Wind Power CDM Projects

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Examensarbete i Hållbar Utveckling 151

Study on Plant Load Factor ofWind Power CDM Projects

Study on Plant Load Factor of

Wind Power CDM Projects

Tianyu Meng

Tianyu Meng

Uppsala University, Department of Earth Sciences

Master Thesis E, in Sustainable Development, 30 credits

Printed at Department of Earth Sciences,

Geotryckeriet, Uppsala University, Uppsala, 2013.

Master’s ThesisE, 30 credits



Supervisor: Eva Friman

Evaluator: Lars Rudebeck

Examensarbete i Hållbar Utveckling 151

Study on Plant Load Factor ofWind Power CDM Projects

Tianyu Meng



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Content1 Introduction ...................................................................................................................... 12 Background ....................................................................................................................... 12.1 The Kyoto Protocol .……................................................................................................... 12.2 Clean Development Mechanism (CDM) ........................................................................... 22.2.1 Overview …….…………………….................................................................................... 2

2.2.2 CDM Benefits ………….………….................................................................................... 32.2.3 CDM Project Cycle…….…………..................................................................................... 32.2.4 CDM Project Additionality……..….................................................................................... 42.3 Wind Power CDM Projects …............................................................................................ 62.3.1 Overview ………………………….................................................................................... 62.3.2 Wind CDM projects’ contribution to sustainable development.......................................... 72.3.3 Issues about Wind CDM Project ........................................................................................ 72.4 Plant Load Factor …………… ........................................................................................... 72.4.1 Estimated PLF …………………….................................................................................... 72.4.2 Actual PLF ………………………….................................................................................. 72.4.3 Relative Variation of PLF …………................................................................................... 83 Methodology ...................................................................................................................... 83.1 Database establishment….................................................................................................... 8

3.1.1 Data selection …………...................................................................................................... 83.1.2 Data collection ………………………….......................................................................... 93.1.3 Data crosscheck…………………....................................................................................... 103.1.4 Data calculations …………………..................................................................................... 103.2 Comparison Analysis ……………….................................................................................. 103.2.1 Comparison objectives and their meanings ......................................................................... 103.2.2 Comparison basis ................................................................................................................. 114 Results…. …………………................................................................................................ 114.1 Project Distribution…........................................................................................................... 114.2 Comparison of all projects…………………………………………………………………. 124.3 Comparison based on scales ………………………………………………………………. 134.4 Comparison based on countries …………………………………………………………… 155 Discussions……………....................................................................................................... 16

5.1 Discussion on Under/Overestimation................................................................................... 165.2 Discussion on Relative Variation of PLF ............................................................................ 186 Conclusions………………….............................................................................................. 187 Acknowledgement……....................................................................................................... 188 References…….................................................................................................................... 19Annex 1…………………………………………………………………………………………… 21



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Study on Plant Load Factor of Wind Power CDM Projects

TIANYU MENG

Meng, T., 2013: Study on Plant Load Factor of Wind Power CDM Projects. Master thesis in Sustainable

Development at Uppsala University, No. 151, 26 pp, 30 ECTS/hp

Abstract: Clean Development Mechanism (CDM), is a market-based mechanism under the Kyoto Protocol. Itallows developed countries to implement emission reduction projects in developing countries, to assist theirsustainable development; meanwhile, developed countries gain credits which could be used to meet part of theiremission reduction targets under this protocol. There is a wide range of various types of CDM projects, amongwhich, wind power projects account for the largest share.

Additionality is a key component for CDM projects’ eligibility and to ensure CDM’s environmental integrity. Itmeans that the emission reduction after the implementation of the project is additional to any that would haveoccurred in the absence of the certified CDM project. For wind CDM projects, the controversy on additionalityraised debate and attention internationally, especially the concern if project developers deliberatelyunderestimated Plant Load Factor (PLF) so as to meet the CDM additionality criterion. At the United Nations

Framework Convention on Climate Change (UNFCCC) CDM Executive Board 63rd meeting, the UNFCCCSecretariat and the Registration and Issuance Team (RIT) proposed different decisions regarding a request forissuance of a Wind CDM project due to different views on the estimated PLF. The Board discussed the issue andrequested a study on the PLF variations, which is the origin, and also a partial content of this thesis.

In this thesis, relevant parameters are firstly defined – parameters such as Estimated PLF, Actual PLF, etc, and to better illustrate the magnitude of the PLF variation, the concept of Relative Variation of PLF is adopted, which ismeasured as the absolute difference of Estimated PLF and Actual PLF compared with Estimated PLF. Then adatabase in spreadsheet with all defined parameters of sampled projects is set up on the basis of collectedinformation and calculation. Afterwards an investigation of PLFs and comparison analyses of Estimated PLFsand Actual PFLs is conducted. Considering there are two groups of Wind CDM projects, i.e. small-scale andlarge-scale; and considering the distributions of projects’ hosting countries, the comparison analyses are thenconducted firstly for all projects, and then separated for small-scale and large-scale projects, and lastly separated

for projects based on different hosting countries. The final results show that a minority of projects haveunderestimated PLFs, and a very small proportion of projects, either in all projects, or on different scales or indifferent hosting countries have underestimated PLFs to a level that is out of acceptable range. Therefore, thestudy concludes that there should be no concern on the PLF issue in Wind CDM projects.

Keywords: Sustainable Development, Wind Power, Clean Development Mechanism, Additionality, Plant LoadFactor

Tianyu Meng, Department of Earth Sciences, Uppsala University, Villavägen 16, SE- 752 36 Uppsala, Sweden



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Study on Plant Load Factor of Wind Power CDM Projects

TIANYU MENG

Meng, T., 2013: Study on Plant Load Factor of Wind Power CDM Projects. Master thesis in Sustainable

Development at Uppsala University, No. 151, 26 pp, 30 ECTS/hp

Summary: Clean Development Mechanism (CDM), is a market-based mechanism under the Kyoto Protocol. Itallows developed countries to implement emission reduction projects in developing countries, to assist theirsustainable development; meanwhile, developed countries gain credits which could be used to meet part of theiremission reduction targets under this protocol.

There is a wide range of various types of CDM projects, among which, wind power projects account for thelargest share. Nevertheless, the controversy of some wind CDM projects raised attention internationally anddebate, such as about low tariff set by host country in order to attract CDM investment, and aboutunderestimated Plant Load Factor (PLF) so as to meet the CDM additionality criterion. At the United NationsFramework Convention on Climate Change (UNFCCC) CDM Executive Board 63

rd meeting, the UNFCCC

Secretariat and the Registration and Issuance Team (RIT) proposed different decisions regarding a request for

issuance of a Wind CDM project due to different views on the estimated PLF. The Board discussed the issue andrequested a study on the PLF variations. This thesis is partially prepared for the Board’s meeting.

In this thesis, relevant parameters are firstly been defined - parameters such as Estimated PLF, Actual PLF,Relative Variation of PLF, etc. Then a database including defined parameters of sampled projects is set up on the

basis of collected information and calculation. Afterwards an investigation of PLFs and comparison analyses ofEstimated PLFs and Actual PFLs are conducted. Considering there are two groups of Wind CDM projects, i.e.small-scale and large-scale; and considering the distributions of projects’ hosting countries. The comparisonanalyses are conducted firstly for all projects, and then separated for small-scale and large-scale projects, andlastly separated for projects based on hosting countries. The final results show that the minority of projects haveunderestimated PLFs, and a very small proportion of projects, either in all projects, or at different scales or indifferent hosting countries have underestimated PLFs to a level that is out of acceptable range. Therefore, thestudy concludes that there should be no concern on the PLF issue in Wind CDM projects.

Keywords: Sustainable Development, Wind Power, Clean Development Mechanism, Additionality, Plant LoadFactor

Tianyu Meng, Department of Earth Sciences, Uppsala University, Villavägen 16, SE- 752 36 Uppsala, Sweden



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Abbreviations:

AAU Assigned Amount UnitCDM Clean Development MechanismCER Certified Emission ReductionCOP Conference of Parties

DNA Designated National AuthorityDOE Designated Operational EntityEE Energy EfficiencyERU Emission Reduction UnitET Emission TradingGEWC Global Wind Energy CouncilGHG Greenhouse GasGW GigawattIETA International Emission Trading AssociationJI Joint ImplementationMW MegawattMWh Megawatt hourPDD Project Design Document

PLF Plant Load FactorRIT Registration and Issuance TeamSPD Strategy and Policy DevelopmenttCO2e Ton of Carbon Dioxide EquivalentUNFCCC United Nations Framework Convention on Climate Change

Definitions:

Party Member country to United Nation Framework Convention on Climate Change



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1. IntroductionAccording to the United Nations FrameworkConvention on Climate Change (hereafter refer asUNFCCC), the Clean Development Mechanism(CDM) is one out of the three flexible market-basedmechanisms defined in the Kyoto Protocol,intended to meet two objectives: i) to assistdeveloping countries in achieving sustainabledevelopment; and ii) to assist developed countriesin fulfilling their emission reduction commitment(Article 12, Kyoto Protocol).

The process works in the following way. Developedcountries (listed as Annex I parties) who haveemission caps, assist developing countries (listed asnon-Annex I parties) who don’t have emission capsto implement emission-reduction projects, through:the provision of capital, transfer of technologies,creation of employment, etc, in order fordeveloping countries to achieve sustainabledevelopment. The specific indicators of sustainabledevelopment were developed by the hostdeveloping countries themselves according to theirnational goals/policies/priorities, and clearlyreflected in the Project Design Document of everyCDM project. At the mean time, saleable andtradable credits (here called Certified EmissionReduction, i.e., CERs) will be issued and can beused by developed countries to offset a part of theirgreenhouse gas (GHG) emission reduction targets

under the Kyoto Protocol. There is a wide range ofsectoral scopes of emission-reduction projects, suchas Energy industries, Manufacturing industries,Chemical industries, Construction, Transport,Mining, Waste management, Solvent use,Afforestation and Reforestation, etc.

According to statistics, Wind power CDM projectsaccount for the largest share – 29% - of all kinds ofCDM projects in pipeline until the end of 2012(CDMpipeline, 2012). However, some of them arecontroversial for a couple of reasons, such as lowtariff set by host country in order to attract CDM

investment, and underestimated Plant Load Factor(PLF) so as to meet the CDM additionalitycriterion, which affects the environmental integrity,which in turn is one of the basic attributes of CDM

projects. At the UNFCCC CDM Executive Board63

rd meeting, the UNFCCC Secretariat and the

Registration and Issuance Team (RIT) proposeddifferent decisions regarding a request for issuanceof a Wind CDM project due to the different viewson the estimated PLF. The Board discussed theissue and in particular discussed the magnitude and

permanence of the PLF variations and the initialPLF estimation in Project Design Document

(PDD).

Following its deliberation, the Board requested theSecretariat to prepare an assessment on thetechnical approaches for the appropriatedetermination of PLFs for wind power projects. Italso requested a review of the determination of PLF

by registered wind CDM project activities, as

compared to actual monitored PLFs achieved bythese registered project activities, for consideration by the Board at a future meeting. With part of therequests as original motivation for the thesis, aswell as among others, the objectives of this thesisare:

1) to investigate the PLFs of wind CDM projects;

2) to conduct a comparative analysis betweenestimated PLFs and actual PLFs in registered wind

projects; and

3) to inquire if the variation between estimatedPLFs and actual PLFs affect the environmentalintegrity.

2. Background

2.1. The Kyoto Protocol The Kyoto Protocol is an international environmenttreaty under United Nations FrameworkConvention on Climate Change (UNFCCC), theultimate objective of which is to ‘stabilize the

greenhouse gas concentration (GHG) in theatmosphere at a level that would prevent dangerousanthropogenic interference with the climate system(UNFCCC Essential Background, 2013)’. ThisProtocol was adopted in 1997 in Kyoto, Japan, andentered into force in 2005 after the elaboration ofconcrete operations and a ratification process formember countries which are called Parties to theProtocol (hereafter, member country to theconvention is referred to as Party).

This treaty recognizes that developed countries aremainly responsible for the current greenhouse gases

concentration in the atmosphere owing to theirindustrial activities during the last more than 150years, and the fact that GHG emission per person indeveloping countries is lower than that indeveloped countries at present. Thus, the Protocol

builds a principle that is ‘common but differentiatedresponsibilities’, based on which, it sets legally

binding obligations of greenhouse gasreductions/limitations for developed countries,while encourage developing countries to reduceGHG emissions. Initially, there are twocommitment periods, from 2008 to 2012 and from2013 to 2020. For the first commitment period, it

targeted 37 industrialized countries and theEuropean Union, and the overall emission reduction



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on average amounted to 5% relative to the 1990slevel (Kyoto Protocol, 1998).

Countries which have emission limitation/reductioncommitments under Kyoto Protocol principally takenational measures to meet their targets. Meanwhile,

to make it more flexible and cost-effective, theProtocol introduced three market-basedmechanisms, consequently creating the concept of‘carbon market’. The mechanisms encompass:

- Emission Trading (ET);- Clean Development Mechanism (CDM)- Joint Mechanism (JI).

Emission Trading allows countries with emissiontargets to trade their commitments under thisProtocol. Specifically, under this Protocol, thetargets of emission reduction/limitation areexpressed as allowed emissions, or the common

used ‘assigned amount’, which could be divided to‘assigned amount units’ (AAUs). According toArticle 17 of the Protocol, the country which hasn’tused up its AAUs is allowed to sell the excess unitsto the countries which over use their own.

Clean Development Mechanism allows countrieswith emission reduction/limitation targets to doemission reduction/removal projects in developingcountries in order to earn salable and tradableCertified Emission Reduction (CER) credits, whichcan be used to meet part of their own targets underthis Protocol.

Joint Implementation, according to Article 6 of theProtocol, enables countries which have emissionreduction/limitation commitments to implementemission reduction/removal projects, referred to as

joint implementation projects, in countries also withsuch commitments so as to earn EmissionReduction Units (ERUs) to meet part of their owntargets under this Protocol.

The working process, taking Clean DevelopmentMechanism as an example, in theory, is like this: aninvestor or governmental body from a developed

country invests in or provides finance to a projectdeveloper in order to implement a CDM project in adeveloping country; afterwards, the investor getscarbon credits (CERs) corresponding to the amountof emission reduction from the project, and can usethem to meet its target under the Kyoto Protocolinstead of reducing its own emission. However, in

practice, the process is much more complex. Normally it involves financial intermediaries whoinvest in CDM projects or purchase CERs, andafterwards sell those CERs tocompanies/governments in developed countries.Sometimes, the CERs could be traded several times.

Besides, project developers may self finance theirCDM projects and then seek buyers for the

generated CERs. Nevertheless, the fundamentalremains the same, which is developed countriesinvest in emission reduction projects in developingcountries, and get the corresponding carbon creditsto off-set their own emission reduction target underthe Kyoto Protocol.

According to the Protocol, the established threemarket-based mechanisms specifically contribute inthe following ways:

i) To help countries with emissionreduction/limitation targets seek cost-effective ways to fulfill theircommitments;

ii) To encourage developing countriescontribute to emission reductionefforts;

iii) To spur private sector to get involvedin the emission reduction projects

from different angles;iv) To stimulate sustainable development

through investment in environmentalfriendly projects, technology transfer,implementation of sustainability

projects, among others.

2.2. Clean DevelopmentMechanism (CDM)As a market-based and project-based mechanism,and the only mechanism which involves bothdeveloping and developed countries under the

Kyoto Protocol, the Clean DevelopmentMechanism was designed to stimulate sustainabledevelopment in developing countries; while givingdeveloped countries flexibility to fulfill theircommitments of emission reduction/limitation(Article 12, Kyoto Protocol).

2.2.1. OverviewCDM projects are as diverse as waste heat recoveryin Pakistan, kiln efficiency in Bangladesh, wind

power in Mexico, methane capture in Chili, landfillgas recovery in Saudi Arabia, reforestation inUganda, soil conversation in Moldova, etc.

According to CDM pipeline, since the first CDM project registered in 2004, up to the end of 2012,the quantities of different type CDM projects arelisted in below Tab. 1. The numbers include 6660ones which are registered with or without issuedCERs, 159 in process of registration, and 2178 atvalidation stage (refer to 2.2.3 of CDM Cycle).

Type Number Percent

Wind 2611 29%

Hydro 2317 26%

Biomass 883 10%

Methane avoidance 758 8%EE own generation 459 5%



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Landfill gas 431 5%

Solar 395 4.4%

EE industry 158 1.8%

Fossil fuel switch 149 1.7%

EE supply side 126 1.4%

EE Households 113 1.26%

Coal bed/minemethane

112 1.24%

N2O 108 1.2%

Afforestation &Reforestation

72 0.8%

Fugitive 65 0.7%

EE Service 42 0.47%

Cement 40 0.44%

Transport 38 0.42%

Geothermal 35 0.39%

Energy distribution 28 0.31%

HFCs 23 0.26%

PFCs and SF6 18 0.20%Mixed renewable 10 0.11%

CO2 usage 3 0.03%

Tidal 1 0.01%

Agriculture 2 0.02%

Total 8997 100%

Tab.1. The numbers and percentages of different CDM project types up to the end of 2012.Source: UNEP Risoe CDM/JI pipeline

The data presented in table 1 reveals that windCDM projects amount to the largest share,

following are Hydro projects, Biomass projects,Methane avoidance projects, and so on.

CDM projects take place worldwide. According tostatistics from CDM Pipeline, up to the end of 2012,the distribution of CDM projects in differentregions are listed in Table 2 as blow.

Region Number of projects

Percentage outof all projects

Africa1 268 2.98%

Asia & thePacific2

7306 81.2%

Europe andCentral Asia3

102 1.13%

Latin America4 1218 13.54%

Middle-East5 103 1.14%

total 8997 100%

Tab.2. The numbers and percentages of different CDM project host regions up to the end of 2012.1South Africa, Kenya, Egypt, Morocco, Nigeria, etc

2China, India, Viet Nam, Thailand, Indonesia, Malaysia,

South Korea, Philippines, Pakistan, Sri Lanka, etc3Uzbekistan, Serbia, Azerbaijan, Cyprus, Moldova, etc

4Brazil, Mexico, Chile, Colombia, Peru, Argentina,

Ecuador, Honduras, Guatemala, Panama, etc5Israel, Iran, Syria, Lebanon, Saudi Arabia, Kuwait, etc

Source: UNEP Risoe CDM/JI pipeline

It’s observed from table 2 that the projects in Asia& the Pacific, and Latin America accounted foralmost 95% of all projects. In Asia & the Pacificregion, China and India hold the first and second

position in terms of CDM projects numberrespectively. And in Latin America, Brazil and

Mexico are the top two. In the table 2, there are4016, 2171, 426, 215 CDM projects in China, India,Brazil, and Mexico respectively. The sum of the

projects in these four countries accounted foraround 79% out of all. However, the numbers of

projects vary with time. The fraction of total projects in the four countries out of all projectsstarted from 50% in 2004, reached the highest - 85%to date in mid 2006, and fell around 50% in the firstquarter of 2013 due to more countries, especially inAfrica, are active, along with changes in policies,financial instruments, incentives to investment andinternational carbon markets, among others (CDM

Pipeline, 2013).

2.2.2. CDM Benefits

The Report of ‘Benefits of the CDM 2012’ issued by UNFCCC, highlights that, from 2004 the firstCDM project registered up to the end of 2012, 161countries and more than 4500 organizations

participated into CDM, more than 1 billion tons ofCO2 equivalent (tCO2e) have been mitigated,renewable energy projects with capacity of 120gigawatts (GW) have been installed, at least 3.6

billion US$ in emission reduction costs have beensaved for developed countries, 9.5 – 13.5 billion

US$ have been earned directly from sale of CERs,and 215.4 billion US$ has been mobilized to CDM

projects in developing countries, as well as othernon-quantified benefits, including transfer oftechnology and know-how, stimulation tosustainable development.

Contribution to sustainable development is afundamental objective and an eligibility criterion ofCDM projects. CDM Executive Board left theresponsibility of specifying sustainabledevelopment indicators to project host countries inline with their own national priorities/policies,

while with consideration of the internationalframework, etc.

The report generalized them from economic,environmental and social perspectives, from studiesof more than 4000 registered CDM projects. In theeconomic dimension, CDM projects stimulateeconomy through job creation for local people,

poverty reduction, enhancement of investment inthis area, cost saving and tax creation for localcommunity or domestically. Besides, they investinto infrastructure, promote technology transfer,stimulate the transition to less carbon-intensive or

low-carbon development, etc. In the environmentaldimension, CDM projects reduce pollutions besides



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GHG emissions, increase renewable energycapacity, enhance the energy security bydiversifying energy sources, and preserve naturalresources by reasonably utilizing natural resourcesand wastes. In the social dimension, they improvethe local health situation, provide training to local

workers, empower women and children, as withaccess to energy they don’t need to spend that muchtime picking wood for fuel, and promote educationas a result of the improved accessibility toeducation resources, and so on. As CDM projectshave a large variety, and each takes place underdifferent circumstances, any CDM project couldcontribute to sustainable development from some ofthe abovementioned aspects or some additionalsides. Those are clearly stated in ‘Description of the

project activity’ in Paragraph 2, Section A inProject Design Document for each CDM project.

2.2.3. CDM Project Cycle There are seven steps for a CDM project from thedesign stage to being issued with CERs (UNFCCC,CDM Project Cycle).

Step 1: Project Design; the project participantsdesign the project according to the Project DesignDocument (hereafter referred to as PDD) developed

by CDM Executive Board, following its relevantapproved emission baseline and monitoringmethodology;

Step 2: National Approval; after the PDD being

completed, the project participants submit it toDesignated National Authority (DNA) which isgranted by a Party to authorize participation inCDM projects, in order to get an approval letter totestify that the proposed project contributes to thecountry’s sustainable development according tonational development priorities, among others;

Step 3: Validation; the Designated OperationalEntity (DOE) which is an individual third partycertifier, validates CDM projects against CDMrequirements;

Step 4: Registration; after validation, theDesignated Operational Entity sends the PDD toCDM Executive Board for registration which is theformal acceptance as a CDM project at United

Nations so as to further get issued CERsaccordingly;

Step 5: Monitoring; once the project has beenregistered as a CDM project, the project

participants are responsible for monitoring actualemission in line with relevant approvedmethodologies;

Step 6: Verification: the Designated OperationalEntity verifies if the emission claimed by project

participants is credible, i.e., if the actual emission isas claimed, and accordingly certifies it.

Step 7: CER Issuance: after verification, theDesignated Operational Entity sends a request forCERs issuance to CDM Executive Board.

CERs, i.e. Certified Emission Reductions,commonly known as ‘carbon credits’, each unit ofwhich is equal to one metric tonne equivalentcarbon dioxide (CO2), expressed as t CO2e.

The CDM Executive Board supervises all the CDM projects under the authorization of the Conferenceof Parties (COP), and makes the final decisionregarding the registration and issuance of CDM

projects.

According to the Term of Reference of the Support

Structure of CDM Executive Board 2012, theUNFCCC Secretariat (hereafter referred to asSecretariat) provides institutional and technicalsupport, including, administering the CDM

processes’ implementation, assessing thecompliance of proposed/registered CDM projectsagainst the requirements, providingrecommendations on the procedures of each CDM

process, etc. In the above listed step 3 and step 7 ofthe CDM project Cycle, i.e., both the Registrationand Issuance steps, the Secretariat does compliancecheck and vetting, and the Executive Board doesvetting. If there is a Party or if three members of the

Executive Board request review forregistration/issuance, the project has to undergoreview.

The Executive Board is assisted by Registration andIssuance Team for both steps. According to theTerm of Reference for the Registration, andIssuance Team (RIT) 2012, the team is constitutedof a group of experts, playing a role in assisting theCDM Executive Board to assess the requests forregistration and issuance of CERs of projects. TheRIT and the Secretariat could hold different viewstowards a project in accordance with their own

judgment, while the CDM Executive Board makesthe final decision. At the CDM Executive Board63

rd meeting, the Secretariat and the RIT proposeddifferent decisions regarding a request for issuanceof a Wind CDM project owing to their differentviews on the estimated PLF. Thus, the Boarddiscussed the issue and in particular discussed themagnitude and permanence of the PLF variationsand the initial PLF estimation in Project DesignDocument (PDD), and afterwards requested theSecretariat to prepare relevant study, which was theorigin of this thesis (refer the first Chapter ofIntroduction).



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2.2.4. CDM Project additionality

The CDM is defined in Article 12 under KyotoProtocol, which specifies several criteria for CDM

project’s eligibility. Three of them are specificallyindicated, which are: i) the participation isvolunteered by approved Parties; ii) the emission

reduction is real and measurable; iii) the emissionreduction is ‘additional to any that would occur inthe absence of the certified CDM project(Paragraph 5, Article 12, Kyoto Protocol)’. In otherwords, additionality to a project implies that afterits implementation, the greenhouse gas emissionsare less than those generated by a plausiblealternative project that would have occurred.

Additionality is a key component for CDM projects. To put the concept easy-to-understand, asdifferent terminologies having been used todescribe it in climate policy literature

(Gillenwater, M, 2012), financial additionality andenvironmental additionality were chosen asexamples to illustrate in the context of CDM.

Financial additionality is often usedinterchangeably with investment additionality. It

basically refers to whether a project is financiallyattractive, or in other words, the investment for the

project would take place, without the revenue from

the CDM credits (Gillenwater, M, 2012). To

conceptualize it, let’s take a solar project as anexample. A solar company is planning to undertakea solar project in a developing country, and 25%

return rate should at least be guaranteed accordingto the budget. If the expected return rate is less than25%, the company would not undertake the project.However, if the project is to be registered as aCDM project, with the crediting, the return ratewould be higher than 25%. Thus, the solar companywould undertake it. This solar project is financiallyadditional. Conversely, if the expected return rate isequal or more than 25%, the project is notfinancially additional as it ‘would have taken place’without revenues from CDM crediting.

Environmental additionality refers to whether a project reduces GHG emissions compared to a baseline. Environmental additionality is measurableand quantifiable. And the reduced emission willfurther be used to calculate the correspondingCERs. To conceptualize it, let’s continue with thesolar project example. To undertake the project, thesolar company needs to calculate the GHGemission and the baseline emission which is theemission that ‘would have taken place with theabsence of this CDM project’. The baselineemission is calculated based on the baselinescenario, which is identified by the solar company(project participant) according to relevant approvedmethodologies and with consideration ofsectoral/national policies and other circumstances,

as well as afterwards verified by DOEs. If theemission from the project is less than the baselineemission, the project is emission additional, in otherwords, environmental additional. And thedifference between the actual emission and baselineemission is the reduced emission. This quantified

reduction is further for the CERs calculation.

The CDM Executive Board issued ‘Tool for thedemonstration and assessment of additionality’,which is used for Project Participants todemonstrate additionality, and also for the DOEsand the Board itself to assess the additionality ofany CDM project.

Y

N

N N n

Y

YOptional

Y NY N

N

Y

Fig.1. the flowchart of steps to demonstrate and assess

additionalitySource: UNFCCC CDM Tools page

Step 0: Is the project is First-of- its-kind project activities?

Step 1: to identify alternatives tothe project according to laws and

regulations

Step 3:Barrier Analysis:i) Is there at least one

barrier preventing theimplementation of

the project withoutthe CDM? And ii) isat least onealternative, other thanthe proposed CDM

project, not prevented by any of the

identified barriers?

Step 2:InvestmentAnalysis:Does the sensitiveanalysis conclude

the project isunlikely to be (themost) financially

attractive?

Step 4: Common practice analysisi) No similar activities can be

observed? ii) if similar activitiesare observed, are there essentialdistinctions between the proposedCDM project activity that can

reasonably be explained?

Project is

additional

Project is non-

additional



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The tool is a step-wise approach and the steps areshown in Figure 1.

Using this tool, the project participants mustexplain ‘why and how the project is additional, andnot the baseline scenario (CDM, PDD)’, by

applying several analyses. Essentially, they need todemonstrate i) in investment analysis step, the proposed project is less financially attractivecompared to the most plausible alternative projector the benchmark; and/or ii) in the barrier analysisstep, the proposed project has to overcome

prohibitive barriers; and iii) in the common practiceanalysis step, the project is not a ‘common

practice’. They need to at first build a baselinescenario and to testify the project itself is not thescenario (World Bank, 2010). Overtime, theinvestment analysis is increased used over barrieranalysis due to its quantitative nature within this

tool (WB, 2010; Schneider, 2011).

The CDM Executive Board also issued ‘Combinedtool to identify the baseline scenario anddemonstrate additionality’ and simplified tools forsmall/micro scale projects. Even with tools foradditionality demonstration, the process is stillcontroversial and has been a subject of debate ininternational climate conferences among differentstakeholders since the establishment of CDM(Schneider, 2011). The main debate is aboutwhether a project is additional or non-additional

based on the information it provided. In the World

Bank’s publication, it is stated that the inability todemonstrate additionality by using the CDM

process is the most common reason that caused therejection of the proposed project at CDM ExecutiveBoard (World Bank, 2010).

The concept of additionality is essential for CDM to preserve environmental integrity which isfundamental in climate regime (Muller B., 2009,World Bank, 2010, Schneider, 2011). Theenvironmental integrity of an off-set mechanismsuch as CDM, refers to that the carbon creditsgenerated from a project accurately correspond to

the actual emission reductions achieved by that project. As CDM is a zero-sum mechanism, itdoesn’t lead to additional emission reduction

beyond the cap which is the emission permittedunder Kyoto Protocol. The carbon credits earnedfrom emission reduction projects in developingcountries are used to offset the same amount ofemissions in developed countries. In other words,through this mechanism, the emissions are virtuallyshifted geographically, instead of reduced. If a

project is non-additional, i.e. business-as-usual, andsells credits to a developed country under CDM, itwill cause the developed country emit more than its

permission without reducing the same amount ofemission in the developing country where the

project takes place, further, cause the increase ofemission over the cap under Kyoto Protocol regime.Therefore, additionality plays a key role to ensurethe environmental integrity of CDM (CarbonMarket Watch, 2008; Muller B., 2009; Streck C.,2010).

2.3. Wind CDM ProjectThe numbers of different project types in table 1shows that up to the end of 2012, wind power CDM

projects accounted for the largest share out of allCDM projects. A total of 2611 wind projects werein ‘CDM Pipeline’ which included 2140 projects instatus of registered with or without issued CERs, 35in process of registration, and 436 at validationstage. Out of the registered 2140 projects, 602 wereissued with CERs which amounted to114213kCERs. Further, there are 41 host countriesspread in Africa, Asia and the Pacific, Europe and

Central Asia, Mid-east as well as Latin America(CDM Pipeline, 2012).

2.3.1. Wind CDM projects’Contributions to SustainableDevelopment The contributions to sustainable development inhost countries are clearly stated in ‘Description ofthe project activity’ in Paragraph 2, Section A inProject Design Document. For wind CDM projects,to summarize, the contributions to sustainabledevelopment in host developing countries are in

ways such as,

(1) from environmental perspective,reducing the greenhouse gas (GHG)emissions primarily CO2 and other air

pollutants, which would otherwise begenerated by fuel-powered plant;

(2) from economical perspective, creating job opportunities during theinstallation and maintenance processof wind power plants;

(3) from social perspective, meeting thedeficit of the electricity and improving

the livelihood in the project area, etc.

Further, regarding any specific case, thecontributions to sustainable development could bemore than abovementioned depending on the givencircumstances. Take the project ‘San CristobalWind Power Project in Ecuador’ (Referencenumber: 1255) as an example, economically, itencouraged a wider use of renewable energytechnologies and provided incentives for privatesector to invest in these technologies, meanwhile, itdemonstrated innovative organizational andadministrative model as the project was constructed

under a public-private cooperation framework;environmentally, it catalyzed the improvement and



- 7 -

transition from diesel power plant and contributed aroadmap for diesel-wind hybrid project in nearbyareas. Take the project ‘Amayo 40MW WindPower Project - Nicaragua’ (Reference number:2315) as another example, it resulted in technologytransfer as it’s the first project that employed this

technology and the wind power equipment provideragreed to train the local workers to guarantee the performance of the facilities.

2.3.2. Issues of Wind CDM ProjectsWind CDM projects were regarded as a safeinvestment. And CDM was observed contributingsignificantly to promoting wind energy, as well asother renewable energy in developing countries, inthe meantime, saving emission reduction costs fordeveloped countries (Pechak O., Mavrotas G.,Diakoulaki D., 2010).

In 2009, the CDM Executive Board shocked thecarbon market by questioning whether some windCDM projects hosted in China met the CDMadditionality requirement. Immediately following,the Executive Board rejected the registration of 10wind projects from China at its 51

st Meeting (EB

51st Meeting Report, 2009) on suspicions that theChinese government was manipulating the feed-intariff of electricity generated by wind power plantsin order to make the wind projects economicallyless viable and, therefore, to meet the CDMadditionality criterion, in order to attract theinternational investment under CDM credits. This

Executive Board’s decision aroused strongreactions. The International Emission TradingAssociation (IETA) and the Global Wind EnergyCouncil (GEWC) heavily criticized the Board forignoring the evidences provided by stakeholders,crossing its mandate boundary of supervision CDM

projects, and failing to substantiate its suspicion(IETA press, 2009). Besides, the Chinesedelegation outright criticized the decision ofrejection of the 10 wind projects’ registration as‘irrational, non-transparent, unfair and interferingwith the national energy policies’ at theCopenhagen Climate Change Conference which

took place soon after that Board Meeting (ChinaOrg, 2009).

The issue of plant load factor in Wind CDM projects has been controversial for a long time.Some professionals/organizations observed that, ina number of wind CDM projects, the Plant LoadFactors in actual operation were higher than thoseestimated by project developers at the design stage.Further, they suspected that those projectdevelopers deliberately underestimated the PlantLoad Factors so as to underestimate the amount ofelectricity, which in turn resulted in making the

projects economically less viable in order to attractinternational investment under the CDM framework.

2.4. Plant Load FactorPlant load factor, is also called capacity factor, loadfactor. In electricity industry, it is the ratio of theactual output of a power plant over a period of time,to its potential output if it had operated at full

nameplate/rated capacity the entire time (WindEnergy Center, 2008). For instance, there is a

power plant with nameplate capacity 1MW, in 1year, if it had operated with full capacity of 1MWfor 24 hours a day for 365 days during the year, theoutput electricity would be 8760MWh (calculatedfrom: 1MW*365(days)*24(hrs/day)); suppose thatin fact the actual output electricity is 6000MWh,then, the plant load factor of this power plant duringthis year is 68% (calculated from: 6000/8760).

Every power plant has its load factor. In wind power projects, the plant load factor is

codetermined and affected by technologicalcharacteristics of installed wind turbines, and windresources like wind speed/ direction/ frequency /density, etc, in the project taken location. As aresult, plant load factor varies from project to

project. According to the wind capacity report(Wind Energy Center, 2008), the typical plant loadfactor of a wind project is ranged from 20% to40%.

2.4.1. Estimated PLFA project developer conducts necessary assessmentand analyses when planning to carry out a wind

project, in order to predict if the outcomes of the project would meet their objectives, financially,socially, etc. Wind CDM project participants needto estimate PLF, thus to estimate the amount ofoutput electricity, combined with other factors, inorder for the investment analysis to testify if this

proposed project meets the CDM additionalitycriterion.

In this study, Estimated PLF is the PLF of a projectestimated at the design stage which is stated in theProject Design Document (PDD).

2.4.2. Actual PLFAccording to the CDM Project Cycle, CERs would

be issued after a CDM project has taken place, project participants have monitored the actualemission reduction of the project, DOEs havevalidated the emission reduction, and finally theCDM Executive Board has agreed to it.

Thus, Actual PLF is the PLF during the operationof a project which has been monitored andvalidated. As there could be one or moremonitoring periods, i.e. one or more operation

periods, for wind CDM projects, the actual PLF isthe final average actual PLF of all the actual PLFsin each monitoring period.



- 8 -

2.4.3. Relative Variation of PLFThe relative variation of PLF is the ratio of thedifference between Estimated PLF and Actual PLFcompared with the Estimated PLF. The calculationmethod is: (Estimated PLF - Actual PLF)/Estimated

PLF.

3. MethodologiesIn this thesis study, several methodologies have

been employed. A database was created, the processof which incorporated data selection including datascreening and mining; data collection and datacalculation which included adoption of electricalmethod of PLF which was illustrated in section 2.4,and adoption of a relative variation concept in thecontext of this study. As well as afterwards the

quantitatively comparative analyses comprisingclassification of data on account of differentreference bases, and elaboration of relevantindicators.

3.1. Database establishmentThe first stage is to set up a comprehensive andaccurate database with necessary information,among which, Estimated and Actual PLF should becontained for further analyses and studies.

The database was basically built from April to July2012 by me after the CDM Executive Board

requested the Secretariat to do the study. Thestudied projects encompassed all the registered asof 26

th July, 2012.

3.1.1. Database selectionThe total of registered wind power CDM projects(hereafter, we refer it as projects) as of 26th July2012 was 1155, among which, 406 projectsreceived CERs.

Out of these 406 projects, there were 4, 43, 55, 59,81, 130 and 23 projects registered in year 2005,2006, 2007, 2008, 2009, 2010, and 2011respectively.

In addition, the hosting countries include:Argentina, Brazil, China, Colombia, Ecuador, India,Korea (Republic of), Nicaragua, Mexico, etc.According to the numbers of projects in differentcountries, China had the largest number of projects,which amounted to 283, and India had the secondlargest number, which amounted to 101, while thetotal projects in all other countries amounted to 22.The projects are presented in table 3, classified byregistration year and by host country.

Year(20) 05 06 07 08 09 10 11 Total

Country

China 1 17 35 42 53 114 21 283

India 0 18 26 16 23 16 2 101

Other 3 8 5 1 5 0 0 22Countries

Total 4 43 66 59 81 130 23 406

Tab.3. Distribution of Wind CDM projects with CERs

issuance based on years and host countries.Source: own elaboration on the basis of UNFCCC CDMdatabase

Out of these 406 projects, around 180 projects weresampled at the beginning, which represented 44%of the total. To ensure the samples objective, theselection was random yet with consideration of the

number distribution in different years and countries.In other words, the samples of each year and eachcountry represented more or less the same

proportion as the samples represented out of total.

To ensure the accuracy of further studies, projectswith incomplete information, or not fullyimplemented were not considered. Some projectsregistered in 2005 or 2006 didn’t have completeinformation, particularly on the estimated netelectricity delivered to the power grid/estimatedoperation hours/estimated PLF. Besides, as many

projects consist of a number of units of individual

wind turbines and took place in several locations,the installation could be by stage. In this case, thecalculation of overall actual PLF couldn’t reflectthe fact. Finally, 150 projects, with necessarydeletion of original samples and addition of other

projects, were sampled and analyzed. Thedistribution of numbers of sample projectsaccording to registration year and host country isshown in Tab. 4 below.

Year(20) 05 06 07 08 09 10 11 Total

Country

China 1 4 12 18 14 34 7 90

India 0 7 8 12 17 6 0 50

Other 1 3 2 1 3 0 0 10Countries

Total 2 14 22 31 34 40 7 150

Tab.4. Distribution of numbers of Wind CDM projectswhich received CERs in sample database.



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3.1.2. Data collectionIn the project database, the information of every

project included: Reference number, Title,Registration date, Host Party, Region, Methodologyapplied, Installed capacity, Estimated net electricity,estimated PLF, Monitoring length, Net electricity in

each monitoring period, Actual PLF in eachmonitoring period, Average actual PLF. All theinformation was publically available on the web ofUNFCCC. Basically, the information was collectedor calculated from Project View Webpage, ProjectDesign Document, and Monitoring Reports. TheProject View Webpage could be assessed on thehomepage of UNFCCC, while the Project DesignDocument and Monitoring Report could bedownloaded from the CDM project search page ofUNFCCC as well.

(1) The information from Project View

WebpageFrom the Project View Webpage, the collectedinformation for each project contains: Reference

Number, Registration date, Host country,Methodology applied. The Project View Webpageis as Fig. 2. It’s accessible from the homepage ofUNFCCC.

Fig.2. The Project View Webpage (UNFCCC CDMProject Cycle Search page).

(2) The information from Registered PDDThe Project Design Document is a masterplate

provided by UNFCCC Executive Board. The CDM project participants need to submit information

required in PDD in order to get projects registeredand issued accordingly. The registered PDD can bedownloaded from the CDM Project Cycle Search

page.

From the registered PDD, the first page of which isas below Fig. 3, the collected information for each

project contains: Installed capacity, Estimatedelectricity generation (EG), Estimated PLF.

Fig.3. The Project Design Document (UNFCCC CDMProject Cycle Search page).

(3) The information from MonitoringReportsFor a project, there could be one or severalmonitoring reports depending on the monitoring

periods. From each Monitoring Report, thecollected information includes: Net electricitydelivered to the grid (measured in MWh), startingand ending date which reflected as length of amonitoring period (measured in day) in database.The monitoring reports could be downloaded fromthe project cycle search webpage. Fig.4 below is thefirst page of a monitoring report.

Fig.4. The project Monitoring Report (UNFCCC CDM

Project Cycle Search page).



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3.1.3. Data cross-checkAfter the database of 150 projects with allinformation listed above had been built, it wasnecessary to run data cross-check, particularly onthe electricity delivered to grid in each monitoring

period and the times of monitoring periods as there

could be several monitoring reports correspondingto several periods. Unconscious missing might havetaken place when collecting information. Thecrosscheck was to ensure the accuracy of thesubsequent calculations and analyses.

The Statistics provided by the Strategy and PolicyDevelopment (SPD) Department at UNFCCCcontained the information of Reference number,Title, Registration date, Host party, Region,Estimated CERs, Length of and Issued CERs ineach Monitoring period of all the 406 wind CDM

projects which have CERs issuances as of 26th July,

2012. The times of monitoring periods are obviousand clear in the statistics. And the electricitydelivered to the grid could be calculated by (CERs/emission factor), according to the CERs stated inthe Statistics and emission factor which was statedin PDD.

3.1.4. Data calculationThe database with necessary information wascollected and crosschecked, including theabovementioned: Reference number, Title,Registration date, Region, Host country,Methodology applied, Installed capacity, Estimated

net electricity, estimated PLF, (each) Monitoringlength, Net electricity in each monitoring periodcollected and crosschecked. The next was tocalculate the Actual PLF and the Relative Variationof PLF.

(1) Calculation of Actual PLFThere are three steps to work out a Actual PLF.

Step 1: to calculate the Gross net electricitydelivered to the grid (measured in MWh): It is sumof electricity delivered to the grid in eachmonitoring period;

Step 2: to calculate the length (measured in day) ofoperation period: It is sum of length of eachmonitoring period;

Step 3: to calculate the overall actual PLF: It isequivalent to the Gross net electricity divided bythe output electricity at rated capacity during this

period. The formula is: Gross net electricity(MWh)/ [total length (days)*Installed capacity(MW)*24(hrs/day)]

(2) Calculation of Relative Variation of PLFAs described in Chapter 2, the Relative Variation ofPLF is the ratio of the difference between Estimated

PLF and Actual PLF compared with the EstimatedPLF, the formula of which is: (Estimated PLF -Actual PLF)/Estimated PLF.

(3) ExampleTo make the calculation process clear, the Wind

CDM project: ‘9MW Wind Power Project in Tamil Nadu by ACC Limited’ with Reference number2679, was taken as an example to show the process.

From the database, the necessary information was picked out for calculation, encompassing:Installed capacity: 9MW;Estimated EG: 24880MWh;Estimated PLF: 31.57%;The length of the 1

st Monitoring period: 378days; Net electricity delivered to the grid in the 1

st

monitoring period: 22793MWh;The length of the 2nd monitoring period: 365days;

Net electricity delivered to the grid in the 2nd

monitoring period: 19499MWh;

Thus, the overall actual PLF: (22793 MWh+19499MWh)/ [(378 days+365 days)*9MW*24hrs/day] =26.35%The relative variation: (31.56% - 26.35%)/31.56%=16%

The database was finalized as an Excel spreadsheetattached as Annex 1. To make it look succinct, itshows the value of estimated/actual PLFs roundedto the second decimal. The database includes 150

wind projects which has been issued CERs at once,registered from 2005 to 2011, hosted by Argentina,Brazil, China, India, Korea (Republic of),

Nicaragua, etc. For each project, the informationcontains: Reference number, Title, Registration date,Region, Host country, Methodology applied,Installed capacity, Estimated net electricity,estimated PLF, (each) Monitoring length, Netelectricity in each monitoring period, Actual PLF,the absolute variation of PLFs, and the relativevariation of PLFs.

3.2. Comparative AnalysisThe study was mainly a comparative study by usingthe created database.

3.2.1. Objects and their meanings incomparisonAs already stated, the Actual PLF was calculated tocompare with the Estimated PLF in order to knowwhether the performance of a project had beenunderestimated or overestimated by the project

participants. If the Estimated PLF is less thanActual PLF, with the result that the estimatedgenerated electricity is less than the actual output

electricity, the project was regarded asunderestimated; conversely, if the Estimated PLF is



- 11 -

greater than Actual PLF, resulting in the estimatedelectricity greater than the actual output electricity,the project was regarded as overestimated. Theunderestimation/overestimation of PLFs gave ageneral view of performance of the Wind powerCDM projects which had been issued with CERs.

After the overview of projects’ performance has been given, it is further necessary to know themagnitude of the over/under performance, theconcepts of which were described as under/overestimation of the PLFs by project developers in the

previous paragraph. In the database, the estimatedPLF varies from project to project, ranging from16%, which is a wind project with referencenumber 1225 in Ecuador, to 48%, the referencenumber of which is 2315 in Nicaragua. Thus, theabsolute difference, i.e., the value of Estimated PLFsubtract Actual PLF, can’t reasonably reflect the

magnitude. For instance, suppose the difference between Estimated PLF and Actual PLF of two projects was equally 5%, one project has estimatedPLF of 20% and the other one 40%, the samedifference of 5% doesn’t mean the same effect to

both projects. Hereby, the concept of relativedifference has been adopted to more effectively andcorrectly reflect the magnitude of under/overestimation.

Moreover, as stated in section 2.2.4, the project participants shall demonstrate the additionality ofthe proposed project in Project Design Document.

The flowchart of tool to demonstrate additionalityis depicted in figure 1. Step 2 - investment analysis- testifies if the proposed project is less financiallyattractive compared to the most plausiblealternative project or the benchmark. This stepincludes a sub-step – sensitivity analysis, whichanalyzes relevant factors to check out if theconclusion regarding the financial attractiveness isrobust to reasonable variations. A plus-minus 10%variation of relevant parameters (such as PLF) isapplied. Hence, if the relative variation falls into acertain range which is between -10% and 10%, inother words, the magnitude of over/under

estimation of performance is between -10% and10%, it is supposed to be acceptable. Otherwise, ifit falls outside this range, the estimation is supposedas defective, particularly, if it is less than -10%, thatis to say, the magnitude of underestimation is morethan 10%, it needs to be questioned if the projecthas properly met additionality criterion.

3.2.2. Basis of comparison

As interpreted in the previous section, thecomparison was at first conducted in all projects togenerate an overview of the performance, as well asmagnitude of over/under estimation of PLFs.

Considering different attributes of wind CDM projects, the following basis was employed.

Firstly, CDM projects are categorized into largescale and small scale groups, for which, themethodological tools to demonstrate additionalityor calculate particular emission are different (CDMMethodology Booklet, 2012). In terms of windCDM projects, the small scale has installed capacity

less than 15MW, while large scale greater than15MW. Capacity of 15MW could be categorizedinto either group depending on which methodologytool it has applied. Therefore, comparison analyseswere separately conducted in small-scale and large-scale groups.

Secondly, as those projects were located worldwide,with regard to the similar geographic characteristicsin the same country or region, while considering

projects’ distribution in different countries (pleaserefer to 3.1.1), comparison analyses wererespectively conducted in China, India, and other

countries as a group.

4. Resul tsThis chapter displays obtained results in accordancewith aforementioned methods for furtherinvestigation and analyses.

4.1. Projects distributionFigure 5 and Figure 6 generate an overview of allwind CDM projects with CERs issuances as of 26

th

July, 2012. Figure 5 shows distribution of projectsin different years. There are 4, 43, 66, 59, 81, 130,and 23 projects registered in year 2005, 2006, 2007,2008, 2009, 2010, and 2011 respectively.

Fig.5. Distribution of Wind CDM projects that receivedCERs by the registration year

Figure 6 presents distribution of projects indifferent countries. It’s clear to see that China andIndia are the major hosting countries. China has thelargest share, which amounts to 283, following byIndia, 101; Brazil and Mexico, 3 equally; Argentina,2; as well as Colombia, Ecuador, Jamaica, Morocco,

4

43

6659

81

130

23

0

20

40

60

80

100

120

140

2005 2006 2007 2008 2009 2010 2011



- 12 -

Nicaragua, Philippines, Viet Nam, 1 equally in eachcountry.

Fig.6. Distribution of Wind CDM projects that receivedCERs by hosting country

4.2. Comparison of all projects

The comparison of Estimated PLF and Actual PLFof all projects in database is shown in Figure 7.

The horizontal axis represents projects, each tick onit corresponding to a project. There are 150 ticks,

that is to say, 150 projects included. And thehorizontal direction is in line with the registrationdate. The vertical axis, with minimum value of 10%and maximum value of 50%, which was adjustedaccording to the need, represents the value of PLF.There are two lines in the figure, the blue onesignifying Estimated PLFs, while the red onesignifying Actual PLFs. Since the number of

projects is integer, the line segment between twodots doesn’t have meaning, only intended to makethe figure clear. Therefore, in this figure, a blue dotand a red dot with the same horizontal value, i.e.,same tick on horizontal axis, correspond to the

same project. Estimated and Actual PLF of the projects are reflected on the vertical axis.

Figure 7 presents a general view of Estimated PLFversus Actual PLF of all Wind CDM projects indatabase. The Estimated PLF ranges from 16% to48%, and 118 projects, accounting for 79% out ofall, have Estimated PLF ranging from 20% to 30%.

As concluded in table 5, there are 33 projects withEstimated PLF lower than Actual PLF, representingthat 22% projects have been underestimated, while117 projects with Estimated PLF greater than

Actual PLF, representing that 78% projects have been overestimated.

Fig.7. Estimated PLF versus Actual PLF of all Wind CDM Projects in database

The relative variations of PLFs are shown in figure8. Similar to figure 7, the horizontal axis represents

projects, and its direction is in line with registration

date. The vertical axis with minimum value of -30%and maximum value of 60%, which were adjusted

according to need, represents the value of RelativeVariation of PLF. The purple line is the function ofthe relative variation of PLF, only valid when its

value on horizontal axis is integer as the number of projects is integer.

283

101

7 3

3

2

1

11

1

11

1

ChinaIndia

Korea (ROK)

Brazil

Mexico

Argentina

Colombia

Ecuador

Jamaica

Morocco

Nicaragua

Philippines

Viet Nam

10%

15%

20%

25%

30%

35%

40%

45%

50%

Estimated PLF Actual PLF



13

Fig.8. Relative variation of PLFs of all Wind CDM Projects in database

It can be seen that the relative variation of PLFsranges from -19% to +49%. As summarized in table5 on the right, there are 58, 5 and 87 projects withrelative variation of PLF (expressed as PLFRV in thetable) between plus-minus 10%, less than -10%,and greater than +10% respectively.

4.3. Comparison based on scales

Following, the comparison is subdivided inaccordance with scale. There are two groups of

projects, small scales and large scales. Figure 9, onthe next page, shows the comparison of EstimatedPLF and Actual PLF of all small-scale projects in

database. This figure is presented in the same wayas that of Figure 7, yet it merely includes small-scale projects rather than all.

Number PercentEstimated PLF<Actual PLF 33 22%

Estimated PLF>Actual PLF 117 78%

-10% ≤ PLFRV ≤ 10% 58 39%

PLFRV < -10% 5 3%

PLFRV > 10% 87 58%

Tab.5. Comparison of Estimated PLF and Actual PLF,and Relative Variation of PLF

There are 39 small-scale projects in total, withestimated PLFs ranging from 16% to 38%, 69% (27

projects) of which ranging from 20% to 30%. 5

projects, representing 13% out of all small-scale projects, were underestimated, while 34 projects,representing 87% were overestimated.

Fig.9. Estimated PLF versus Actual PLF of small-scale Wind CDM Projects

The relative variations of PLFs of small-scale projects are shown in figure 10. This figure is presented the same way as figure 8, only except thisone merely includes small scale projects. 69% of

projects have Estimated PLF ranging from 20% to30%.

It can be seen that the relative variation of PLFsranges from -17% to +48%. As summarized in table6, there are 9, 1and 29 projects with relativevariation of PLF between plus-minus 10%, lessthan -10%, and greater than +10% respectively.

-19%

49%

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

60%

Relative Variation of PLFs

10%

15%

20%

25%

30%

35%

40%

45%

50%




14

Fig.10. Relative Variation of PLF of small-scale Wind CDM Projects

Number PercentEstimated PLF<Actual PLF 5 13%


-10% ≤ PLFRV ≤ 10% 9 23%

PLFRV < -10% 1 3%

PLFRV > 10% 29 74%

Tab.6 . Comparison of Estimated PLF and Actual PLF,and Relative Variation of PLF of small-scale projects

For large-scale projects, in the same way as for thesmall-scale ones, figures 11 and 12 show theEstimated PLF versus Actual PLF, and Relative

Variation of PLF of large-scale projects. These twofigures give an intuitive and general view of thedifferences. The relevant data has been summarizedin table 7. It is observed that there are 111 largescale projects, among which, 28 projects,

accounting for 25% were underestimated, while 83 projects, accounting for 75% were overestimated.In addition, 49, 4, 58 projects have PLF relativevariation between plus-minus 10%, lower than -10% and more than 10%, respectively.

Number Percent

Estimated PLF<Actual PLF 28 25%


-10% ≤ PLFRV ≤ 10% 49 44%

PLFRV < -10% 4 4%

PLFRV > 10% 58 52%

Tab.7. Comparison of Estimated PLF and Actual PLF,and Relative Variation of PLF of large-scale projects

Fig.11. Estimated PLF versus Actual PLF of large-scale Wind CDM Projects

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

60%

Relative Variation of PLF

10%

15%

20%

25%

30%

35%

40%

45%

50%




15

Fig.12. Relative Variation of PLF of large-scale Wind CDM Projects

4.4. Comparison based on

countries

This section is going to demonstrate the comparisonresults according to hosting countries. There are

three projects’ groups, namely, China, India, andother countries. Figures showing comparisons of

Estimated and Actual PLF, and Relative variationof PLF present in the same way as those in previoustwo sections, only except they include different

projects.

Fig.13. Estimated PLF versus Actual PLF of Wind CDM Projects in China

To avoid repeating the explanation of meanings ofthose figures themselves which were detailed

explained in section 4.2, we are now just going tointerpret them and fetch information. Figure 13 and

14 are applied to projects hosted in China, figure 15and 16 for India, while figure 17 and 18 for other

countries. The relevant information fetched fromthe figures has been summarized in table 8.

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

60%


10%

15%

20%

25%

30%

35%

40%

45%

50%




16

Fig.14. Relative Variation of PLF of Projects in China

Fig.15. Estimated PLF versus Actual PLF of Projects in India

Fig.16. Relative Variation of PLF of Projects in India

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

60%


10%

15%

20%

25%

30%

35%

40%

45%

50%


-30%

-20%

-10%

0%10%

20%

30%

40%

50%

60%




17

Fig.17. Estimated PLF versus Actual PLF of projects inother countries

Fig.18. Relative Variation of PLF of Projects in othercountries

China Percent India Percent Others Percent

Estimated PLF<Actual PLF 25 28% 7 14% 1 10%

Estimated PLF>Actual PLF 65 72% 43 86% 9 90%

-10% ≤ PLFRV ≤ 10% 42 47% 12 24% 4 40%

PLFRV < -10% 4 4% 1 2% 0 0

PLFRV > 10% 44 49% 37 74% 6 60%

Tab.8. Comparison of Estimated PLF and Actual PLF, and Relative Variation of PLF in China, India and other countries

From figure 13, it can be seen that the EstimatedPLF of the projects hosted in China range from19% to 34%. 78 projects, accounting for 87% inthis group, have Estimated PLF ranging from 20%to 30%. As summarized in table 7, 28% projectshave been underestimated, while 72% projects have

been overestimated. Further, 4% of projects have

relative variation lower than -10%.

Figure 15 reveals that the range of Estimated PLFof projects located in India is between 17% and37%. And there are 39 projects, which account for78% in this group, with Estimated PLF falling

between 20% and 30%. As concluded in table 8, thePLFs of 14% projects were underestimated, while86% were overestimated. Moreover, 2% of projectshave relative variation lower than -10%.

As the projects hosted in other countries exceptChina and India are only 10 in this database, it’s

very clear to get the general view of it from figure17. The Estimated PLF varies a lot from 16% to48%. As the hosting countries in this group comefrom different continents, the projects in this grouphave more individual characteristics. Only 1 projecthas Estimated PLF between 20% and 30%.However, in terms of under/overestimation, 1

project has been underestimated while 9overestimated. And no project has relative variationof PLF less than -10%.

5. DiscussionThe results in the previous chapter show that, ingeneral wind CDM projects with CERs issuanceincreased in number during these years of the first

commitment period. The projects in 2011 were notso many which is reflected in figure 5 as theywould only be issued after monitoring of theiroperation, in other words, as of the establishment ofdatabase, the majority of them hadn’t finished thefirst monitoring period.

With the increase in number of the registered windCDM projects, along with the controversy of theadditionality itself, the suspicion of the reliability ofwind CDM projects’ additionality criterion cameout. Excluding the tariff things which are politicaland controversial all the time, Plant Load Factorissue is more traceable as the Estimated PLF isstated in PDD clearly except a few ones registeredin early year like 2005 or 2006 which are notincluded for this study, and the actual PLF could becalculated from relevant information publicallyavailable in monitoring reports. Both kinds of PLFsare the fundamental factors for this issue.

5.1. Discussion on Underestimationand OverestimationPLF is a complex trait, determined and affected bythe technological characteristics of the windturbines, and wind resources such as wind speedand wind direction in project taken location. Thus,the prediction beforehand can’t be precise. Fromthis study, most projects have Estimated PLFfalling between 20% and 30%. And on average, theEstimated PLF in small-scale group is lower thanthat in large-scale group.

Overall, from this study, PLFs of 22% of projectshave been underestimated at the design stage, while

10%

15%

20%

25%

30%

35%

40%

45%

50%

Estimated PLF Actual PLF-30%-20%-10%

0%

10%20%30%40%50%60%

Relevant Variation of PLF



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the PLFs of 78% of projects have beenoverestimated. Even the projects withunderestimated PLF are the minority, 22% of

projects are still a big amount. From this point, it isreasonable that people have observed some WindCDM projects had underestimated PLF, further

speculated that some project developers mightdeliberately lower the PLF at the designing stage inorder to make the project less profitable in order tomeet the additionality criterion under CDM.

Considering the subdivision of projects on the basisof scale, it can be seen that underestimation rate ofsmall-scale projects is lower than that of large-scale

projects, 13% and 25% respectively, which are bothminorities in each group though.

For projects hosted in China, India and all othercountries, 28%, 14% and 10% of projects in each

group respectively were underestimated. In eachgroup, the underestimated projects belong to theminorities. Projects in China have a higherunderestimation rate compared with that of bothother groups. From this perspective, along with thatChina has the largest share of wind CDM projects,among other reasons; it is understandable thatPLF/additionality issue has been raised at someextent.

5.2. Discussion on Relative Variation ofPLFsAs a predicted PLF can’t be exactly the same as

that in operation, the estimated PLF is either loweror higher than actual PLFs. In other words, the PLFis either under or over estimated beforehand.Therefore, it is unwarrantable to judge if a projectmeets additionality criterion only depending on theunder/over estimation of PLF in terms of PLF issue.This, however, is actually the judgmentfundamentally made by many people.

It is thus vital to know the magnitude of thevariation between both PLFs of a project. In thisstudy, the magnitude of that variation is defined asrelative variation of PLFs, and in line withsensitivity analysis, the range of -10% and +10% issupposed to be acceptable. In this study, the highestrelative variation is 49%, while the lowest is -19%.

39% of all projects in this study have relativevaration of PLFs falling in the range of plus andminus 10%, hereby, the Estimated PLFs of those projects are supposed to be generallyunquestionable. Besides, as the overestimation ofPLF doesn’t matter in terms of additionality issue,if the relative variation is more than 10%, where58% of projects are in this case, the estimated PLFis regarded inaccurate, yet not affecting theadditionality criterion. Except those two types,there are only 3% of projects left, with relative

variation of PLFs lower than -10%. These projects,rather than the projects with underestimated PLFswhich account for 22% of all, should be the originof suspicions regarding additionality issue. As the

proportion is small, it can’t be a powerful argumentregarding deliberately underestimating PLFs in

wind CDM projects to underestimate the output power in order to make it less economicallyattractive, further, to meet the additionalitycriterion. Therefore, generally, there is no strongevidence showing the CDM’s additionality feature

being affected, in turn, the environmental integrity being affected in wind CDM projects (refer to2.2.4),

In small-scale and large-scale projects, 23% and44% of each group respectively have acceptablePLFs estimation with relevant variation between

plus-minus 10%. Besides, 3% and 4%, both small

proportions more or less the same as that of all projects, of projects in each group respectively,have underestimated PLF with magnitude of lessthan -10%. Hereby, it can be seen that the PLFissue is not particularly notable either in small-scale

projects or large-scale projects.

As divided in accordance with hosting countries,47%, 24% and 40% of projects hosted in China,India, and other countries respectively haveacceptable PLF relative variation. Moreover, veryfew projects in each group, have underestimatedPLF with magnitude of less than -10%. Therefore,

it is obvious that the PLF issue is not particularlyremarkable in any country.

6. ConclusionFrom the study several conclusions came out. Atfirst, in terms of the physical characteristics, mostwind CDM projects have Estimated PLFs between20% and 30%, and PLF of a small-scale project isless than that of a large-scale project on average.Secondly, the minority of wind CDM projects haslower Estimated PLF than Actual PLF. Thirdly,

there should be no concerns on the estimation of thePLF value of the registered CDM projects,regardless of scales, or hosting countries, from theadditionality point of view. Further, since theadditionality feature has been ensured, theenvironmental integrity is also ensured for WindCDM projects.

7. AcknowledgementMy hearty gratitude goes to EU, who fully fundedmy master study in Europe. And I’m very

privileged to prepare part of this study withUNFCCC, where colleagues shared their insightswith me both personally and professionally,



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particularly, Maxim, Roy and Pedro who providedinnovative suggestions when plenty of uncertaintiescame out in the process of database establishmentand data elaboration. I also feel very thankful to mythesis supervisor, Eva, who was always supportive,and my thesis evaluator, Lars, who provided critical

suggestions so that the thesis could be moreintegrated. Last but not least, my utmost love andthanks go to families and friends, who are alwaysthere, backing me up to go through all the ups anddowns.

8. ReferencesCarbon Market Watch, Additionality and Baselines,

2008, Assessed at

<http://carbonmarketwatch.org/category/additionality-and-baselines/>

China Org, UN COP15 Copenhagen ClimateChange Conference, Review on Chinese wind

power projects, 2009, Assessed at < http://www.china.org.cn/environment/Copenhagen/2009-12/10/content_19040396.htm >

Gillenwater, M, What is Additionality: A long

standing problem, January 2012, Greenhouse GasManagement Institute, Princeton University,Assessed at: < http://ghginstitute.org/wp-content/uploads/content/GHGMI/AdditionalityPaper_Part-1(ver3)FINAL.pdf >

IETA (International Emission TradingAssociation), Press release, Blow Right off Course?

CDM Executive Board Turns Against Renewable

Energy Development, 2009, Assessed at < http://www.ieta.org/index.php?option=com_content&view=article&id=117:blown-right-off-course?-cdm-executive-board-turns-against-renewable-energy-development&catid=21:archived-press-releases&Itemid=107 >

Muller B., Additionality in Clean Development

Mechanism - Why and What, March 2009, Oxford

Institute for Energy Studies EV 4, assessed at: < http://www.oxfordclimatepolicy.org/publications/d ocuments/EV44.pdf >

Pechak O., Mavrotas G., Diakoulaki D., Investigating the Role of the Clean Development

Mechanism within the Global Green Energy

Market: The Case of Wind Energy, 2010, IEEE.

Schneider L., Assessing the additionality of CDM

projects: practical experiences and lessons learned ,2011, Climate Policy.

Shreck C., The Concept of Additionality under theUNFCCC and the Kyoto Protocol - Implications for

Environmental Integrity and Equity, 2010,University College London.

UNEP Riso Center, CDM Pipeline, The distribution

of the project among the project types, 2012,Assessed at < http://www.cdmpipeline.org/cdm-

projects-type.htm >

UNFCCC, CDM, CDM Benefits, 2012, Assessed at<http://cdm.unfccc.int/about/dev_ben/index.html>

UNFCCC, CDM, CDM Executive Board 63rd

Meeting, 2012, Assessed at <https://cdm.unfccc.int/Meetings/MeetingInfo/DB/R CFV7EBNTD03U54/view>

UNFCCC, CDM, CDM Project Cycle Search

webpage, assessed at:<http://cdm.unfccc.int/Projects/projsearch.html>

UNFCCC, CDM, Executive Board of Clean

Development Mechanism 51st Meeting Report,

2009, Assessed at<http://cdm.unfccc.int/EB/051/eb51rep.pdf>

UNFCCC, CDM, Project Design Document of

Project 1255: San Cristobal Wind Power Project

in Ecuador , assessed at: < http://cdm.unfccc.int/Projects/DB/SGS-UKL1185291192.39/view >

UNFCCC, CDM, Project Design Document of

Project 2315: Amayo 40MW Wind Power Project – Nicaragua, Assessed at<http://cdm.unfccc.int/filestorage/j/z/QK078TFCA

N9DZHX6RSPYJ5L2B4VI1O.pdf/eb72_meeting%20report.pdf?t=eE98bWp5NWFwfDDoZgcNlnA6E8J77TOtnCRF>

UNFCCC, CDM, Term of Reference of the Support

Structure of the CDM Executive Board (Version

03.1), 2012, Assessed at :<https://cdm.unfccc.int/Reference/Procedures/panels_proc02.pdf>

UNFCCC, CDM, Term of Reference for Registration and Issuance Team (08 Version),

2012, Assessed at:<http://cdm.unfccc.int/Reference/Procedures/reg_pr oc02.pdf >

UNFCCC, Kyoto Protocol to United Nations

Convention to Climate Change, 1998, Assessed at<http://unfccc.int/resource/docs/convkp/kpeng.pdf>

UNFCCC, CDM, What is CDM? Assessed at:<http://cdm.unfccc.int/about/index.html>

http://carbonmarketwatch.org/category/additionality-and-baselines/



http://www.china.org.cn/environment/Copenhagen/2009-12/10/content_19040396.htm


http://www.cdmpipeline.org/cdm-projects-type.htm


https://cdm.unfccc.int/Meetings/MeetingInfo/DB/RCFV7EBNTD03U54/view


http://cdm.unfccc.int/Projects/projsearch.html

https://cdm.unfccc.int/Reference/Procedures/panels_proc02.pdf


http://cdm.unfccc.int/Reference/Procedures/reg_proc02.pdf


http://unfccc.int/resource/docs/convkp/kpeng.pdf

http://unfccc.int/resource/docs/convkp/kpeng.pdf





http://cdm.unfccc.int/Projects/projsearch.html











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Wind Energy Center, Wind Power: Capacity

Factor, Intermittency, and what happens when the

wind doesn’t blow? 2009 , University ofMassachusetts Amherst

World Bank, 10 Years of Experience in Carbon

Finance: Insights from working with the Kyoto Mechanisms, 2010, Assessed at :< http://siteresources.worldbank.org/INTCARBONFI

NANCE/Resources/10_Years_of_Experience_in_CF_August_2010.pdf >

http://siteresources.worldbank.org/INTCARBONFINANCE/Resources/10_Years_of_Experience_in_CF_August_2010.pdf








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Annex 1:



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Wind Power CDM Projects

Documents

Transcript of Wind Power CDM Projects