central African Power PoolCCGT combined-cycle gas turbineCMP Continental Power Systems Master PlanCO2 carbon dioxideCSP concentrated solar powerDC direct currentDN
40、I direct normal irradiationDR Congo Democratic Republic of the CongoEAPP East African Power PoolECCAS Economic Community of Central African StatesECOWAS Economic Community of West African StatesEEZ exclusive economic zoneEU European UnionGDP gross domestic productGHI global horizontal irradiationGW
41、gigawattGWh gigawatt hourHFO heavy fuel oilHVDC high voltage direct currentIAEA International Atomic Energy AgencyIIASA International Institute of Applied System AnalysisIRENA International Renewable Energy AgencykTCO2 kilotonnes of carbon dioxidekV kilovoltkW kilowattkWh kilowatt hourMESSAGE Model
42、for Energy Supply Strategy Alternatives and their General Environmental ImpactMSR model supply regionMW megawattMWh megawatt hourOCGT open-cycle gas turbineOECD Organisation for Economic Co-operation and DevelopmentO&M operation and maintenanceLCOE levelised cost of electricityLT low tensionLTES lon
43、g-term energy scenariosPP power plantPV photovoltaicROR run-of-riverSAPP South African Power PoolSPLAT System Planning Test model UN United NationsUSD UnitedStates dollarVRE variable renewable energyWAPP West African Power Pool9CENTRAL AFRICAREPORT BACKGROUNDBetween 2020 and 2023,IRENA implemented t
44、he Regional Africa Modelling Analysis&Planning Support Programme for Central Africa,in partnership with the Central African Power Pool(CAPP).1 The programme gave practical training and insight into how to develop national and regional generation capacity expansion scenarios that can inform the energ
45、y planning process.It was delivered to over 70 key staff from the regions national energy institutions.This report aims to build on that work by performing a consolidated regional analysis of potential scenarios for regional long-term power sector development.In doing so,it provides a foundation of
46、transparent power sector data,as well as providing scenarios for long-term infrastructure development to local stakeholders.As the region embarks on the development of its first official regional power sector masterplan,the capacity built by the IRENA-CAPP programme and this report are both seen as
47、essential inputs.KEY CHARACTERISTICS OF THE REGIONAL POWER SECTOR LANDSCAPE:Electricity demand may expand significantly from a very low baseline.Despite pockets of progress in recent decades for certain CAPP countries,Central Africa continues to be a region with one of the lowest levels of electrici
48、ty access in the world.As of 2023,four CAPP countries had overall electricity access of less than 20%,while 7 out of the regions 11 countries had access levels below 50%.Except for Gabon,all of the regions countries were below the global average.As a result,there is enormous scope for electricity de
49、mand growth.While reference projections largely track historical trends,these would still indicate a doubling of regional electricity demand by 2040.A more ambitious level of development,such as that necessary to meet the aspirations of the African Union(AU)Agenda 2063,would indicate a nearly 350%in
50、crease in regional electricity demand by 2040.In such a scenario,peak load is projected to exceed existing and committed capacity by about 10gigawatts(GW)a nearly 50%gap by 2040.This shows the clear need to plan and commit further investments in new generation projects.Hydropower dominates existing
51、and planned regional power supply.At the start of 2023,installed power generation capacity in the CAPP region was just over 11GW,of which hydropower made up roughly 75%.Hydropower continues to be the main category of new capacity being planned in the region,making up over 85%of committed and candida
52、te projects,including the major Grand Inga hydropower project in the Democratic Republic of the Congo(DR Congo).With over 20GW of hydropower potential at the Grand Inga site reflected in the modelling horizon nearly two times more than the total current installed capacity in all of Central Africa th
53、is projects potential development is emblematic of the regions ambitions to become an electricity exporter to the continent.It is also indicative of the regions rich renewable resources.1 IRENA is grateful for the generous support of the Walloon Government of Belgium,which made the programme and thi
54、s report possible.EXECUTIVE SUMMARY10PLANNING AND PROSPECTS FOR RENEWABLE POWER There is a major ambition to develop cross-border trade beyond its current,limited,scope.As of 2023,existing cross-border transmission capacity within the CAPP region was mainly limited to infrastructure between DR Congo
55、,Rwanda and Burundi.That year,this infrastructure accounted for around 515megawatts(MW)of the 601MW of total intra-CAPP capacity.Indeed,in 2023 there was more capacity between bordering countries/regions and the CAPP,with just over 1GW of cross-border infrastructure connecting DR Congo,Rwanda and An
56、gola to the Eastern African Power Pool(EAPP)and Southern African Power Pool(SAPP)countries.Planned projects reflect a strong ambition to change this picture,however.These projects aim to develop a more comprehensive cross-border transmission infrastructure within the CAPP,along with more export capa
57、city to other regions.If all planned projects were to be developed,this infrastructure expansion would represent a more than ten-fold increase in current transmission capacity to other regions.It would also represent a twenty-fold increase in intra-CAPP transmission capacity.KEY INSIGHTS FROM THE RE
58、SULTS:In all the scenarios covered by this report,renewables are central to meeting demand and trade expansion in Central Africa.In every scenario,out to the modelling horizon of 2040,hydropower remains the largest renewable energy source in the region,supplying nearly 70%of its electricity.Reductio
59、ns in the cost of solar photovoltaic(PV)and wind are driving their expansion in the regional capacity mix.In all scenarios,the share of these two technologies rise from nearly zero today to at least 7%of regional production by 2040.Due to regional climate conditions,solar PV is set to grow faster.In
60、 scenarios with high demand,solar and wind reach 14%-20%of total production by 2040,while their role is even more important in scenarios with challenging future hydropower conditions,such as project delays and dry years.Although certain countries have gas capacity in the planning pipeline,in all sce
61、narios,the share of fossil fuels in regional electricity production falls from todays already low level.In the majority of scenarios,it falls to below 5%of production by 2040.Interestingly,across almost all scenarios,the overall gas capacity begins to decrease by 2040 as the costs of renewable techn
62、ologies and batteries continue to decline.This implies that these plants do not have a promising long-term outlook in the region.There is large,untapped potential for cross-border electricity trade inside and outside the CAPP region.More cross-border infrastructure would allow lower-cost renewable r
63、esources to be used more extensively,displacing more costly fossil fuel use.Consistently,exports from the CAPP to other regions also lower costs and emissions for Africa as a whole,particularly in western and southern Africa.For this reason,by the mid-2030s,in all scenarios,cross-border interconnect
64、ion capacity in the CAPP region grows over ten-fold to a total of at least 10GW.This would result in lower power sector costs.In scenarios where all physically possible interconnectors in the CAPP region are allowed,the highest total interconnector capacity reaches around 40GW by the early 2030s and
65、 nearly 50GW by 2040.11CENTRAL AFRICA The Grand Inga hydropower project has a major influence on the evolution of inter-regional trade and the regional power system in Central Africa.Compared to the scenario with the most trade in 2040,regional results without the Grand Inga expansion contain 73%les
66、s interconnector capacity,or around 13GW of capacity versus around 48GW.Without Grand Inga,there are also 81%fewer net exports from the region.Without the expansion of Grand Inga,other CAPP countries will need to plan for different capacity and production mixes.Angola,Cameroon,the Republic of the Co
67、ngo and Gabon are the most affected in terms of capacity,but different variations of renewable and battery storage capacity could be cost-competitive in filling the gap in the 2030s.In all scenarios,significant investment must be planned to meet the expected expansion of demand.Even in the scenario
68、with the lowest investment needs,the overall amount implies costs,in US dollar(USD)terms,of over USD5billion per year,on average,for the regional power system.About two-thirds of this would be dedicated to capacity investment.Cumulative system costs and investment in the CAPP region vary significant
69、ly depending on future assumptions in the areas of demand and cross-border trade.The highest-cost scenario reaches just over USD145billion between 2022 and 2040.This figure is around 48%or USD47billion higher than the lowest cost scenario for the region,which is around USD97billion over the same per
70、iod.2 The most significant driver of the difference is the level of investment in capacity to meet higher or lower regional demand and export demand.These results highlight how important the planning of interconnector and export capacity development(and thus the role of the CAPP in leading such disc
71、ussions)will be in the future overall costs and investment needs of the region,as well as of the continent as a whole.This is particularly the case for any large-scale hydropower projects,such as Grand Inga,which are to some extent linked to cross-border infrastructure.2 For reference,IRENA estimate
72、s that the whole of Africa saw about USD 60 billion of investment in renewable energy between 2000-2020(IRENA,2023a).12PLANNING AND PROSPECTS FOR RENEWABLE POWER1.1 BACKGROUND:THE IRENA REGIONAL MODELLING ANALYSIS&PLANNING SUPPORT PROGRAMMEIn Central Africa,IRENA has implemented a wide range of prog
73、rammes to support the development of renewable energy.Since 2013,IRENA member states in this region have also registered particular interest in strengthening energy planning capacity.This is to allow regional governments to develop robust energy sector objectives,plans and climate targets.The Region
74、al Renewable Energy Roadmap of the Economic Community of Central African States(ECCAS),endorsed in 2021,aimed to identify key activities in addressing energy transformation among its members.The roadmap had two main recommendations:first,to strengthen the capacity for long-term energy planning proce
75、sses with the tools to link the assessment of renewable potential to actual development;and second,to prepare national and regional master plans for the power or energy sectors that accounted for an increased share of variable renewables.In partnership with the Central African Power Pool(CAPP),betwe
76、en 2020 and 2023,IRENA followed through on these recommendations by implementing the Regional Modelling Analysis&Planning Support Programme for Central Africa.3 This programme delivered both methodological and practical training to official experts from the regions national energy institutions.It fo
77、cused on how to develop national and regional generation capacity expansion scenarios,in order to inform the energy planning process.Over the course of two,six-month training phases,roughly 70 technical planning experts from all CAPP member states participated.Activities included:an e-learning cours
78、e for the Model for Energy Supply Strategy Alternatives and their General Environmental Impact(MESSAGE)capacity expansion software,implemented with the support of the International Atomic Energy Agency(IAEA);four training workshops on long-term planning with renewables and the IRENA System Planning
79、Test(SPLAT)-MESSAGE modelling framework;and on-request tutoring support for modelling and preparation of national summary reports.The programme was closely integrated with the African Continental Power Systems Master Plan(CMP)development,led by the African Union Development Agency-New Partnership fo
80、r Africas Development(AUDA-NEPAD).Key financial support was provided for this by the European Union(EU),with IRENAs support as a modelling partner.The outcome of this programme has been enhanced energy planning capacity for CAPP member-state planning authorities.A foundation of transparent power sec
81、tor data and scenarios for long-term infrastructure development,owned by local stakeholders,has also been established.Both of these developments are seen as essential inputs as the region embarks on the development of its first,official,regional power sector masterplan.3 IRENA is grateful for the ge
82、nerous support of the Walloon Government of Belgium,which made the programme and this report possible.1INTRODUCTION13CENTRAL AFRICA1.2 THE REPORT IN CONTEXTThis report is part of the IRENA series,Planning and Prospects for Renewable Energy,which focuses on renewable electricity generation in African
83、 power pools.It aims to build on the work of the IRENA-CAPP Regional Modelling Analysis&Planning Support Programme by performing a consolidated regional analysis of potential scenarios for long-term power sector development in the region.In doing so,it partially documents the inputs and outputs of t
84、he SPLAT-Africa model that were elaborated by participants in the IRENA-CAPP programme.Based on the additional feedback from regional stakeholders given at a high-level review workshop in July 2023,this report also presents scenarios that have been further elaborated by IRENA for power system expans
85、ion in Central Africa through to 2040.These scenarios include the potential for interconnections within and outside the region.While the work of this report is firmly based on regional engagement,it does not necessarily reflect countries official positions,nor does it intend to prescribe a path of p
86、ower sector development.4 The assessment is based on certain assumptions surrounding power sector development,which stakeholders in the region may regard differently.Local experts are advised to continue exploring different assumptions in order to develop their own scenarios for comparison.The resul
87、ts from the analysis presented here are intended to support that effort and contribute to the forthcoming national and regional dialogue,as CAPP member states prepare to meet ambitious renewable energy targets and develop the regions first official power sector masterplan.The results also highlight
88、the utility of the SPLAT-Africa model as a freely available tool to develop and explore national and regional power sector scenarios.Chapter 2 of the report presents an overview of the methodology used in the analysis,including a description of the SPLAT-Africa model and its structure.More detailed
89、elaboration of the modelling exercises inputs is provided throughout Chapter 3,which also provides insight into the regions electricity sector landscape.Chapter 4 presents a detailed overview of the results for the different scenarios explored in the modelling exercise,while Chapter 5 offers high-le
90、vel conclusions from the analysis.The data appendix that will be made available on the report homepage on the IRENA website,presents more detailed data used in the study and country-level results.As of the date of this reports publication,the Central African region does not have an official regional
91、 power sector masterplan.It is hoped that the analysis presented here and the IRENA-CAPP Regional Africa Modelling Analysis&Planning Support Programme that has informed this report will be valuable inputs in the development of such a plan.To further support improved development and use of long-term
92、scenarios,IRENA has also investigated the experience of existing African power pool plan development in the publication Scenarios for the energy transition:Experience and good practices in Africa(IRENA,2023b).This was undertaken as part of the agencys Long-Term Energy Scenarios(LTES)network.In that
93、report,several best practices from the experience of the Eastern African Power Pool(EAPP)and the West Africa Power Pool(WAPP)were highlighted and are summarised below:4 The CAPP member country teams that attended the SPLAT-MESSAGE training sessions are not responsible for the final specific results
94、presented in this report,which are a product of IRENAs modelling and analysis.Box 1 Scenarios for the energy transition:The African power pool experience14PLANNING AND PROSPECTS FOR RENEWABLE POWER A bottom-up approach in developing regional master plans Energy scenario development by the EAPP and W
95、APP is a collaborative process between member state ministries,utilities and regional organisations.As illustrated in the figure below,a bottom-up approach is used in the EAPP,where master plans are developed at the national level and then used as the basis for the regional master plan.Figure 1 Gove
96、rnance structure of the development of the EAPP Master PlanIn the WAPP,the master plan was validated by a committee within the power pool,endorsed by the Executive Board and sent to the General Assembly for its approval.The regions heads of state were then presented with the plan for their agreement
97、.Broad stakeholder participation in long-term energy scenario(LTES)development:In both EAPP and WAPP,the scope of the LTES is defined,validated and agreed upon by all members.The modelling of LTES and identification of energy planning strategies is also participated by government institutions,the pr
98、ivate sector,academia and other research institutions.This broad participation by stakeholders with different priorities serves to build consensus around scenarios and policy development.Scenario update and use beyond development is well-defined:There is an expectation that the WAPP Regional Master
99、Plan is to be updated frequently enough to account for changing factors.These could include the continued development of renewable energies,as well as emerging technologies or strategies at the country level.In the EAPP,regional energy scenarios that are devised are used to support technical discuss
100、ions at the national level.This aims to ensure that targets and decisions at the national level are aligned with regional strategy.Capacity building is conducted through continuous training:To reinforce energy planning capacity,the EAPP prepares annual training sessions for member states and incorpo
101、rates these into the EAPP Short-Term Action Plan.Box 1 ContinuedConsultantsNational master plansPlanning committeeTechnical committeeEastern Africa PowerPool(EAPP)EAPP GeneralSecretariatRegional(EAPP)Master PlanValidation by all EAPPmembersUtilities ministries,regional economic communities(RECs)15CE
102、NTRAL AFRICAThe SPLAT-Africa model used in this report was developed using the MESSAGE software a dynamic,bottom-up,multi-year energy system modelling platform that applies linear and mixed-integer optimisation techniques.MESSAGE was originally developed at the International Institute of Applied Sys
103、tem Analysis(IIASA),but has been enhanced by the IAEA.The modelling platform is a flexible framework within which the actual SPLAT-Africa model has been developed.The SPLAT-Africa model consists of demand projections,a database of cross-border transmission infrastructure,power generation technologie
104、s characterised by economic and technical parameters,and information regarding existing infrastructure and its remaining life span.Starting with the existing power infrastructure in the region,the model calculates an evolution of technically feasible technology mixes that achieve a least-cost object
105、ive over the planning period(i.e.minimal total discounted system costs,including investment,operation and maintenance O&M,fuel and any other user-defined costs),while meeting various system requirements(e.g.supply matching demand at a given time;sufficient resources and capacity in place to supply d
106、esired production)and user-defined constraints(e.g.reserve margin,speed of technology deployment,emission limits,policy targets).The model inputs described above can be varied according to the users preference to explore different scenarios of system evolution under particular sets of assumptions.Th
107、e models“solution”includes,inter alia,investment in new technologies,production,fuel use and trade.Economic and environmental implications associated with the identified least-cost systems can also be calculated with the model.The SPLAT-Africa model used for this analysis covers all 11 CAPP member c
108、ountries:Angola,Burundi,Cameroon,the Central African Republic,Chad,the Democratic Republic of the Congo(DR Congo),Equatorial Guinea,Gabon,the Republic of Congo,Rwanda and So Tom&Prncipe.So Tom&Prncipe is considered as a separate entity in the modelling,as it is not connected to the mainland electric
109、ity grid.5 The modelling of Central African countries is part of the broader SPLAT-Africa framework,which has been entirely developed and is regularly updated by IRENA.As such,the Central African countries that constitute the CAPP can be modelled individually,as part of an isolated Central Africa re
110、gion,or modelled to reflect all the cross-border interconnections with countries outside of that region.The scenarios developed over the course of this modelling exercise utilise this range of structures to explore the impacts of various interconnection possibilities on power sector development.More
111、 information on assumptions and definitions in the scenarios developed can be found in the following chapters.5 The particular geographical situation of Equatorial Guinea should also be well-noted,as its capital is on an island,while part of the country is on the mainland with direct land borders to
112、 neighbouring countries.2OVERVIEW OF METHODOLOGY16PLANNING AND PROSPECTS FOR RENEWABLE POWERThe key characteristics of the SPLAT-Africa model used in this report are:Countries are modelled as separate nodes,interlinked by transmission lines.Each node,representing the power system of a single country
113、,is characterised as shown in Figure 2 below.Demand for electricity is defined at the“sent-out”level,i.e.before transmission and distribution.See point 1 on electricity demand in chapter 3 below for more detail.Computation is made of a least-cost power supply system that meets the given demand while
114、 satisfying all user-defined constraints.“Least-cost”is defined for the region as a whole,over the entire modelling period.There is explicit modelling of four categories of power generation options for all existing and known generation technologies,and cross-border transmission.The four categories a
115、re:existing capacity;committed site-specific projects that are expected to be commissioned;candidate site-specific projects that are under consideration;and non-site specific(generic)options.See section A.3,Electricity generation options,and point 3 of Chapter 3,for more details.Reliability of suppl
116、y is addressed by assigning a 10%reserve margin above peak load.Different technologies are also assigned different levels of“firm”capacity to satisfy that margin,based on the nature of the resource.See Section A.5,Constraints related to system and unit operation,for more detail.The implementation of
117、 the IRENA-CAPP Regional Modelling Analysis&Planning Support Programme was closely integrated with the development of the CMP,led by AUDA-NEPAD,with key financial support from the EU,which IRENA supports as a modelling partner.As such,a wide range of model inputs outlined in this report draw upon th
118、e work completed in the CMP project,which also had the full participation of the CAPP.Further methodological details for the SPLAT-Africa model used for the Central Africa region can be found in the methodological appendix at the end of this report.17CENTRAL AFRICAFigure2 Schematic overview of the r
119、eference energy system of each country node in the SPLAT-Africa modelNotes:All technologies with an asterisk(*)are provided with a specific temporal availability profile(see chapter 3 below);technologies with two asterisks(*)allow for generic capacity expansion subject to stakeholders preference.HFO
120、=Heavy Fuel Oil;OCGT=Open-Cycle Gas Turbine;CCGT=Closed-Cycle Gas Turbine;ROR=run-of-river;PV=photovoltaic;CSP=concentrating solar power.Primary(secondary in other country)River flows*TertiaryStorage Hydro reservoirs Pumped storage Battery storageFinalSecondaryUser defined existing,committed,candida
121、tes and pre-loaded generic candidates Gas extraction&imports Coal mining&imports Fuel production&imports Biomass collection Uranium mining&imports Gas-fired plants OCGT/CCGT*Coal-fired plants*HFO-fired plants*Biomass-fired plants*Nuclear plants*Geothermal plants Batteries(one generic candidate per c
122、ountry)InterconnectionsCombustionCombustionCombustionCombustionFissionAll plants site specific and no pre-loaded generic expansion candidates Run-of-river hydropower plants*Reservoir hydropower plants Pumped storage plantsWith pre-loaded geospatial clusters as candidates(2,5 or 10 for each country,d
123、epending on country size),with site-specific profiles and grid and road expansion CAPEX Solar PV plants*Solar CSP plants*Onshore wind plants*Offshore wind plants*ReleasesFillingTradeDispatch StorageReleases StorageDistribution end demandConsumer end demandDistribution gridTransmission grid18PLANNING
124、 AND PROSPECTS FOR RENEWABLE POWERThis report takes into account the below characteristics of the regional power sector and makes the following assumptions when considering its development:1 ELECTRICITY DEMAND MAY EXPAND SIGNIFICANTLY FROM A VERY LOW BASELINEDespite pockets of progress for certain C
125、APP countries in recent decades,the CAPP region continues to have some of the lowest levels of electricity access and generation per capita in the world.As shown in the figures below,in 2022,four CAPP countries had overall electricity access of less than 20%,while 7 out of 11 countries had access ra
126、tes below 50%.All except Gabon were below the global average.Levels of electricity use for those with access were also far below the global average.As of 2022,electricity generation per capita in the CAPP countries ranged from 0.5%to 28%of the global average.As a result,there is enormous scope for e
127、lectricity demand growth in the region.Electricity demand assumptions in this report take this into account and are based on secondary,or sent-out electricity demand projections(i.e.at the utility level,before transmission)developed as part of the CMP project.Econometric modelling was performed for
128、the CMP using forecast values for country-level demand drivers.These included gross domestic product(GDP)per capita,population,the urbanisation rate,electricity consumption per capita and the electricity access rate.6 Modelled projections were then cross-referenced with available projections in offi
129、cial regional power pool and national masterplan documents.In some cases,reference demand projections were adjusted as necessary to align with official projections through consultations held within IRENA and CMP training sessions.Alternative scenarios for demand forecasts were also created using alt
130、ernative projections and assumptions for the key driving parameters.These parameters included GDP per capita,the electricity access rate and electricity consumption per capita.While reference projections largely track historical trends,these still show a doubling of regional electricity demand by 20
131、40.A high alternative demand scenario reflects a more ambitious level of development,made to meet the aspirations of the African Union(AU)Agenda 2063.This includes the achievement of 100%electricity access and an increase in each countrys per capita electricity consumption over the modelling horizon
132、 to align with the next highest income level category(e.g.a moving from lower-middle income to middle income).Such a scenario would represent a nearly 350%increase in regional electricity demand by 2040.Figure 4 presents the projection of secondary electricity demand utilised for this analysis.Detai
133、led country-level data can be found in the data appendix that will be made available from the report download page on the IRENA website.6 Sources for these values include IIASA,the United Nations(UN),the African Energy Commission and the IEA.Full detail behind any values and methodologies used in th
134、e CMP programme can be found in the CMP programme documentation:https:/cmpmwanga.nepad.org/publications 3REGIONAL POWER SECTOR OVERVIEW AND KEY SCENARIO ASSUMPTIONS19CENTRAL AFRICAFigure 3 Electricity access(top)and electricity generation per capita(bottom)in CAPP countries,2000-2022 Source:(Ember a
135、nd Energy Institute,2023;IEA et al.,2023).Note:kWh=kilowatt hour.%kWh10090807060504030201004 0003 5003 0002 5002 0001 5001 000500020002001200220032004200520062007200820092010201120122013201420152016201720182019202020212022200020012002200320042005200620072008200920102011201220132014201520162017201820
136、19202020212022AngolaBurundiCentral African RepublicCameroonDR CongoRepublic of the CongoEquatorial GuineaGabonRwandaSo Tom and PrncipeChadWorld20PLANNING AND PROSPECTS FOR RENEWABLE POWER2 EXISTING AND PLANNED REGIONAL POWER SUPPLY IS MAINLY RENEWABLE DUE TO HYDROPOWER Existing power generation in t
137、he CAPP region has been integrated into the SPLAT-Africa model based on the latest available data provided and reviewed by official regional and national planning representatives in the IRENA-CAPP Regional Modelling Analysis&Planning Support Programme and the CMP programme.An overview of existing ge
138、neration capacity is presented in Figure 5 below.At the start of 2023,installed power generation capacity in the CAPP region stood at just over 11gigawatts(GW),of which Angola and DR Congo accounted for more than half.As hydropower makes up over 90%of the capacity mix of each of these countries,the
139、region-wide supply mix is also majority hydropower(75%),followed by gas(14%)and diesel(7%).Heavy fuel oil(HFO)contributed 4%,with the remainder made up of other small capacities.Although fossil fuel capacity is relatively less prominent at the regional level,several countries in the region,such as C
140、had,Republic of the Congo,Equatorial Guinea,Gabon,Rwanda,and So Tom and Prncipe,currently rely heavily on such capacity.Country-level detail of existing capacity are given in the data appendix accompanying this report.Figure 4 Secondary(sent-out)electricity demand projections,2019-2040,by country No
141、te:GWh=gigawatt hours.GWh150 000140 000130 000120 000110 000100 00090 00080 00070 00060 00050 00040 00030 00020 00010 0000 2019 2021 2023 2025 2027 2029 2031 2033 2035 20372039 2040 2019 2021 2023 2025 2027 2029 2031 2033 2035 20372039 2040ReferenceHighDemSo Tom and PrncipeCentral African RepublicBu
142、rundiChadEquatorial GuineaRwandaGabonRepublic of the CongoCameroonDR CongoAngolaWorld21CENTRAL AFRICAFigure 5 Total existing capacity per CAPP country per technology(as of start of 2023)Notes:Capacity values are meant to reflect total installed capacity.They therefore may not reflect differences in
143、effective capacity due to operational issues.ROR=run of river,MW=megawatt.%1009080706050403020100AngolaBurundiCameroonCentral African RepublicChadRepublic of the CongoDR CongoEquatorial GuineaGabonRwandaSo Tom and PrncipeSolar PV8401122Hydro ROR827501401581 9061271021232Hydro dam2 95818958741 080228
144、12HFO20186114132570Gas12026790545515737227Diesel3515040356224945857829Coal15Biomass9MW4 5004 0003 5003 0002 5002 0001 5001 000500022PLANNING AND PROSPECTS FOR RENEWABLE POWERFuture site-specific project information was originally developed by IRENA based on official national and regional masterplan
145、documents and desk research to cross-check international databases.The final information used in this report also reflects a full review and revision by national and regional stakeholders in both IRENA and CMP trainings.An overview of site-specific project capacity beyond 2022 in CAPP countries in t
146、he SPLAT-Africa model is presented in the figures below,which show the capacities of committed and candidate projects.Committed projects are those which are considered certain to come online in a known future year,while candidate projects reflect known sites in the planning process that do not yet h
147、ave a determined construction date.Although certain countries have nationally-significant amounts of gas capacity in the planning process,hydropower continues to be the main category of new capacity being planned in the region.This is particularly the case for candidate projects,which also include t
148、he major Grand Inga hydropower project in DR Congo.With the modelling horizon reflecting over 20GW of hydropower potential at the Inga site a figure that is nearly twice the total current installed capacity in all of Central Africa Grand Ingas envisaged development is both emblematic of the regions
149、rich renewable resources and its ambitions to become an electricity exporter for the continent.7 Beyond these site-specific capacities,additional future capacity options are included in the model.The section below,Renewable generation options,provides details of the regions wider renewable potential
150、.8 Detailed technical parameters for these technologies(e.g.costs,efficiency,construction duration,lifetime)are summarised in the data appendix accompanying this report.7 Note that the site has up to 40 GW of potential capacity,but not all of which is included for potential construction by 2040 unde
151、r the analysis assumptions.In addition,challenges in the development of the Grand Inga project cannot be ignored in a prudent planning process.For this reason,although the project is officially a candidate for development,the modelling for this report also explores the impact of delays or alternativ
152、es to the Grand Inga project on regional power sector development.8 This section focuses on hydro,solar and wind power;more detail on the modelling methodology for all future capacity options can also be found in Section A.3,Electricity generation options.23CENTRAL AFRICAFigure 6 Total committed sit
153、e-specific capacity per CAPP country per technology (as of start of 2023)%1009080706050403020100AngolaBurundiCameroonCentral African RepublicChadRepublic of the CongoDR CongoEquatorial GuineaGabonRwandaSo Tom and PrncipeSolar PV42412375045Hydro ROR121871432001241467Hydro dam2 100525160112Gas3812056D
154、iesel36Coal130MW3 0002 5002 0001 5001 000500024PLANNING AND PROSPECTS FOR RENEWABLE POWERFigure 7 Total candidate site-specific capacity per CAPP country per technology (as of start of 2023)%1009080706050403020100AngolaBurundiCameroonCentral African RepublicChadRepublic of the CongoDR CongoEquatoria
155、l GuineaGabonRwandaSo Tom and PrncipeWind Onshore204Solar PV1682731563304045Hydro ROR1 7172885 7424061 46119 3691 4404345Hydro dam7151 927Gas2 8501 46430Diesel7323Coal500Biomass225MW25 00020 00015 00010 0005 0000Notes:Data presented here reflects site-specific candidate project capacity included in
156、the model horizon i.e.up to 2040.This is an important distinction for the Grand Inga hydropower project,which has up to 40GW of potential capacity,but not all of which is included for potential construction by 2040 under the analysis assumptions.25CENTRAL AFRICAThe figure below presents a projection
157、 of the lifetime of existing power plants and committed projects,compared to the projected peak load under the reference and high demand scenarios used in this study.Although current total installed capacity figures appear in excess of peak load,one must consider that the capacity factor of hydropow
158、er plants i.e.the availability of capacity to meet peak load is typically below 100%.This is due to dependence on hydrological conditions to various extents,while installed capacity values for all technologies may also not reflect differences in effective capacity due to operational issues.9 For the
159、se reasons,new power generation projects must be planned and investments committed to meet future electricity demand under both scenarios.This is particularly the case in the high-demand scenario,in which peak load is projected to exceed existing and committed capacity by nearly 10GW by 2040.Before
160、that point,existing and committed total capacities in the region above the peak demand projections going into the 2030s reflect the regional ambition to become an important centre for electricity exports in the continent,as discussed in point 3 below in this chapter.9 These factors are taken into co
161、nsideration in the modelling for this study.For more details,see Appendix:Methodological details.Figure 8 Existing and committed capacity in Central Africa by technology,compared with projected peak load,2020-2040 MW26 00024 00022 00020 00018 00016 00014 00012 00010 0008 0006 0004 0002 0000202020212
162、022202320242025202620272028202920302031203220332034203520362037203820392040Solar PV utilityLarge hydro RORLarge hydro damNatural gasHFODieselCoalPeak load(reference)Peak load(high)26PLANNING AND PROSPECTS FOR RENEWABLE POWERRENEWABLE GENERATION OPTIONSLarge hydropowerWith hydropower as the largest s
163、ource of current and planned regional power supply,it is important to ensure it is well-represented in regional planning and modelling processes.Due to the variability in climate zones within and across African countries and corresponding patterns of rainfall and river flow,it is critical to model t
164、he following aspects of hydropower generation:10 The seasonality in power generation caused by river inflow,constrained by possible discrepancies between maximum river discharge and maximum turbine flow,and mitigating effects that the presence of reservoirs can have on this seasonality.The flexibili
165、ty that reservoir hydropower plants can provide to support VRE integration on a sub-daily basis,modulated by their seasonal availability.These aspects were modelled at the plant level for existing,committed and candidate plants,using the African Renewable Energy Profiles for Energy Modelling(AfREP)-
166、Hydro database published by IRENA for the benefit of the modelling community(IRENA,2021a;Sterl et al.,2021).This database uses a continental-level river flow dataset in combination with technical information at the hydropower plant level to estimate seasonal capacity factor profiles.In the modelling
167、 for this report,two alternative scenarios related to large hydropower were also considered,based on guidance from participants in the IRENA-CAPP Regional Modelling Analysis&Planning Support Programme.These were:a scenario where all hydro production is subject to dry year assumptions;and a scenario
168、where all candidate hydropower greater than 1GW is delayed by five years.Dry year assumptions are based on the range of river flow simulations underpinning the AfREP-Hydro database(for more detail,see(Sterl et al.,2021).Large hydropower capacity in CAPP countries in the SPLAT-Africa model is summari
169、sed in Table 1.Detailed parameters for existing and planned hydropower projects are given in the data appendix accompanying this report.10 For more detail on the links between renewable energy resources and weather and climate conditions,see WMO and IRENA,2023.27CENTRAL AFRICATable 1 Existing and id
170、entified hydropower projects,as of start of 2023(MW)11 Or of a countrys Exclusive Economic Zone,in the case of offshore wind.12 This is the case as long as the 5%are within the range of potential deemed commercially exploitable(Sterl et al.,2022).This was the case for most countries.EXISTINGEXISTING
171、 TOTALCOMMITTEDCOMMITTED TOTALCANDIDATECANDIDATE TOTALGRAND TOTALMWHydro reservoirHydro RORHydro reservoirHydro RORHydro reservoirHydro RORAngola2 9587063 6642 1001212 2217151 7172 4328 317Burundi1850688787288288443Cameroon95819605255251 9275 7427 6699 154Central African Republic4040406406446Republi
172、c of the Congo741582321 4611 4611 693DR Congo1 0801 9062 98616014330319 36919 36922 658Equatorial Guinea127127200200327Gabon2281023311241241 4401 4401 895Rwanda121231351121462584343435So Tom&Prncipe2277454554Grand total5 3293 2158 5432 8978273 7242 64230 51033 15245 420Notes:Official national docume
173、nts reviewed and updated as part of the IRENA-CAPP Regional Modelling Analysis&Planning Support Programme and CMP programme.ROR=run-of-river.Variable renewable power generation:Solar and windWhile the SPLAT-Africa model includes project-specific solar and wind supply options,this resource pool is li
174、mited in size,covering only a small portion of the extensive resource base in the region.To sufficiently cover the resource potential beyond the current project pipeline,geographic clusters of high-potential sites have been included in the model(IRENA,2024).The clusters are based on IRENAs concept o
175、f model supply regions(MSRs),which are model-ready candidate regions with specific capacity potential,infrastructure costs and generation profiles at the country-level.For the majority of countries in Africa,even after excluding unsuitable or protected areas,the potential of variable renewable energ
176、y(VRE)covers large portions of the countrys surface area.In SPLAT-Africa,expansion of VRE technologies is limited to 5%of a countrys surface area.This has been done in order to reduce model data inputs while maintaining enough potential resource options for future system expansion.To do this,exploit
177、able potential in a country(available as MSRs)was screened for the areas representing the 5%most attractive regions of a countrys surface area.11,12“Most attractive”is defined as those areas where power plants would have the lowest expected levelised cost of electricity(LCOE).This LCOE has been calc
178、ulated after considering the effects of resource quality(i.e.the level of solar irradiation and wind speed),as well as the distance from existing grid infrastructure that would lead to additional expense for grid and road 28PLANNING AND PROSPECTS FOR RENEWABLE POWERnetwork build-out.13 The resulting
179、 set of geospatially referenced regions thus represents a realistic selection of the most promising locations in each country for constructing power plants,while covering possible spatial resource divergences within that country.Significant solar PV potential is present in every country.The SPLAT-Af
180、rica model can therefore invest in solar PV clusters in any CAPP country.This is not the case for onshore wind,for which no high-quality potential MSRs were identified within the CAPP region for Burundi,Equatorial Guinea,Gabon and Rwanda.14 There were therefore no interesting options for the SPLAT-A
181、frica model to invest in regarding onshore clusters in these countries.Solar CSP was taken to be able to compete economically with solar PV only if it had thermal storage included.Therefore,solar CSP with a typical amount of storage(six hours)was included in the model as technology,but solar CSP wit
182、hout storage was excluded.Candidate clusters for solar CSP were developed in a comparable way as for solar PV,but using normalised direct normal irradiation(DNI)as a proxy for capacity factor profiles instead of global horizontal irradiation(GHI).To reduce computational burden in the modelling,a max
183、imum of two clusters per country were used.Due to the geographic disparity in DNI(as opposed to GHI,which is relatively uniformly distributed),not all countries boast realistically exploitable solar CSP potential.In the CAPP region,no solar CSP MSRs were identified for Rwanda,Equatorial Guinea,Gabon
184、 or the Republic of the Congo.Offshore wind profiles were obtained in an identical way to onshore wind profiles,as described in(Sterl et al.,2022).Three adaptations were made,however.First,two types of offshore wind power plants floating and fixed were considered,based on seabed depth.Floating MSRs
185、were those at an average depth of 50meters to 800 metres(beyond which regions were excluded from consideration),while fixed plants were those in shallower MSRs.Floating wind farms have a higher level of capital expenditure(CAPEX).Second,the cost of grid connection was differentiated by the offshore
186、portion and the onshore portion,with offshore transmission infrastructure assumed to cost more per kilometre than onshore infrastructure.Third,the area considered for offshore wind MSRs was limited to the Exclusive Economic Zone(EEZ)of any applicable country.Similarly to solar CSP,to reduce computat
187、ional burden the offshore wind MSRs were grouped into two clusters for each country.15 Based on this analysis,the set of countries with offshore wind potential in Africa was relatively limited.Indeed,among non-landlocked countries in Central Africa,clusters of offshore wind potential were only avail
188、able for Angola.16The figures below provide an example of the VRE potential included in the modelling as future investment options in Angola(the full set of country views can be found in the data appendix accompanying this report).13 For all other parameters(e.g.exclusion criteria,expected losses,et
189、c.)for solar PV and wind clusters,the reader is referred to(Sterl et al.,2022).14 Based on the various assumed exclusion criteria for any site to qualify as commercially exploitable.These criteria included a minimum threshold for resource quality of 6 metres per second(m/s)annual average wind speed
190、at 100 metres in height.15 In clustering offshore wind MSRs,individual clusters might include both areas suitable for fixed turbines and areas suitable for floating turbines.The“majority rule”was adopted to allocate the structure type(fixed/floating)to a cluster and thus the costs.16 No MSRs were id
191、entified for the rest of the countries after assuming the various exclusion criteria.These included a minimum threshold for resource quality of 7.5 m/s annual average wind speed at 100 metres in height for any site to qualify as commercially exploitable.29CENTRAL AFRICATable 2 Total solar and wind c
192、apacity potential included in CAPP countries in the SPLAT-Africa model(MW)MWSOLAR PVSOLAR CSPWIND OFFSHOREWIND ONSHORETOTALAngola206 252111 75812 56261 435392 006Burundi3 327833 410Cameroon76 37641 25721 188138 822Central African Republic102 74855 197752158 698Chad208 678112 798186 751508 227Republi
193、c of the Congo55 7862355 810DR Congo385 43941 8681 840429 146Equatorial Guinea4 2024 202Gabon43 05843 058Rwanda4 0544 054Total1 089 921362 96112 562271 9901 737 433Source:(IRENA,2024).Figure 9 Country-level detail on technical VRE potential(MW)in the SPLAT-Africa model:Example of Angola Cluster numb
194、er(total MW)12345678910Major citiesTransmission linesDistribution linesLakesRiversRoadCountry boundariesSolar PV Model SupplyRegions(MSR)*ANGOLA(53,936 MW)(6,788 MW)(57,202 MW)(37,826 MW)(50,499 MW)(0 MW)(0 MW)(0 MW)(0 MW)(0 MW)Datasets sourcesMajor cities:Natural Earth,available at https:/ Wild Lif
195、e,available at https:/www.worldwildlife.org/pages/global-lakes-and-wetlands-databaseRivers:Natural Earth,available at https:/ Schipper,A.M.(2018):Global patterns of current and future road infrastructure.Environmental Research Letters,13-064006.Data is available at www.globio.infoTransmission and di
196、stribution lines:Arderne,C.,Zorn,C.,Nicolas,C.,Koks,E.E.,2020.Predictive mapping of the global power system using open data.Sci Data 7,19.https:/doi.org/10.1038/s41597-019-0347-4Country boundaries:Global Administrative Unit Layers(GAUL)ANGOLASolar PV MSRsCluster number(total MW)1(53 936 MW)2(6 788 M
197、W)3(57 202 MW)4(37 826 MW)5(50 499 MW)6(0 MW)7(0 MW)8(0 MW)9(0 MW)10(0 MW)Major citiesTransmission linesDistribution linesLakesRiversRoadsCountry boundaries0 86 172 258 km30PLANNING AND PROSPECTS FOR RENEWABLE POWERFigure 9 ContinuedCluster number(total MW)12345678910Major citiesTransmission linesDi
198、stribution linesLakesRiversRoadCountry boundariesOnshore wind ModelSupply Regions(MSR)*ANGOLA(13,859 MW)(1,232 MW)(8,332 MW)(1,081 MW)(36,932 MW)(0 MW)(0 MW)(0 MW)(0 MW)(0 MW)ANGOLAOnshore wind MSRsCluster number(total MW)1(13 859 MW)2(1 232 MW)3(8 332 MW)4(1 081 MW)5(36 932 MW)6(0 MW)7(0 MW)8(0 MW)
199、9(0 MW)10(0 MW)Major citiesTransmission linesDistribution linesLakesRiversRoadsCountry boundaries0 86 172 258 kmClusternumber(totalMW)12PortsMajorcitiesTransmissionlinesDistributionlinesLakesRiversRoadCountryboundariesDatasetssourcesMajorcities:NaturalEarth,availableathttps:/ wind MSRsCluster number
200、(total MW)1(5 052 MW)2(7 509 MW)PortsMajor citiesTransmission linesDistribution linesLakesRiversRoadsCountry boundaries0 90 180 270 km31CENTRAL AFRICA3 THERE IS A MAJOR AMBITION TO DEVELOP CROSS-BORDER TRADE BEYOND ITS CURRENT LIMITED SCOPE The information used here regarding existing cross-border t
201、ransmission infrastructure and planned projects is based on official national and regional planning documents collected and reviewed by CAPP members as part of the IRENA and CMP capacity building programmes.The capacities and first years of possible construction of all regional interconnectors for C
202、APP are summarised in Table 4,with further details and cost parameters for all continental options in the data appendix accompanying this report.As of 2023,existing cross-border transmission capacity within the CAPP region was mainly limited to infrastructure between DR Congo,Rwanda and Burundi(arou
203、nd 515MW of the total 601MW of intra-CAPP capacity).At that time,however,greater capacity had been installed between the CAPP countries and bordering countries and regions.Just over 1GW of cross-border infrastructure existed connecting DR Congo,Rwanda and Angola to the Eastern African Power Pool(EAP
204、P)and Southern African Power Pool(SAPP)countries.Committed and candidate projects reflect a strong ambition to change this picture,however,by developing more comprehensive cross-border transmission infrastructure within CAPP,along with more export capacity to other regions.As the table below shows,c
205、ommitted projects would represent a three-fold increase in the current transmission capacity to other regions,and a seven-fold increase in intra-CAPP transmission capacity(all planned before 2030).If all candidate projects were also developed,this would represent a more than ten-fold increase in cur
206、rent transmission capacity to other regions,and a twenty-fold increase in intra-CAPP transmission capacity.Figure 9 ContinuedDisclaimer:These maps are provided for illustration purposes only.Boundaries and names shown on these maps do not imply the expression of any opinion on the part of IRENA conc
207、erning the status of any region,country,territory,city or area or of its authorities,or concerning the delimitation of frontiers or boundaries.DatasetssourcesMajorcities:NaturalEarth,availableathttps:/ CSP MSRsCluster number(total MW)1(72 080 MW)2(34 356 MW)Major citiesTransmission linesDistribution
208、 linesLakesRiversRoadsCountry boundaries0 90 180 270 km32PLANNING AND PROSPECTS FOR RENEWABLE POWERTable 3 Existing,committed and candidate cross-border transmission infrastructure(MW)INTRA-CAPPEXTRA-CAPPExisting6011 022Committed3 6462 114Candidate7 7938 778Given the importance of this infrastructur
209、e development in the region,this study explores two possible cross-border trade conditions:“Reference”and“Full Continental”.It also explores the impact of interconnector project delays.Under Reference scenario conditions,trade between countries is limited by existing infrastructure and planned cross
210、-border transmission projects.Any hypothetical projects that are not currently identified are only included under Full Continental scenario conditions.In interconnector delay scenarios,the delays implemented are as follows:a four-year delay for any project planned for 2024;a three-year delay for any
211、 project planned for between 2025 and 2030;and a two-year delay for any project planned between 2030 and 2040.This assumes a gradual improvement in mitigating delays as experience in the construction of cross-border transmission infrastructure improves.This was deemed more reasonable than a standard
212、 delay over the course of the modelling period.Importantly,cross-border interconnections with all other regions have also been considered in the modelling exercise.Although the focus of this report and analysis is on the Central African region,the SPLAT-Africa model allows all countries to be includ
213、ed in the modelling simultaneously.It is especially important to have a more realistic picture of any imports or exports that may be taking place from and to the Central African regions neighbours,given its central location on the continent,both geographically and in terms of renewable energy resour
214、ces.Table 4 Site-specific cross-border transmission infrastructure summaryCOUNTRY 1COUNTRY 2DESCRIPTIONSTATUSINSTALLATION/FIRST YEARTOTAL CAPACITY(MW)AngolaNamibiaExisting Angola-Namibia(LT 132 kV Ondjiva(Angola)Efunja(Namibia)Existing201210AngolaDR CongoCommitted Angola-DR Congo(220 kV Maquela do Z
215、ombo-Kuilo)Committed2026318AngolaRepublic of the CongoCommitted Angola-Republic of the Congo-DR Congo 400 kV(Inga-Cabinda-Pointe Noire)Committed20281 514AngolaNamibiaCommitted Angola-Namibia(LT 400 kV Cahama(Angola)-Kunene(Namibia)Committed20271 514AngolaDR CongoCandidate Inga NZeto Phase 1 DR Congo
216、-Angola(Matadi-Nzeto)400 ACCandidate20301 663BurundiRwandaBurundi-Rwanda 110 kVExisting198712BurundiRwandaCommitted Burundi-Rwanda(Gitega-Gisagara)220 kVCommitted2025100BurundiRwandaCandidate Burundi-Rwanda(Gitega-Kigoma)220 kVCandidate202318433CENTRAL AFRICACOUNTRY 1COUNTRY 2DESCRIPTIONSTATUSINSTAL
217、LATION/FIRST YEARTOTAL CAPACITY(MW)BurundiDR CongoCandidate DR Congo-Burundi 400 ACCandidate2022748BurundiRwandaCandidate Rwanda-Burundi(Ruzuzi-Bujumbura)220 ACCandidate2029610CameroonChadCommitted Cameroon-Chad 220 kV(Maroua-Ndjamena)Committed2025200CameroonCentral African RepublicCandidate Cameroo
218、n-Central African Republic 220 kV(Dimoli)Candidate2035185CameroonChadCandidate Cameroon-Chad 400 kVCandidate20301 900CameroonGabonCandidate Cameroon-Gabon(Memveele-Bata-Ntoum)Candidate2030210CameroonNigeriaCandidate WAPP(Nigeria)-CAPP(Inga-Cameroun)Candidate2033814Central African RepublicDR CongoBan
219、gui-ZongoExisting20215Republic of the CongoCentral African RepublicCandidate Congo-Central African Republic 220 kV(Dimoli)Candidate2027185Republic of the CongoGabonCandidate Congo-Gabon 400 kV(Grand Poubara)Candidate2024400DR CongoBurundiDR Congo-Burundi 70 kV Existing201065DR CongoRepublic of the C
220、ongoDR Congo-Republic of the Congo 200 kV(Inga-Brazzaville)Existing201080DR CongoRwandaDRC-Rwanda(Goma-Rubavu)220 kVExisting2023400DR CongoRwandaDRC-Rwanda 30 kV Existing201039DR CongoUgandaDRC-Uganda(Beni-Nkenda)Existing202326DR CongoZambiaDRC-Zambia(3 x Lumumbashi-Luano 220 AC)Existing2010230DR Co
221、ngoCentral African RepublicMobayi-MobayeExisting20031DR CongoAngolaCommitted DRC-Angola-Republic of the Congo 400 kV(Inga-Cabinda-Pointe Noire)400 kVCommitted20261 514DR CongoNigeriaCandidate DR Congo-South Africa Grand Inga HVDC Phase 1(Inga-Calabar)600 HVDCCandidate20301 030DR CongoSouth AfricaCan
222、didate DR Congo-South Africa Grand Inga HVDC Phase 1(Inga-Merensky)600 HVDCCandidate20301 130Table 4 Continued34PLANNING AND PROSPECTS FOR RENEWABLE POWERCOUNTRY 1COUNTRY 2DESCRIPTIONSTATUSINSTALLATION/FIRST YEARTOTAL CAPACITY(MW)DR CongoEgyptCandidate DR Congo-South Africa Grand Inga HVDC Phase 1(I
223、nga-Region Caire)600 HVDCCandidate20302 514DR CongoZambiaCandidate DR Congo-Zambia(Matadi/Kolwezi-Lumwana/Solwezi)500 DCCandidate20312 000Equatorial GuineaCameroonCandidate Cameroon-Equatorial Guinea(Memveele-Bata-Ntoum)Candidate2030210GabonEquatorial GuineaCandidate Gabon-Equatorial Guinea(Memveele
224、-Bata-Ntoum)Candidate2030210GabonEquatorial GuineaCandidate Gabon-Equatorial Guinea(Mongomo-Oyem)Candidate2029300NamibiaAngolaCommitted ANNA Namibia-Angola(Omatando-Xangongo/Baynes-Cahama)400 AC/400 ACCommitted2025600RwandaUgandaExisting Rwanda-Uganda(Birembo-Mirama)220 kVExisting2019300RwandaUnited
225、 Republic of TanzaniaRwanda-Tanzania(Rilima-Rusumo)220 kVExisting202343RwandaUgandaRwanda-Uganda(Shango-Mirama)220 kVExisting201950RwandaDR CongoCandidate DR Congo-Rwanda(Kamanyola-Rusizi)220 kVCandidate2029600RwandaDR CongoCandidate DR Congo-Rwanda(Poids-Bukari)220 ACCandidate2030388United Republic
226、 of TanzaniaRwandaCandidate Rwanda-Tanzania(Gasogi-Rusumo)220 ACCandidate2022181United Republic of TanzaniaBurundiCandidate Tanzania-Burundi(Kigoma-Musimba)400 ACCandidate20221 109Notes:Official national documents reviewed and updated as part of the IRENA-CAPP Regional Modelling Analysis&Planning Su
227、pport Programme and CMP programme.Capacity values are meant to reflect total installed capacity and therefore may not reflect differences in effective capacity due to operational issues.LT=low tension,kV=kilovolt,AC=alternating current,HVDC=high voltage direct current,DC=direct current.Table 4 Conti
228、nued35CENTRAL AFRICA3.1 GENERAL DEFINITION OF SCENARIOSThe table below shows the main scenarios developed for this report.These were based on the work and feedback from all the participants in the IRENA-CAPP Regional Africa Modelling Analysis&Planning Support Programme.Six scenarios were explored un
229、der the two conditions regarding cross-border interconnection outlined above “Reference”and“Full Continental”giving a total of 12 scenarios.The basic Reference scenario reflects power system development in the absence of any major constraints,based on the detailed capacity statistics and assumptions
230、 outlined previously in this chapter.In this scenario,cost-competitiveness acts as the key driver for the deployment of technologies.In terms of technology costs,the scenario reflects reductions in renewable energy costs consistent with global observations and trends.Alternate scenarios are based on
231、 key priority areas identified by regional stakeholders for exploration,as discussed in previous sections of this chapter.These include more ambitious demand projections,major project delays,hydropower availability and interconnector development.17 For more detail on any demand related assumptions s
232、ee point 1 above in this chapter on electricity demand.18 For more detail on any hydropower related assumptions see point 2 above in this chapter on electricity generation options.19 For more detail,see point 3 above in this chapter on cross-border trade.Table 5 Capacity expansion scenarios NAME1Ref
233、erenceReference demand projections from the modelling performed in the CMP programme.17 All committed and planned projects considered.2RefHydroDelayReference scenario with all candidate hydro projects larger than 1 GW delayed by 5 years.183RefHydroDryReference scenario with all hydro production subj
234、ect to dry year assumptions.4RefInterconDelayReference scenario with all candidate interconnectors delayed.195RefHighDemReference scenario with high demand projections from the modelling performed in the CMP programme.6RefDelayDryHighReference scenario with a combination of all constraints imposed i
235、n the previous four alternate scenarios(numbers 2 to 5).7FullContinentalReference scenario with all physically possible interconnectors allowed,as of 2030.812All other reference scenarios above(numbers 2 to 6)with“Full Continental”interconnector conditions.36PLANNING AND PROSPECTS FOR RENEWABLE POWE
236、R4.1 CAPACITY AND GENERATIONFigure 10 and Figure 11 below show the high-level capacity results obtained across all scenarios in the modelling,as well as the difference between the Reference and alternative scenarios in those results.General insights from these results are discussed below,with more s
237、pecific and country-level insights related to hydropower,solar,wind,batteries,fossil fuels and cross-border trade in the sections that follow.In all scenarios with reference demand projections,renewable sources hydropower and solar PV,plus(in certain countries)onshore wind meet the vast majority of
238、projected demand until 2040 at the regional level.This is also the case for scenarios with larger exports to other regions(the FullContinental scenarios).Only in the scenarios where demand becomes much higher,around two times the reference demand,do we see new fossil fuel infrastructure being built
239、in significant capacities in the results.Overall,even though the type of capacity mix is broadly similar across scenarios,it is clear that the total capacity required to be built in the region is quite sensitive to different future conditions.All scenarios need to at least double todays regional cap
240、acity by 2040 to meet projected demand.In the scenarios with the lowest overall capacity needs(Reference scenarios with interconnector or hydropower delays),total capacity grows from around 12GW currently to around 30GW in 2040.In all but one scenario where all physically possible interconnections a
241、re allowed in the model after 2030(the Full Continental scenarios),total capacity in the region grows to over 40GW.In the scenario with the highest overall capacity in the region the Full Continental scenario with high demand and no challenging conditions(FullConHighDem)nearly 65GW of capacity is bu
242、ilt by 2040.This is more than two times the capacity required in the basic Reference scenario,and would imply a 500%increase from todays capacity in the region.4MODELLING RESULTS37CENTRAL AFRICAFigure 10 Capacity results in all scenarios Capacity(MW)70 00060 00050 00040 00030 00020 00010 0000Referen
243、ceRefHydroDryRefHydroDelayRefInterconDelayRefHighDemRefDelayDryHigh201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040Capacity(MW)70 000 60 00050 00040 00030 00020 00010 0000FullContinentalFullConHydroDryFul
244、lConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHigh201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040WindSolar PV:utilityBattery storageLarge hydro RORBiomassLarge hydro damNatural gasHFOGeo
245、thermalDieselCoal Peak demand38PLANNING AND PROSPECTS FOR RENEWABLE POWERFigure 11 Difference in capacity results relative to Reference and Full Continental scenarios WindSolar PV:utilityBattery storageLarge hydro RORBiomassLarge hydro damNatural gasHFODieselCoalCapacity(MW)25 000 20 00015 00010 000
246、5 0000-5 000-10 000-15 000ReferenceRefHydroDryRefHydroDelayRefInterconDelayRefHighDemRefDelayDryHigh201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040Capacity(MW)25 00020 00015 00010 0005 0000-5 000-10 000-
247、15 000FullContinentalFullConHydroDryFullConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHigh20192023202720312035204020192023202720312035204020192023202720312035204020192023202720312035204020192023202720312035204020192023202720312035204039CENTRAL AFRICAFigure 12 and Figure 13 show produ
248、ction results across all scenarios,as well as the difference between the Reference and alternative scenarios in those results.As shown in Figure 12 below,in all scenarios,the CAPP region exports to other regions,making use of its low-cost renewable resources and hydropower in particular.The amount t
249、he region exports by 2040 is largely the same across all reference scenarios that do not allow for generic interconnection options.This is the case even in the scenario with the most challenging export conditions,which include delays to interconnector projects and large hydropower projects,dry year
250、conditions,and high demand across the continent.In scenarios in which the construction of new interconnector capacity beyond the current project pipeline is allowed,however,we see nearly double the amount of exports to other regions.By 2040,the amount exported rises from around 60gigawatt hours(GWh)
251、in Reference scenarios to around 140GWh,except in the scenario with the most challenging export conditions(FullConDelayDryHigh).Before 2040,the other major difference across scenarios is due to delays in large hydropower projects and interconnectors,which both contribute to reduced exports in the 20
252、30s,relative to scenarios without delays.40PLANNING AND PROSPECTS FOR RENEWABLE POWERFigure 12 Production results in all scenarios GWh250 000 200 000150 000100 00050 0000-50 000-100 000-150 000ReferenceRefHydroDryRefHydroDelayRefInterconDelayRefHighDemRefDelayDryHigh201920232027203120352040201920232
253、027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040WindSolar PV:utilityBattery storageLarge hydro RORBiomassLarge hydro damNatural gasHFOGeothermalElectricity net importsDieselCoalSent out demandGWh250 000 200 000150 000100 00050 0000-50 00
254、0-100 000-150 000FullContinentalFullConHydroDryFullConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHigh20192023202720312035204020192023202720312035204020192023202720312035204020192023202720312035204020192023202720312035204020192023202720312035204041CENTRAL AFRICAFigure 13 Difference in
255、 production results relative to Reference and Full Continental scenarios GWhGWh200 000150 000100 00050 0000-50 000-100 000-150 000200 000150 000100 00050 0000-50 000-100 000-150 000ReferenceRefHydroDryRefHydroDelayRefInterconDelayRefHighDemRefDelayDryHigh201920232027203120352040201920232027203120352
256、040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040FullContinentalFullConHydroDryFullConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHigh20192023202720312035204020192023202720312035204020192023202720312035204020192023202720312035204020192
257、0232027203120352040201920232027203120352040WindSolar PV:utilityLarge hydro RORBiomassLarge hydro damNatural gasHFOGeothermalElectricity net importsDieselCoal42PLANNING AND PROSPECTS FOR RENEWABLE POWERIn terms of production share,Figure 14 shows that the share of fossil fuels in electricity producti
258、on falls from todays already low level to below 5%of production by 2040 in the majority of scenarios.In all reference demand scenarios,the share of hydropower in production grows from its current level,supplying at least 80%of the electricity in the region over the modelling horizon.This is the case
259、 even in scenarios with delays to large hydropower and dry year conditions.The share of solar and wind goes from nearly zero to at least 7%of regional production by 2040 in all scenarios.In scenarios with high demand,solar and wind reach 13%-20%of production by 2040,with the highest values in the sc
260、enarios with challenging hydropower conditions(delays and dry years)and strong exports to other regions.43CENTRAL AFRICAFigure 14 Production share across scenarios%GWh%GWhReferenceFullContinentalRefHydroDryFullConHydroDryRefHydroDelayFullConHydroDelayRefInterconDelayFullConInterconDelayRefHighDemFul
261、lConHighDemRefDelayDryHighFullConDelayDryHigh201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203
262、120352040201920232027203120352040 VREOther RELarge hydroFossil 10090807060504030201001009080706050403020100Note:RE=renewable energy.44PLANNING AND PROSPECTS FOR RENEWABLE POWERFigure 15 and Figure 16 display the country-level results for capacity and generation mix in 2040.In many countries,the resu
263、lts show a strong presence of both hydropower and solar PV.Across all scenarios,these two sources making up more than 75%of the capacity mix for Angola,Burundi,the Central African Republic,DR Congo and Rwanda.Onshore wind appears across all but one scenario where there is good potential in Cameroon
264、and Chad,particularly in high-demand cases in Chad.While natural gas and diesel capacities still make up between 20%and 50%of the mix in most scenarios for Chad,Republic of the Congo,Equatorial Guinea and Gabon,they constitute a much smaller share of production in those countries by 2040,as they are
265、 used more to meet model reserve margin requirements(along with more battery capacity)in those countries.This is especially the case in the Full Continental interconnection scenarios with a greater amount of cross-border trade.More detail on the country-specific trade results is discussed in Section
266、 4.3 below,Cross-border electricity trade.45CENTRAL AFRICAFigure 15 Country-level breakdown of the power capacity mix by 2040,by scenario%CapacityAngolaBurundiCameroonCentral African RepublicChadRepublic of the CongoDR CongoEquatorial GuineaGabonRwandaSo Tom and PrncipeReferenceRefHydroDry RefHydroD
267、elay RefInterconDelay RefHighDem RefDelayDryHighReferenceRefHydroDry RefHydroDelay RefInterconDelay RefHighDem RefDelayDryHighReferenceRefHydroDry RefHydroDelay RefInterconDelay RefHighDem RefDelayDryHighReferenceRefHydroDry RefHydroDelay RefInterconDelay RefHighDem RefDelayDryHighReferenceRefHydroD
268、ry RefHydroDelay RefInterconDelay RefHighDem RefDelayDryHighReferenceRefHydroDry RefHydroDelay RefInterconDelay RefHighDem RefDelayDryHighReferenceRefHydroDry RefHydroDelay RefInterconDelay RefHighDem RefDelayDryHighReferenceRefHydroDry RefHydroDelay RefInterconDelay RefHighDem RefDelayDryHighRefere
269、nceRefHydroDry RefHydroDelay RefInterconDelay RefHighDem RefDelayDryHighReferenceRefHydroDry RefHydroDelay RefInterconDelay RefHighDem RefDelayDryHighReferenceRefHydroDry RefHydroDelay RefInterconDelay RefHighDem RefDelayDryHigh1009080706050403020100WindSolar PV:utilityBattery storageLarge hydro ROR
270、BiomassLarge hydro damNatural gasHFOGeothermalDieselCoal46PLANNING AND PROSPECTS FOR RENEWABLE POWERFigure 15 Continued%CapacityAngolaBurundiCameroonCentral African RepublicChadRepublic of the CongoDR CongoEquatorial GuineaGabonRwandaSo Tom and PrncipeFullContinentalFullConHydroDryFullConHydroDelayF
271、ullConInterconDelayFullConHighDemFullConDelayDryHighFullContinentalFullConHydroDryFullConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHighFullContinentalFullConHydroDryFullConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHighFullContinentalFullConHydroDryFullConHydroDelayF
272、ullConInterconDelayFullConHighDemFullConDelayDryHighFullContinentalFullConHydroDryFullConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHighFullContinentalFullConHydroDryFullConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHighFullContinentalFullConHydroDryFullConHydroDelayF
273、ullConInterconDelayFullConHighDemFullConDelayDryHighFullContinentalFullConHydroDryFullConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHighFullContinentalFullConHydroDryFullConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHighFullContinentalFullConHydroDryFullConHydroDelayF
274、ullConInterconDelayFullConHighDemFullConDelayDryHighFullContinentalFullConHydroDryFullConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHigh1009080706050403020100WindSolar PV:utilityBattery storageLarge hydro RORBiomassLarge hydro damNatural gasHFODieselCoal47CENTRAL AFRICAFigure 16 Coun
275、try-level breakdown of the power generation mix by 2040,by scenario%GWhAngolaBurundiCameroonCentral African RepublicChadRepublic of the CongoDR CongoEquatorial GuineaGabonRwandaSo Tom and PrncipeReferenceRefHydroDry RefHydroDelay RefInterconDelay RefHighDem RefDelayDryHighReferenceRefHydroDry RefHyd
276、roDelay RefInterconDelay RefHighDem RefDelayDryHighReferenceRefHydroDry RefHydroDelay RefInterconDelay RefHighDem RefDelayDryHighReferenceRefHydroDry RefHydroDelay RefInterconDelay RefHighDem RefDelayDryHighReferenceRefHydroDry RefHydroDelay RefInterconDelay RefHighDem RefDelayDryHighReferenceRefHyd
277、roDry RefHydroDelay RefInterconDelay RefHighDem RefDelayDryHighReferenceRefHydroDry RefHydroDelay RefInterconDelay RefHighDem RefDelayDryHighReferenceRefHydroDry RefHydroDelay RefInterconDelay RefHighDem RefDelayDryHighReferenceRefHydroDry RefHydroDelay RefInterconDelay RefHighDem RefDelayDryHighRef
278、erenceRefHydroDry RefHydroDelay RefInterconDelay RefHighDem RefDelayDryHighReferenceRefHydroDry RefHydroDelay RefInterconDelay RefHighDem RefDelayDryHigh100806040200-20-40-60WindSolar PV:utilityLarge hydro RORBiomassLarge hydro damNatural gasHFOGeothermalElectricity net importsDieselCoal48PLANNING A
279、ND PROSPECTS FOR RENEWABLE POWERFigure 16 Continued%GWhAngolaBurundiCameroonCentral African RepublicChadRepublic of the CongoDR CongoEquatorial GuineaGabonRwandaSo Tom and PrncipeFullContinentalFullConHydroDryFullConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHighFullContinentalFullCo
280、nHydroDryFullConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHighFullContinentalFullConHydroDryFullConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHighFullContinentalFullConHydroDryFullConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHighFullContinentalFullCo
281、nHydroDryFullConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHighFullContinentalFullConHydroDryFullConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHighFullContinentalFullConHydroDryFullConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHighFullContinentalFullCo
282、nHydroDryFullConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHighFullContinentalFullConHydroDryFullConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHighFullContinentalFullConHydroDryFullConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHighFullContinentalFullCo
283、nHydroDryFullConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHigh100806040200-20-40-60WindSolar PV:utilityLarge hydro RORBiomassLarge hydro damNatural gasHFOGeothermalElectricity net importsDieselCoal49CENTRAL AFRICAHydropowerHydropower accounts for over 80%of production across all ref
284、erence demand scenarios and over 65%of production in high demand scenarios.It is therefore important to understand the potential development of this resource in the CAPP region and its impacts on the regional system.This section discusses key insights regarding hydropower evident in this reports res
285、ults.Figure 17 and Figure 18 present the hydropower capacity results across all scenarios,as well as the differences between scenarios relative to the Reference and Full Continental scenarios.Even in the scenario with the lowest hydropower buildout(the Reference scenario with hydro delays),current h
286、ydropower capacity in the region more than doubles,growing from around 8GW to just over 20GW by 2040.There is no major difference in the range of hydropower capacity built by 2040 in all scenarios with reference interconnector conditions i.e.only interconnector projects in the current pipeline.Altho
287、ugh capacity is lower in the mid-2030s in scenarios with delays to hydropower plants and interconnectors,the model still gives a result of at least 20GW in those conditions.This implies that this capacity is worthwhile across a range of future conditions,if the interconnectors that are in the pipeli
288、ne can be built.Dry year conditions and project delays to interconnectors also have an effect on the amount and timing of hydropower built across the model horizon.This is the case in both the Reference and Full Continental interconnection conditions.In terms of lower final hydropower capacity value
289、s in 2040,only hydropower project delay scenarios reduce capacity substantially in comparison with the Reference scenario.In scenarios with those conditions,other regions build their own additional capacity to fill the gap left by fewer hydropower exports from CAPP in the 2030s.Between 7GW and 8GW l
290、ess hydropower is developed in CAPP by 2040 as a result.The shortfall is mainly from the Grand Inga project,for which further details are provided below.50PLANNING AND PROSPECTS FOR RENEWABLE POWERFigure 17 Hydropower capacity in all scenarios Capacity(MW)Capacity(MW)35 000 30 00025 00020 00015 0001
291、0 0005 000035 000 30 00025 00020 00015 00010 0005 0000ReferenceRefHydroDryRefHydroDelayRefInterconDelayRefHighDemRefDelayDryHigh2019202320272031203520402019202320272031203520402019202320272031203520402019202320272031203520402019202320272031203520402019202320272031203520402019202320272031203520402019
292、20232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040FullContinentalFullConHydroDryFullConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHighLarge hydro RORLarge hydro dam Peak demand51CENTRAL AFRICAFigure 18 Difference in hy
293、dropower capacity results relative to Reference and Full Continental scenarios Capacity(MW)Capacity(MW)11 0006 0001 000-4 000-9 000-14 00011 0006 0001 000-4 000-9 000-14 000ReferenceRefHydroDryRefHydroDelayRefInterconDelayRefHighDemRefDelayDryHigh20192023202720312035204020192023202720312035204020192
294、0232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040FullContinentalFullConHydroDryFullConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHigh2019202320272031203520402019202320272031203520402019202320272031203520402019202320272031203520402019202320272
295、03120352040201920232027203120352040Large hydro RORLarge hydro dam52PLANNING AND PROSPECTS FOR RENEWABLE POWERThe single largest driver of the regional-level results described above is the development of the Grand Inga hydropower project in DR Congo.As shown in Figure 19,this project is chosen for de
296、velopment in every scenario,while for a view of the impact on results without Grand Inga see Box 4:Grand Inga:Implications on model results.In the scenario with the lowest amount of Grand Inga development the Reference scenario with five-year hydro delays 7.8GW of additional capacity is added betwee
297、n 2035 and 2040.In scenarios with the highest amount of development four scenarios from the Full Continental interconnection conditions all 11GW of the third phase of Inga is built by 2030,while 7.4GW of the fourth phase is built by 2037.This gives a total of over 20GW of Inga capacity.Hydropower pr
298、oduction from this build-out alone is enough to meet the regions total demand beyond 2030 in non-delay scenarios.A substantial driver of hydropower capacity build out,however(and especially Grand Inga buildout)is for export to other regions.This can be seen in the mirrored patterns of hydropower pro
299、duction and net exports in the results in Figure 20,as well as in the much higher capacity in scenario results where the model allows interconnections beyond the current project pipeline.The main destination for these exports is southern and western Africa,as discussed in more detail in Section 4.3,
300、Cross-border electricity trade.The Full Continental scenario with high demand sees the most hydropower capacity development,with capacity quadrupling to over 33GW(10GW more than the Reference scenario).In all scenarios the overall composition of hydropower shifts to ROR hydropower over the time hori
301、zon as more ROR capacity is built,particularly since the expansion phases of Grand Inga are included in the model as ROR.By 2040,in all the scenarios,ROR hydropower accounts for at least 55%of hydropower production,rising to 73%in the Full Continental scenario with dry hydro conditions.It should als
302、o be noted that to some extent,complementarity between production profiles and types of hydropower projects across different countries in the region also drives the construction of plants,as well as cross-border interconnection(see Box 3:SPLAT-Africa dispatch results for more detail).53CENTRAL AFRIC
303、AFigure 19 Grand Inga development across all scenarios Capacity(MW)Capacity(MW)ReferenceFullContinentalRefHydroDryFullConHydroDryRefHydroDelayFullConHydroDelayRefInterconDelayFullConInterconDelayRefHighDemFullConHighDemRefDelayDryHighFullConDelayDryHigh20192023202720312035204020192023202720312035204
304、0201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040Large hydro ROR Inga_1Large hydro dam Inga_2Large hydro dam
305、 Inga_3_phase_ABCLarge hydro dam Inga_4_Phase_D25 00020 00015 00010 0005 000025 00020 00015 00010 0005 000054PLANNING AND PROSPECTS FOR RENEWABLE POWERFigure 20 Hydropower production in all scenarios GWhGWh250 000 200 000150 000100 00050 0000-50 000-100 000-150 000250 000 200 000150 000100 00050 000
306、0-50 000-100 000-150 000ReferenceFullContinentalRefHydroDryFullConHydroDryRefHydroDelayFullConHydroDelayRefInterconDelayFullConInterconDelayRefHighDemFullConHighDemRefDelayDryHighFullConDelayDryHigh201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920
307、232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040Large hydro RORLarge hydro damElectricity net importsSent out demand55CENTRAL AFRICAAs shown in Figure 21 below,co
308、untry-wise,DR Congo is driving regional development and scenario differences,due to Grand Inga.The development of hydropower is also strong in Angola,Cameroon,Gabon and Rwanda,but differs only slightly across scenarios for these countries.The Grand Eweng dam in Cameroon is the only other large plant
309、 where development differs across scenarios to a material degree(between zero and 500MW in dry versus reference conditions,suggesting this project is sensitive to future climate conditions).56PLANNING AND PROSPECTS FOR RENEWABLE POWERFigure 21 Results by country for hydropower capacity in scenarios
310、with the lowest(RefHydroDelay),top,and the highest(FullConHighDem),bottom(DR Congo separated)Capacity(MW)AngolaBurundiCameroonCentral African RepublicChadRepublic of the CongoEquatorial GuineaGabonRwandaSo Tom and Prncipe2019202320272031203520402019202320272031203520402019202320272031203520402019202
311、320272031203520402019202320272031203520402019202320272031203520402019202320272031203520402019202320272031203520402019202320272031203520402019202320272031203520407 0006 0005 0004 0003 0002 0001 0000Large hydro RORLarge hydro damPeak demand57CENTRAL AFRICAFigure 21 ContinuedCapacity(MW)AngolaBurundiCa
312、meroonCentral African RepublicChadRepublic of the CongoEquatorial GuineaGabonRwandaSo Tom and Prncipe2019202320272031203520402019202320272031203520402019202320272031203520402019202320272031203520402019202320272031203520402019202320272031203520402019202320272031203520402019202320272031203520402019202
313、320272031203520402019202320272031203520407 0006 0005 0004 0003 0002 0001 0000Large hydro RORLarge hydro damPeak demand58PLANNING AND PROSPECTS FOR RENEWABLE POWERFigure 21 Continued:Democratic Republic of Congo results for hydropower capacity in scenarios with the lowest(RefHydroDelay),left,and the
314、highest(FullConHighDem),right.Capacity(MW)Capacity(MW)DR CongoDR Congo20192023202720312035204020192023202720312035204025 00020 00015 00010 0005 000025 00020 00015 00010 0005 0000Large hydro RORLarge hydro dam Peak demand59CENTRAL AFRICASolar,wind and batteriesIn the modelling results,solar power mak
315、es up the next largest source of electricity production in the region after hydropower.Wind also plays an important role in countries such as Cameroon and Chad.This section discusses key insights in the results regarding solar and wind,as well as their complementary technology:batteries.As mentioned
316、 previously,the share of solar and wind goes from virtually zero to at least 7%of production by 2040 in all scenarios.In scenarios with high demand,solar and wind reach nearly 15%of production by 2040,while reaching around 20%of production in scenarios with challenging hydropower conditions(i.e.dela
317、ys and dry years).Figure 22 and Figure 23 present the capacity of these sources across scenarios,as well as differences in alternate scenarios in comparison to the Reference and Full Continental scenarios.In the model results,the amount of solar PV and wind built varies widely between scenarios.For
318、solar,for example,by 2040,we see a minimum of nearly 5GW in the Reference scenario with interconnector delays,while there is a maximum of nearly 19GW in the Full Continental scenario with high demand,project delays and dry year conditions.For wind,we see a minimum of just over 0.5GW in the Reference
319、 scenario and a maximum of just over 3GW in the Full Continental scenarios with high demand.Interestingly,batteries appear more strongly in the mid-2020s and early 2030s in scenarios with the more constrained Reference interconnection conditions.This implies that in scenarios where more possible int
320、erconnections are available,the flexibility required in the regional CAPP system is met by imports and/or exports in those years,rather than batteries.20 Both interconnector delay scenarios have the highest amount of battery capacity installed in the early 2030s,at around 400MW.By 2040,however,batte
321、ry capacity difference under the various interconnector scenario conditions is not as strong,as battery capacity is built across all scenarios to match the strong VRE capacity additions in late model years.20 For more detail on flexibility in the model dispatch results,see Box 3,SPLAT-Africa dispatc
322、h results.60PLANNING AND PROSPECTS FOR RENEWABLE POWERFigure 22 Solar PV,onshore wind and battery capacity across all scenarios Capacity(MW)25 000 20 00015 00010 0005 0000ReferenceRefHydroDryRefHydroDelayRefInterconDelayRefHighDemRefDelayDryHigh2019202320272031203520402019202320272031203520402019202
323、32027203120352040201920232027203120352040201920232027203120352040201920232027203120352040Capacity(MW)25 000 20 00015 00010 0005 0000201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040FullContinentalFullConHy
324、droDryFullConHydroDelayFullConInterconDelayFullConHighDemFullConDelayDryHighWindSolar PV:utilityBattery storage Peak demandThe largest driver of differences in scenarios for these technologies is higher demand than expected in the reference projections.In high demand cases,between 18GW and 24GW of c
325、ombined solar,wind and battery capacity are built,showing that these technologies are typically being chosen by the model as complements to low-cost hydropower options,or as those options run out in the model horizon.Dry year conditions also have a modest impact on the deployment of these three tech
326、nologies,as more capacity is built in the mid-2030s to make up for lower hydropower production.61CENTRAL AFRICAFigure 23 Difference in solar PV,onshore wind and battery capacity results relative to Reference and Full Continental scenarios Capacity(MW)Capacity(MW)15 00012 0009 0006 0003 0000-3 00015
327、00012 0009 0006 0003 0000-3 000ReferenceFullContinentalRefHydroDryFullConHydroDryRefHydroDelayFullConHydroDelayRefInterconDelayFullConInterconDelayRefHighDemFullConHighDemRefDelayDryHighFullConDelayDryHigh20192023202720312035204020192023202720312035204020192023202720312035204020192023202720312035204
328、0201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040201920232027203120352040WindSolar PV:utilityBattery storage62PLANNING AND PROSPECTS FOR RENEWABLE POWERCountry-wise,as shown in Fig
329、ure 24 below,Cameroon and Angola have the two largest amounts of solar,wind and battery in most scenarios.With the exception of DR Congo,solar plays a significant role in all other countries in the Reference scenarios.In higher-demand scenarios,however,all countries across the board make significant
330、 use of these technologies.In Full Continental high demand scenarios,even DR Congo builds over 4GW of solar PV by 2040,to complement their larger exports of hydropower to other regions.While wind power appears in all scenarios in the region-wide results,it should be highlighted that it is concentrat
331、ed in most scenarios in Cameroon and Chad,the two countries with the best wind resources.21 21 For more detail on the geographical locations of VRE options chosen by the model,see Box 2,Geographic location of potential VRE projects:Example of IRENA Model Supply Regions in Angola.63CENTRAL AFRICAFigu
332、re 24 Results by country for the lowest solar PV,onshore wind and battery capacity(RefInterconDelay),top,and the highest(FullConHighDem),bottom Capacity(MW)AngolaBurundiCameroonCentral African RepublicChadRepublic of the CongoDR CongoEquatorial GuineaGabonRwandaSo Tom and Prncipe20192023202720312035
333、20402019202320272031203520402019202320272031203520402019202320272031203520402019202320272031203520402019202320272031203520402019202320272031203520402019202320272031203520402019202320272031203520402019202320272031203520402019202320272031203520406 0005 0004 0003 0002 0001 0000WindSolar PV:utilityBattery storage Peak demand64PLANNING AND PROSPECTS FOR RENEWABLE POWERFigure 24 ContinuedCapacity(MW)Ang
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