111sap carbon refit

7/29/2019 111sap Carbon Refit

1/18

Carbon REFITCase Study for the Southern AfricanPower Pool Region

Martin Burian and Christof Arens

Corresponding Author:Martin BurianTel. ++49 40 6030 6805

e-mail: [email protected]

Wuppertal and Hamburg, October 2012

Carbon

MarketCase

St

udy


2/18

I

Table of Contents

ABBREVIATIONS AND ACRONYMS II

1 INTRODUCTION AND BACKGROUND 1

1.1 Introduction to the Carbon REFIT 1

1.2 Background 1

2 CARBON REFIT DESIGN AND IMPACT 4

2.1 Design Options 4

2.2 Determination of Carbon REFIT 5

2.3 Potential Impacts of Carbon REFIT 5

2.4 Environmental Integrity 7

3 CONCLUSION 9

REFERENCES 10

ANNEX I MODEL CASH FLOW FOR HPP 11

ANNEX II SAPP CAPACITY ADDITIONS 13

ANNEX III FINANCIAL BENCHMARKS FOR ENERGY PROJECTS IN THE SAPP

REGION 15

List of Figures and Tables

Figure 1: Revenue Streams of a Model Hydro Power Plant 6Table 1: Import to Demand Ratio for Selected SAPP Countries 2

Table 2: SAPP Power Utility Members and Host Countries 2Table 3: Summary of the Regional SAPP GEF 3Table 4: Determination of Carbon REFIT 5Table 5: Hydro Power Plant - Financial Evaluation 5

Table 6: Revenue Streams of a Model Hydro Power Plant 6Table 7: Hydro Power Plant Input Parameters 11

Table 8: Hydro Power Plant - Basic Operating Parameter 12

Table 9: Hydro Power Plant - Cash Flow Calculation 12Table 10: Hydro Power Plant - Financial Evaluation 12Table 11: SAPP Capacity Additions 13

Table 12: UNFCCC IRR Benchmarks for Energy Projects 15


3/18

II

A B B R E V I A T I O N S A N D A C R O N Y M S

ACAD African Carbon Asset Development Facility

BM Build MarginBMU German Federal Ministry for the Environment, Nature Conservation

and Nuclear SafetyCDM Clean Development MechanismCDM EB CDM Executive BoardCER Certified Emission ReductionsCO2e Carbon Dioxide and Equivalences measured in Carbon DioxideCOP Conference of the Parties to the UNFCCCCPA CDM Programme of ActivitiesDNA Designated National AuthorityDOE Designated Operational EntityDRC Democratic Republic of CongGEF Grid Emission FactorGHG Greenhouse GasesGW Giga Watt Installed CapacityGWh Giga Watt HourIPP Independent Power ProducerIRR Internal Rate of ReturnkW KilowattLDC Least Developed CountryMW Megawatt Installed Capacity

MWh Megawatt HourNAMA Nationally Appropriate Mitigation ActionNMM New Market MechanismNPV Net Present ValueOM Operational MarginPES Project Electricity SystemPPA Power Purchase AgreementREFIT Renewable Feed in TariffRSA Republic of South AfricaSAPP Southern African Power PoolSAPP CC SAPP Coordination Centre

SADC Southern African Development CommunitySBL Standardized BaselineSSA Sub-Saharan AfricaSSC Small ScaleUNFCCC United Nations Framework Convention on Climate ChangeUSD US Dollars


4/18

1

1 I N T R O D U C T I O N A N D B A C K G R O U N D

1 . 1 I n t r o d u c t i o n t o t h e C a r b o n R E F I T

Many African countries do not offer incentives for the promotion of renewable energy projects

through a Renewable Energy Feed-in Tariff (REFIT). Usually, the revenues of IndependentPower Producers (IPPs) are negotiated through Power Purchasing Agreements (PPAs). In

those countries which introduced a REFIT, such as the Republic of South Africa (RSA), thefeed-in tariffs are subject to political debates and were changed several times. Both options,

PPA and REFIT, may not offer the financial security to develop renewable energy projects witha lifetime of, for example, 30 years. Carbon Finance, even though subject to price changes(i.e. /CERs) is linked to registering a renewable energy project under the UN FrameworkConvention on Climate Change (UNFCCC). Such revenues are per se independent frompolitical changes and the development stages of the national renewable energy framework.

This short study sketches the idea of a Carbon REFIT for Southern Africa, covering the regionof the Southern African Power Pool (SAPP). As such, this REFIT could link nine countries,providing an independent framework for the promotion of renewable energies in the region.

Based on the Grid Emission Factor (GEF) of the region and a price of carbon, this would resultin a financial incentive (in USDc/kWh) payable for each renewable kWh fed into the grid. Thisincentive could be financed by Annex I countries, for example

as supported Nationally Appropriate Mitigation Actions (NAMA) (with or withoutcrediting), or a

sectoral New Market Mechanism (NMM), conceptualized for the electricity sector and

potentially covering all nine countries.

The Carbon REFIT may be designed with or without crediting of emission reductions, whichmay depend on the political preferences of Annex I countries as well as the outcome of furtherUNFCCC negotiations. But the payment may be based on the volume of renewable energy fed

into the grid (i.e. performance oriented).

1 . 2 B a c k g r o u n d

In the Southern African Development Community (SADC) region, many countries depend on

electricity imports, and electricity trade between countries is very common. In five countries,imports account for a particularly substantial share of their electricity demand (Table 1). The

SAPP as a SADC entity manages electricity trades of all SAPP members through the SAPPCoordination Centre (SAPP CC) based in Harare, Zimbabwe.

As a coordination center, the SAPP CC not only arranges regional electricity trades, but also

fulfils regional coordination functions with respect to the planning of capacity additions and thedevelopment of energy regulations / policies. As such, the SAPP CC is an important hub for

the development of a regional grid emission factor. SAPP currently comprises 15 powerutilities as members (Table 2).

These system-interconnections result in serious consequences for CDM project development.Countries with a high share of hydro power generation, such as Zambia or DemocraticRepublic of the Congo (DRC), encounter difficulties in showing that renewable energy projectsconducted on their territory result in CO2 emissions reductions (i.e. even though hydro power

reduces CO2-intensive electricity imports and / or exports may replace CO2-intensive electricitygeneration in other countries). This is due to the Grid Emissions Factor, which is generally

developed at the national level.


5/18

2

Table 1: Import to Demand Ratio for Selected SAPP Countries

Botswana 63.5%

Lesotho 28.5%

Namibia 52.0%

Mozambique 50.0%

Swaziland 59.0%

Source: Data provided by SAPP CC

The GEF determines the amount of Certified Emission Reductions (CERs) that a renewable

energy project can generate from feeding 1 MWh of electricity into the electricity grid. If theGEF amounts to, for example, 1 tCO2/MWh, a CDM project generates one CER per MWh. In

case the GEF is zero, renewable energy CDM projects cannot generate any CERs.

As can be seen in the Table 2, there are 12 public utilities and three private sector power utilitymembers in SAPP, which were admitted based on their substantial contribution to power

trades in the SAPP region. The three private entities are:

HCB, an IPP with an installed generating capacity of 2,075 MW in Mozambique,

Motraco, the owner and operator of 1,450 MW cross-border transmission infrastructure

from the Republic of South Africa (RSA), to Mozambique via Swaziland; CEC, the owner and operator of power infrastructure in the copper belt of Zambia that

currently accounts for about 50% of ZESCOs demand.

Table 2: SAPP Power Utility Members and Host Countries

No. Country Power Utility Abbreviation

1 AngolaEmpresa Nacional de Electicidade de

AngolaENE

2 Botswana Botswana Power Cooperation BPC

3 DRC Societ Nacional dElectricit SNEL4 Lesotho Lesotho Electricity Corporation LEC

5 Malawi Electricity Supply Commission of Malawi ESCOM

6 Mozambique Electricidade de Mozambique EDM

7 Mozambique Hidroelectrica de Cahora Bassa HCB

8 Mozambique Mozambique Transmission Company Motraco

9 Namibia NamPower NamPower

10 RSA Eskom Eskom

11 Swaziland Swaziland Electricity Board SEB

12 Tanzania Tanzania Electricity Supply Company TANESCO

13 Zambia Zambia Electricity Supply Corporation ZESCO

14 Zambia Copperbelt Energy Corporation CEC

15 Zimbabwe Zimbabwe Electricity Supply Authority ZESA


6/18

3

With the current changes in the regulatory frameworks in the SADC energy sector, it isexpected that there will be more private sector actors such as Power Brokers and others inSAPP in the future.

In the context of the African Carbon Asset Development (ACAD) facility, GFA ENVEST andthe Coordination Center of the Southern African Power Pool developed a technical solution forthe GEF problem: the regional GEF (Burian / Maviya 2012). It is based on an energy modelcovering the nine interconnected countries: Botswana, Democratic Republic of the Congo,

Lesotho, Mozambique, Namibia, South Africa, Swaziland, Zambia and Zimbabwe. All thesecountries are members of the SAPP. The nine countries were included into one regional so-called Project Electricity System (PES). The PES is the geographical area for which the BuildMargin (BM) and the Operating Margin (OM) are determined. The development of oneregional PES was conducted in accordance with UNFCCC rules and procedures by provingthat there are no transmission barriers according to the CDM EBs definition.

Based on standard weighting of the BM and the OM, the SAPP region offers a GEF of 0.9176tCO2/MWh. Details can be found in Table 3. Guidance on the selection of alternative weights

can be found in the tool (CDM EB63, Annex 19, page 18f).

Table 3: Summary of the Regional SAPP GEF

OM Emission Factor (in t-CO2/MWh) 0.9346

BM Emission Factor (in t-CO2/MWh) 0.9007

Weight of theOM

Weight of theBM

CM EmissionFactor

Wind and solar power generation project activitiesfor the first crediting period and for subsequentcrediting periods

0.75 0.25 0.9261

All other projects for the first crediting period 0.5 0.5 0.9176

All other projects for the second and thirdcrediting period

0.25 0.75 0.9092

The GEF calculation was submitted to Carbon Check, a Designated Operational Entity (DOE)located in South Africa. The DOE validated the GEF according to all applicable rules andconfirmed the final value in a validation statement. In an effort which was well coordinated by

UNEP/ACAD, all nine countries submitted the GEF on 17 August 2012 as a StandardizedBaseline (SBL) to the UNFCCC Secretariat.

Following the CDM Executive Boards procedures (CDM EB66, Annex 49), an initialassessment was conducted in September 2012. Thereafter the SBL was evaluated by two

members of the CDM Methodology Panel and forwarded as first SBL worldwide forconsideration by the CDM EB.

At its 70th meeting the CDM EB noted: The Board welcomed the first standardized baselineGrid emission factor for the Southern African power pool submitted for its consideration

(CDM EB70, 48) but requested the Secretariat to further work on issues such as institutionalprocedures for future updating. Thus, though being the most advanced SBL so far, theapproval of the SAPP Grid Emission Factor is pending for the time being.


7/18

4

2 C A R B O N R E F I T D E S I G N A N D I M P A C T

2 . 1 D e s i g n O p t i o n s

The SAPP GEF Standardized Baseline defines baseline emissions for energy projects feeding

electricity into the Southern African Power Pool grid. Therefore, it could be used as thebaseline for a regional carbon finance scheme beyond the CDM incentivizing renewable

energy projects. Different design options for such a sectoral scheme are theoretically possible:

First, it could take the form of a regional supported NAMA (here: RAMA). NAMAs are definedas mitigation actions by developing countries ... supported and enabled by technology,financing and capacity building, in a measurable, reportable and verifiable manner (Decision1/CP.13). The current scientific discourse accompanying the UNFCCC negotiations comprisesthe concept of credited NAMAs which may generate offset credits. Such credits may be

issued on the basis of the installation of renewable energy installations which were triggered

by a national / regional REFIT scheme. The revenues made from selling the carbon creditswould go directly into financing the feed-in tariff. As the baseline for the scheme would be theSAPP GEF standardized baseline, a regional NAMA or RAMA would be possible that covers

all nine countries.

Second, following the EUs suggestions for sectoral crediting mechanisms, the scheme couldcover the sector (renewable) energy generation in the region. This mechanism would need to

take the projected installation of renewable energy as baseline and would issue credits in casethe scheme triggers a higher penetration rate of renewable energy projects. As such, the

scheme would rather have a technology penetration target and would be based on theperformance of the sector.

Third, a combination of CDM and other policy instruments is possible. Puhl (2011) sketches a

system that links a REFIT in Thailand with programmatic CDM and NAMAs/sectoral creditingschemes. This sketch is arranged in three major layers:

The promotion of renewable energy through a REFIT results in additional costscovered by the electricity consumers through higher prices. The increase in electricity

prices is subsequently reduced to an appropriate level by adding two more layers.

Second Phul proposes the development of a CDM Programme of Activities undercurrent rules. The carbon revenues are used to partially refinance the cost of theexisting REFIT, so that the payments of consumers are reduced.

On top of this scheme, a NAMA layer is put which helps limiting the price increasedue to the REFIT. This NAMA support may set in once the additional cost burden forelectricity consumers reach an appropriate level.

From the outset, the RAMA option promises the best results as it directly targets theinstallation level and can therefore directly finance the feed-in tariff. Moreover, additionalitymatters can be addressed well under such regimes, see below. The layer-system is regardedas too complicated at first sight when considering the regional coverage that is intended here.

The advantage of such a Carbon REFIT system would certainly be the existence of a reliablescheme incentivizing renewable energy production which would be independent from politicalpreferences and debate in the different countries. The difficulties with the South African REFITare a viable example of these constraints.

A possible anchor point for the scheme would be the SAPP Coordination Centre. Being aSADC entity, it facilitates the operation of the common energy market and monitors thetransactions between the members. Its technical knowledge and coordinating role may make it

an appropriate hub for innovative energy projects in the region.


8/18

5

2 . 2 D e t e r m i n a t i o n o f C a r b o n R E F I T

In order to evaluate the potential impact of a Carbon REFIT (subsequently referred to as CR),the potential carbon revenue of such a scheme shall be estimated. This builds on:

the grid emission factor, which was determined for the nine countries to amount to0.9176tCO2/MWh. That is, for the generation of one MWh, the regional electricitysystem emits approximately 0.9176tCO2.

the price of one tCO2e reduced, which was assumed to be at 10USD/tCO2. This maybe high compared to the current CER price but seems reasonable when usinghistorical mid to long term CER prices as benchmark for the financial contributionsunder a future supported NAMA/NMM scheme.

Based on above values, the CR is determined as follows:

!" !"#$!"

= !"# !"#2!"

!!"#$%!"#$%&&%!'!"#$%&!"#(!"#$!"#2

)

Following above formula results in Carbon REFIT of 0.9176 USDc/kWh. The input and output

data is presented in below table.

Table 4: Determination of Carbon REFIT

Item Unit Value

Price of Emission Reduction USD/tCO2 10.00

Grid Emission Factor tCO2/MWh 0.9176

Carbon REFIT USDc/kWh 0.9176

2 . 3 P o t e n t i a l I m p a c t s o f C a r b o n R E F I T

This section evaluates the potential impacts of the Carbon REFIT. The evaluation builds on amodel cash flow for a hydro power plant. The cash flow and its input parameters are presented

in Annex I. The cash flow is based on an average discount rate (based on UNFCCCs financialbenchmark data for the SAPP Region) as determined in Annex III.

This cash flow gives a first and rough approximation of the financial framework for hydropower projects (which may be the financially most attractive renewable energy project type).Based on this cash flow, the financial attractiveness of a model hydro power plant isevaluated. As financial indicators, the Internal Rate of Return (IRR) and the Net Present Value(NPV) are determined. Both, IRR and NPV are determined for the scenario with and without

carbon revenues. The findings of the financial evaluation are presented in table 5.

Table 5: Hydro Power Plant - Financial Evaluation

IRR w/o Carbon Revenues in % 10.90%IRR with CarbonRevenues

in % 15.70%

NPV w/o CarbonRevenues

inUSD

-3,995,979NPV with CarbonRevenues

in USD 3,766,217


9/18

6

In the without Carbon REFIT scenario, table 5 shows that the projects Internal Rate of Returnamounts to 10.90% and its Net Present Value is negative. In CDM terms, in order to proveadditionality, the projects IRR must be below the benchmark of 12.88%, as determined in

Annex III. Hence, this model hydro power plant would qualify under the CDM.

The with Carbon REFIT scenario shows a more favorable picture. Based on the CarbonREFIT, the proposed projects IRR lies significantly above the benchmark. Also the projectsNPV becomes positive.

Also in terms of significance, the Carbon REFIT may be a substantial contribution. The

evaluation of the revenues of electricity sales and from the Carbon REFIT indicates that theREFIT may make up for approx. 29% of the model hydro power plants revenues.

Table 6: Revenue Streams of a Model Hydro Power Plant

Item USDc/kWh %

Electricity Revenue 2.25 71.03%

Carbon Revenue 0.92 28.97%

Total 3.17 100.00%

Figure 1: Revenue Streams of a Model Hydro Power Plant

This first approximation shows that the above sketched Carbon REFIT may be central topromoting renewable energy projects in the region. Still, this issue may require a more detailedevaluation, such as the evaluation of cash flows for different technologies (wind, biomassresidue projects, solar and hydro power plants of different sizes) as well as different business

models (operation under a PPA or e.g. operation under the power pool).

71%

29%

ElectricityRevenue CarbonREFIT


10/18

7

2 . 4 E n v i r o n m e n t a l I n t e g r i t y

Within the system sketched above, two elements need to be accounted for when ensuringenvironmental integrity: the risk of double counting as well as the additionality of the emission

reduction. These two issues are subsequently discussed in detail.

Double counting occurs if a project applies for the Carbon REFIT while at the same timemaking use of the CDM. This would result in double counting of emission reductions, one timethrough the CDM, one time through the Carbon REFIT.

This problem may besolved by requiring that projects covered by the Carbon REFIT must notapply for being registered under the CDM or under a similar mechanism. This may bedocumented e.g. by signing a respective agreement between the power project and the

institution in charge for the management of the Carbon REFIT. Moreover this may becontrolled by regularly screening of UNFCCCs CDM database.

The question of additionality is a more complex and challenging task. The additionality proof

usually is accomplished by demonstrating that the proposed CDM projects IRR is below thebenchmark for (energy) projects as e.g. stipulated by the Guidelines on the Assessment ofInvestment Analysis (CDM EB62, Annex 5). Not considering additionality hence involves the

risk that also projects with IRRs above the benchmark may be accounted towards the climatechange mitigation objectives of Annex I countries. Subsequently two design options formanaging additionality of a Carbon REFIT are briefly laid out.

First, it may be agreed to define an eligibility list. Such a list may specify scales and types ofprojects which may be eligible for participating in the Carbon REFIT.

In general terms, it shall be noted that all SADC countries are characterized by difficult

investment climates for energy projects. Annex III evaluates the investment benchmark forenergy projects for all nine SAPP countries as specified by the UNFCCC for the additionality

proof. The benchmark ranges from 10.8% (Botswana) to 14.5 % (DRC and Mozambique), thesimple average for the SAPP region amounts to 12.88%. Consequently, if a project is above

this benchmark, it may not be additional.

The small number of renewable energy projects developed in the past years indicates thatthese high investment benchmarks pose a financial barrier for project finance. Against thisbackground, an eligibility list may be developed, in order to allow only for those projects under

the Carbon REFIT, which may not be financially attractive with additional revenues. This listmay be constrained to e.g.:

Including a maximum size for hydro power plants, e.g. 100 MW, as small hydro

schemes are tentatively more expensive (in USDc/kWh) than large power plants, Hydro power plants shall be compliant to the guidelines of the World Commission on

Dams (WCD); The power density of dams shall be at least 4W per square meter (as specified in

ACM2 Grid Connected Electricity Generation from Renewable Sources, (CDM EB67) Biomass projects shall be restricted to the use of biomass residues (as specified in

ACM6 Consolidated Methodology for Electricity and Heat Generation from Biomass),or

Biomass from dedicated plantations (e.g. reforestation) without the clearing of intactforest sites (e.g. AM42 Grid-connected Electricity Generation Using Biomass fromNewly Developed Dedicated Plantations).

Among above project types, hydropower is considered as the financially most attractivetechnology. Chapter 2.3 above provides a model cash flow for a 50MW hydro power station,

which has been adapted to the region. As discussed above, even though hydropower beingthe financially most attractive technology, the cash flow shows that due to the high financialcosts, such a project may be additional under current CDM rules. The above approach shall


11/18

8

be considered as a first sketch and will need further evaluation and close coordination withlocal stakeholders.

The second design option for additionality may build on a CDM-style investment test and a

barrier analysis (Okubo et al. 2011). As for the investment test, one would need to calculatethe difference between the REFIT and the electricity price. On top of that, the differencebetween the typical cost for renewable energy-generated electricity and the cost of fossil fuel-based energy would need to be assessed. The test would be passed as long as both values

are positive. The barrier test would look at the capital investments needed and assess whetherthe existence of the crediting scheme helps removing the investment barriers by increasingrevenues. It would also be possible to work with a technologic penetration analysis for acountry with similar development indicators but with a REFIT.

Finally, it may be the case that the overall emissions of the regional electricity systemincrease, even despite the financial support through the Carbon REFIT. This may be as newfossil fuelled power plants are commissioned and / or the load of the existing fossil powerplants is increased. In this regard, the sketched Carbon REFIT may not be considered as a

sectoral benchmark for Southern Africa with an absolute or relative baseline. It is merely aninstrument for promoting and supporting renewable energy on a project-by-project case similar

to a CDM Programme of Activities for Southern Africa.


12/18

9

3 C O N C L U S I O N

This short study outlines the opportunities for using the SAPP GEF Standardized Baseline for

a regional carbon crediting scheme. Especially when designed as a regional version ofNationally Appropriate Mitigation Action (RAMA), the scheme looks promising, as many

prerequisites for a possible NAMA crediting are fulfilled. These include a well calculatedbaseline emissions factor (the SAPP GEF), excellent monitoring conditions (renewableelectricity produced), and good options for assessing additionality. Such a scheme would helppromoting renewable energy in southern Africa and would align perfectly with feed-inprogrammes already under consideration (such as in Zambia) and with existing schemes

facing implementation difficulties as in RSA. Another option to be explored could be a pilotscheme for a New Market Mechanism as currently discussed under the AWG-LCA in the

climate negotiations.

Further research would be needed in order to develop a robust approach for such a scheme.Inter alia, conceptual detail needs to be analyzed further, such as different design options or

the evaluation of cash flows for different technologies. At the international level, questionssuch as whether policy-based actions such as REFIT could qualify as a NAMA need to be

answered.

The impact of varying carbon prices is a major issue. This could be accounted for, e.g. bydefining the scheme as a strategic partnership between Annex I and Non-Annex I countries.

This partnership would guarantee the purchase of the credits generated at a fixed carbonprice.

Further questions relate to the entity administering the regional scheme. The SAPPCoordination Centre may be well suited for this task. On the other hand, one has to accountfor, inter alia, different national approval procedures and laws. Therefore, it might be better to

chose a light umbrella framework and have national schemes under it.Taking these two issues together, it might be worth exploring whether a regional development

bank could administer the scheme in the form of a fund or facility. This could take away theresponsibility from the national governments which are confronted with budget constraints and

limited capacities. This approach would also help securing a fixed carbon price. One optionwould be a partnership with a regional development bank and the German KfW which bothhas a wealth of experience with incentive schemes and is active in the region.


13/18

10

R E F E R E N C E S

Burian, Martin and Johnson Maviya (2012): Unlocking CDM Development in Southern Africa

Developing a Regional Grid Emission Factor. In: German Federal Environment Ministry (Ed.):Mitigating Climate Change, Investing in Development. Berlin.

CDM EB70 (2012): Meeting Report CDM Executive Board Seventieth Meeting, Version 1,

Date of Meeting: 10 to 23 November 2012, Place of Meetoing: Doha, Qatar,

CDM EB69 (2012): ACM6 Consolidated Methodology for Electricity and Heat Generationfrom Biomass, Version 12.1.1, UNFCCC.

CDM EB67 (2012):ACM2 Grid Connected Electricity Generation from Renewable Sources,Version 13, UNFCCC

CDM EB66, Annex 49 (2011): Guidelines for Quality Assurance and Quality Control of Data

used in the Establishment of Standardized Baselines, Version 1, UNFCCC.

CDM EB62 Annex 5 (2011): Guidelines on the Assessment of Investment Analysis, Version 5,UNFCCC

CDM EB55, (2010):AM42 Grid-connected Electricity Generation Using Biomass from Newly

Developed Dedicated Plantations, Version 2.1, UNFCCC

Okubo, Yuri, Daisuke Hayashi and Axel Michaelowa (2011): NAMA crediting: how to assessoffsets from and additionality of policy-based mitigation actions in developing countries. In:

Greenhouse Gas Measurement & Management, 1, 2011, 3746.

Puhl, Ingo (2011): Linking Domestic Incentives (feed-in-tariff) with Carbon Market Mechanismsand NAMA to Deliver Renewable Energy at Scale. Presentation at IETA side event, 5 Dec2011, UNFCCC COP 17. Durban.


14/18

11

A N N E X I M O D E L C A S H F L O W F O R H P P

In order to evaluate the potential impact of a Carbon REFIT, this section presents a model

cash flow for a hydro power plant. This model builds on the Levelized Electricity Cost model of the World Bank and was

adopted to a hydro power plant of 50MW installed capacity. The discount rate was determined at 12.88%, based on the UNFCCC benchmarks for

energy projects in the SAPP region, please refer to Annex III. The electricity price was estimated at 2.5 USDc/kWh and shall reflect the revenues that an

IPP can realize under a PPA.

Table 7 below presents the basic input parameters.

Table 7: Hydro Power Plant Input Parameters

Item Unit ProjectCase

InstalledCapacity MW 50.00

De-RatingbyUse in% 0.40%

Project'sOwnElectricityDemand in% 0.30%

NetEffectiveCapacity 49.65

LoadFactor MW 40.00%

NetElectricityGeneration GWh/yr 173.97

TotalInvestment MillionUSD 30.00

Non-FuelVariableCost USD/MWh 0.11

FixedOMCost MillionUSD/yr 0.12PlantLife Years 50.00

Discountrate in% 12.88%

ElectricityPrice USDc/kWh 2.25

GridEmissionFactor tCO2/MWh 0.92

PriceofEmissionReduction USD/tCO2 10.00

CarbonRevenue USDc/kWh 0.92

Amortization MillionUSD/yr 0.60

ProfitTax in% 0.20

CalculatedbasedontheLevelizedElectricityGeneratingCostModeloftheWorldBankincludedin

IslamicRepublicofIran-PowerSectorNote,WorldBank,2006,Annex5.


15/18

12

The below table shows the basic operating parameters of the model hydro power plant rangingfrom investment costs up to the potential revenues from a Carbon REFIT. These revenues andcosts are presented from year 1 to year 50 (i.e. the end of the plant life time).

Table 8: Hydro Power Plant - Basic Operating Parameter

Item

Unit\Yea

r1 2 3 4 5 50

Investment USD/yr15,000,000 15,000,000 - - - -

NetElectricity

Generation GWh/yr 174 174 174 174 174

Non-FuelVariable

Cost USD/yr 19,137 19,137 19,137 19,137 19,137

FixedOMCost USD/yr121,000 121,000 121,000 121,000 121,000 121,000 121,000

TotalAnnual

Costs USD/yr15,121,000 15,121,000 140,311 140,311 140,311 140,311 140,311

Amortization USD/yr 600,000 600,000 600,000 600,000 600,000

Electicity

Revenues USD/yr 3,914,406 3,914,406 3,914,406 3,914,406 3,914,406

Emission

Reductions tCO2/yr- - 159,638 159,638 159,638 159,638 159,638

CarbonRevenues USD/yr- - 1,596,382 1,596,382 1,596,382 1,596,382 1,596,382

Based on the above operating parameter, the below table presents the cash flow of the modelhydro power plant. Amortization, as determined in Table 4, was added back to the cash flow.The results are presented twice, as Net Profit with Carbon Revenues and Net Profit w/oCarbon Revenues.

Table 9: Hydro Power Plant - Cash Flow Calculation

Electicity

Revenues USD/yr- - 3,914,406 3,914,406 3,914,406 3,914,406 3,914,406

CarbonRevenues USD/yr - - 1,596,382 1,596,382 1,596,382 1,596,382 1,596,382

TotalAnnual

Costs USD/yr15,121,000 15,121,000 140,311 140,311 140,311 140,311 140,311

Amortization USD/yr - - 600,000.00 600,000.00 600,000.00 600,000.00 600,000.00

GrossProfit USD/yr 15,121,000 15,121,000 5,970,477 5,970,477 5,970,477 5,970,477 5,970,477

Profittax USD/yr 1,194,095 1,194,095 1,194,095 1,194,095 1,194,095

NetProfitwith

CarbonRevenues USD/yr

15,121,000 15,121,000 4,776,381 4,776,381 4,776,381 4,776,381 4,776,381

NetProfitw/o

CarbonRevenues USD/yr 15,121,000 15,121,000 3,499,276 3,499,276 3,499,276 3,499,276 3,499,276

Based on above cash flow, it is possible to determine the financial attractiveness of the hydropower plant. The financial attractiveness is expressed through the Internal Rate of Return(IRR) and the Net Present Value (NPV). Both, IRR and NPV are determined for the scenariowith- and without carbon revenues. The findings of the financial evaluation are presented inbelow table.

Table 10: Hydro Power Plant - Financial Evaluation

IRRw/oCarbonRevenues in% 10.90% IRRwithCarbonRevenues in% 15.70%NPVw/oCarbonRevenues inUSD -3,995,979 NPVwithCarbonRevenues inUSD 3,766,217


16/18

13

A N N E X I I S A P P C A P A C I T Y A D D I T I O N S

Table 11: SAPP Capacity Additions

No. Country ProjectName Capacity[MW]ExpectedCommissioning

Date

1 Angola Mambas 25 2011

2 Angola Goverehabilitation 60 2011

3 Angola CambambeII 260 2013

4 Angola CambambeII 260 2014

5 Botswana Orapa 90 2011

6 Botswana MorupuleBExpansion(Phase1) 600 2012

7 Botswana Mmamabula(MDDP) 300 2015

8 DRC Inga1Rehabilitation 15 2011

9 DRC Nseke 60 2011



12 DRC Nzilo 25 2013

13 DRC Busanga 240 2016

14 DRC Inga3 4320 2018

15 Lesotho LesothoWind 25 2012

16 Lesotho MuelaII 73 2014

17 Malawi Kapichira 64 2013

18 Malawi Songwe 150 2014

19 Malawi LowerFufu 100 2015

20 Malawi Ngana 300 2016

21 Malawi Mpatamanga 310 2018

22 Mozambique Moamba 150 2013

23 Mozambique Moatize 300 2014

24 Mozambique Benga 300 2014

25 Mozambique Moatize 300 2015

26 Mozambique Benga 300 2015

27 Mozambique Moamba 150 2015

28 Mozambique HCBNorthBank 1245 2017

29 Mozambique MphandaNkuwa(PhaseI) 1500 2017

30 Namibia Anixas 22,5 2011

31 Namibia Ruacana 83 2012

32 Namibia Wind 60 2013

33 Namibia OrangeRiver 43 2013

34 Namibia Kudu 800 2015

35 Namibia BaynesNew 500 2018

36 Swaziland Lubhuku 300 2015

37 Swaziland Magududza 140 2020

38 SouthAfrica Komati 430 2011

39 SouthAfrica EskomCo-generation 100 2011

40 SouthAfrica Komati 288 2012

41 SouthAfrica OCGTIPP 1050 2013


17/18

14

42 SouthAfrica OCGTIPP 800 2013

43 SouthAfrica IngulaPumpedStorage 100 2013

44 SouthAfrica EskomSolar 100 2013

45 SouthAfrica Medupi 722 2014

46 SouthAfrica IngulaPumpedStorage 999 2014

47 SouthAfrica Kusile 1446 2015




51 SouthAfrica EskomCoal 600 2016







58 Tanzania SingidaWind 50 2011

59 Tanzania SaoHillCo-generation 10 2011

60 Tanzania Ubongo 100 2012

61 Tanzania Mwanza 60 2012

62 Tanzania Kiwira 200 2014

63 Tanzania MnaziBay 300 2014

64 Tanzania Kiwira 200 2014

65 Tanzania Kinyerezi 240 2014

66 Tanzania Mchuchuma 600 2015

67 Tanzania Ngaka 400 2016

68 Tanzania Ruhudji 358 2017

69 Zimbabwe Hwange1&2Rehabilitation 140 2011

70 Zimbabwe SmallThermalsRehabilitation 105 2011

71 Zimbabwe Chisumbanje 20 2011

72 Zimbabwe Chisumbanje 20 2013

73 Zimbabwe KaribaSouthExtension 300 2015

74 Zimbabwe Hwange7 300 2016

75 Zimbabwe Hwange8 300 2017

76 Zimbabwe Lupane 150 2017

77 Zimbabwe Lupane 150 2018

78 Zimbabwe GokweNorth 1400 2018

79 Zimbabwe Batoka 800 2020

80 Zambia LunsemfwaHydro 6 2012

81 Zambia KaribaNorthBankExtension 360 2013

82 Zambia Itezhi-Tezhi 120 2014

83 Zambia Kabompo 34 2015

84 Zambia LHPC 160 2016

85 Zambia Kalungwishi 220 2016

86 Zambia KafueGorgeLower 600 2017

Source:SAPPPowerPoolprovidedbySAPPCC


18/18

15

A N N E X I I I F I N A N C I A L B E N C H M A R K S F O RE N E R G Y P R O J E C T S I N T H E S A P P R E G I O N

Table 12: UNFCCC IRR Benchmarks for Energy Projects

No. Country Benchmark(in%)

1 Botswana 10.80%

2 DRC 14.50%

3 Lesotho N.A.

4 Mozambique 14.50%

5 Namibia 12.90%

6 RSA 10.90%

7 Swaziland 12.90%

8 Zambia 13.25%

9 Zimbabwe 13.25%

Average 12.88%

Source:CDMEB62,Annex5,GuidelinesfortheAssessmentofInvestmentAnalysis,Appendix

'Defaultvaluesfortheexpectedreturnonequity',8

111sap carbon refit

Documents