PDD Tres Hermanas Trabajo

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PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Vers ion 03

CDM Executive Board

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CLEAN DEVELOPMENT MECHANISM

PROJECT DESIGN DOCUMENT FORM (CDM-PDD)Version 03 - in effect as of: 28 July 2006

CONTENTS

A. General description of project activity

B. Application of a baseline and monitoring methodology

C. Duration of the project activity / crediting period

D. Environmental impacts

E. Stakeholders comments

Annexes

Annex 1: Contact information on participants in the project activity

Annex 2: Information regarding public funding

Annex 3: Baseline information

Annex 4: Monitoring plan


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SECTION A. General description of project activity

A.1. Title of the project activity:

Title:Tres Hermanas Wind FarmVersion:Version 1.0Date:November 7, 2011

A.2. Description of the project activity:The project activity involves the development of a wind power facility comprising an installed capacity of90 MW. The facility will be connected to the Peruvian grid through the Peruvian National InterconnectedElectric Grid (Sistema Elctrico Interconectado Nacional, SEIN).

The proposed project activity is the installation of a new grid-connected renewable power plant/unit,according to the methodology ACM002 / Version 12.1.0. The baseline scenario is the following:

Electricity delivered to the grid1 by the project activity would have otherwise been generated by the

operation of grid-connected power plants and by the addition of new generation sources, as reflected in

the combined margin (CM) calculations described in the Tool to calculate the emission factor for an

electricity systemVersion 02.2.1.

Prior to the start of the implementation of the project activity no other facilities of any kind exist in thearea where the wind farm is going to be installed. These lands do not have any specific current use, so the

project will not affect any human activity.

The scenario prior to the implementation of the project activity is considered as the baseline scenario.

Currently the fuel mix for the production of energy is based on a mix between fossil fuels and hydropower plants; in this scenario the consumption of fossil fuels generates a considerable amount ofGreenhouse Gas (GHG) emissions to the environment. Without the development of the project activitythe scenario discussed would remain the same.

The proposed project activity reduces the emissions of GHG by generating ecosystem friendly electricitythrough wind turbines, which will substitute electricity from fossil fuel based power plants (baselinescenario).

On the other hand, even when renewable energy options have to face regulatory, economic and technicalobstacles hindering their development; it is necessary to consider them to reduce the high GreenhouseGas (GHG) emissions that are causing irreversible damages to the environment.

Also the development of the Tres Hermanas Wind Farm will allow the achievement of several objectiveswhich represent a contribution to the sustainable development at local, regional and global levels. Someexamples of these contributions are:

1In this case the grid is the National Interconnected Electric Grid (SENI)


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Environmental sustainability:

Use of renewable energy resources for electricity generation which otherwise would have beengenerated through fossil fuels based power plants contributing with a reduction in GHGemissions.

Impulse of the environmental sustainability by diminishing exploitation and exhaustion ofnatural, finite and non-renewable resources, like coal and natural gas.

Not generating any significant negative environmental impact during the construction andimplementation of the project.

Economic and social sustainability:

Creation of new employment opportunities in the area: mainly during the construction phase butalso along the lifetime of the wind farm because of maintenance and operation stages.

Some regions within the country do not have energy generation infrastructure; the project activitywill contribute to the improvement of the current situation satisfying the growing demand forelectricity and making possible the energy distribution to more isolated zones, improving the lifequality of the Peruvian folk.

According to the information mentioned before, the project will contribute to the development of thecountry and will also serve as an example to demonstrate that in Latin America the wind energy plants are

becoming also a suitable commercial option, encouraging the development of similar projects to supplyenergy from renewable sources, reducing the Greenhouse Gas (GHG) emissions to the environment evenmore.

A.3. Project participants:

Name of Party involved (*)((host) indicates a host Party)

Private and/or publicentity(ies) project participants(*) (as applicable)

Kindly indicate if the Partyinvolved wishes to beconsidered as projectparticipant (Yes/No)

Peru (Host)Parque Elico Tres Hermanas

S.A.C. (private entity)No

United KingdomCO2Global Solutions

International S.A. (Privateentity)

No

(*) In accordance with the CDM modalities and procedures, at the time of making the CDM-PDD public

at the stage of validation, a Party involved may or may not have provided its approval. At the time ofrequesting registration, the approval by the Party(ies) involved is required.

Table1.Project Participants

A.4. Technical description of the project activity:

A.4.1. Location of the project activity:

A.4.1.1. Host Party(ies):

Peru


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A.4.1.2. Region/State/Province etc.:

Nazca province.

A.4.1.3. City/Town/Community etc.:

Marcona District, Ica Department.

A.4.1.4. Details of physical location, including information allowing theunique identification of this project activity (maximum one page):

The wind farm will be located in Nazca province with the following coordinates:152300 S and750340 W

Figure1. Location of the Project activity

A.4.2. Category (ies) of project activity:

Sectoral Scope 1. Energy Industries (renewable - / non-renewable sources)

A.4.3. Technology to be employed by the project activity:

The project activity involves the development of a wind power facility comprising an installed capacity of90 MW. This activity will generate energy that is considered clean and this energy generated willreplace the energy generated by the actual scenario.

The current situation in the Peruvian grid is that the generated energy is produced on one hand, throughthe consumption of fossil fuels (residual diesel, coal and natural gas), and on the other through theoperation of hydro power plants. This scenario is considered as the baseline and also as the scenario priorto the start of the project activity.

In the current scenario the main source of the GHG emissions are the power fuel plants. These plantsconsume different types of fossil fuels for energy production, and due to the growing energy demand inPeru, these fossil fuel plants will continue to operate and consume more fossil fuels in order to supply thatenergy demand.

In order to mitigate GHG emissions it is necessary to develop new projects that could generate energywithout producing those emissions, such as energy projects that involve the use of renewable resources(solar, hydro, wind).


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This project activity will reduce the emission of Greenhouse Gases (CO 2, please refer to section B.3)through the substitution of fossil fuels (the main producers of greenhouse gases) by renewable energysources (which are considered to have an emission factor of 0 tCO2/MWh) for power generation. Doingthis, the project activity will generate clean energy and will substitute the energy generated by fossilfuels.

The above mentioned project activity consists in a 90MW wind power facility, which is expected toproduce 415.723 GWh with an average plant load factor of 52.73% (4,619 equivalent hours)2. Theminimum expected operational lifetime is 20 years3.

The Project will be equipped with G-80 2.0 MW turbines manufactured by Gamesa; the selection of theseturbines was based on suitability studies for the particular strong and continuous wind conditions that

prevail at the projects site and the general region, as well as on a maintenance and operation criterion.

The design power generation per turbine will be 2000 kW.

Total Power Capacity 90 MW

Rated Power per turbine 2.0 MW

No. of turbines 45 -

Equivalent annual operating hours 4,619 hr

Annual Production 415,273 GWh

Plant load factor 52.73 %

Transmission line Voltage 220 kV

Diameter 80 m

Swept area 5,027 m2

Hub Heigth 78 mTable 2.Power plant characteristics

For the projects implementation, an arrangement consisting of 45 Gamesa G-80, each of 2.0 MW designcapacity turbines has been selected. Each one will be mounted on a 78 m steel tower and will have a rotordiameter of 80 m.

Real-time information about weather monitoring stations and electrical substation operation conditionswill be gathered and then displayed on the computers monitor in the control room.

The projects implementation through training for operation and maintenance sessions, besides theindividual benefits of the wind farm (clean electricity production) will represent a knowledge and

2 Concession Contract for Energy Supply, page 25 stipulates the plant load factor that the project developercompromises with the Ministry of Energy and Mines. This value is validated according the "Guidelines for thereporting and validation of Plant Load Factors Version 01.

Than mentions the following:

3. The plant load factor shall be defined ex-ante in the CDM-PDD according to one of the following three options:

(a) The plant load factor provided to banks and/or equity financiers while applying the project activity for project

financing, or to the government while applying the project activity for implementation approval.

3Wind Measurement International. Operational and Maintenance Costs for Wind Turbines Available at:http://www.windmeasurementinternational.com/wind-turbines/om-turbines.php
http://www.windmeasurementinternational.com/wind-turbines/om-turbines.phphttp://www.windmeasurementinternational.com/wind-turbines/om-turbines.phphttp://www.windmeasurementinternational.com/wind-turbines/om-turbines.php


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technological transfer to the host country. Also as no wind farms have been built in the country, it is to beexpected that when built, the project will awaken the interest of the Peruvian folk for this kind oftechnologies, spreading the technology and knowledge throughout the potential wind farm regions ofPeru.

A.4.4. Estimated amount of emission reductions over the chosen crediting period:

The crediting period commences on January 1, 2015 with total emissions reductions of 2,003,575 tons ofCO2.

YearAnnual estimation of emissionreductions in tonnes of CO2e

2015 286,225

2016 286,225

2017 286,2252018 286,225

2019 286,225

2020 286,225

2021 286,225

Total estimated reductions (tonnes ofCO2e)

2,003,575

Total number of crediting years 7 Years

Annual average over the creditingperiod of estimated reductions (tonnes of

CO2e)286,225

Table 3.Emissions reduction.

A.4.5. Public funding of the project activity:

No public founding is used for this project activity

SECTION B. Application of a baseline and monitoring methodology

B.1. Title and reference of the approved baseline and monitoring methodology applied to theproject activity:

For the project activity, the approved baseline methodology used is ACM0002 Version 12.1.0:

Consolidated baseline methodology for grid-connected electricity generation from renewable sources.

This methodology also refers to the latest approved versions of the following tools:

Tool to calculate the emission factor for an electricity system (ver. 02.2.1).

Tool for the demonstration and assessment of additionality (ver. 05.2.1).

Combined tool to identify the baseline scenario and demonstrate additionality (ver. 3.0.1).

Tool to calculate project or leakage CO2emissions from fossil fuel combustion (ver. 2).

B.2. Justification of the choice of the methodology and why it is applicable to the projectactivity:

The methodology ACM0002 ver. 12.1.0 is applicable to:


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Grid-connected renewable power generation project activities that (a) install a new power plant at a

site where no renewable power plant was operated prior to the implementation of the project activity

(green field plant)

The proposed project activity involves the installation of a new power plant for renewable electricitygeneration that will be connected to the Peruvian national grid.

The project activity is the installation, capacity addition, retrofit or replacement of a power plant/unit of

one of the following types: hydro power/unit (either with a run-of-river reservoir or an accumulation

reservoir), wind power plant/unit, geothermal power plant/unit, solar power plant/unit, wave power

plant/unit or tidal power plant/unit

The project activity consist in the installation of a wind power plant unit, therefore, the project activity

complies with the applicability condition.

In the case of capacity additions, retrofits or replacements (except for wind, solar, wave or tidal power

capacity addition projects which use Option 2: on page 11 to calculate the parameter EGPJ,y): the

existing plant started commercial operation prior to the start of a minimum historical reference period of

five years, used for the calculation of baseline emissions and defined in the baseline emission section, and

no capacity expansion or retrofit of the plant has been undertaken between the start of this minimum

historical reference period and the implementation of the project activity

The project activity consist in the installation of a new wind power plant, therefore, the last condition ofapplicability does not apply because the project activity doesnt consist in a capacity addition, retrofit orreplacement.

In case of hydro power plants, one of the following conditions must apply:

The project activity is implemented in an existing reservoir, with no change in the volume ofreservoir.

The project activity is implemented in an existing reservoir, where the volume of reservoir isincreased and the power density of the project activity, as per definitions given in the Project

Emissions section, is greater than 4 W/m2

The project activity results in new reservoirs and the power density of the power plant, as perdefinitions given in the Project Emissions section, is greater than 4 W/m2.

This applicable condition is in the case of a hydro plant, for this reason this condition does not apply to

this project activity.

The methodology is not applicable to the following:

Project activities that involve switching from fossil fuels to renewable energy sources at the siteof the project activity, since in this case the baseline may be the continued use of fossil fuels at

the site.

Biomass fired power plants.

Hydro power plants that result in new reservoirs or in the increase in existing reservoirs wherethe power density of the power plant is less than 4 W/m2.


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The projects activity is neither a fired power plant nor a hydro power plant; also it does not use anybiomass for its operation. It consists in the installation of a new wind farm (which does not use any fossilfuels) to generate clean electricity.

B.3. Description of the sources and gases included in the project boundary:As indicated in the methodology ACM0002 Version 12.1.0, the project boundary will cover any CO 2emissions from electricity generation by fossil fuel fired power plants that is displaced by the projectactivity.

Source Gas Included? Justification/Explanation

Baselin

e CO2 emissions from electricity

generation in fossil fuel fired powerplants that are displaced due to theproject activity.

CO2 Yes

Main emission source. Allpower plantsinterconnected to the

Peruvian grid areincluded.

CH4 No Minor emission source.

N2O No Minor emission source.

ProjectActivity

For geothermal power plants, fugitiveemissions of CH4 and CO2 from noncondensable gases contained ingeothermal steam.

CO2 NoNot applicable to theproposed project activity.

CH4 NoNot applicable to theproposed project activity.

N2O NoNot applicable to the

proposed project activity.

CO2 emissions from combustion offossil fuels for electricity generation insolar thermal power plants andgeothermal power plants.



N2O NoNot applicable to theproposed project activity.

For hydro power plants, emissions ofCH4 from the reservoir.



N2O No

Not applicable to the

proposed project activity.Table 4.Sources and gases included in the project boundary

The projects flow diagram is shown next:


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From the above, and in consistence with the version ACM0002 ver. 12.1.0 for the cases of installationof a new grid-connected renewable power plant/unit. The baseline scenario is defined as the Electricitydelivered to the grid by the project activity that would have otherwise been generated by the operation of

grid-connected power plants and by the addition of new generation sources, as reflected in the combined

margin (CM) calculations described in the Tool to calculate the emission factor for an electricity

system.

B.5. Description of how the anthropogenic emissions of GHG by sources are reduced belowthose that would have occurred in the absence of the registered CDM project activity (assessmentand demonstration of additionality):

The proposed projects activity will reduce GHG emissions due to the electricity generation that in theabsence of the project would be generated by fossil fuel based technologies and would be consumed by

the national grid. The expected reductions from the project are 2,003,575 tons of CO 2e during the 7 yearscrediting period.

The next table shows the official forecast of the Peruvian electricity generation mix (MW)5.

*The capacity of wind power is not provided in the study due to it slow capacity

Technology* 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 % 2020

Thermal 3,063 3,063 3,161 3,679 3,668 4,436 4,867 4,867 4,867 6,407 6,407 55.3%

Hydro 2,882 3,062 4,122 5,162 5,162 5,162 5,162 5,162 5,162 5,162 5,162 44.7%

Total 5,945 6,125 7,283 8,841 9,030 9,598 10,029 10,029 10,029 11,569 11,569 100.0%

Table 5.New capacity generation forecast (MW).

As it can be seen in the table, the renewable energy is based on hydro power plants and no wind energy isconsidered in the forecast because this technology is not attractive in the country. It is important toremark that is very unlikely that the wind power facility projected in this forecast will become a reality ifit does not receive an incentive for its development, such as the CERs from CDM projects.

Analysis of the additionality of the project

At the present time, in Peru, the wind power generation is not an attractive investment in a business as-usual-scenario. However, in order to demonstrate that the proposed project activity is not the baselinescenario, the Tool for demonstration and assessment of additionality ver. 05.2.1will be applied.

The steps to demonstrate that the project activity is not the baseline scenario will be listed next:

5Ministry of Energy and Mines Ministerio de Energa y Minas. Plan referencial de electricidad 2008-2017. Chart3.28 page 171.


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Step 1. Identification of alternatives to the project activity consistent with current laws andregulations

Definition of alternative scenarios to the project activity that otherwise could be implemented in absenceof the project activity.

Sub-step 1a. Define alternatives to the project activity.

The project activity consists in clean energy generation that will supply the Peruvian electricity grid. Thealternatives would be that other power plants provide the electricity to the grid; among these, thefollowing are mentioned:

1. The proposed project activity is not undertaken as a CDM project activity; it would be a wind-

based electrical power station of 90 MW with a plant load factor 52.73 % which does not obtainCERs from a CDM registry.

This option will bring environmental benefits, but the project would not be profitable without thesupport of CDM incentives. A wind farm requires a large initial investment and for this reason itrequires the support of CDM incentives.

2. Continuation of the current situation: Parque Elico Tres Hermanas S.A.C. does not implementthe project; the customers will continue purchasing the electricity from the National grid(Baseline Scenario).This scenario consists in the continuation of the current practices, which is the use of carbonintensive electricity sources in the isolated system, and the non-implementation of the Proposed

Project Activity as reflected in the combined margin calculations.

Under this scenario the increasing demand for electricity of the national grid will be met by amixture of existing installed capacity and new capacity additions. According to historical data,the electricity demand will increase with an average of approximately 7% every year, thereforenew power plants (renewable- no renewable) will be built in order to satisfy that demand. Thetable 5 shows that in the year 2020 more thermal than hydro plants will be built in order to satisfythe Peruvian electricity grid.

3. The same power generation supplied through mini-hydro plants.This alternative scenario consists in the installation of a different renewable source into thePeruvian Electrical System (SEIN). The renewable energy units to install would be new mini-

hydro plants, with the same configuration of the proposed project activity.

Due to the size of the project activity, hydropower plants could only be a viable alternative ifthere were either a group of mini-hydro power plants or at least one large hydropower plant to beinstalled.However, in the region where the project will be installed there are no resources toinstall a new mini-hydro plant.

4. The same power generation through power plants from fossil fuels.This alternative scenario consists in the installation of carbon fuel based power plants into the

National Interconnected Electrical System (SEIN).The development of a fossil fuel plant couldnot be considered as an alternative because the following:


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Parque Elico Tres Hermanas S.A.C. is a company dedicated to the construction and

operation of wind farms. The construction of a thermoelectric power plant is not thephilosophy of the company.

The construction of a fossil power plant is not considered as a CDM project, becausethere is not any reduction of GHG emission due to the project activity.

The electricity generation through power plants from fossil fuels is not possible because ParqueElico Tres Hermanas S.A.C. is not interested in the generation of energy trough carbon intensivesources, therefore this scenario is eliminated.

Sub-step 1b.Consistency with mandatory laws and regulations.

In Peru, the Ministry of Energy and Mines Ministerio de Energa y Minas (MINEM) is the entity in

charge of appointing Independent Producers of electrical energy. Therefore, last September 30, 2011 theproject Tres Hermanas Wind Farm obtained the approval to provide renewable energy to the NationalInterconnected Electric System.

Other alternative that was mentioned in the sub-step 1a is the implementation of a mini-hydro powerplant. National regulations of the host country approve the construction of such installations.

However, Parque Elico Tres Hermanas S.A.C is a company whose core business is the development ofrenewable energy (wind) projects as is stated in its incorporation deed where the companys purpose isestablished. This purpose includes the development of the necessary activities for the start-up, operationand maintenance of a wind farm. For this reason the development of a mini-hydro is eliminated andexcluded for any further analysis

In the analysis of the possible alternatives of the project, there are still two alternatives for the project:

The proposed project activity is not undertaken as a CDM project activity.

Continuation of the current situation: Parque Elico Tres Hermanas S.A.C. does not implementthe project (baseline scenario).

With the information presented above it can be concluded that the two alternatives are viable options.These options will be analyzed in the investment analysis in order to demonstrate the additionality of the

project.

Step 2. Investment analysis

Sub-step 2a. Determine appropriate analysis method

According to the Tools for the demonstration and assessment of additionality three analysis methodsare suggested: simple cost analysis (option I), investment comparison analysis (option II) and benchmarkanalysis (option III).

As the project activity generates other income than carbon credits due to the sale of electricity to the grid,simple cost analysis cannot be applied.

Comparison analysis method (option II) is applicable to projects whose alternatives are also investmentprojects, only on such basis, comparison analysis can be conducted, but due that the alternative baseline


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scenario of the project is the National Interconnected Electricity System (SEIN) rather than newinvestment projects, option II is also not an appropriate method for the decision-making context.Benchmark analysis (option III) is selected for this project activity.

Sub-step 2b. Option III. Apply benchmark analysis

For the benchmark analysis, the IRR is considered the most suitable indicator according to the projecttype. The project IRR will be used, since it includes all in and out cash flows.

According to the Tool for the demonstration and assessment of additionality(Version 05.2.1) option dwas used to determine the discount rate and benchmark used for the benchmark analysis.

d)Government/official approved benchmark where such benchmarks are used for investment

decisions

In order to estimate an adequate discount rate to evaluate the project activitys financial feasibility, it hasbeen selected a discount rate of 12% as a benchmark to evaluate the economic viability of an investmentin the electric sector in Peru. This 12% discount rate emerged in several studies as well as in officialgovernmental decisions related to project investment evaluation.

The 12% benchmark is considered to be a good approach for a project in Peru. Such figure was used insome registered projects in that country like Yanampampa Hydroelectric Power Plant, registered on the18thDecember 2010 with 3545 as registration number.

This 12% rate appeared officially for the first time in December 1992 with the issuance of the Electric

Concession Law as an opportunity cost of investment for the new additions to the system in order toforecast and determine the regulated tariff in Peru 6. Even independent studies such as one performed bythe World Bank in 2009 for renewable plants, mention that the benchmark could be between 12 and 14%,to be conservative the benchmark used in this project is 12%7.

Sub-step 2c. Calculation and comparison of financial indicators

For the economic analysis, the following data were used.

Annual production 415,723 MWh/yr

Sales Price 69 USD/MWh

Total investment 208,000,000 USD

Project duration 20 Yr

Transmission cost 0.91 USD/MWh

Land rent cost 0.0411 USD/m2-year

Maintenance cost (infrastructure) 25,000 USD/yr

COES Cost 0.75% Incomes

Local Taxes (OSINERGMIN) 1% Incomes

6Ley de concesiones elctricas y reglamento. Article 79, Page 35.7Year 2009. Presentation of a World Bank Study regarding the Economic and Technical feasibility of Hydropower

plants in Peru use the benchmarks of 12% and 14% as benchmarks to determine the viability of the projects.

http://siteresources.worldbank.org/INTPERUINSPANISH/Resources/EnriqueCrousillat_Sesion2.pdf
http://siteresources.worldbank.org/INTPERUINSPANISH/Resources/EnriqueCrousillat_Sesion2.pdfhttp://siteresources.worldbank.org/INTPERUINSPANISH/Resources/EnriqueCrousillat_Sesion2.pdfhttp://siteresources.worldbank.org/INTPERUINSPANISH/Resources/EnriqueCrousillat_Sesion2.pdf


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O&M electromechanical (year 3-5)

O&M electromechanical (year 6-20)

38,000

42,560

Euro/WT

Table 6.Financial Characteristics.

The Tres Hermanas Wind Farm projects cash flow shows that the IRRs for the development of theproject activity with and without considering CER revenues are the following:

With/without CER revenues IRRWithout CER revenues 9.35%

With CER revenues 11.48%Table 7. IRR of project

The IRR of the project activity without the CERs income (9.35%) is below the financial benchmark(12%), demonstrating that the project activity by itself is not economically feasible; On the other hand if

the CDM registration is obtained, the IRR for the project activity taking into account the income from theCERs sales will increase up to 11.48%. From the economic model it can be assumed that both IRRfigures are pre-tax as well as the chosen benchmark figure. Even though that the IRR figure is smallerthan the benchmark when not taking into consideration the CERs benefit, the environmental andsustainable development contribution to the country and economic benefits that Parque Elico TresHermanas S.A.C. will acquire derived from the projects activity registration as a CDM project are asubstantial and important incentive for the projects implementation.

This section permits us to conclude that the project can be considered as a CDM project activity, and thatthe benefits and incentives derived from the CERs revenues will alleviate or will overcome the financialhurdles described.

Sub-step 2d. Sensitivity Analysis

The main driver for performing a sensitivity analysis would be the price of the tCO2 in organized markets.The increment of the IRR for scenarios with different price of tCO2:

Price of tCO2 (US$/tCO2)5 10 15 20 25

IRR 10.23% 11.09% 11.94% 12.77% 13.58%

Projects IRR increment 0.89% 0.86% 0.85% 0.83% 0.81%Table 8. Increase on IRR with different scenarios.

In the Guidance on the Assessment of Investment Analysis version 05, paragraph 20 mentions thefollowing:

Only variables, including the initial investment cost, that constitute more than 20% of either total project

costs or total project revenues should be subjected to reasonable variation (all parameters varied need

not necessarily be subjected to both negative and positive variations of the same magnitude).

For the last paragraph, the explanation of each variable that it is used in sensibility analysis is thefollowing:


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Investment: The paragraph mention that the investment cost should be including in the sensibility

analysis. O&M: This cost represent about the 40% of the total cost, this is consistent with the paragraph of

the Tool.

Land rent cost: This cost represent about the 30% of the total cost, this is consistent with theparagraph of the Tool.

Sales price: The paragraphs mention that the total revenues should be including in the sensibilityanalysis.

These financial indicators fluctuated within the range of -10% to +10% according the next table. Theimpact of the electricity prices on IRR is most significant.

Total Investment -10% -5% 5% 10%Project IRR 10.95 % 10.12% 8.64% 7.57%

Electricity Prices -10% -5% 5% 10%

Project IRR 7.54% 8.45% 10.22% 11.07%

O&M -10% -5% 5% 10%Project IRR 9.49% 9.42% 9.27% 9.20%

Land Rent Cost -10% -5% 5% 10%Project IRR 9.43% 9.39% 9.31% 9.26%

Table 9. Financial Parameters.

In conclusion the project is in accordance with the requirements of this step and its demonstrated that the

project activity is additional; this conclusion is supported by the following: The project IRR without the CERs incentives (9.35%) its below the benchmark (12%).

In the sensitivity analysis the variables that have the most impact in the IRR of the project is theelectricity price and the total investment. However it is clearly demonstrated that in the most

positive scenario when the electricity price increased by 10%, the projects IRR only increase to11.07%, which compared with the benchmark is below, for this reason its demonstrated theadditionality of the project.

So, developing the project without the CERs incentive (alternative 1, Sub-Step 1a) is not possible.

Therefore, the additionality of the project activity is clearly demonstrated based on the Investmentanalysis, Step 2 and the baseline of the project activity is the continuation of the current situation

(alternative 2, Sub-Step 1a).

Step 3 Barrier analysisN/A

Step 4. Common practice analysisThe common practice analysis was made according the Guidelines on Common Practice version 01.0.The steps of the common practice analysis are the following:

Step 1: Calculate applicable output range as +/-50% of the design output or capacity of theproposed project activity.


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The capacity of the project activity is 90 MW. Therefore the applicable output range is 45-135 MW. Thisrange will be applied for the following steps.

Step 2: In the applicable geographical area, identify all plants that deliver the same output orcapacity, within the applicable output range calculated in Step 1, as the proposed project activityand have started commercial operation before the start date of the project. Note their number N all.Registered CDM project activities shall not be included in this step.

The following table shows the power plants of the Interconnected National Electric System that have anoutput capacity within the range of 45-135 MW.

Table 10. Common practice calculation8

Therefore, Nall= 22

Step 3: Within plants identified in Step 2, identify those that apply technologies different that thetechnology applied in the proposed project activity. Note their number N diff.

8COES SINAC. Estadstica de Operaciones 2010. Pages 30 and 33. Available at:http://www.coes.org.pe/wcoes/coes/salaprensa/memoria.aspx

Plant Capacity Type

Similar

Technology Nall Ndiff

STAROSA WEST TG7-GAS 109.13 Thermoelectric NO 1 1

STAROSA WEST TG7-GAS CON H2O 123.91 Thermoelectric NO 1 1

STA ROSA UTI 5 - GAS 53.06 Thermoelectric NO 1 1

STA ROSA UTI 6- GAS 52.58 Thermoelectric NO 1 1

AGUAYTIA TG1 - GAS 88.44 Thermoelectric NO 1 1

AGUAYTIA TG2 - GAS 86.96 Thermoelectric NO 1 1

Malacas2 TG4 - GAS 90.33 Thermoelectric NO 1 1

Malacas2 TG4 - GAS con H2O 102.74 Thermoelectric NO 1 1

ILO1 TV3 - R500 67.74 Thermoelectric NO 1 1

ILO1 TV4 - R503 64.33 Thermoelectric NO 1 1

Trujillo Norte -D2 62.13 Thermoelectric NO 1 1Sta Rosa West TG7 - D2 112 Thermoelectric NO 1 1

Sta Rosa West TG7 - D2 con H2O 121.33 Thermoelectric NO 1 1

Sta Rosa UTI 6 -D2 52.54 Thermoelectric NO 1 1

Sta Rosa UTI 5 -D2 51.73 Thermoelectric NO 1 1

CH Malpas 48.02 Hydro NO 1 1

CH Yaupi 110.21 Hydro NO 1 1

CH Matucana 128.58 Hydro NO 1 1

CH Moyopampa 66.13 Hydro NO 1 1

CH Machupicchu 88.8 Hydro NO 1 1

CH Carhuaquero 95.11 Hydro NO 1 1

CH San Gabn 113.1 Hydro NO 1 1
http://www.coes.org.pe/wcoes/coes/salaprensa/memoria.aspxhttp://www.coes.org.pe/wcoes/coes/salaprensa/memoria.aspxhttp://www.coes.org.pe/wcoes/coes/salaprensa/memoria.aspx


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As it can be observed all the power plants have a different technology that the technology applied in theproposed project activity (Wind Farm). Therefore, N

diff= 22

Step 4: Calculate factor F=1-Ndiff/Nallrepresenting the share of plants using technology similar tothe technology used in the proposed project activity in all plants that deliver the same output orcapacity as the proposed project activity.

According to the last steps, the calculation of the Factor F is the following:F = 1 Ndiff/Nall

Where:Nall= 22Ndiff= 22

Therefore, F = 1- (22/22) = 0

According to the Guidelines on Common Practice version 01.0 if the value of the F factor is more than0.2 and the difference between Nall and Ndiff is more than 3, the project activity is a common practice. Forthis project activity the value calculated of the F factor is 0.

Therefore, the project activity is not a common practice.

Sub-step 4a. Analyze other activities similar to the proposed project activity.

Tres Hermanas Wind Farm is a pioneering project in Peru in all aspects: technology applied (wind), scale

of renewable energy development (90 MW). Currently there is NO wind energy capacity installed in thecountry9 as a whole and a further challenge will be its connection to the national grid. Therefore, the

project cannot be considered as common practice.

To the contrary, the past and current common energy practice of the national grid, SEIN, shows that theincrease in electricity generation has been achieved through thermal and hydro power plants.

From the 20% most recently installed capacity in Peru (Build Margin, MWh), 91.5% is produced fromfossil fuel-fired plants and only 8.5% comes from hydro power plants.

The table 10 shows the electricity plan for other conventional renewable source operated power plants(wind, geothermic and hydro power, < 20 MW). The following table is evidence that no other wind farm

has been installed and that the first one is expected to be built in the year 2011.

9Per Sector Elctrico 2010 page 08. Available at:http://www.minem.gob.pe/publicacion.php?idSector=6&idPublicacion=52
http://www.minem.gob.pe/publicacion.php?idSector=6&idPublicacion=52http://www.minem.gob.pe/publicacion.php?idSector=6&idPublicacion=52http://www.minem.gob.pe/publicacion.php?idSector=6&idPublicacion=52


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Power

(MW) 2010 2011 2012 2013 2014 2015 2016 2017 TotalWind 0 50 50 50 50 50 100 100 450

Geothermic 0 0 0 0 0 25 50 50 125

HP


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2017 Mini hydro Hydro 53

Table 12. Conservative expansion plan for the SEIN (2011-2017)11

Analysing the Table 11, it can be concluded that the increase in demand of electricity in Peru for the next4 years will be offset mostly by the construction of new thermoelectric power plants, and for the yearsafter, the demand will be covered by renewable resource power plants (mainly hydro).

We can then conclude that the development and operation of a wind farm it is not considered as acommon practice. The common practice in Peru is mainly the development of hydropower plants and insecond term the development of thermal plants.

Up to the submission of this PDD, there is no wind energy capacity installed in Peru. Similar projects tothe one described in this PDD have been identified, but none of them has progressed to implementation

yet, thus experience with installing and operating wind capacity in the host country is still unprecedented.

Sub-step 4b. Discuss any similar options that are occurring.

The information presented in the previous section (Sub-step 4a) clearly indicates that despite a growinginterest in wind energy in Peru, none of the project proposals has gone ahead with implementation due toa variety of obstacles. As mentioned before, the temporal concession allowed the developer to performdifferent studies, but for the construction and operation of a wind farm, a definitive concession ismandatory, which up to this date none of the project proposals have become.

As a result of applying the Tool for demonstration and assessment of additionality ver. 05.2.1 it isconcluded that based on conservative approaches and assumptions the proposed projects activity Tres

Hermanas Wind Farm fulfills all the additionality requirements, demonstrating that the CDM registrationis required and fundamental for its implementation.

B.6. Emission reductions:

B.6.1. Explanation of methodological choices:Emissions reductions

According to the methodology ACM0002 v.12.1.0 the emission reductions are calculated as follows:

=

(1)Where:

ERy Emissions reductions in yeary(tCO2e/yr)BEy Baseline emissions in yeary(tCO2/yr)PEy Project emissions in yeary(tCO2e/yr)

11Ministry of Energy and Mines. Mistrio de Energa y Minas.Plan Referencial de Electricidad 2008-2017. TableN RE-09, page 35-36.


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Project emissions

In accordance with the guidelines established on the methodology ACM0002 ver. 12.1.0, the GreenhouseGas (GHG) emissions of the project do not have to be considered because the projects activity is not

based on either hydroelectric nor on geothermic energy.

The project emissions are calculated as follows

= , + , + ,

(2)Where:PEy Project emissions in yeary(tCO2e/yr)PEFF,y Project emissions from fossil fuel consumption in yeary(tCO2/yr)

PEGP,y Project emissions from the operation of geothermal power plants due to the release ofnon-condensable gases in yeary(tCO2e/yr)

PEHP,y Project emissions from water reservoirs of hydro power plants in yeary(tCO2e/yr)

Based on the following sentence taken from the ACM0002 / version 12.1.0 methodology description thevalue of PEywas considered zero:

For most renewable power generation project activities, PEy=0

The proposed project activity is not related with the development of a geothermic or hydro power plant,therefore in conclusion the project emission of the project is considered zero (PEy=0).

Leakage

Based on the next quote taken from the methodology ACM002 ver.12.1.0, the leakage emissions areconsidered zero:

No leakage emissions are considered. The main emission potentially giving rise to leakage in the context

of electric sector projects are emissions arising due to activities such as power plant construction and

upstream emission from fossil fuel use (e.g. extraction, procession, transport). These emissions sources

are neglected

Baseline emissions

BEy= EGPJ,yEFgrid,CM,y(3)

Where:

BEy Baseline emissions in yeary (tCO2/yr)EGPJ,y Quantity of net electricity generation that is produced and fed into the grid as a result of

the implementation of the CDM project activity in year y (MWh/yr). This variable will bemeasured with a meter installed in the substation


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EFgrid,CM,y Combined margin CO2 emission factor for grid connected power generation in year ycalculated using the latest version of the Tool to calculate the emission factor for anelectricity system(tCO2/MWh)

It is important to mention that the EFgrid,CM,y will be calculated according the latest version of the Tool tocalculate the emission factor for an electricity systemversion 02.2.1

As the project activity is being developed in a site where no renewable power plant was operated prior tothe implementation, then according to the methodology ACM0002/version 12.1.0:

EGPJ,y= EG facility,y (4)

Where:

EGPJ,y Quantity of net electricity generation that is produced and fed into the grid as a result ofthe implementation of the CDM project activity in year y (MWh/yr). This variable will bemeasured with a meter installed in the substation.

EFgrid,CM,y Quantity of net electricity generation supplied by the project plant/unit to the grid in yeary (MWh/yr). This variable will be measured with a meter installed in the substation.

For the calculation of the emission factor, which will yield the total equivalent CO 2 emission reduction forthe whole crediting period, a Combined Margin (EFgrid,CM,y) will be used in accordance with the Tool tocalculate the emission factor for an electricity systemversion 02.2.1

The steps to following for calculate emission factor are:

1. Identify the relevant electricity systems.2. Choose whether to include off-grid power plants in the project electricity system (optional).3. Select a method to determine the operating margin (OM).4. Calculate the operating margin emission factor according to the selected method.5. Calculate the build margin (BM) emission factor.6. Calculate the combined margin (CM) emission factor.

Step 1.Identify the relevant electricity systems.

The Peruvian grid is connected through the National Interconnected Electric System (SEIN, SistemaElctrico Interconectado Nacional); hereby the relevant electric power system is the entire SEIN grid. To

calculate the operating margin, the electricity generation per hour in the host country (Peru) will beneeded, which is published by the SEIN.

The scope of the project is clearly identified in terms of geographical location and connection to theelectricity system. The information of the grid characteristics is given in the Annual Memories (MemoriasAnuales) prepared by the Committee of Economic Operation of National Interconnected Electric System(Comit de Operacin Econmica Del Sistema Interconectado Nacional, COES SINAC).

These boundaries include all the geographic areas and infrastructures within the entire Peruvian territory,as well as energy transmission and distribution inside the Peruvian system. The parameters of thePeruvian energy system plus detailed information about electricity generation and transmission can be


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found on the Committee of Economic Operation of National Interconnected Electric System webpage(http://www.coes.org.pe).

Figure 3.Schematic map of SEIN. Source: Committee of Economic Operation of National Interconnected ElectricSystem (http://www.coes.org.pe/wcoes/coes/infoperativa/mapasein.aspx)

Step 2. Choose whether to include off-grid power plants in the project electricity system (optional)

Project participants may choose between the following two options to calculate the operating margin andbuild margin emission factor:

Option I: Only grid power plants are included in the calculation.

Option II: Both grid power plants and off-grid power plants are included in the calculation.

Parque Elico Tres Hermanas S.A.C. has chosen Option I and only grid power plants are included in thecalculation.

Step 3.Select a method to determine the operating margin (OM)

The Operating Margin refers to the actual energy generation mix installed in Peru. For its calculations, theDispatch Data method has been selected from the four options proposed in the Tool to calculate theemission factor for an electricity system. This method was selected because the information of electricitygenerated by hours is available and this method would be more accurate and therefore preferable.


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For the simple Dispatch Data method, the emission factor is calculated using the following data vintage:

Ex postoption: If the ex post option is chosen, the emission factor is determined for the year inwhich the project activity displaces grid electricity, requiring the emissions factor to be updatedannually during monitoring. If the data required to calculate the emission factor for year y isusually only available later than six months after the end of year y, alternatively the emissionfactor of the previous year y-1 may be used. If the data is usually only available 18 months afterthe end of year y, the emission factor of the year preceding the previous year y-2 may be used.The same data vintage (y, y-1 or y-2) should be used throughout all crediting periods.

Step 4: Calculate the operating margin emission factor according to the selected method.

The Dispatch Data calculation for the OM emission factor (EFgrid,OM-DD,y) is determined based on the grid

power units that are actually dispatched at the margin during each hour h where the project is displacinggrid electricity. This approach is not applicable to historical data and, thus, requires annual monitoring of

EFgrid,OM-DD,y.

The emission factor is calculated as follows:

(5)

Where:

EFgrid,OM-DD,y Dispatch data analysis operating margin CO2emission factor in yeary(tCO2/MWh).

EGPJ,h Electricity displaced by the project activity in hour h of yeary (MWh).EFEL,DD,h CO2emission factor for grid power units in the top of the dispatch order in hour

h in yeary (tCO2/MWh).EGPJ,y Total electricity displaced by the project activity in yeary (MWh).h Hours in yeary in which the project activity is displacing grid electricity.y Year in which the project activity is displacing grid electricity.

If hourly fuel consumption data is available, then the hourly emissions factor is determined as:

(6)

Where:

EFEL,DD,h CO2emission factor for grid power units in the top of the dispatch order in hourh in yeary (tCO2/MWh)

FCi,n, Amount of fossil fuel type i consumed by grid power unit n in hour h (Mass orvolume unit)

NCV i,y Net calorific value (energy content) of fossil fuel type i in yeary (GJ/mass orvolume unit)


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EFCO2,i, CO2emission factor of fossil fuel type i in yeary (tCO2/GJ)EG

n,h Electricity generated and delivered to the grid by grid power unit n in hour h

(MWh)n Grid power units in the top of the dispatch (as defined below).i Fossil fuel types combusted in grid power unit n in yeary.h Hours in yeary in which the project activity is displacing grid electricity.y Year in which the project activity is displacing grid electricity.

The CO2emission factor of the grid power units n (FEEL,n,y) should be determined as per the guidance forthe simple OM, using the Options A1, A2 or A3.

To determine the set of grid power units n that are in the top of the dispatch, obtain from a nationaldispatch center:

The grid system dispatch order of operation for each grid power unit of the system includingpower units from which electricity is imported.

The amount of power (MWh) that is dispatched from all grid power units in the system duringeach hour h that the project activity is displacing electricity.

At each hour h, stack each grid power units electricity generation using the merit order. The group ofgrid power units n in the dispatch margin includes the units in the top x% of total electricity dispatched inthe hour h, where x% is equal to the greater of either:

(a) 10%.(b) The quantity of electricity displaced by the project activity during hour h divided by the total

electricity generation by grid power plants during that hour h.

The data of the electricity generated in Peru has been obtained from the Committee of EconomicOperation of the National Interconnected Electric System (COES SINAC), the information obtained isnext resumed:

Energy generated by each power plant of the SEIN of the year 201012.

Thermal efficiency of each power plant13.

Marginal cost of each power plant14.

12Committee of Economic Operation of National Interconnected Electric System.Available at:http://www.coes.org.pe/wcoes/coes/sicoes/default.aspx

13Committee of Economic Operation of National Interconnected Electric SystemEstadstica de Operaciones2010.Table No 4.7.page 30 Column "Efic. Termica (%)"

14Committee of Economic Operation of National Interconnected Electric SystemEstadstica de Operaciones2010.Table No 4.7. page 30. Column CV (n)
http://www.coes.org.pe/wcoes/coes/sicoes/default.aspxhttp://www.coes.org.pe/wcoes/coes/sicoes/default.aspxhttp://www.coes.org.pe/wcoes/coes/sicoes/default.aspx


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Step 5: Calculate the build margin (BM) emissions factor.

The build margin emissions factor is the generation-weighted average emission factor (tCO 2/MWh) of allpower units mduring the most recent yearyfor which power generation data is available, calculated asfollows:

(7)

Where:

EFgrid,BM,y Build margin CO2emission factor in year y (tCO2/MWh).EGm,y Net quantity of electricity generated and delivered to the grid by power unit m in year y

(MWh).EFEL,m,y CO2emission factor of power unit m in year y (tCO 2/MWh).m Power units included in the build margin.

y Most recent historical year for which power generation data is available.

Step 6: Calculate the combined margin (CM) emission factor.

The combined margin emission factor is calculated as follows:

,, = ,, + ,,

(8)Where:

EFgrid,OM,y Operating margin CO2 emission factor in year y (tCO2/MWh).EFgrid,BM,y Build margin CO2 emission factor in year y (tCO2/MWh).wOM Weighting of operating margin emissions factor (%).wBM Weighting of build margin emissions factor (%).

For wind and solar projects, due to their intermittent and non-dispatch able nature, the default weights areas follows: wOM= 0.75 and wBM= 0.25.

B.6.2. Data and parameters that are available at validation:There are not data or parameters that will maintain fixed during the crediting period. The electricitygenerated by the project activity and the emission factor of the National Interconnected System will bemonitored. Therefore, all this information can be found in the section B.7.1

B.6.3. Ex-ante calculation of emission reductions:Project emissions

The proposed project is not based on hydroelectric or geothermic energy, and therefore it is not necessaryto consider the Greenhouse Gas (GHG) emissions of the project, this asseveration is in accordance withthe guidelines established by the methodology ACM0002 ver.12.1.0, which mentions the following:

For most renewable power generation project activities, PEy=0


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This project activity is neither related with the development of a geothermic plant nor with a hydropower plant, in conclusion the project emission is considered zero (PE

y=0).

Leakage

The following quote regarding to the leakage of the project was taken from the methodology ACM002ver.12.1.0:

No leakage emissions are considered. The main emission potentially giving rise to leakage in the context

of electric sector projects are emissions arising due to activities such as power plant construction and

upstream emission from fossil fuel use (e.g. extraction, procession, transport). These emissions sources

are neglected

In conclusion the leakage emissions are considered zero.

Baseline emissions

In order to calculate the baseline emissions it is necessary to obtain the emission factor of the grid, whichis composed of two parts: Operating Margin (EFgrid,OM,y) and Build Margin (EFgrid,BM,y).

The Operating Margin emission factor calculation for 2010 is 0.729tCO2/MWh (see details inAnnex 3)

The Build Margin emission factor calculation for 2010 is 0.567tCO2/MWh (see details in Annex3)

The baseline emission factor is calculated as the weighted average of the Operating Margin emissionfactor and the Building Margin emission factor. For wind and solar projects, the default weights are asfollows: WOM= 0.75 and WBM= 0.25 (because of their intermittent and non-dispatchable nature).

Thus, the ex-postbaseline emission factor will be: 0.75*0.7290+ 0.25* 0.5670= 0.6885tCO2/MWh

Baseline emission factor = 0.6885tCO2/MWhAnnual generation = 415,723 MWhBaseline Emissions = 286,225 tCO2/year

Emission Reductions

The emission reduction by the project activity is the difference between the baseline emissions, projectemissions and emissions due to leakage. Since there are no project emission and no emission due toleakage, the emission reductions will be the baseline emission. This baseline emission is the baselineemission factor multiplied by the energy generation.

ERy= BEyPEy

Where:ERy = Emission reductions in yeary (t CO2e/yr)BEy = Baseline emissions in yeary (t CO2/yr)PEy = Project emissions in yeary (t CO2e/yr)


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Baseline Emissions = 286,225 tCO2/yearProject Emissions = 0 tCO2/yearEmissions reductions = 286,225 tCO2/year

B.6.4 Summary of the ex-ante estimation of emission reductions:

Total emission reduction during the crediting period is: 2,003,575 tCO2 (See Annex 3)

Estimation of the emission reductions:

Year

Estimation of

project activityemissions (tonnesof CO2e)

Estimation of

baseline emissions(tonnes of CO2e)

Estimation of

leakage (tonnes ofCO2e)

Estimation of

overall emissionreductions (tonnesof CO2 e)

2015 0 286,225 0 286,225

2016 0 286,225 0 286,225

2017 0 286,225 0 286,225

2018 0 286,225 0 286,225

2019 0 286,225 0 286,225

2020 0 286,225 0 286,225

2021 0 286,225 0 286,225

Total(tonnes of

CO2e)0

2,003,5750

2,003,575

Table 13. Estimation emission reductions.

B.7. Application of the monitoring methodology and description of the monitoring plan:

B.7.1 Data and parameters monitored:

Data / Parameter: EGfacility,yData unit: MWh/yr

Description: Electricity supplied to the grid by the project.

Source of data to beused:

Energy meters installed in the exit of the Wind Farm and the substation.

Value of data appliedfor the purpose ofcalculating expectedemission reductions insection B.5

The project has not been implemented, therefore, the available estimation hasbeen used (415.723 GWh), according to the plant load factor that is established inthe Concession Contract for Energy Supply between Parque Elico TresHermanas S.A.C. and Ministry of Energy and Mines.

Description ofmeasurement methodsand procedures to beapplied:

Electricity meters

The description of the EGfacility,ycalculation is explained in the Annex 4 of thisdocument.

Electricity dispatched will be monitored using official measurements inaccordance with the procedures and protocol established by the COES.


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The entity that will undertake the measurements is the COES SINAC (Comitde Operacin Econmica del Sistema Interconectado Nacional). Continuousmeasurement reported every 15 minutes.

QA/QC procedures tobe applied:

Cross check measurement results with the records of sold electricity; ParqueElico Tres Hermanas S.A.C. shall issue invoices for the energy sales.

Any comment: The data will be archived in electronic way. Archived data kept during thecrediting period and two years later.

Data / Parameter: EFgrid, CM,yData unit: tCO2/MWh

Description: Combined margin CO2 emission factor for grid connected power generation inyearycalculated using the latest version of the Tool to calculate the emission

factor for an electricity systemSource of data to beused:

Estimated figure based on 75% of OM and 25% of BM values

Value of data appliedfor the purpose ofcalculating expectedemission reductions insection B.5

0.6885 tCO2/MWh. This value will change because the emission factor is expostand need to be actualized yearly, with the latest available data of the OM andBM.

Description ofmeasurement methodsand procedures to beapplied:

This variable is calculated using the Tool to calculate the emission factor for anelectricity system / Version 02.2.1 with 1 year vintage data and option of ex postcalculation based on 75% of OM and 25% of BM values. Computed once duringPDD finalization.

QA/QC procedures tobe applied:

N/A

Any comment: N/A

Data / Parameter: m,yData unit: %

Description: Average net energy conversion efficiency of power unit m in yeary

Source of data to beused:

Data provided by COES, Annual Memory 2010.

Value of data appliedfor the purpose of

calculating expectedemission reductions insection B.5

Data used is presented in the spreadsheet for Grid Emission FactorCalculation.15

Description ofmeasurement methodsan15d procedures to beapplied:

Each year this data will be checked with the last available annual report ofCOES.The proportion of data to be monitored is 100% and the data will be archivedelectronically.

15COES "Estadstica de Operacin 2010". Table 4.7. Page 30. Efficiency of the power plant %


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QA/QC procedures to

be applied:

If the data obtained from the manufacturer, the utility and the dispatch center of

Official records are significantly lower than the default value provided in Annex1 of the Tool to calculate the emission factor for an electricity systemversion02.2.1. Project proponents should assess the reliability of the values, and

provide appropriate justification if deemed reliable. Otherwise, the defaultvalues provided in Annex 1 shall be used.

Any comment: Data will be kept for two years after the end of the crediting period or the lastissuance of CERs for this project activity, whatever occurs later.

Data / Parameter: EFCO2i,yData unit: tCO2/GJ

Description: Average CO2 emission factor of fuel type iused in yeary

Source of data used: IPPC 2006 default values for the fuel types (lower value).

Value applied: Diesel Oil: 72,600Natural Gas: 54,300Residual Fuel Oil: 75,500Coal: 87,300

Justification of thechoice of data ordescription ofmeasurement methodsand procedures actuallyapplied :

Fuel emission factors have been selected from the IPPC guidelines, followingthe conservative assumptions established in the monitoring worksheets.

Any comment: -

B.7.2. Description of the monitoring plan:

1. Introduction

The Monitoring Plan defines the process of gathering data required for:

The preparation of a periodical report on the monitoring of reductions in CO 2 emissionsattributable to the Tres Hermanas Wind Farm, which should be verified for the periodicalissuance of the CERs (see Annex 4).

2. Duration

The Monitoring Plan will be implemented over the 7-year crediting periods of project activity. All dataand evidences collected as part of monitoring will be archived electronically and be kept at least for 2years after the end of the last crediting period.

3. Preparation of an annual report on the monitoring of emission reductionsa. Grid emission factor:

Operating margin emission factorThe operating margin is considered ex-post.For more information see Annex 3.

Build margin emission factorThe build margin is considered ex-post. For more information see Annex 3.


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b. Data quality control and assurance

Quality of data used in the estimation of CO2 emission reductions is controlled and/or assured by meansof:

Using internal controls:

A measuring system must be approved by COES.

Power meters (and safety power meters) must comply with technical requirements and becertified.

Preventive and corrective maintenance of the measuring system must be performed, includingcalibration of power meters.

Undertake data validations:

Double check of data on electricity supplied by the wind farm to the grid with the invoice ofenergy sale.

3.3. Responsibilities

The planned operational and management structure that will monitor emission reductions of the projectwill include:

Person(s) responsible for monitoring, recording, reporting and archiving measured data.

Person(s) responsible for checking data and sales invoices.

Person(s) responsible for performing the emission reduction calculations based on themethodology and preparing the Monitoring Report as appropriate.

Person(s) responsible for reviewing and approving the calculations and Monitoring Report.


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Figure 4.Flow diagram of monitoring emissions

B.8 Date of completion of the application of the baseline study and monitoring methodology andthe name of the responsible person(s)/entity(ies)Date of completion: 07/11/2011

Alfonso Lanseros ValdsPartner [email protected]

CO2Global Solutions International S.A. (Project Participant)Claudio Coello 76 Bajo CMadrid 28001, Spain

Tel: +34 917814148Fax: +34 917814149www.co2-solutions.com

SECTION C. Duration of the project activity / crediting period

C.1. Duration of the project activity:

C.1.1. Starting date of the project activity:

30/11/2013

CDM Project Manager(Parque Elico Tres HermanasS.A.C. and CO2Global Solutions

International S.A.)

CDM Team(Parque Elico Tres HermanasS.A.C. and CO2Global Solutions

International S.A.)

Technical Department(Parque Elico Tres Hermanas

S.A.C.)

Monitoring Engineers

ResponsibilityReview and approve

calculations and MonitoringReport

Calculations and ElaborateMonitoring Report

Check, authorize & forwardmonitoring data

Monitor record, report andarchive data
mailto:[email protected]:[email protected]://www.co2-solutions.com/http://www.co2-solutions.com/http://www.co2-solutions.com/mailto:[email protected]


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Is the date that Parque Elico Tres Hermanas S.A.C. will sign the contract of the wind turbines.This represents the most cost of the investment and with this event the PP compromises with thedevelopment of the project activity

C.1.2. Expected operational lifetime of the project activity:The project activity is expected to have a minimum lifetime of 20 years and 0 months.

C.2. Choice of the crediting period and related information:

The crediting period choice is renewable.

C.2.1. Renewable crediting period:

The crediting period is of 7 years and 0 months and will be renewable twice.

C.2.1.1. Starting date of the first crediting period:

01/01/2015

C.2.1.2. Length of the first crediting period:

Parque Elico Tres Hermanas S.A.C. will select 7 years 0 months with a renewable crediting period oftwo times.

C.2.2. Fixed crediting period:

NA

C.2.2.1. Starting date:NA

C.2.2.2. Length:NA

SECTION D. Environmental impacts

D.1. Documentation on the analysis of the environmental impacts, including transboundaryimpacts:

As requirements of the Ministery of Energy and Mines, the project participant needs to present the

Environmental Impact Study of the project activity, in order to obtain the environmental license of theproject. Due to the project activity expects to start in the year 2015, the environmental impact study is inprocess and its expected to be concluded in the first semester of the year 2012.

Parque Elico Tres Hermanas S.R.L. will generate energy by means of renewable sources, in particular,the wind.

The evaluation of environmental impacts of the project is considering the following activities:

Construction (Civil work, operation of machinery, mounting of wind turbines and auxiliaryequipment)

Operation (wind turbines, transmission line)

Conclusion (removal of equipment, removal of concrete).


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The environmental assessment carried out identified the environmental impacts of the project in order topropose mitigation measures to minimize these impacts. In general, a wind power generator is a devicewhich produces electricity and is much friendlier to the environment than the actual electricity generation

process. Such generators have favourable environmental aspects due to their operational characteristics,and further that, is an example of clean energy that that doesnt produce considerable emissions into theenvironment.

Until today no significant negative impacts have been founded.

D.2. If environmental impacts are considered significant by the project participants or the hostParty, please provide conclusions and all references to support documentation of an environmentalimpact assessment undertaken in accordance with the procedures as required by the host Party:

The environmental impact study is in process, until today no mayor impacts have been founded.One impact is the collision of birds; this is considered temporary impact which will be reduced furtherdue to the adaptation of animals to the new environment.

SECTION E. Stakeholders comments

E.1. Brief description how comments by local stakeholders have been invited and compiled:Local stakeholders refer to the communities that will be directly affected by the development of the

project. In this case, people from communities close to the project were invited to express their commentsabout the project activity, the date of the stakeholders consultation was 04 November 2011.

The stakeholders consultation consisted in a presentation were the members of Parque Elico TresHermanas S.A.C. presented the project to the community and show the advantages and the benefits thatthe project will bring to the community. In order to confirm this stakeholders consultation the PP willgive the copies of the survey, pictures and the invitation of the stakeholders consult.

E.2. Summary of the comments received:

Some of the comments received of the local community are the following:

The project is an opportunity for spreading the importance of environmental care.

It is expected that the project will bring benefits for the community, as new job opportunities anddevelopment of services for the community.

The project will have a huge impact for the society, the local economy and the environment

This kind of projects brings more jobs to the community.

With the project, it is expected that new business opportunities for the community will be created.

In general, the people consider important the development of this kind of projects because theythink that the project will improve the environment and it is a clean manner of generate energy.

E.3. Report on how due account was taken of any comments received:Most of the people see as a positive and optimistic way the development of the project activity. The maincomments are involved to the economic benefits that the project activity will bring to the region (due tothe generation of jobs) and the environmental benefits (due the generation of clean energy). Thecommunity expresses the approval of the project activity.


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Annex 1

CONTACT INFORMATION ON PARTICIPANTS IN THE PROJECT ACTIVITY

Organization: Parque Elico Tres Hermanas

Street/P.O.Box: Av. Victor Andrs Belaunde

Building: 887

City: Carmen de la Legua

State/Region: Callao

Postfix/ZIP:

Country: Peru

Telephone: 0051 1 562 3003

FAX:E-Mail: [email protected]

URL:

Represented by: Fernando Jernimo Snchez de Lamadrid

Title:

Salutation:

Last Name: Snchez de Lamadrid

Middle Name: Jernimo

First Name: Fernando

Department:

Mobile: 0051 975 596 436

Direct FAX:Direct tel:

Personal E-Mail:
mailto:[email protected]:[email protected]:[email protected]


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CDM Executive Board

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Organization: CO2Global Solutions International S.A.

Street/P.O.Box: C/ Claudio CoelloBuilding: 76, Bajo C

City: Madrid

State/Region: Madrid

Postfix/ZIP: 28001

Country: Spain

Telephone: (+34) 91 7814148

FAX: (+34) 91 7814149

E-Mail: [email protected]

URL: www.co2-solutions.com

Represented by: Alfonso Lanseros Valds

Title: Partner consultant

Salutation: Mr

Last Name: Lanseros

Middle Name:

First Name: Alfonso

Department: CDM Development

Mobile:

Direct FAX: (+)34 91 781 41 49

Direct tel: (+)34 91 781 41 48

Personal E-Mail: [email protected]
mailto:[email protected]:[email protected]://www.co2-solutions.com/http://www.co2-solutions.com/mailto:[email protected]:[email protected]:[email protected]://www.co2-solutions.com/mailto:[email protected]


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Annex 2

INFORMATION REGARDING PUBLIC FUNDING


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PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

CDM Executive Board page 37

Annex 3

BASELINE INFORMATION

Emission Factor of each thermal plant

Thermal Plants Technology Fuel m,2010* EF CO2 i,2010**(KgCO2/TJ)

EF EL,m,2010(tCO2/MWh)

AGUAYTIA 1 Gas Turbine Natural Gas Natural Gas 30.00% 54,300 0.652

AGUAYTIA 2 Gas Turbine Natural Gas Natural Gas 30.00% 54,300 0.652

CICLO COMBINADO Combined Cycle Gas-Steam Diesel 2 29.00% 72,600 0.901

CHILINA (SULZ 12) Diesel Diesel 2 39.00% 72,600 0.670

CHICLAYO OESTE Diesel Diesel 2 34.00% 72,600 0.769

CHIL T.VAPOR 3 Steam Turbine / Residual R500 23.00% 75,500 1.182

CHIMBOTE TG3 Gas Turbine Diesel Diesel 2 24.00% 72,600 1.089

BELLAVISTA (MAN1) Diesel Diesel 2 38.00% 72,600 0.688

ILO1 CATKATO Diesel 2 / Residual Diesel 2 42.00% 72,600 0.622

ILO1 T.GAS 1 Gas Turbine Diesel Diesel 2 30.00% 72,600 0.871

ILO1 T.GAS 2 Gas Turbine Diesel Diesel 2 33.00% 72,600 0.792

ILO1 T.VAPOR 3 Steam Turbine / Residual R500 39.00% 75,500 0.697

ILO1 T.VAPOR 2 Steam Turbine / Residual R500 39.00% 75,500 0.697

ILO2 TV CARB1 Steam Turbine / Coal Coal 40.00% 87,300 0.786

MALACAS TG1 Gas Turbine Natural Gas Natural Gas 21.00% 54,300 0.931

MALACAS TG2 Gas Turbine Natural Gas Natural Gas 22.00% 54,300 0.889

MALACAS2 TG4 Gas Turbine Natural Gas Natural Gas 27.00% 54,300 0.724

MOLLENDO 1,2,3 Diesel 2 / Residual R500 43.00% 75,500 0.632

OQUENDO TG 1 Gas Turbine Natural Gas Natural Gas 34.00% 54,300 0.575

PIURA1 Diesel 2 / Residual Diesel 2 37.00% 72,600 0.706

PIURA2 Diesel 2 / Residual Diesel 2 37.00% 72,600 0.706

STAROSA TG8 Gas Turbine Natural Gas Natural Gas 35.00% 54,300 0.559

SHOUGESA CUMMINS Diesel 2 / Residual Diesel 2 38.00% 72,600 0.688


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SHOUGESA TV1 Steam Turbine / Residual R500 28.00% 75,500 0.971



TAPARACHI Diesel Diesel 2 35.00% 72,600 0.747

PIURA TG Gas Turbine Diesel Diesel 2 21.00% 72,600 1.245

TRUJILLO_NORTE Diesel Diesel 2 38.00% 72,600 0.688

TUMBES Diesel 2 / Residual Residual 6 43.00% 75,500 0.632

UTI_5 (STAROSA) Gas Turbine Natural Gas Natural Gas 29.00% 54,300 0.674

UTI_6 (STAROSA) Gas Turbine Natural Gas Natural Gas 27.00% 54,300 0.724

WESTINGHOUSE Gas Turbine Natural Gas Natural Gas 30.00% 54,300 0.652

VENTANILLA TV Combined Cycle NaturalGas

Natural Gas 50.00% 54,300 0.391

VENTANILLA 3 Combined Cycle NaturalGas

Natural Gas 35.00% 54,300 0.559

VENTANILLA 4 Combined Cycle NaturalGas

Natural Gas 34.00% 54,300 0.575

CHILCA 1 TG1 Gas Turbine Natural Gas Natural Gas 35.00% 54,300 0.559



KALLPA TG1 Gas Turbine Natural Gas Natural Gas 34.00% 54,300 0.575



INDEPENDENCIA Diesel Diesel 2 39.00% 72,600 0.670

PISCO TG1 Gas Turbine Natural Gas Natural Gas 27.00% 54,300 0.724

PISCO TG2 Gas Turbine Natural Gas Natural Gas 27.00% 54,300 0.724

LFLORES TG1 Gas Turbine Natural Gas Natural Gas 34.00% 54,300 0.575

* Source:COES "Estadstica de Operacin 2010", table 4.7 mentions the Efficiency of the power plant, page 30.**See the next table.


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Type of Fuel

D2 Residual Natural Gas Coal

EFCO2(Kg/Tj) 72,600 75,500 54,300 87,300

Source: IPCC default values at the lower limit of the uncertainty at a 95% confidence interval as provided in table 1.4 of Chapter1 of Vol. 2 (Energy)of the 2006

Marginal Cost - MeritOrder 2010

Powerplant TechnologyVariable Cost

(US/MWh)EF EL,m,2010(tCO2/MWh)

KALLPA TG3 Gas Turbine Natural Gas 11.21 0.575



VENTANILLA TV CombinedCycle Natural Gas 12.62 0.391

CHILCA 1 TG1 Gas Turbine Natural Gas 16.04 0.559



VENTANILLA 3 Gas Turbine Natural Gas 17.56 0.559

VENTANILLA 4 Gas Turbine Natural Gas 17.96 0.575

STAROSA TG8 Gas Turbine Natural Gas 18.28 0.559

WESTINGHOUSE Gas Turbine Natural Gas 20.23 0.652

INDEPENDENCIA Diesel 22.78 0.670PISCO TG1 Gas Turbine Natural Gas 23.78 0.724

PISCO TG2 Gas Turbine Natural Gas 23.78 0.724

UTI_5 (STAROSA) Gas Turbine Natural Gas 24.18 0.674

UTI_6 (STAROSA) Gas Turbine Natural Gas 25.25 0.724

LFLORES TG1 Gas Turbine Natural Gas 28.72 0.575

OQUENDO TG 1 Gas Turbine Natural Gas 29.16 0.575


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AGUAYTIA 1 Gas Turbine Natural Gas 31.90 0.652

AGUAYTIA 2 Gas Turbine Natural Gas 32.18 0.652

ILO2 TV CARB1 Steam Turbine / Coal 43.27 0.786

MALACAS2 TG4 Gas Turbine Natural Gas 66.09 0.724

MOLLENDO 1,2,3 Diesel 2 / Residual 110.69 0.632

TUMBES Diesel 2 / Residual 126.42 0.632

MALACAS TG2 Gas Turbine Natural Gas 133.43 0.889

CHILINA (SULZ 12) Diesel 133.65 0.670

MALACAS TG1 Gas Turbine Natural Gas 135.98 0.931

ILO1 T.VAPOR 3 Steam Turbine / Residual 138.16 0.697

ILO1 T.VAPOR 2 Steam Turbine / Residual 147.22 0.697

SHOUGESA TV3 Steam Turbine / Residual 163.32 0.906



ILO1 CATKATO Diesel 2 / Residual 195.59 0.622

CHIL T.VAPOR 3 Steam Turbine / Residual 199.93 1.182

SHOUGESA CUMMINS Diesel 2 / Residual 206.16 0.688

PIURA2 Diesel 2 / Residual 211.25 0.706

PIURA1 Diesel 2 / Residual 215.42 0.706

BELLAVISTA (MAN1) Diesel 215.95 0.688

TRUJILLO_NORTE Diesel 224.60 0.688

CHICLAYO OESTE Diesel 231.18 0.769

TAPARACHI Diesel 234.21 0.747

ILO1 T.GAS 2 Gas Turbine Diesel 240.46 0.792CICLO COMBINADO CombinedCycle Gas-Steam 254.85 0.901

ILO1 T.GAS 1 Gas Turbine Diesel 260.42 0.871

CHIMBOTE TG3 Gas Turbine Diesel 327.70 1.089

PIURA TG Gas Turbine Diesel 357.41 1.245

Source: COES "Estadstica de Operacin 2010", table 4.7 mentions the technology and the variable cost of each power plant, page 30.


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The marginal costs have been taken from the annual statistics of the dispatch center and are called variable cost

Operating Margin

Please refer to excel spreadsheet to see the detailed calculation of the operating margin.

The emission factor is calculated as follows:

(9)

EFgrid,OM-DD,y= 0.729 tCO2/MWh

Build Margin

Plant Year Technology 2010 totalproduction inGWh

EmissionFactor(tCO2/MWh)

%Generation

%Acumulate

Emissions(tCO2)

CH PARAMONGA 2010 Hydro 77.48 0 0.24% 0.24% 0

KALLPA TG3 2010 Gas Turbine NaturalGas

1078.30 0.575 3.40% 3.65% 619,961

CH RONCADOR 2010 Hydro 7.65 0 0.02% 3.67% 0

LFLORES TG1 2010 Gas Turbine NaturalGas

13.08 0.575 0.04% 3.71% 7,522

INDEPENDENCIA 2010 Diesel 5.27 0.670 0.02% 3.73% 3,530

PISCO TG1 2010 Gas Turbine NaturalGas

3.60 0.724 0.01% 3.74% 2,608

PISCO TG2 2010 Gas Turbine NaturalGas

10.20 0.724 0.03% 3.77% 7,382


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1288.98 0.575 4.07% 7.84% 741,088

TRUJILLO NORTE 2009 Diesel 120.97 0.688 0.38% 8.22% 83,202

CHILCA 1 TG3 2009 Gas Turbine NaturalGas

930.46 0.592 2.94% 11.16% 551,169

STAROSA TG8 2009 Gas Turbine NaturalGas

763.86 0.559 2.41% 13.57% 426,629

CHILCA 1 TG2 2007 Gas Turbine Natural

Gas

406.19 0.559 1.28% 14.85% 226,860


880.43 0.575 2.78% 17.63% 506,198

CHILCA 1 TG1 2006 Gas Turbine NaturalGas

1,092.95 0.559 3.45% 21.08% 610,426

Total 6,679,413.74 3,786,577

EF grid,BM,2010 0.567 TCO2/MWh

(1) Source: COES "Estadistica de Operacin 2010" page 5 mentions the new plants installed to the SEIN(2) Source: COES Estadistica de Operacin 2009 page 6 mentiosn the new plants installed to the SEIN (3) COES Power plants electric generation report of December 2008(4) COES Power plants electric generation report of December 2007(5) Information of CDM registered project Huanza Hydroelectric Project.

BM Margin: 0.567tCO2/MWh

Emissionfactorex-ante = 0.75*OM+ 0.25*BM = 0.6885tCO2/MWh


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WFmLossyfacility EGXEG ,, =

Annex 4

MONITORING INFORMATION

A.Measuring and calculation procedure.

1. Measuring.The operation department will obtain the readings from the meters installed monthly, they will reportthem in the spreadsheet for measurement control and they will store the data discharged from the metersin electronic format.

Part of the operation department personnel from the wind farm will be taking the reading measurements

and will be in charge of doing these tasks.

2. Monitoring of electricity generation (crosscheck):

There will be one meter at the exit of the wind farm and one meter in the substation (delivery point), themeter in the wind farm will measure the gross energy and the meter in the substation will measure the netenergy.

Beside this project, there are other projects that are estimated to operate at the same time and theseprojects will also join the same transmission line. If all projects are joining the same transmission line, themeter at the substation may not only measure the net energy of the project Marcona Wind Farm, for thisreason the following calculation is proposed to measure the net energy of the project.

In order to calculate the net energy of the project it is necessary to calculate a power loss factor (XLoss)due to energy loss thro

PDD Tres Hermanas Trabajo

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