CLEAN DEVELOPMENT MECHANISM PROJECT DESIGN DOCUMENT FORM ... · PDF filepallasca motil chauall...

PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 02 CDM – Executive Board page 1

This template shall not be altered. It shall be completed without modifying/adding headings or logo, format or font.

CLEAN DEVELOPMENT MECHANISM PROJECT DESIGN DOCUMENT FORM (CDM-PDD)

Version 02 - in effect as of: 1 July 2004)

CONTENTS A. General description of project activity B. Application of a baseline methodology C. Duration of the project activity / Crediting period D. Application of a monitoring methodology and plan E. Estimations of GHG emissions by sources F. Environmental impacts G. 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



SECTION A. General description of project activity A.1 Title of the project activity: Tarucani I (“the project”) Version 2 September 14th, 2005 A.2. Description of the project activity: The project is a hydropower plant with an existing reservoir, where the volume of the reservoir will not be increased. The project’s purpose is renewable electricity generation to be supplied to the National Interconnected Electric Grid (“SEIN”). It will be located in Peru, in the south-western department of Arequipa. The project is neither constructed nor financed as of today and is existence is only based on the sponsoring company decisive will to develop it. The project’s installed capacity and estimated yearly average generation is 49 MW (“megawatts”) and 282,528 MWh (“megawatts hours”), respectively. The project is expected to displace 153,957 tons of carbon dioxide equivalent (“tCO2e”) per year, which accounts for 1,077,699 tCO2e for the first crediting period (7 years), generating the equivalent amount of greenhouse gasses (“GHG”) emissions reductions (“ERs”). The project’s GHG emissions will be negligible. Therefore, there will be no need to monitor leakage and it will not be taken into account when calculating the project ERs. The project will take advantage of an existing hydraulic infrastructure1 composed by: The Condoroma water regulating reservoir, which has 260 millions cubic meters (“m3”) of water capacity, an earth dam located between 4,058 and 4,158 meters (“m”) above sea level (“asl”), the Tuti intake works at the Colca River, and over 100 kilometers (“km”) of channels and tunnels2. The project will connect to this hydraulic infrastructure at the terminal tunnel structure, by means of an appropriate structure with a spillway and gates. The project will use an 8.3 km-conveying channel with a maximum flow capacity of 34m3/s; at the end of the channel there will be a 1,200m-penstock; the penstock will lead to a powerhouse with one 49MW-capacity generating unit. The project will count with a 331m-net head. The Majes irrigation system and the project will use the total water flow of the Colca River, which is regulated at the Condoroma reservoir. The water concession for the project has been granted to Tarucani Generating Company SA (“the sponsor”) by the Peruvian Ministry of Agriculture and it is based upon the use of the water flow required for agriculture downstream the project. The project will not have facilities to regulate any water flow (or energy production) since the control of the water discharges will continue to be managed by the agricultural authority of the region, named the Watering District of Majes-Siguas-Chivay. The spatial extent of the project boundary will be the National Interconnected Electric Grid (“SEIN”). The project will be connected to the SEIN through a 91.5 km. transmission line to the Cerro Verde Substation, which belongs to Red de Energía del Perú S.A (“REP”). The expected generated electricity will be sold to private industrial clients in the Cerro Verde Substation. The project will have an expected minimum operating life of 40 years. The project contributes to sustainable development by:

1 Built as part of the Majes irrigation system in 1984. 2 The existing hydraulic infrastructure discharges through a spillway to the Huasamayo gully.



a) Displacing expensive heavy fuel, diesel, coal and gas fired generation and at the same time, reducing CO2 emissions to the atmosphere by generating energy without greenhouse gases (GHG) emissions.

b) Employing local labour in construction and plant management3. c) Purifying/cleaning of the water for irrigation. d) Contributing to Peru’s fiscal accounts through the payment of taxes. e) Helping the country improves the hydrocarbons trade balance through reduction of oil imports

to be used for electricity generation. f) Spurring Arequipa department’s economy since it consumes materials of Arequipa such as

cement, metals, wood, and construction equipments, among others. g) Reducing the erosion of the Huasamayo gully, which is a mayor problem to the agriculture

downstream the project site, by way of diverting the water from the terminal tunnel to the power house. h) The project’s sponsor (“the sponsor”) agreed to a broad social and environmental sustainable

development plan in benefit of local stakeholders. This plan will be monitored, according to the project’s Sustainable Development Monitoring Plan (“SDMP”), which is part of the project Monitoring Plan (MP)4. A.3. Project participants: Name of Party involved (*) ((host) indicates a host Party):

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

Kindly indicate if the Party involved wishes to be considered as project participant (Yes/No)

Peru (host) Tarucani Generating Company S.A.

Yes

(*) 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 of requesting registration, the approval by the Party(ies) involved is required. Note: When the PDD is filled in support of a proposed new methodology (forms CDM-NBM and CDM-NMM), at least the host Party (ies) and any known project participants (e.g. those proposing a new methodology) shall be identified. Source: Own production A.4. Technical description of the project activity: A.4.1. Location of the project activity: A.4.1.1. Host Party(ies): Republic of Peru. A.4.1.2. Region/State/Province etc.: Department of Arequipa (Arequipa Region) / Caylloma province / Lluta district. A.4.1.3. City/Town/Community etc: Querque community (in the Lluta District).

3As of today, there is high unemployment in Arequipa; there are no projects like this that will help creating jobs. 4 Seen under Annex 4.



A.4.1.4. Detail of physical location, including information allowing the unique identification of this project activity (maximum one page): The project will be located in the south-western Peruvian department of Arequipa, in the Caylloma province, in the Lluta district (180 km northeast from Arequipa), in the Querque community. The direct area of influence is estimated to be less than 969 hectares5. This area is limited by the portion of the Quebrada Huasamayo between the water intake and the water discharged point.

5According to the project’s Environmental Impact Assessment (“EIA”).



MALPASO

ICAVILLACURI

NASCA

OROYA NUEVA

TARMA

CONDORCOCHA

HUARAZ

BAGUA GRANDE

MOYOBAMBA

PIURA OESTE

ABANCAYANDAHUAYLAS

QUILLABAMBA

MACHU PICCHUAYACUCHOINGENIOCAUDALOSA

CAÑETE

TAMBO DE MORA

PISCOPARACAS

SANTA MARGARITA

PALPA PUQUIO

MARCONASAN NICOLAS

INDEPENDENCIA

RESTITUCION

JAUJA

CHUMPE

LA OROYAHUARAL

HUACHO

ANDAHUASI

SAN JUAN

HUINCO

CALLAHUANCAMOYOPAMPAHUAMPANIBALNEARIOS

SANTA ROSAVENTANILLA

CHAVARRIAZAPALLAL

CAHUA

UCHUCCHACUA

HUARMEY

CHIMBOTE

CASMA

SAN JACINTO

NEPEÑA

SIHUASLA PAMPA

CAÑON DEL PATO

CARAZAUCAYACU

YARINACOCHA

RIOJA

PUCALLPA

TINGO MARIA

HUANUCO

PALLASCA

MOTILCHAUALL

TRUJILLO NORTETRUJILLO NORTE

TUMBESZORRITOS

MALACASTALARA

El ARENAL

PAITA

SULLANA

VERDUN

CURUMUY

CHULUCANAS

MUYO

IQUITOS

REPARTICION

BAGUA CHICA

TARAPOTO

JAEN

LA PELOTA

ZARUMILLA

PACASMAYO

CARHUAQUERO

CHICLAYOOESTE

CAJAMARCACHILETEGALLITO CIEGOGUADALUPE

MOTUPE

LA VIÑA

ILLIMO

VIRU

CARHUAZ

TICAPAMPAVIZCARRA

PARAMONGA

POMACOCHA

PARAGSHA II

GOYLLARISQUIZGA

CHUPACA

HUAYUCACHI

MANTARO

CACHIMAYO INCA

COMBAPATA

SICUANI

TINTAYA AYAVIRI

C H SAN GABAN

SAN RAFAEL

AZANGARO

JULIACATAPARACHI

PUNO ILAVE

POMATA

MOLLENDOTOQUEPALA

ARICOTA 2EL AYRO

TOMASIRI

TACNAPARA

LA YARADA

CALANA

TOQUELA ALTO

TARATACHALLAHUAYA

ARICOTA I

BOTIFLACAMONTALVOMOQUEGUA

ILO

MAJES

CHILINA

CHARCANII,II,III,IV,VI

SOCABAYA

CHARCANI V

REPARTICION

CHUQUIBAMBILLA

DOLORESPATA

CHALHUANCA

PTO. MALDONADO

PACHACHACA

OLMOS

PIURA

CAJABAMBA

YANACOCHA

GERA

BELLAVISTA

AGUAYTIA

CHUNCHUYACU

MATUCANA

HUANCAVELICA

S.E. CALLALLI

CHAHUARES

ANTAURA

ILO 2

S.E. COTARUSI

BELLA UNION

ANTAMINA

YAUPICARHUAMAYO

EL SANTA

COBRIZA

HUANTA

TRAPECIO

MISAPUQUIO

SAN ANTONIOSAN IGNACIO

The Project in the SEIN

Ecuador

Colombia

Brazil

Chile

Bol

ivia

Pacific Ocean

The Project

Source: COES Statistics - SEIN Map. A.4.2. Category(ies) of project activity: The project falls into: Scope number: 1 Sectoral scope: Renewable energy



A.4.3. Technology to be employed by the project activity: The technology to be employed will be based on conventional Francis turbines and generators that are widely used all over the world. The penstock will lead to a powerhouse with one generating unit 49 MW capacity. The generating unit will be coupled to a synchronous generator (3-phase) 62.5 MVA nominal capacity. The water will be discharged into Huasamayo gully, which will return the water to the Majes irrigation system; hence, the water to be used is fed back into the already existing hydraulic system. The control building, which includes the control room, offices and auxiliary installations, will be adjacent to the powerhouse. The control room will be equipped with a modern system for automatic and remote control (SCADA). The project will be connected to the SEIN through a new 91.5 km overhead transmission line of 138 kV to the Cerro Verde substation. The project will transfer environmentally safe and sound technology and know how to Peru by hiring local labour in all of its implementation phases. During operation, the staff working in operation and maintenance of the project will be local people6 previously trained if necessary. A.4.4. Brief explanation of how the anthropogenic emissions of anthropogenic greenhouse gas (GHGs) by sources are to be reduced by the proposed CDM project activity, including why the emission reductions would not occur in the absence of the proposed project activity, taking into account national and/or sectoral policies and circumstances: The project will generate GHG-neutral electricity which will be supplied to the SEIN. Hence, the project will displace fossil-fuel based electricity that otherwise would be supplied to the SEIN. The project is expected to displace 153,957 tons of carbon dioxide equivalent (“tCO2e”) per year7, which accounts for 1,077,699 tCO2e for the first crediting period (7 years). ERs are not likely in the absence of the project activity, because of barriers that hydropower plants’ developers need to overcome in Peru and the existence of other available alternatives for generation that are more financially attractive in Peru. The barriers faced by the project include national policies, sectoral policies and the Camisea8 particular circumstance that foster natural gas-fired electricity generation projects discouraging hydropower plants projects in the country. National policies are currently fostering the national use of the Camisea natural gas deposits with special emphasis on promoting the gas-fired electricity generation in Peru; and is also fostering gas exploration in the national territory (i.e. to be used by the Camisea LNG project). The aggressive intervention of the government in the market in order to secure the success of the Camisea project and the success of the future natural gas-fired electricity generation industry started in 1998, after the exit of Shell, company that discovered the Camisea gas existence in Peru. That emissions reductions are not likely in the absence of the Clean Development Mechanism (“CDM”) project activity is further analyzed under B.3. The project has not started construction as of today because it has not achieved a financial closure yet; the sponsor has been looking for a financial closure for

6 Unless technically skilled labor is required. 7 ER estimates are based on the “Consolidated Baseline Methodology for grid-connected electricity generation from renewable sources”

(ACM0002). 8 “The San Martin and Cashiriari fields, jointly known as Block-88 (“Camisea”) are home to one of the most important non-associated natural gas reserves in Latin America. The Camisea reserves are ten times greater than all other existing natural gas reserves in Peru”-Source: www.camisea.com.pe. Camisea was discovered between 1983 and 1987, but the Camisea project only recently became operational, in August 2004. Moreover, the acquisition of the concession rights for the block 56 (Pagoreni), which would enlarge the proven reserves of Natural Gas in Peru has been granted already for exploration and exploitation.



the past 4 years and is still doing so. The sponsor believes that carbon finance revenues will alleviate the financial hurdles faced by the project to some extent. A.4.4.1. Estimated amount of emission reductions over the chosen crediting period: The project will reduce 153,957 tCO2e annually once implemented, generating an expected total of 1,077,699 tCO2e for the duration of the initial 7-year crediting period; 3,233,097 tCO2e over the 21-year period. The project estimated annual ERs, over the 21-year crediting period, are as follow:

Year Annual estimation of emissions reductions in tonnes of CO2e

2008 115,4682009 153,9572010 153,9572011 153,9572012 153,9572013 153,9572014 153,9572015 153,9572016 153,9572017 153,9572018 153,9572019 153,9572020 153,9572021 153,9572022 153,9572023 153,9572024 153,9572025 153,9572026 153,9572027 153,9572028 153,9572029 38,489

Total estimated reductions (tonnes of CO2e) 3,233,097Total number of crediting years 21

Annual average over the crediting period of estimated reductions (tonnes of CO2e) 153,957

Source: Own production. A.4.5. Public funding of the project activity: The project has not received and will not receive any type of public funding or public financial help. SECTION B. Application of a baseline methodology



B.1. Title and reference of the approved baseline methodology applied to the project activity: Approved consolidated baseline methodology ACM0002: Consolidated baseline methodology for grid-connected electricity generation from renewable sources (“the methodology”). The methodology will be used in conjunction with the approved monitoring methodology ACM0002 (“the monitoring methodology”). B.1.1. Justification of the choice of the methodology and why it is applicable to the project activity: The project is a grid-connected zero-emission renewable power generation activity and meets all the conditions stated in the methodology (ACM0002). These conditions are: • The project supplies electricity installed capacity addition (49 MW) from a hydropower source; it is a

hydro-power plant with an existing reservoir; where the volume of the reservoir is not increased. • The project is not an activity that involves switching from fossil fuels to renewable energy at the

project site • The electricity grid (the SEIN) is clearly identified and information on the characteristics of this grid

is available. B.2. Description of how the methodology is applied in the context of the project activity: The baseline scenario is “electricity that would have been otherwise generated by the operation of grid-connected power plants and by the addition of new generating sources”. Following the methodology, the baseline emission factor is calculated as a combined margin (“CM”), consisting of the simple average of the operating margin emission factor (“OM”) and the build margin emission factor (“BM”). All margins are expressed in tCO2/MWh. CM= 0.5 x OM + 0.5 x BM According to the methodology, the combined margin is deemed to represent the tCO2/MWh that would have been emitted in the absence of the project. Emissions reductions will be claimed based on the total CO2 emissions mitigated by the project. The project boundary considered is the SEIN. The following four steps have to be made in order to calculate the project’ baseline emissions and the project’s ERs9. Step 1: Calculation of the OM The OM selected was the Dispatch Data Analysis Operating Margin Emission Factor (“DDA-OM”) because the methodology specifies that the Dispatch Data Analysis OM is the first methodological choice where the required data is available. The DDA-OM should hold for the first crediting period. The DDA-OM is calculated as: E_OMy/EGy. E_OMy = Sum of [average tCO2/MWh emitted by plants that fall within the top 10% of grid dispatch each hour of the year “times” the project generation in MWh each hour of the year] And, EGy = The project generation in the year in which actual project generation occurs. For the project “the year” will run from April 1st to March 31st, being the first year of the first crediting period April 2008-March 2009 and the last year of the first crediting period April 2014-March 2015. 9 Since no leakages or emissions were identified for the project the emissions reductions will be equal to the baseline emissions.



The resulting DDA-OM was 0.72614 tCO2/MWh and was obtained from dividing E_OMy by EGy, as explained above.10 Step 2: Calculation of the BM Following the methodology, the BM is defined as the generation-weighted average emission factor (tCO2/MWh) of a sample of power plants. Such sample should be composed by either the 5 most recently built plants or the plants whose aggregated generation comprises the most recent 20% of the SEIN generation in the year of project generation occurrence11 whichever group’s generation is greater – both list should exclude CDM-Status Plants12. The methodology, gives 2 options for the calculation of the BM. The second option was selected (“BM2”) for the sake of conservativeness – this option does not include in-construction plants in the sample and must be updated annually ex-post for all crediting periods. The selection of BM2 for the BM should hold for the first crediting period of the project. The formula to apply to the selected sample is: EF_BMy (tCO2/MWh) = [ ∑i,m(Fi,m,y)x (COEFi,m)] / [ ∑mGENm,y]; m = plants of the selected sample, F = their annual generation in MWh, COEF = their tCO2/MWh factor, GEN= total sample’s annual generation, i=technology. In the monitoring of the project’s ERs, the plants capacity additions to consider in the BM should be obtained by comparing annual statistics of installed capacity in the SEIN across latest years, and by selecting from these additions identified, only the ones that represent new units added or no more than 5-year old plants interconnected to the SEIN (“Newly Built”) – this criteria was established for the sake of conservativeness, and avoid being biased by old plants that get interconnected to the SEIN, rehabilitation of plants, and/or upgrades13. “Newly Built” capacity additions from 1988-200314 can be seen in E.4. Out of identified “Newly Built” capacity additions in the SEIN, the 5 most recent plants/units built were: 1)Yarinacocha(2003), 2)Huanchor(2002), 3)Tumbes(2001), 4)Yanango(2000) and 5)Chimay(2000), whose comprised annual generation was 1,300.5 GWh. The identified “Newly Built” capacity additions in the SEIN built since year 1993 up to 2003 composed the 20% most recently built plants in generation; these plants comprised annual generation was 3,860.08 GWh. Hence, the latter group was selected in the BM2 calculation because its comprised generation was greater. In the monitoring this comparison between both samples should be made annually ex-post. The BM2 is calculated as the average tCO2 emitted by the selected sample. Following the methodology, the resulting BM2 was = 0.36371 tCO2/MWh15. Step 3: Calculation of the CM Following the methodology, the baseline emission factor is the CM calculated as the weighted average of the OM and the BM- default weights of 50%, 50% were kept. This calculation was made as follows:

10 See more in detail explanation in E.4. 11 To determine the baseline, the 3 most recent years’ annual average generation of the new units added to the SEIN was taken because the project has not generated electricity yet. 12 As of today, the project is one among others CDM-Status Plant in Peru (SEIN). 13 Source data for the BM calculation is in annex 3: Installed capacity per power plant of the SEIN as of December 31st at years 1996 to 2003 and SEIN installed capacity additions from 1998 to 2003 (all categories). 14 The entire list of capacity additions in the SEIN (all sorts) from 1988 to 2003, can be seen in annex 3. 15 See more in detail explanation in E.4.



CM= 0.5xOM+ 0.5xBM CM= 0.5x(0.72614) + 0,5x(0.36371) = 0.54493 tCO2/MWh Step 4: Calculation of the project’s ERs prior to validation Leakage is inexistent for the project and so it does not enter the calculation of estimated ERs. The project’s emissions are also zero and do not enter the calculation of ERs. Therefore, the project’s ERs are estimated to be equal to the baseline emissions. The estimated ERs per year for the project are obtained from the following multiplication: Estimated baseline emissions = CM x (estimated annual project generation in MWh). Estimated ERs per year = CM x (estimated annual project generation in MWh). Estimated ERs per year = 0.54493 tCO2/MWh x 282,528 MWh. = 153,957 tCO2e or 153,957 ERs. The ERs per year estimated for the first crediting period equal 153,957 tCO2e/yr times 7, which is equal to 1,077,699 tCO2e or Estimated ERs16. B.3. Description of how the anthropogenic emissions of GHG by sources are reduced below those that would have occurred in the absence of the registered CDM project activity: The following steps from the “Tools for the demonstration and assessment of additionality” (EB16 Report) will be completed in this section: Step 0: Preliminary screening based on the starting date of the project activity Step 1: Identification of alternatives to the project activity consistent with current laws and regulations Step 2: Investment analysis. Step 3: Barriers analysis Step 4: Common practice analysis Step 5: Impact of registration of the proposed activity as a CDM project activity Step 0 - Preliminary screening based on the starting date of the project activity The project participated in the two first global Carbon Expo held in Cologne on June 2004 and on May 2005. The starting date of the project activity (considered to be the starting date of the project ‘s construction), planned to be April 1st 200617, will occur only after the registration of the project, as the sponsor considers carbon finance an integral and essential part of the project and that the project will not happen without it. In any case, project participants do not wish to have the crediting period starting prior to the registration of the project. Hence, step 0 is waived for the project. Meaning the project is additional under step 0. Step 1 - Identification of alternatives to the project activity consistent with current laws and regulations Sub-step 1a. Define alternatives to the project activity: The identified realistic and credible alternatives available to the project participants that provide outputs or services comparable with the proposed CDM project activity are three: 1) Implement the project as a hydropower plant development without CDM assistance 16 All margins were rounded to the fifth decimal, but the CERs per year were rounded down to the nearest integer. 17 The construction period will last 24 months.



2) Implement the project as a natural gas power plant 3) Do not implement any power generation project Sub-step 1b. Enforcement of applicable laws and regulations The identified alternatives are in compliance with all applicable legal and regulatory requirements. The 3 identified alternatives comply with Peru’s Electric Concession Law of 1992 -Law 25844 (“ECL”). Some relevant articles of Peru’s ECL that imply that the alternatives are a real possibility available to the project participants are: a) From Article 1- electricity generating activities can be developed by natural or juridical persons, whether they are national or foreigners. The juridical persons (private companies) should be incorporated under Peruvian laws; b) From Article 3 - A concession is required for the development of hydropower plants (or geothermal plants)18 if their installed capacity is greater than 10 MW; c) From Article 4 – An authorization is required to develop fossil-fuel fired thermal plants with installed capacity greater than 500 kW, and hydropower plants and geothermal plants if their installed capacity is less than or equal to 10 MW; d) From Article 6 – The concessions and authorizations can be granted by Peru’s Department of Energy and Mines (“MINEM”), who would establish for so a registration process; e) From Article 7 – electricity generating activities that do not require concession or authorization could be developed freely upon compliance with technical standards and dispositions of environmental conservation and cultural patrimony conservation - the owner of the title of these activities should inform the MINEM the initiation of activities and the technical characteristics of the project and installations; and, f) From Article 9 – The Peruvian government preserve the environmental conservation and the cultural patrimony of the nation, as well as the rational use of the natural resources in the development of activities related to generation, transmission and distribution of electricity. Because none of the identified alternatives breaks any legal or regulatory requirement or are posed to do so in the future - including the fact that none of the three alternatives are posed to go against technical standards and dispositions of environmental conservation and cultural patrimony conservation, all 3 scenarios are in compliance with all applicable laws and regulations and are also realistic and credible alternatives available to the project participants. Meaning the project is additional under step 1. Step 2 – Investment Analysis This analysis shows why the proposed project activity is economically and financially less attractive than other alternatives identified, without the revenue from the sale of CERs. To conduct the investment analysis the following four sub-steps will be taken: Sub-step 2a. Determine an appropriate analysis method The CDM project activity generates financial and economic benefits other than CDM related income, therefore the Cost Analysis (Option I) cannot be taken. Out of the comparison analysis (Option II) and the benchmark analysis (Option III), the benchmark analysis (Option III) was chosen. Sub-step 2b - Option III. Apply the benchmark analysis The identified financial indicator is: Unit cost of service ($/MWh) The indicator for the project is: Levelized cost of electricity production ($/MWh) The relevant benchmark value is the SEIN Long Run Marginal Cost (LRMC) ($/MWh) (“LRMC”). 18 As of today, geothermal generation is inexistent in Peru. The Geothermal Law (Law 26848) was approved in July 1997.



Both unit costs of service ($/MWh) include cost of investment and of operation and maintenance and reflect a present value $/MWh; hence are comparable. The LRMC represents standard costs in the market, considering the specific risk of the project type, and it is not linked to the subjective profitability expectation or risk profile of a particular project developer. That the project is not the most inexpensive alternative in the market will be demonstrated in sub-step 2c. Sub-step 2c – Calculation and comparison of financial indicators19 Levelized cost of the project: The formula to calculate the levelized cost for the project is the following: Cost per MWh = [Investment x CRF + O&M Annual] /Annual Generation (MWh) Where, Investment: Total investment in the project ($) - not including value added tax (“VAT”) equal $50.01

million. In the present calculation the VAT is added but discounted by the fiscal credit, the final financial cost of this was calculated to be 4% of 50.01 million, which when added gives a total investment of $52.01 million.

CRF: Capital recovery factor equals 0.14075 CRF equals the equivalent annual cost of the capital investment/ capital investment

CRF =Annuity of $52.01 million20 at 14% discount rate and 40 years of annual payments21

$52.01 million CRF= $7.3222 = 14.075%

$52.01 O&M: Annualized operation and maintenance costs. It does neither include financial costs nor

income tax23 and equals $4.28 million. $4.28 million includes variable costs (additives, lubricants, spares, materials and other maintenance expenses - all expresses in US$/MWh); and fixed costs (payroll expenses for employees in charge of the plant operation, plant supervision, plant maintenance, plant security, secondary and principal transmission system payments, contributions to the energy regulator agency (“OSINERG”) and Committee of Economical Dispatch (“COES”), and other general expenses-all expressed in US$/kW- month, that have been annualized).

Generation: Annual average generation in MWh equals 282,528 MWh24.

19 Detailed data for calculation and modeling of Minimum Cost Expansion Plan is in annex 3 under “Details of LRMC variables”. 20 Being $52.01 million the present value of the annuity. 21 And zero ending cash balance. 22 In Excel [PMT (14%, 40, 52.01, 0)] = Annuity of $ 52.01 million at 14% discount rate and 40 years of annual payments, being $ 52.01 million the present value of the annuity, zero residual value. Some engineers would argue that $7.32 million is implicitly composed by the capital cost and the depreciation cost. 23 Since the latter will depend on an unknown variable which is the project net income. 24 This is the generation before any transmission or distribution losses occur, making the calculation comparable with the LRMC, in which power plants generation also reflect the production before transmission or distribution losses occur. This is also consistent with reality, because the production/supply needed to satisfy the electricity demand need to account for transmission and distribution losses – meaning power plants need to produce more than what their will receive. For the project, transmission losses expected to occur in the Tarucani –Cerro Verde transmission line are 2.79% of the electricity produced onsite (282,528MWh), accounting for 7,869 MWh. This makes a 274,645 production net of transmission losses. Note that if transmission losses were considered for the project levelized cost calculation, the project levelized cost would have become even more expensive. Since transmission losses are not included in the project levelized cost calculation the investment analysis is being conservative.



The calculation for the project levelized cost is the following:

Levelized Cost for Tarucani

Unit The Project (Tarucani) Capacity MW 49 Total Investment $Million 52.01 Annual Cost: Capital $Million 7.32 O&M $Million 4.28 Total Annual Cost $Million 11.60 Plant Factor % 65.82% Generation MWh 282,528 Levelized Cost $/MWh 41.06

Source: Singles parameters were provided by the sponsor, calculations are own production. The Long Run Marginal Cost of the SEIN (LRMC): The LRMC ($/MWh) is the equivalent cost per MWh estimated to supply the additional demand of the SEIN in future years (2007-2017, for this forecast). This cost includes Investment (“I”) and Operations and Maintenance (“O&M”) costs. The LRMC is calculated taken into account the additional future demand and the cost incurred to serve that demand, with investments in new plants and the O&M cost of both new and existent plants (according to a dispatch simulation). The LRMC calculation considers that the new capacity addition installed will be fulfilled with the most economically efficient alternatives available in the market. The LRMC was calculated by using the Wien Automatic System Planning Package (“WASP”), version III. The WASP generated sequences of projects that comply with limit values for maximum and minimum reserves for each alternative technology specified. The WASP targets at minimizing the LRMC of the SEIN. The LRMC uses the following formula:

Source: Peru’s baseline study 200325. Where26, I: Sum of equivalent annual investment costs for a year O&M: Annual costs in operation and maintenance NSE: Annual losses in distribution and transmission D: Annual demand projected r: Discount rate: 14% n: 2007-2017

25 Large study contracted by the World Bank, developed by a MINEM expert. 26The detailed description of the variables and sources for their values can bee seen in annex 3.



Calculation of LRMC of the SEIN27

Year Demand GWh

Incremental Demand

GWh

I28 1000$

O&M29 1000$

NSE 1000 US$

Total Cost 1000 US$

2006 23,219.4 - - - - - 2007 24,061.9 843 8,853 14,740 0 23,593 2008 24,935.4 1,716 36,165 9,770 0 45,935 2009 25,789.3 2,570 36,165 34,340 0 70,505 2010 26,681.4 3,462 45,018 48,480 0 93,498 2011 27,587.9 4,369 72,329 47,190 0 119,519 2012 28,548.6 5,329 72,329 67,870 0 140,199 2013 29,539.3 6,320 108,494 75,870 0 184,364 2014 30,563.2 7,344 108,494 92,510 0 201,004 2015 31,618.3 8,399 108,494 113,000 0 221,494 2016 32,709.9 9,491 117,347 137,600 0 254,947 2017 33,839.2 10,620 144,658 145,150 0 289,808

NPV (14%) 27,443 397,930 349,525 - 747,456 LRMC 27.24 $/MWh

Source: Sectoral Baseline Study 2003. LRMC=747,456/27,44330 = $27.24 The resulting LRMC of the SEIN is $27.24 /MWh. Comparison: Both the LRMC and the project levelized cost are comparable because they have the same nature of components (both I and O&M), both reflect a present value of $/MWh31; and moreover the discount rate is 14% for both. Since the project has a higher cost indicator than the benchmark ($41.06 per MWh > $27.24 per MWh), the project cannot be considered financially attractive. Sub-step 2d. Sensitivity Analysis The following variables will undergo a sensitivity analysis to prove the robustness of the conclusion given in sub-step 2c. For the SEIN LRMC ($/MWh)32: a) Equivalent annual investment cost b) Discount rate For the project levelized cost ($/MWh): a) Load factor b) The initial investment cost c) Discount rate

Sensitivity Analysis for the SEIN LRMC ($27.24/MWh)

27 The numbers in the table reflect a present value as of the end of each year – Except for the NPV of the sum of them , which reflect a present value as of April 1st, 2008 (date of the project commissioning), which allows it to be comparable to the project’s levelized cost. 28Equivalent annual cost of capacity additions selected by WASP. 29Simulation of future supply to attend the projected demand was forecasted by WASP. 30 This number reflects a present value as of April 1st 2008 (date of the project commissioning). 31As of April 1st 2008 (date of the project commissioning). 32Note that a load factor sensitivity analysis can not be performed for the LRMC, because in the LRMC calculation, the load factor varied per plant, per month, and per year.



Values as of April 1st 2008

DataY 12% 14% 16% r=0% 90% 100% 110% 12% 14% 16% 12% 14% 16% 12% 14% 16%

2007 867 871 875 843 21,234 23,593 25,952 21,844 21,941 22,036 24,271 24,379 24,485 26,698 26,816 26,933 2008 1,576 1,555 1,535 1,716 41,342 45,935 50,529 37,973 37,472 36,986 42,192 41,636 41,096 46,411 45,799 45,206 2009 2,108 2,043 1,982 2,570 63,455 70,505 77,556 52,039 50,452 48,940 57,821 56,058 54,377 63,604 61,664 59,815 2010 2,535 2,415 2,302 3,462 84,148 93,498 102,848 61,616 58,689 55,948 68,463 65,210 62,165 75,309 71,731 68,381 2011 2,856 2,673 2,504 4,369 107,567 119,519 131,471 70,325 65,809 61,654 78,139 73,121 68,505 85,953 80,433 75,355 2012 3,111 2,860 2,633 5,329 126,179 140,199 154,219 73,655 67,716 62,346 81,839 75,240 69,274 90,023 82,764 76,201 2013 3,294 2,975 2,692 6,320 165,928 184,364 202,800 86,480 78,112 70,678 96,089 86,791 78,531 105,698 95,470 86,384 2014 3,418 3,033 2,697 7,344 180,904 201,004 221,104 84,183 74,703 66,429 93,537 83,004 73,810 102,891 91,304 81,191 2015 3,490 3,042 2,659 8,399 199,345 221,494 243,643 82,826 72,209 63,104 92,028 80,232 70,115 101,231 88,256 77,127 2016 3,521 3,016 2,590 9,491 229,452 254,947 280,442 85,121 72,908 62,616 94,578 81,009 69,573 104,036 89,110 76,531 2017 3,518 2,960 2,498 10,620 260,827 289,808 318,789 86,393 72,699 61,360 95,992 80,777 68,178 105,591 88,855 74,996

30,293 27,443 24,967 60,463 742,455 672,710 612,098 824,949 747,456 680,109 907,444 822,201 748,120 90%*I

12% 24.51 12.36 14% 24.5116% 24.52

100%*I12% 27.2314% 27.2416% 27.24

110%*I12% 29.9614% 29.9616% 29.96

100%*I90%*I

SENSITIVITY ANALYSIS FOR THE SEIN LRMC (2007-2017)

NPV of Annual Investments=

110%*IIncremental GWh

r=0%EAC=I Discount Rate Sensitivity

Source: Sectoral Baseline Study 2003 – Sensitivity analysis is own production, chart model taken from Public Poechos I PDD. From the chart above it can be observed that the LRMC is basically not affected by changes in discount rates, but only by changes in the equivalent annual investment costs33. Sensitivity analysis for the project ($41.06/MWh)

Change in Load Factor (LF*%)LF all else constant

100% 90% 95% 100% 105% 110%Capacity MW $49.00 $49.00 $49.00 $49.00 $49.00 $49.00 Total Investment $Million $52.01 52.01 52.01 $52.01 52.01 52.01Annual Cost: -Capital $Million $7.32 7.32 7.32 $7.32 7.32 7.32 -O&M $Million $4.28 4.28 4.28 $4.28 4.28 4.28Total Annual Cost $Million $11.60 11.60 11.60 $11.60 11.60 11.60Plant Factor % 65.82% 59.24% 62.53% 65.82% 69.11% 72.40%Generation MWh 282,528 254,275 268,402 282,528 296,654 310,781 Levelized Cost $/MWh 41.06 45.62 43.22 41.06 39.11 37.33

LEVELIZED COST FOR THE PROJECT40 years of payment

14% discount rate

Source: Singles parameters were provided by the sponsor, calculations are own production. From the chart above it can be observed that the project levelized cost continues being higher than the LRMC, under load factor sensitivities of +/-10% change. In the chart below it can be observed the project’ sensitivity analysis matrix. In this matrix, the load- factor sensitivity run was +/-10%, the initial-investment-cost sensitivity run was +/-10%, and the discount-rate sensitivity run was +/- 2 basis points. 33 The values in the chart above (costs and GWh.) have bee re-expressed to reflect their present value as of April 1st 2008 (date of the project commissioning) to allow comparison with the project levelized cost figures involved.



90% 95% 100% 105% 110%Equivalent Annual Investment Cost ("EAIC") 46.81 I*90% 12% $5.68 $5.68 $5.68 $5.68 $5.68

14% $6.59 $6.59 $6.59 $6.59 $6.5916% $7.51 $7.51 $7.51 $7.51 $7.51

52.01 I*100% 12% $6.31 $6.31 $6.31 $6.31 $6.3114% $7.32 $7.32 $7.32 $7.32 $7.3216% $8.34 $8.34 $8.34 $8.34 $8.34

57.21 I*110% 12% $6.94 $6.94 $6.94 $6.94 $6.9414% $8.05 $8.05 $8.05 $8.05 $8.0516% $9.18 $9.18 $9.18 $9.18 $9.18

Annual O&M $4.28 $4.28 $4.28 $4.28 $4.28Equivalent Annual Cost ("EAC") 46.81 I*90% 12% $9.96 $9.96 $9.96 $9.96 $9.96

14% $10.87 $10.87 $10.87 $10.87 $10.8716% $11.79 $11.79 $11.79 $11.79 $11.79

52.01 I*100% 12% $10.59 $10.59 $10.59 $10.59 $10.5914% $11.60 $11.60 $11.60 $11.60 $11.6016% $12.62 $12.62 $12.62 $12.62 $12.62

57.21 I*110% 12% $11.22 $11.22 $11.22 $11.22 $11.2214% $12.33 $12.33 $12.33 $12.33 $12.3316% $13.46 $13.46 $13.46 $13.46 $13.46

Levelized Cost 46.81 I*90% 12% 39.17 37.11 35.25 33.57 32.05 (Total Equivalent 14% 42.75 40.50 38.47 36.64 34.97

Annual Cost$/GenerationMWh) 16% 46.37 43.93 41.73 39.74 37.94 52.01 I*100% 12% 41.65 39.46 37.48 35.70 34.08

14% 45.62 43.22 41.06 39.11 37.33 16% 49.65 47.04 44.68 42.56 40.62

57.21 I*110% 12% 44.13 41.81 39.72 37.83 36.11 14% 48.50 45.95 43.65 41.57 39.68 16% 52.93 50.15 47.64 45.37 43.31

Load Factor Sensitivity

Source: Singles parameters were provided by the sponsor, calculations are own production. Comparison of the project’s levelized costs against the not-efficient scenario for the benchmark:

Change in Investmentfor the Project 90% 95% 100% 105% 110%

46.81 I*90% 12% Additional Additional Additional Additional Additional29.96 14% Additional Additional Additional Additional Additional

16% Additional Additional Additional Additional Additional110% Investment Cost 52.01 I*100% 12% Additional Additional Additional Additional Additional

14% Additional Additional Additional Additional Additional16% Additional Additional Additional Additional Additional

57.21 I*110% 12% Additional Additional Additional Additional Additional14% Additional Additional Additional Additional Additional16% Additional Additional Additional Additional Additional

Benchmark- Not efficient MarketDiscount Ratefor the Project

Change in Load Factor for the Project (LF*%)

Source: Singles parameters were provided by the sponsor, calculations are own production. Comparison of the project’s levelized costs against the base scenario for the benchmark:






Discount Ratefor the ProjectBenchmark- Base Scenario for the Market

Change in Load Factor

Source: Singles parameters were provided by the sponsor, calculations are own production. Comparison of the project’s levelized costs against the efficient scenario for the benchmark:








Benchmark- Most efficient MarketDiscount Ratefor the Project


Source: Singles parameters were provided by the sponsor, calculations are own production. By analyzing the comparative charts above, it can be concluded that the project is additional – meaning that its cost per MWh is higher than the market’s in all the sensitivity scenarios run. Regardless of how the market performs, the project is additional at all discount rates, at all load factors and at all initial investment costs run in the sensitivity analysis34. Hence, since the project financially unattractiveness concluded in Sub-Step2c. has proved to be robust to reasonable variations in the critical assumption, the project is unlikely to be financially attractive. Meaning the project is additional under step 2. Since the project financial unattractiveness concluded in Sub-step 2.c.has proved to be robust to reasonable variations in the critical assumptions, the project is unlikely to be financially attractive. Meaning the project is additional under Step 2. Step 3. Barrier Analysis Sub-step 3 a. Identify barriers that would prevent the implementation of the type of the proposed project activity Hydropower plants projects face barriers that prevent them from being carried out if they are not registered as CDM activities. In particular, the project faced two main barriers: investment barriers and barrier due to prevailing practice. Investment Barrier: The project is neither constructed nor financed as of today. The main investment barrier for hydropower plants originates from the high up-front initial investment fixed cost needed. This fact joined to Peru’s financial risk, high cost of capital35and un-sophisticated capital market36 prevents this type of large investments in Peru. In particular for the sponsor, the fact that it is not a well-known international company or institution that could provide assets as real guarantees enforces this barrier. This fact has blocked a project finance possibility, as remarked by the sponsor after his 4 year experience of unsuccessfully trying to get project finance by contacting multilateral agencies, international private equity funds, and global investment banking firms37. The only way the sponsor pretends to overcome this barrier is by capitalizing CDM Revenue so that the project can become a reality.

34 The discount rate sensitivity analysis run implicitly incorporates all other risk impacts not herewith sensivitized (i.e. gas price). Nevertheless, gas price raise was sensitivitized in the LRMC for illustrative purposes only; this sensitivity run is presented in Annex 3. 35 Recently, the Economist Intelligence Unit Limited (February 8, 2005), EIU Riskwire – commented on Peru’s financial risk and cost of capital, as follows: “Corporate finance is widely available, but costly, with average commercial interest rates for dollar loans around 10%, and for local currency loans around 15-20%”. 36 Debt funding is not available for long maturity projects, in particular such leveraged projects, regardless of the project profitability, in Peru. The Peruvian banking system is short-term based. As of January 31st, 2005, lending from the entire banking system was 65% of less than-one-year maturity and 35% of more-than-one-year maturity - Source: Peru’s Insurance and Banking Superintendence: www.sbs.gob.pe. Unfortunately there is no more detailed public data than this, regarding lending sorted by maturity in the Peruvian Banking System. 37 The Economist Intelligence Unit Limited (February 8, 2005), EIU Riskwire added on Peru’s financial risk and cost of capital, that “Banks remain wary of lending to small and medium-sized businesses, and will do so until the economy shows strong signs of growth and the bad-debt ratio falls further.”



The Investment barrier hereby referred to affect Peruvian highly capital intensive projects was strengthened from the second half of 1998, when a worldwide flight-to-quality phenomenon hit Peru in 2 ways mainly: preventing international investors to lend to the Peruvian banking system and preventing the Peruvian banking system to lend to highly leveraged projects (commonly highly capital intensive projects) that do not have large companies as project developers (the project case). The flight to quality worldwide phenomenon was triggered by the successive global emerging markets crisis, which started in 199738, “private capital flows to emerging markets had all dried up by 2001”39. The graphs below show the effects of the emerging market crisis.

Net Private Capital Inflows (1985-2003) - (Billions of $)

Source: International Monetary Fund (“IMF”), World Economic Outlook. In this scenario, only the prospects of carbon finance revenue are capable of lower the investments barriers faced by the project. To illustrate, carbon finance could reduce the hydropower plant average turnkey cost of US$975,00040/MW in 12%41. Depending upon the load factor and future CERs price, the impact of carbon finance on the financial viability of the project could be even greater. (b) Barrier due to prevailing practice: Existing pro-Camisea42 policies, which started in 1998 would have led and will led to the implementation of a technology with higher emissions, which is natural gas-fired electricity generation. It is envisaged that the existing regulatory framework favoring gas-fired electricity generation will impact Peru’s overall generation prevailing practice towards gas as gas pipelines spread in the country and as more gas is discovered.

38 Thailand crisis, July 1997; Russian Crisis August 1998; Brazil devalues and floats in February 1999; Turkey floats the lira in February 2001; Argentina defaults in December 2001 – Following the successive crises in Asia (1997) and Russia (1998). 39 The Unholy Trinity of Financial Contagion, by Kaminsky, Reinhart, and Vegh; Journal of Economics Perspectives – Volume 17-Number 4 – Fall 2003 - pg 63. 40 See the table of “technology comparison between simple cycle gas turbines and river hydro” in lines below. 41 Taking a 65% load factor, 1 MW will generate 5,694 MWh, which could reduce 5,694 times 0.54493 (baseline emission factor), or 3,102 tCO2 (ERs). Considering a price of $5.63 (weighted average trading price of CERs between the period of January 2004 and April 2005 - according to the State and Trends of Carbon Market 2005 publication made by the IETA and the WBCFB) per ER in 21 years, the 1 MW would receive $116,783 in net present value at 14% discount rate. Hence out of an average turnkey cost per MW ($975,000/MW) a 12% turnkey cost reduction will be achieved, approximately. 42 “The San Martin and Cashiriari fields, jointly known as Block-88 (“Camisea”) are home to one of the most important non-associated natural gas reserves in Latin America. The Camisea reserves are ten times greater than all other existing natural gas reserves in Peru”-Source: www.camisea.com.pe. Camisea was discovered between 1983 and 1987, but the Camisea project only recently became operational, in August 2004. Moreover, the acquisition of the concession rights for the block 56 (Pagoreni), which would enlarge the proven reserves of Natural Gas in Peru has been granted already for exploration and exploitation.



The clear governmental pro-Camisea position that started in 1998 after the exit of the Shell has made the situation for hydropower-plant projects keep worsening as of today, as long as more governmental incentives have been offered to the natural gas-fired electricity generation industry.

The Camisea project’s chronology Activity 1981 …1987 1988 …1996 ...1998 1999 2000 2001 2002 2003 2004… 2007 …2033 ...20401. Exploration2. Intl. Public Bidding for Licence Agreement and concession right & Award3. License agreement for extraction (*) (*)4. Concession agreement for transportation (*) - BOOT (*)5. Concession agreement for distribution (*) - BOOT (*)6. LNG Project / pending (*) (*)7. Letter of credit for transportation (*) - $99 million (*)8. Letter of credit for extraction (*) - $92 million (*)9. Construction phase10. Operation phase11. Approval of Environmental and Social Impact Assessment - Upstream12. Approval of Environmental and Social Impact Assessment - Downstream13. Eximbank decision to deny $214 million loan14. Inter-American Development Bank approves financing for $270 million (*) = begin (!) = San Martin and Cashigari found by Shell

! No findings

Source: MINEM information (2003), table is own production. After the exit of Shell43, in mid 1998, the Peruvian government decided to aggressively promote thermal technology based on natural gas. Beginning that same year, it halted the definitive and temporal concessions for hydropower plants through Law 26980 issued in September 1998, Law 27133 issued in June 1999, and Law 27239 issued in December 199944. No hydropower plants definite concessions were granted in 1999 to 200045, showing the clear impact and determination of President Fujimori’s laws against hydropower plants developments and in favor of gas-fired electricity generation. This governmental position against hydropower plants had two main impacts, less new experience with hydropower development in Peru and increased risk in Peru’s hydropower generation industry as perceived by foreigners as well as by locals due to biased sectoral political interventions in the electricity generation market. Around August 2004th, the date of the Camisea project commissioning, the government released laws DS 019-2004 on June 25th, 200446 and DS 041-2004-EM on November 24th, 200447; and DS 107-2004-EF on August 5th, 200448; to promote natural gas based electricity generation and to exempt the selective consumption tax to gas, respectively. These three laws released were aimed at making gas an even more competitive option for generation.

43Company that discovered the Camisea gas in Peru. 44(1)September 27th, 1998: Law 26980 – “Law that modified several articles and definitions annexed to ECL”. On its third Transitory Disposition mandated the suspension for 9 months in the presentation of requests for temporal and definite concessions for hydropower plants. (2)June 4th, 1999: Law 27133 – “Law of Promotion of the Natural Gas Industry” – On its Unique Complementary Disposition extended the suspension of hydropower plants for 12 additional months from June 1999. (3)December 22nd, 1999: Law 27239 – “Law that modified several articles of the ECL” - On its Unique Complementary Disposition mandated that priorities to admit new temporal and definitive concession in hydropower plants would be determined as a function of the national development. 45 Source: Last-10-year list of definite concessions granted by Peru’s Department Energy and Mines (“MINEM”). 46 Indicates that for the next 2 years from June 25th, 2004, the guarantee required by article 66 of the ECL Rules will be reduced to 0.25% (before 1%) of total project budget with a ceiling of 200 UIT(“Unidad Impositiva Tributaria”) (before 500 UIT), when the request for Authorization is for natural gas-based electricity generation. 47 Supreme Decree that promotes the installation of thermal plants that use natural gas as fuel. 48 Clarifies that natural gas on its gassy-state will not be comprised in the New Appendix III , which attains Selective Consumption Tax (“ISC”) affection only, of the Value Added Tax’s Texto Unico Ordenado and ISC Law.



Furthermore, the government has recently completed the technical studies of the “Country Gasification Project”, which considers the installation of regional natural gas pipelines to transport the Camisea gas to Ayacucho, Cuzco, Ica, and Junin; and announced that the next step would be the selection of investors to build those natural gas pipelines. On promoting investment on gas pipelines, the government gave Supreme Decree 038-2004 on October 21st, 2004, Supreme Decree 016-2004-EM on June 10th, 2004; Supreme Decree 018-2004-EM on June 16th, 2004. These 3 laws clarified gas pipeline installations’ security measures and ownership requirements, paving the way for new investments. The impact of this government-driven project on electricity prices is devastating for hydropower developers who now have to compete not only with a cheaper technology available (combined cycle plants), but also with a much cheaper locally available fuel. According to MINEM49, the two expected Camisea impact scenarios for Peru’s electricity industry are: 1) Hydro-thermal Scenario: At the end of 2027, the SEIN will have an installed capacity of 66% thermal and 34% hydro. The current situation of the installed capacity of the SEIN is 40% thermal and 60% hydro. 2) Thermal Scenario: If all the additions in electricity generation would be natural gas-fired thermal plants, at the end of 2027 the SEIN would have an installed capacity 75% thermal and 25% hydro. In both scenarios, the electric sector would be the main consumer of the Peruvian natural gas industry. In the hydro-thermal scenario the natural gas demand for generation would be 800 million cubic feet per day (“MMCFPD”) and that in the thermal scenario would be 1000 MMCFPD by 2027. It is foreseen that gas-fired power plants will start been built/accommodated by a change from oil to gas, because of the existing gas governmental promotional laws and regulations as gas pipeline installations spread in the country and as more gas-wells get discovered in the national territory i.e. recently, BPZ Energy Inc. has discovered gas in the north of the country and is planning to build a 150 MW gas power plant by using the discovered gas at the same time- the financing of this project is closed with the International Financial Corporation. There are a number of gas plants and conversion to gas being developed in Peru; these are listed in the Step 4. Common Practice Analysis. Sub-step 3b. Show how the identified barriers would not prevent the implementation of at least one of the alternatives: The two identified barriers that the project faced will not prevent the alternative: “implement the project as a natural gas-fired power plant”. (a) Investment barrier (Barrier 1): -Affected less strongly natural gas project developments (Alternative 2) because of three reasons: - The lower investment needed to build a natural gas-fired power plant. A hydropower plant investment is needier of financing than a gas-fired power plant because of the much higher up-front investment cost needed for the prior. The table below shows that the turnkey cost50 per MW of a run-of-river hydropower plant ($975,000) is more than double that of a simple cycle gas power plant ($475,000), on average.

49 MINEM-Electricity General Directive, http://www.minem.gob.pe/electricidad/estadisticas/informativo/informativo8.pdf. 50Turnkey meaning the investment needed to put a power plant in operation.



Technology Simple Cycle RiverComparison Gas Turbine Hydro

Size Range (MW) 0.5 - 450 .02 - 1

Efficiency (%) 21% - 45% 60-70%

Gen Set Cost ($/MW) 300,000 to 600,000 NA

Turnkey Cost-No Heat 300,000 to 650,000 750,000 to 1,200,000Recovery ($/MW)Source: Meherwan P. Boyce, Ph.D, P.E (2002); "Gas Turbine Engineering Handbook", p.8

-The faster time it takes to put the brand-new engines in operation for the natural gas-fired power plant, which exposes lenders to less risk. -The shorter time it takes in recovering the initial investment made which exposes lenders to less risk. -Does not prevent “not implementing any power generation project” (Alternative 3), but in fact fosters it. Evidence of this is provided in the Newly Built 1998-2003 power plants table, shown under the Common Practice Analysis, in which it can be seen that the 3-year average of new capacity additions in the SEIN has decreased in 92% in the 3 most recent years (2001-2003) when compared with the previous three years (1998-2000)51. (b)Barrier due to prevailing practice (Barrier 2): -Do not prevent the implementation of natural gas fired power plants (Alternative 2). In fact natural gas power fired plants is the beneficiary of all these policies and government interventions in the electricity market and energy sector from the second half of 1998. -Do not impose penalties to “not investing” (Alternative 3), thus Alternative 3 is not prevented by Barrier 2 either. Since the Alternatives are affected less strongly/not prevented by the identified barriers that the project faced, they are both viable alternatives and should not be eliminated from consideration. Having been identified two barriers that prevented the implementation of this type of proposed project activity (hydropower plants) but did not prevent/affect less strongly at least one of the alternatives identified, the project is additional under Step 3. Step 4. Common Practice Analysis Sub-step 4a. Analyze other activities similar to the proposed project activity Hydropower generation investment barrier and prevailing practice barrier existed both from the second half of 1998 - it is from the second half of 1998 that hydro development can not be considered anymore common practice. Although it can not be said that the emerging market conditions will not improve in the future, it can certainly be said that hydro development participation in power generation installed capacity will keep shrinking until 2027- based on MINEM forecasts, because of the Camisea project occurrence and the political backing that Peru’s natural gas-fired electricity generation is being granted, against hydropower plant development. All newly built hydropower plants that started operations from 1998 and all in-construction hydropower plants as of December 2003, except for CDM project activities will be analyzed in this section. In

51 Being the average annual capacity additions in 1998-2000, 275.87 MW, and 20.93 MW in 2001-2003.



addition, gas projects (Alternative 2) and the no implementation of any electricity generation project (Alternative 3) will be discussed under this Sub-Step (4a.) The list of in-construction projects and electricity generation newly built plants from 1998 in Peru is provided below:

In-construction projects (and their project generation by 200852) Plants in construction Situation Additions in Installed Capacity (MW) Fuel Type Projected Annual GWh2004SANTA ROSA II In construction 1.3 Hydro 6VENTANILLA TG3 Conversion 164.1 Gas 697VENTANILLA TG4 Conversion 160.5 Gas 1,4402005YUNCAN In construction 130 Hydro 909 Source: Own production with data of GART (4-year projections of May 2004) and MINEM projection for generation of Santa Rosa II

SEIN Capacity Additions from 1998 to 2003 Years Techn Addition Install.Cap.

Category Added (MW)1998AGUAYTIA 1 DRY GAS Newly built 86.3AGUAYTIA 2 DRY GAS Newly built 86.3TG MALACAS PM GAS Newly built 102.21999SAN GABAN II HYDRO Newly built 55.0CALANA R6 Newly built 6.4MOLLENDO TGM D2 Newly built 90.02000SAN GABAN II HYDRO Newly built 58.1ILO2 TVC COAL Newly built 145.0C.H. CHIMAY HYDRO Newly built 156.0C.H. YANANGO HYDRO Newly built 42.32001TUMBES R6 Newly built 18.32002C.H. HUANCHOR HYDRO Newly built 18.92003YARINACOCHA R6 Newly Built 25.6

Source: COES Analyzing hydropower plants development (Alternative 1): Newly built hydro power plant that started operation since 1998 cannot be considered common practice, but rather sporadic especial conditions of the projects’ developers.

-Yuncan Project (will start operations in 2005): TheYuncan Project recent sponsor: Tractebel, has planned to obtain CDM Status and is currently working on that process, a communication letter about this intention has been provided to the World Bank. As it is a CDM Status plant it will not enter the analysis.

-Santa Rosa II Project (has started operations in 2004): Santa Rosa II is a micro hydropower plant of 1.5 MW. Its sponsors applied to The World Bank to attain CDM status in early 2003 and by now they have signed an ERPA with the Community Development Carbon Fund (CDCF)

-Huanchor Hydropower plant (2002):

52 Year in which annual generation of these projects stabilizes (especially that of the natural gas projects).



Huanchor (18.9 MW) started construction in 1999. It is owned by The Grupo Gubbins. The Grupo Gubbins is a large Peruvian investment group53. The sponsor purpose was to use hydro resources that were available close to its mines. Thus, the financial returns on that project were enhanced by savings in actual electricity expenses of the sponsors’ mines (which consumes an important proportion of total Huanchor total generation). As natural gas was not available in the area surrounding the sponsor mines, the cheaper option was to build a hydropower plant. Because of the synergies Huanchor provides to its sponsor, Huanchor is not comparable to The Project. SINERSA is also not financially comparable to the Grupo Gubbins regarding access to financing.

-Chimay (2000) and Yanango (2000) Hydropower Plants: Commonly called “Chinango”, Chimay and Yanango account for 198.3 MW of installed capacity. The total investment was $200 million approx. The projects started constructions works in 1997, and were developed simultaneously by Edegel. Both are located approximately 125 miles east of Lima. The projects are separate facilities but do share a common transmission line, a new 120 kilometers, and a 220 kV line. This large investment was started just before the emerging markets crisis that strongly hit Latin America from 199854 and in view of a good financial situation enjoyed by the sponsors, by 1997. Endesa Chile is a 37% Edegel shareholder. Enersis is a 60% Endesa-Chile shareholder, and Endesa-Spain is a 65% Enersis shareholder. Enersis’ and Endesa’s revenue for year 2003 were $3,998,967,000 and $20,899,871,000 respectively. Both sponsors are not comparable to the project’s sponsor in access to financing, as of today, and they were certainly in a superior financial standing in 1997. Also the Chinango Project’s sponsors enjoyed a better international investment climate in 1997 than SINERSA did in 2002. The Projects started construction works prior to pro-Camisea policies.

-San Gaban II (1999, 2000) Hydropower Plant (2 units): Units developed and fully owned by the government (as of today), the San Gaban II hydropower plant with an installed capacity of 113.1 MW55 started its preliminary construction works in 1995. In May 1996, the civil works were called into a public bid. The winner was a Peruvian-Brazilian-French Consortium that started civil works in September 1996 and took 3 years to finish them. San Gaban II was concluded in 1999. The external financing was $155 million approx., granted by The Japan Bank for International Cooperation ($130 million) and the CAF ($25 million). The total cost of this project was $208 million. San Gaban II, is currently under 100% ownership of the Peruvian Government through Fondo Nacional de Financiamiento de la Actividad Empresarial del Estado (FONAFE). Discussing natural gas-fired power plants development (Alternative 2): -Ventanilla TG3 and Ventanilla TG4 (2004): Ventanilla TG3 and TG4 are the first plants converted to use Camisea’s natural gas, and are property of Etevensa; furthermore in May 2006, the gas combined cycled technology will be ready to operate in Ventanilla TG4. These plants respond to Pro-Camisea governmental policies because Etevensa was committed to install a 320 MW gas-fired power installed capacity in order to win the transferal of Camisea’s Take or Pay Contract from ElectroPeru56. -TG Malacas and Aguaytia 1 and 2 (1998): These plants have been developed by the private sector, and by using the only two discovered gas wells in Peru besides Camisea. Although, they are not consequence of the Camisea circumstance, they show that gas per se is an attractive generation technology in Peru. The Aguaytia gas price does not differ greatly from the Camisea Gas price that is set for electricity generators consumers. After the commercial operation of Ventanilla TG3 and TG4 in August 2004, it is foreseen that other gas-fired power plants concessions requests will be presented to the MINEM.and granted, thus making 53 Which has stakes in Sociedad Minera Corona (assets of $36.06 Million up to June 2004), Sociedad Minera La Cima (assets for $19.8 Million up to June 2004) and Inversiones Agricolas S.A (asset information not publicly available). 54 Russian crisis. 55 Two units of approximately the same installed capacity. 56 The TOP is mentioned under Step 3 Barrier Analysis (Sub-Step 3.a.) faced by The Project.



alternative 2 a plausible future common practice. The expected prevailing practice of the gas-fired option for generation in Peru is starting to show with large gas-fired power plants being constructed and/or accommodated to function with the Camisea gas. As of today, there are 3 large plants that are functioning with the Camisea gas, which have started to operate: -Ventanilla TG3: 164.1 MW from September 2004 -Ventanilla TG4: 160.5 MW from September 2004 -Santa Rosa TG7: 121.3 MW from June 2005. The three of them used to operate with oil but have converted to gas when the Camisea-gas became available in their location. There are 2 large Camisea gas-fired power plants projects that have started construction this year. Chilca TG1: 165 to be commissioned in November 2006 Chilca TG2: 165 to be commissioned in November 2006 The conversion to combined cycle (“cc”) of these two plants will add to an installed capacity of 520 MW, and as cc they both are to be commissioned in April 2007. Tractebel’s request of 360 MW approximately installed capacity (not yet in construction) and EGECHILCA’s request of 520 MW installed capacity (mentioned above) are two of the most publicly known natural gas-fired-power-plant concession requested to the MINEM. Discussing the no implementation of any power generation project (Alternative 3): -In the Newly Built 1998-2003 power plants table shown above it can be seen that the 3-year annual average of new capacity additions in the SEIN has decreased in 92% in the 3 most recent years (2001-2003) when compared with the previous three years (1998-2000)57. This proves that the country can experience also scarcity in generation projects, in certain years; Alternative 3 although plausible in certain periods of time is not likely to become a common practice because of market forces. Sub-step 4b. Discuss any similar options that are occurring: No similar activities (hydropower plants) in terms of access to financing, international investment climate or developed under the same clear governmental pro-Camisea position have been identified from 1998. The only hydro power plant development that can be comparable to the project in regards to depressed international investment climate (investment barrier) and starting construction after the clear pro- Camisea governmental position (barrier due to prevailing practice) is Huanchor, but this project activity has essential distinctions with the project, these distinctions have been analyzed in Sub-step 4a. Why the other hydropower plant activities are no comparable to the project has also been analyzed under Sub-step 4a. Since similar activities (hydropower plants) have essential distinctions with the project activity that can reasonably be explained and which have been presented under Sub-Steps 4a and 4b, the claim that the proposed activity is common practice is not called into question. Thus, the project is not common practice but a very unusual occurrence that endangered its existence without attaining CDM Status. Meaning the project is additional under Step 4. Step 5. Impact of CDM Registration CDM registration will alleviate the financial hurdles of the project (Step 2. Investment analysis) since it would provide risk-free revenue58, attached to the project’s annual generation. If CERs revenues are used to offset the project’s O&M annual costs, the project’s levelized cost will decrease and so will the

57 Being the average annual capacity additions in 1998-2000, 275.87 MW, and 20.93 MW in 2001-2003. 58 Except for CDM risk.



project’s financial unattractiveness. The sponsor considers the potential impact of CDM Registration very important for the project’s financial viability due to the potential CERs price upside and potential CERs high liquidity in the international market. As of today, taking a credible CERs price of $5.63 per tCO2e - which is the weighted average CERs price between January 2004 and April 200559 - CERs revenues could reduce the project’s financial gap (difference between the project levelized cost and the SEIN LRMC) in 21%, going from a $13.82/MWh60 to $10.93/MWh61 - reducing almost one fifth down the financial gap that the project faced without CERs revenues.

Source: Single parameters were provided by the sponsor, calculations are own production. Depending on future CERs price, the impact of carbon finance on the financial viability of the project could be even greater. i.e. Upon registration and promptly CERs sell in the EU ETS, as long as issues that explain the difference between the CERs price and the currently higher EUA price are overcome62, the project’s CERs from the start of its crediting period (April 1st, 2008) up to December 31st, 2012 could achieve a higher-than-$5.63 price, reducing the project financial gap in a greater percentage –assuming that EUA price continue to be priced higher. Moreover, CDM registration also alleviates the barriers faced by the project (Step 3. Barrier analysis). Investment barrier (Barrier 1) that impedes funding is alleviated when CDM registration is achieved. When CDM registration is achieved the sponsor could discount or borrow against CERs revenues at a low interest rate63. The sponsor is currently evaluating this possibility to satisfy its own cash flow commitments. Since the capital investment is so large, debt becomes a necessity more than an optimization of shareholder value for the project Barrier due to prevailing practice (Barrier 2) will be alleviated. CERs revenues will allow the project to better compete with more efficient technologies available in the country (open cycle and combined cycle

59 International Emissions Trading Association and The World Bank Carbon Finance Business (Washington DC, May 2005) - State and Trends of Carbon Market 2005, Page 4. 60 $41.06 minus $27.24. 61 $38.17 minus $27.24, for a CERs revenues stream of 21 years. 62Delivery risk from 2005-2007, uncertainty related to technical aspects of the import of CERs into the EU ETS, among others. These and further explanations of the difference in EUA and CER prices are stated by: International Emissions Trading Association and The World Bank Carbon Finance Business (Washington DC, May 2005) - State and Trends of Carbon Market 2005, Page 4. 63Given that this revenue streams has CDM risk only.

CER 7 years PV of CDM Revenue as of April 1st 20083,722,864

Equivalent Annual Revenue$523,975In millions

$0.52CER 14 years PV of CDM Revenue as of April 1st 2008

$5,210,659Equivalent Annual Revenue

$733,375In millions

$0.73CER 21 years PV of CDM Revenue as of April 1st 2008

$5,805,237Equivalent Annual Revenue

$817,059In millions

$0.82

+ CERs + CERs + CERs7 years 14 years 21 years

Capacity MW 49.00 49.00 49.00 49.00Total Investment $Million 52.01 52.01 52.01 52.01Annual Cost:Income CERS $Million 0.00 -0.52 -0.73 -0.82Capital $Million 7.32 7.32 7.32 7.32O&M $Million 4.28 4.28 4.28 4.28Total Annual Cost $Million 11.60 11.08 10.87 10.78Plant Factor % 65.82% 65.82% 65.82% 65.82%Generation MWh 282,528 282,528.00 282,528.00 282,528.00 Levelized Cost $/MWh 41.06 39.21 38.47 38.17CERs/yr (tCO2) 153,957 Change in $/MWh: -4.52% -6.32% -7.04%CDM Revenue/yr ($) 866,778

SENSITIVITY ANALYSIS FOR THE PROJECT LEVELIZED COST ($/MWh)

14% discount rate

40 years of payment



Camisea-natural-gas-based electricity generation), and also to better manage the lower electricity market price-consequence of the incorporation of more efficient technologies to the system. The CERs revenue could also offset the fiscal incentives given by the Peruvian government to natural gas-fired power projects/plants (i.e. Selective Consumption Tax exemption for the gas). In addition to that, the sponsor, who has not yet found partners to develop the project, expects to get exposure for the project upon its registration to interested green field equity investors – the sponsor needs another partner to make the project a realistic possibility capable of overcoming the barriers identified. It is likely that potential investors who can be attracted by the project after registration will have an interest that goes beyond the financial returns and are rather interested in the positive environmental impact of the project, which can only be certified after the project’s CDM registration. Since the approval and registration of the project as a CDM activity alleviate the economic and financial hurdles (Step 2) and other identified barriers (Step 3) to a reasonable extent, it is concluded that the project is additional under Step 5. Because all of the above steps were satisfied, the CDM project activity is not the baseline scenario, meaning the project is additional. B.4. Description of how the definition of the project boundary related to the baseline methodology selected is applied to the project activity: As of today, the spatial extent of the project boundary includes all power plants connected physically to the SEIN. No electricity exports or imports have occurred in the SEIN as of today but will be monitored, and be included in the project boundary according to the methodology, if any. B.5. Details of baseline information, including the date of completion of the baseline study and the name of person (s)/entity (ies) determining the baseline: The baseline study was completed on 04/04/2005 by: Tarucani Generating Company S.A Tarucani Generating Company S.A is a project participant listed in Annex 1. 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: 01/04/2006 (DD/MM/YYYY) C.1.2. Expected operational lifetime of the project activity: 40y-0m. C.2 Choice of the crediting period and related information: C.2.1. Renewable crediting period C.2.1.1. Starting date of the first crediting period: 01/04/2008



C.2.1.2. Length of the first crediting period: 7y-0m. C.2.2. Fixed crediting period: C.2.2.1. Starting date: N/A C.2.2.2. Length: N/A SECTION D. Application of a monitoring methodology and plan D.1. Name and reference of approved monitoring methodology applied to the project activity: “Consolidated monitoring methodology for zero-emissions grid-connected electricity generation from renewable sources (ACM0002)” The above methodology is hereafter referred to as the “monitoring methodology”. D.2. Justification of the choice of the methodology and why it is applicable to the project activity: The project will be a grid-connected zero-emission renewable power generation activity and meets all the following conditions that are stated in the monitoring methodology (ACM0002): • The project supplies electricity capacity addition from hydropower source; it is a hydropower plant with

existing reservoir where the volume of the reservoir is not increased. • The project is not an activity that involves switching from fossil fuels to renewable energy at the project

site; • The electricity grid is clearly identified (as the SEIN) and information is publicly available on the

characteristics of the grid. No leakages or project’s GHG emissions exist and hence will not be monitored. The following variables will be monitored as stipulated by the monitoring methodology: • Electricity generation from the project (double checking through quality control/assurance

procedures). • The latest SEIN grid data supplied by the COES is used for the calculation of the DDA-OM, and for

the BM. Both margins are to be calculated ex-post annually based on the most recent statistics available as directed in the project’s monitoring plan (“MP”)



D.2. 1. Option 1: Monitoring of the emissions in the project scenario and the baseline scenario D.2.1.1. Data to be collected in order to monitor emissions from the project activity, and how this data will be archived: ID number (Please use numbers to ease cross-referencing to D.3)

Data variable

Source of data

Data unit

Measured (m), calculated (c) or estimated (e)

Recording frequency

Proportion of data to be monitored

How will the data be archived? (electronic/ paper)

Comment

D.2.1.2. Description of formulae used to estimate project emissions (for each gas, source, formulae/algorithm, emissions units of CO2 equ.) The project emissions are zero. D.2.1.3. Relevant data necessary for determining the baseline of anthropogenic emissions by sources of GHGs within the project boundary and how such data will be collected and archived : ID number (Please use numbers to ease cross-referencing to table D.3)

Data variable Source of data

Data unit Measured (m), calculated (c), estimated (e),

Recording frequency

Proportion of data to

be monitored

How will the data be archived?

(electronic/ paper)

Comment

1. EGh Electricity supplied to the grid by the project

COES MWh Directly Measured

Hourly measuremen

t and monthly

recording

100% electronic Electricity supplied by the project to the grid. Double check with receipt of sales. As the project operator will be an active

member of COES, all data will come from COES.



2. EFy CO2 emission

factor of the grid

Own production

tCO2/MWh c yearly 100% electronic Calculated as the average of the OM and BM emission factors

3. EF omy CO2 Operating

Margin Emission

Factor of the grid

Own production

tCO2/MWh c yearly 100% electronic Calculated as indicated in the relevant OM baseline method (DDA-OM)

4. EF bmy CO2 Build Margin

emission factor of the

grid

Own production

tCO2/MWh c yearly 100% electronic Calculated as Sum(Fi,yxCOEF)/Sum(Gen m,y) over

recently built power plants defined in the baseline methodology (BM2)

5. F i,y Amount of each fossil

fuel consumed by each power source/plant

Own production

by using COES Net efficiency

conversions (NECs) annual data*

TJ e monthly 100% electronic Reliably estimated with the Annual Plant Fuel Requirement (APFR) Formula64: Gen (KWh)*3.6*10^6/(NEC*10^12)=TJ, where Net efficiency conversions (“NECs”) are the average real NECs per technology. Real NECs per power plant need to be taken from most recent COES annual Statistics. The monitoring of parameter 5 should be done monthly but at the end of the year NECs per technology should be replaced by using the most recent year published NECs information, accordingly. *COES monitors fuel consumption by calculating it from electricity produced and real NECs per power plant. This is the same approach that will be used to monitor Parameter 5 in The Project’s MP.

64 The APFR Formula has been taken from The Green House Assessment Handbook (September, 1998) – a World Bank document.



6. COEFi CO2 emission

coefficient of each fuel

type i

Own production

tCO2e/mass or volume

unit

c yearly 100% electronic COEFs need to be updated annually with annual Real NECs data, published by COES. Average COEFs per technology will need to be calculated separately by the ERCP Manager by using the average Real NECs per technology, which are to be calculated separately as well. The COEF formula to use is the following: COEFs per technology = [3.6 x (44/12) x C x O] / [103 x NEC average per technology]-This formula is deducted from the APFR formula

7. Gen Hourly electricity

generation of all units f the

grid

COES MWh m Hourly measured by

monthly recording

100% electronic Should be taken from COES.

8. Plant Name

Identification of power

plants for the OM

COES Text e yearly 100% of set plants

electronic Identification of plants to calculate OM

9. Plant Name

Identification of power

plants for the BM

COES Text e yearly 100% of set of plants

electronic Identification of plants (m) to calculate BM

11. The merit order in

which power plants are dispatched

by documented

evidence

COES Text m Weakly 100% Paper for original documents, else

electronic

Required to stack the plants in the dispatch data analysis



11a. GENimports

Electricity imports to

The Project’s electricity

system

COES KWh c yearly 100% electronic Obtained from the latest local statistics. If local statistics are not available, IEA statistics are used to determine imports.

Imports are not expected but will be monitored if any

11.b. COEFimport

s

CO2 emission

coefficient of fuels used in connected electricity systems (if

imports occur)

COES tCO2e/mass or unit volume

c yearly 100% electronic Obtained from the latest local statistics. If local statistics are not available, IPCC default values are used to calculate them

Baseline Emission Parameters numbering use ID numbers defined in the ACM0002 Methodology/Version 01’s page 13 (http://cdm.unfccc.int/EB/Meetings/015/eb15repan2.pdf.). D.2.1.4. Description of formulae used to estimate baseline emissions (for each gas, source, formulae/algorithm, emissions units of CO2 equ.) See Section E.4. for baseline emissions calculations (prior to validation estimate). D. 2.2. Option 2: Direct monitoring of emission reductions from the project activity (values should be consistent with those in section E). D.2.2.1. Data to be collected in order to monitor emissions from the project activity, and how this data will be archived: ID number(Please use numbers to ease cross-referencing

to table D.3)

Data variable

Source of data

Data unit

Measured (m), calculated (c), estimated (e),

Recording frequency

Proportion of data to

be monitored

How will the data be archived? (electronic/

paper)

Comment



D.2.2.2. Description of formulae used to calculate project emissions (for each gas, source, formulae/algorithm, emissions units of CO2 equ.): N/A. D.2.3. Treatment of leakage in the monitoring plan D.2.3.1. If applicable, please describe the data and information that will be collected in order to monitor leakage effects of the project activity ID number(Please use numbers to ease cross-referencing to table D.3)

Data variable

Source of data Data

unit

Measured (m), calculated (c) or estimated (e)

Recording frequency

Proportion of data to be monitored

How will the data be archived? (electronic/ paper)

Comment

N/A. D.2.3.2. Description of formulae used to estimate leakage (for each gas, source, formulae/algorithm, emissions units of CO2 equ.) N/A. D.2.4. Description of formulae used to estimate emission reductions for the project activity (for each gas, source, formulae/algorithm, emissions units of CO2 equ.) N/A. D.3. Quality control (QC) and quality assurance (QA) procedures are being undertaken for data monitored Data (Indicate table and ID number e.g. 3.-1.; 3.2.)

Uncertainty level of data (High/Medium/Low)

Explain QA/QC procedures planned for these data, or why such procedures are not necessary.



1 Low COES and own records are used to ensure consistency Others Low IEA statistics (for energy data) are used to check local data D.4 Please describe the operational and management structure that the project operator will implement in order to monitor emission reductions and any leakage effects, generated by the project activity No especial monitoring equipment is needed. The sponsor will count with a monitoring plan and pre-programmed spreadsheets so the sponsor will just need to collect the information as described and apply the formulas as directed in the monitoring plan. The collection sources of the data will not be in any case the project’s own records but COES records of hourly production to keep the highest transparency and accuracy of the data. The project staff designated will confirm these data with own records and own records will be double checked with sales receipts. D.5 Name of person/entity determining the monitoring methodology:

The monitoring methodology and MP were completed on 04/04/2005 by Tarucani Generating Company S.A Tarucani Generating Company S.A is a project participant listed in Annex 1.



SECTION E. Estimation of GHG emissions by sources E.1. Estimate of GHG emissions by sources: The project shall be responsible for zero GHG emissions. Hydropower plants built over existing reservoirs where the volume of the reservoir is not increased are classed as zero emission projects and there are no associated emissions in the project boundary. E.2. Estimated leakage: The project is not responsible for any leakage. E.3. The sum of E.1 and E.2 representing the project activity emissions: The project is not responsible for any project activity emission, and leakage is zero. The sum of these two estimates is zero. E.4. Estimated anthropogenic emissions by sources of greenhouse gases of the baseline: The methodology stipulates that the baseline of the project is the CM, which is the average of the OM and BM. Estimated anthropogenic emissions were calculated for the project following a 4-step-process: Step 1 – Calculation of the OM Step 2 – Calculation of the BM Step 3 – Calculation of the CM Step 4 – Calculation of the project’s ERs prior to validation Step 1 – Calculation of the OM Out of four options for the OM, the Dispatch Data Analysis Operating Margin Emission Factor (DDA-OM) was taken; as it constitutes the first methodological choice where data is available, according to the methodology. The formula for the DDA-OM used was provided by the methodology: EF_OMy Dispatch Data (tCO2/MWh)= E_OMy/EGy E_OMy = Sum of [average tCO2/MWh emitted by plants that fall within top 10% of grid dispatch each hour of the year “times” the project generation in MWh each hour of the year] EGy = The project generation in the year For this calculation the units’ hourly generation of 2003 was utilized, which was the most recent statistic data available. Because at the time the baseline calculation was completed, the project hourly generation data for a whole year was inexistent, it was assumed that the project operated at full capacity and dispatched equally during all hours of the year. Considering this assumption, the variables were defined as follows: -EGy: An “approximation” to MWh generated in 2003 by the project - was obtained from multiplying installed capacity (MWh) of the project times 8760. -EGh: An “approximation” to MWh generated in each hour of 2003 - assumes that the project produces at its full installed capacity (49MWh) each hour. -Fi,n,h: Electricity output in MWh hourly produced in 2003 by each unit of the SEIN that fall within the top 10% of grid dispatch.



-COEFi,n65: The tCO2/MWh factors assigned to each unit of the SEIN according to its technology – For hydropower plants the COEF = 0. The information of the hourly generation of all SEIN units and their COEF associated was organized in columns (in EXCEL), where the position of the columns was sorted according to a “monthly grid dispatch merit order” calculated66. This organization helped to identify the plants that fall within top 10% of grid dispatch each hour of the year. The resulting Dispatch Data Analysis Operating Margin emission factor was 0.72614 tCO2/MWh and was obtained from dividing E_OMy by EGy =97,960/134,904.

E_OMy: SUM Egh*EF_DDh 97,960 134,904 :EGy EOMy/Egy: Operating Margin DDA_OM 0.72614 :EF_OMy DD (TCO2/MWh)

Source: Taken from Pubic Poechos I PDD. Step 2 – Calculation of the BM According to the methodology, the BM is defined as the generation-weighted average emission factor of either the 5 most recent or the most recent 20% of power plants built (in generation), whichever group’s annual generation is greater. Both lists of plants should exclude CDM-status plants. Out of the 2 options for the BM, option 2 was selected for the sake of conservativeness; this option does not include in-construction plants in the samples and requires an annual ex-post calculation for the first crediting period. The formula applied to the selected sample was: EF_BMy (tCO2/MWh) = [∑I,m Fi,m,y,xCOEFi,m] / [∑mGENm,y] F=Generation of each plant of the selected sample; COEF=tCO2/MWh of each plant of the selected sample; GEN=Generation of each plant of the selected sample. For the BM2 calculation, any increase in installed capacity in the SEIN was identified and considered only if the increase was made in new units added (No: upgrades, rehabilitations or interconnections of old units). The following list shows the capacity additions (new units’) in the SEIN from 1988 to 2003, and their annual generation. As the project did not generate yet, the annual generation of the additions taken was the average of their three most recent year’s generations.

Newly Built = Only when new units are added - interconnectionof units less than 5 years old are included

Interconnection = Old unit that gets interconnected to SEIN

Rehabilitation = Reconstruction of a plant that was broken down

Upgrade = Same unit that increases its installed capacityby technological improvements or adjustments

Classification of SEIN Addition in Installed Capacity (MW)

Source: Taken from Pubic Poechos I PDD67.

Generation of Additions to the SEIN (1988-2003)68 65 COEFs assigned to each unit of the SEIN according to their technology can be seen in annex 3 using IPCC 1996 values. 66 This was done by a simple average of the four weekly Santa Rosa Equivalent Cost Soles/MWh (merit orders) assigned to each unit of the SEIN, by COES, in a month. 67 Interconnection excludes units interconnected considered in the newly built category.



Years Techn Addition Install.Cap. 2001 Gen 2002 Gen 2003 Gen Annual GenerationCategory Added (MW) (GWh) (GWh) (GWh) (GWh)

1988C.H. CARHUAQUERO HYDRO Newly built 75.1 469.27 479.41 458.78 469.16CHARCANI (I-V) HYDRO Newly built 136.80 842.17 641.80 660.24 714.741993TG VENTANILLA 2 D2 Newly built 100 2.40 2.45 1.54 2.13TG VENTANILLA 1 D2 Newly built 100 2.40 2.45 1.54 2.131995CALANA R6 Newly built 19.2 33.02 25.72 45.81 34.851996STA. ROSA WESTING D2 Newly built 127.7 9.41 5.61 11.60 8.881997C.H. GALLITO CIEGO HYDRO Newly built 34.0 183.53 149.71 121.79 151.68TG VENTANILLA D2 Newly built 184.0 4.41 4.51 2.83 3.92MOLLENDO MIRLESS R500 Newly built 31.7 10.98 9.53 35.37 18.631998AGUAYTIA 1 GAS Newly built 86.3 230.80 412.26 466.80 369.95AGUAYTIA 2 GAS Newly built 86.3 216.30 332.89 367.97 305.72TG MALACAS PM GAS Newly built 102.2 206.23 181.35 274.30 220.631999SAN GABAN II HYDRO Newly built 55.0 357.38 376.19 356.34 363.30CALANA R6 Newly built 6.4 11.01 8.57 15.27 11.62MOLLENDO TGM D2 Newly built 90.0 0.73 0.86 1.43 1.012000SAN GABAN II HYDRO Newly built 58.1 377.51 397.38 376.41 383.76ILO2 TVC COAL Newly built 145.0 338.78 845.93 859.44 681.38C.H. CHIMAY HYDRO Newly built 156.0 724.76 752.96 825.87 767.86C.H. YANANGO HYDRO Newly built 42.3 214.60 239.13 202.28 218.672001TUMBES R6 Newly built 18.3 22.38 20.73 27.99 24.362002C.H. HUANCHOR HYDRO Newly built 18.9 - 36.86 144.64 144.642003

YARINACOCHA R6 Newly Built 25.6 - - 56.88 144.97

% Inst Cap*TGen

Source: Taken from Pubic Poechos I PDD. Out of the list above, it can be seen that the 5 most recently built plants up to 2003 were: 1)Yarinacocha, 2) Huanchor, 3)Tumbes, 4)Yanango and 5) Chimay, and their comprised annual generation was 1,300.5 GWh. Because the annual generation of the 20% most recently built was greater, 3,860.08 GWh, the latter group was selected for the BM calculation. The 20% most recently built plants69, in generation, comprises the whole list above except for 1988 capacity additions in the SEIN. Because the tCO2 that each unit of the selected sample emits is a direct function of the technology it uses; the selected sample of “newly built” plants was organized (clustered) by technology and each technology’s annual electricity generation output was transformed back to its fuel consumption caloric value through the annual plant fuel requirement formula: APFR (TJ) = Gen (KWh) x 3.6 x 10^6 / (NEC x 10^12) and multiplied by carbon content factor (“C”) x oxidation factor (“O”)70 x 44/12 (the C-CO2 mass conversion factor). The total tCO2 per fuel type obtained was added up and the result was divided by the total generation (MWh) of the selected sample. Hence a weighted average tCO2/MWh of the selected sample was obtained. The resulting BM2 was 0.36371 tCO2/MWh, and was obtained from dividing total tCO2 emitted from the selected sample “by” total generation of the selected sample.

68 In the table, San Gaban appears twice because the increases on its installed capacity were 2 units, the first one was put in operation in 1999 and

the second one in 2000 – each unit generation was considered accordingly. Yarinacocha generation was annualized since it did not operate for a full year yet as of December 2003.

69 Exactly, the selected sample’s generation comprises 19.69% (or 20% rounding to the nearest integer) of 2001-2003 average annual generation of the SEIN (19,603 GWh). 70 C and O use IPCC-1996 world wide values per fuel type.



Technologies in Selected Sample Most Recent Year Gen (GWh) % per technology APFR C O 44/12 CO2 Emissions(tCO2)Coal 681.38 18% 7,433.28 25.80 0.980 3.67 689,124d2 18.06 0% 186.12 20.20 0.990 3.67 13,647r6 215.80 6% 1,807.54 21.10 0.990 3.67 138,445

r500 18.63 0% 204.82 21.10 0.990 3.67 15,688Dry Gas 675.68 18% 7,484.40 15.30 0.995 3.67 417,776

Pure Methane Gas 220.63 6% 2,443.85 14.50 0.995 3.67 129,282Dry Gas CC 0.00 0% 0.00 15.30 0.995 3.67 0

Hydro 2,029.91 53% 0.00 0.00 0.000 0.00 0TOTAL 3,860.08 100% 1,403,961

BM2= 0.36371 tCO2//MWh Source: Taken from Pubic Poechos I PDD. Step 3 – Calculation of the CM The baseline emission factor was calculated as a combined margin (CM), consisting of the simple average71 of both the resulting OM and the resulting BM. All margins are expressed in tCO2/MWh. CM = 0.5 x OM + 0.5 x BM CM = 0.5 x (0.72614) + 0.5 x (0.36371) = 0.54493 tCO2/MWh The resulting baseline emission factor was 0.54493 tCO2/MWh. Step 4 – Calculation of the project’s ERs prior to validation Because the project itself does not produce any emission and there is no leakage, the baseline emissions were estimated to be equal to the project ERs. The estimated ERs per year for the project were obtained from the following multiplication: Estimated baseline emissions = CM x (Estimated annual project generation in MWh) Estimated ERs per year = CM x (Estimated annual project generation in MWh) Estimated ERs per year = 0.54493 tCO2/MWh x 282,528 MWh = 153,957 tCO2e or 153,957 ERs Assuming the 3 most recent years (data used for the calculations) were average years in hydrological conditions. The ERs per year estimated for the first crediting period are: Estimated ERs for the first crediting period=153,957 tCO2/yrx 7yrs=1,077,699tCO2e or Estimated ERs72. E.5. Difference between E.4 and E.3 representing the emission reductions of the project activity: The ERs of the project equal the baseline emissions because the project itself does not produce any emission and leakage is inexistent. E.6. Table providing values obtained when applying formulae above:

Year Total baseline emissions (tCO2e) Total Project emissions (tCO2e) ERs(tCO2e)

2008 115,468 0 115,468 2009 153,957 0 153,957 2010 153,957 0 153,957 2011 153,957 0 153,957 2012 153,957 0 153,957 2013 153,957 0 153,957 2014 153,957 0 153,957 2015 153,957 0 153,957 2016 153,957 0 153,957 2017 153,957 0 153,957

71 The default weights (50%,50%) were kept. 72 All margins were rounded to the fifth decimal, but the CERs per year was rounded down to the nearest integer.



2018 153,957 0 153,957 2019 153,957 0 153,957 2020 153,957 0 153,957 2021 153,957 0 153,957 2022 153,957 0 153,957 2023 153,957 0 153,957 2024 153,957 0 153,957 2025 153,957 0 153,957 2026 153,957 0 153,957 2027 153,957 0 153,957 2028 153,957 0 153,957 2029 38,489 0 38,489 Total 3,233,097 0 3,233,097

Source: Own calculations. SECTION F. Environmental impacts F.1. Documentation on the analysis of the environmental impacts, including transboundary impacts: An Environmental Impact Assessment (“EIA”) was a legal requirement for the project. Peru’s ECL’s Article 25 lists the EIA as a requirement to obtain a definitive concession from Peru’s Ministry of Energy and Mines (“MINEM”). The project needed a definitive concession to be granted by the MINEM73, because it attained the construction and operation of an electricity generation activity of more than 10MW of installed capacity. Numerous environmental assessment documents were completed during the preparation of the project’s EIA. Construction impacts are going to be well managed through proper environmental practices, as enumerated in an Environmental Management Plan (“EMP”), which is part of the EIA. The project’s EIA’s approval by the MINEM, was required by the host party to grant the project’s electricity generation concession. The project EIA has been approved by the MINEM and as required by Law, has been developed by an environmental consulting firm authorized by the MINEM-Environmental Division. The firm that performed the EIA was Inspecciones Tecnicas S.A (INTESA). F.2. If environmental impacts are considered significant by the project participants or the host Party, please provide conclusions and all references to support documentation of an environmental impact assessment undertaken in accordance with the procedures as required by the host Party: Environmental impacts were not considered significant. Furthermore, since the project is the first hydropower plant project evaluated by the Peruvian government to be able to apply to the Clean Development Mechanism74, the project had an additional thorough review of environmental impacts made by the MINEM (a requirement of the DNA at that time) – the questionnaire of the environmental impacts that had to be completed is made available to the Designated Operational Entity (“DOE”). Below is listed the potential environmental impacts and the mitigations measure to be taken, included n the project’s EMP, that the sponsor is keen to abide.

73 Articles 3 and 24 of ECL define in which cases “a concession” and “a definitive concession” are required, respectively. 74 The National Commission of Environment (“CONAM”) approved on November 8th, 2002 that the project applies to the CDM.



EIA’s Potential Negative Impacts and Mitigation Measures - During Plant’s Construction

Affected Mean Features Mitigation mesuare Water -Contamination of the river, due to solid waste

that could be deposit in the river, during the project’s construction.

-There will be no contamination from solid residues in the water. The water intake will be at 2 meters of height. There is no population or planned worker-camping fields next to the river.

Air -Emission of GHG that are caused by transportation of the equipment and materials. -Contamination due to accumulation of solid waste.

-Few equipment and vehicles will be used, so that emissions of GHG will be negligible. -All solid residues will be buried in landfills75.

Earth -Motion in the land due to excavation and exploiting works. -Contamination of the land due to oils and fuels that fall into the ground.

-The material excavated that is not used will be transported to a landfill. -The oil residues will be either transported to companies that could use them, or recycled by MINEM-authorized enterprises.

Surroundings -Bothering noises due to the transportation of equipment and materials.

-The noise emitted by the equipment of the construction will be monitored to abide to Peruvian environmental laws and regulations.

Source: The project’s EIA and the sponsor.

EIA Potential Negative Impacts and Mitigation Measures - During Operation and Maintenance

Affected mean Features Mitigation measure Water -Decrease in the river volume between the

water intake and the water discharged back to the river. -Fuels and oils used by the equipment and vehicles that can fall into the water. -Badly managed solid waste that can fall into the water and could attract parasite carried animals.

-There will be no decrease in the water volume. The water flow is regulated by the Agricultural Authority of the region. -The infrastructure surrounding the water channel will prevent oils from falling into the water. -The average temperature of the water in the channel is 10 Celsius, few fishes (except for “truchas76”) live in the water to be used by the project; no other parasite carried animals (such as rats) could live in

75Built specially for the project or a landfill that is close to the project site. 76A fish resistant to cold river water.



the water to be used by the project. Solid waste will be prevented from falling into the water. All solid waste generated by the project will be transported to a landfill.

Air -Contamination due to organic solid waste -There will be no contamination from solid residues because they will be taken to a landfill.

Earth -Barrier effect of the channel and the road. -Instability and erosion of the land. -Contamination of the land due to fuels, and oils from the equipment and the solid waste that falls into the earth.

-There are no native animals living in the land of the project’s direct area of influence or in the area surrounding it, because there is no vegetation, and the land is arid and rocky. -Because the land is rocky there is stability in the project’s infrastructure. It rains very little in the area. However all preventive measures for land erosion will be taken. -Oils residues will be taken care similarly to what it is planned to be done in the construction phase. Solid waste will be taken to a landfill.

Surroundings Presence of new infrastructure: channels, roads, powerhouse, transmission line.

-The project construction and operation will not cause a high increase in the level of noise in the environment.

Source: The project’s EIA and the sponsor



SECTION G. Stakeholders’ comments G.1. Brief description how comments by local stakeholders have been invited and compiled: Stakeholders to be directly affected by the project were composed by the Querque community population only. Querque is the closest town to the project site. As part of the EIA, the Querque population was called into a public consultation meeting. Querque is the only town that is close to the project site, and the sponsor’s wished to open a positive relationship with them. For this public consultation, Querque’s authorities were contacted to coordinate which day is best to set the consultation meeting, the accordance was a Sunday since Querque’s working population works also on Saturdays. The communication of the place and date of the Sunday meeting was made orally, because there was no other way of mass communication in Querque. G.2. Summary of the comments received: The project was positively received by the Querque community. Since the Querque community economy is based mainly on agriculture, some of the comments of the public consultation regarded the water to be used by the project; other comments regarded improvement in the local town (i.e. construction of roads, electrification, classrooms in the local school) and fostering the animal and vegetation proliferation. The Querque population also expressed keen interest in being hired by the project. The needs expressed by Querque were not mainly related with the project impacts, but rather on Querque needs. G.3. Report on how due account was taken of any comments received: The broad social plan developed by the sponsor for the Querque community accounts for a total budget of $550,000, which is to be wholly assumed by the sponsor. This plan77, named “portfolio of projects for the socio-economic development of the Querque community, the Lluta district, the Caylloma province, and the Arequipa Department”, more than satisfy all the comments received on the day of the public consultation; and brings proof of the sponsor high social sensitivity. Specifically, the plan includes: -Electrification of Querque. The investment will consist of an electricity-fed line of 22.9/0.22 kV and 50 KVA that will go from the Tarucani Substation to the Querque community. -Financing for the creation of the local administration system for the town. -Enlargement and repairing of the water channel system. -Bridges over the Huasamayo and Querque hills. -Driving road to join Querque and Huasamayo. -Road to allow entrance to the ruins “Llacctapata”. -Cheese-maker factory. -Truchas nest to foster truchas reproduction. -Reforestation project which includes reforestation of eucalipt, quenhua, intimpa, and other local vegetation. -Program of reproduction of Vicuñas78. -Installation of public phones to be property of Querque. -Installation of Internet to be property of Querque. -Installation of parabolic satellite to be property of Querque -Installation of public light to be property of Querque. -Construction of school rooms for the local school. -Improvement in a local hospital stand. -Implementation of a small basic drugstore.

77 Made available to the DOE. 78 Peruvian native animal in extinction.



-Exploitation of the tourism potential of Llacctapata ruins. -Basic training in hospitality and providing of financing for the business of tourists’ accommodations. Besides this portfolio of investments in benefit of the Querque community, the project will hired local labor in all of its implementation phases. The Querque community will count with priority for being hired79.

79 Except when it is required to hire technically skilled labor



Annex 1 CONTACT INFORMATION ON PARTICIPANTS IN THE PROJECT ACTIVITY

Organization: Tarucani Generation Company S.A Street/P.O.Box: Av. El Parque Norte 1174 Building: City: Lima State/Region: Lima Postfix/ZIP: L-41 Country: Peru Telephone: FAX: E-Mail: URL: Represented by: Title: Chairman Salutation: Engineer Last Name: Suazo Middle Name: First Name: Miguel Department: Mobile: Direct FAX: Direct tel: Personal E-Mail:

Annex 2 INFORMATION REGARDING PUBLIC FUNDING

N/A

Annex 3 BASELINE INFORMATION

NECs & IPCC 1996 values per technology (C & 0) that will hold for the first crediting period

COEF(tCO2/MWh)Type of Fuel D2 R6 R500 Gas Dry Gas PM Coal

NEC 34.93% 42.98% 32.74% 32.50% 32.50% 33.00%C Content 20.20 21.10 21.10 15.30 14.50 25.80

Oxidation Factor 0.99 0.99 0.99 0.995 0.995 0.98COEF(tCO2/MWh) 0.76 0.64 0.84 0.62 0.59 1.01

Open Cycle

COEF(tCO2/MWh)Type of Fuel D2 R Gas Dry Gas PM Coal

NEC 55.00% 55.00% 54.00% 55.00% 55.00%C Content 20.20 21.10 15.30 14.50 25.80

Oxidation Factor 0.990 0.990 0.995 0.995 0.980COEF(tCO2/MWh) 0.48 0.50 0.37 0.35 0.61

Combined Cycle



COEF(tCO2/MWh)Type of Fuel D2 R Gas Dry Gas PM Coal

NEC 80% 80% 80% 80% 80%C Content 20.20 21.10 15.30 14.50 25.80

Oxidation Factor 0.990 0.990 0.995 0.995 0.980COEF(tCO2/MWh) 0.33 0.34 0.25 0.24 0.42

Cogeneration

Source: Own production. NECs were calculated by assigning to each plant of the SEIN the NECs suggested by the World Bank Green House Assessment handbook and if not provided by this source, the NECs offered by current engines in the market – The values are specified in the following tables:

Net Efficiency Conversions suggested by WB GH Assessment Handbook 150 MW - 80% load factor-Coal fired Power Plant Conventional Utility Scale-Gas Power Plant Cogeneration

33.00% 32.50% 80.00% Source: Green House Assessment Handbook, A Practical Guidance Document for the Assessment of Project-level Greenhouse Gas Emissions, September 1998 - pg. 24 -25.

Net Efficiency Conversion per type of plant offered in the market. Type of plant

Type of Fuel D2 R6 Gas D2 R6 Coal D2 Gas

Net Efficiency Conversion (%) 34% 43% 37% 36% 32% 37% 55% 54%

Combined CycleHeat TurbineGas TurbineDiesel Engine

Source: Specification given by top-of-the-line engines offered in the market by: GE, Siemens, & other well-known manufacturers – 2003 survey used in previous Peru’s BL calculation – It was considered that R6 NECs were similar to R500 NEC per technology – so the R500 class was not added in the table. By clustering all plants by fuel type, an average NEC per fuel type for the SEIN (using the 2003 production of the plants as the weighting factor) was obtained as follow:



Efficiency Conversion per technologyThermal plants Net Efficiency Conversion:

Thermal plants TOTALVerdun ALCO9 (4) 0.000ILO 2 TV1 859.440 coal 33.00% 859.440 Tcoal 33.0%TG Santa Rosa UTI 5.008 d2 36%TG Santa Rosa BBC(1) 0.000 d2 36%TG Santa Rosa WTG 11.603 d2 36%GD Piura 2 0.464 d2 34%TG Piura 0.040 d2 36%GD Paita 0.852 d2 34%GD Sullana 2.299 d2 34%GD Chiclayo Oeste 9.215 d2 34%TG Trujillo 0.238 d2 34%TG Chimbote 0.491 d2 36%TG Ventanilla 5.910 d2 36%Cummins 0.604 d2 34%Mollendo TG1, TG2 1.428 d2 36%ILO CATKATO 0.155 d2 34%ILO TG1 0.117 d2 36%ILO TG2 0.086 d2 36%CT Moquegua 0.078 d2 34%CT Dolorespata 0.031 d2 34%CT Tintaya 1.747 d2 34%CT San Rafael (2) 0.000 d2 34%CT Bellavista 0.192 d2 34%CT Taparachi 2.656 d2 34% Diesel ConversionPiura 1 Residual 15.023 d2 34% 62.589 TD2 34.93% EfficiencyChilina D2 4.352 d2 36%Malacas 395.072 gas 32.50% Dry Gas Con 32.50% 834.815TGN4 341.020 gas 32.50% EfficiencyTG1 3.508 gas 32.50% Pure Me. Gas ConversionTG2 12.408 gas 32.50% Efficiency 32.50% 395.072TG3 38.137 gas 32.50%TG1 Aguaytía 466.823 gas 32.50% 1,229.887 TGasTG2 Aguaytía (3) 367.991 gas 32.50%San Nicolás TV1 20.041 r500 32%San Nicolás TV2 4.419 r500 32%San Nicolás TV3 27.247 r500 32%CT Chilina 15.197 r500 37.5%Mollendo Mirrlees 35.382 r500 43.0%ILO TV1 51.463 r500 32%

ILO TV2 92.533 r500 32%

ILO TV3 153.153 r500 32% 640.949 Tr500 32.74%ILO TV4 241.513 r500 32%Yarinacocha (5) 56.882 r6 43.0%TV Trupal 0.271 r6 32.0%GD Pacasmayo 17.546 r6 43.0%Tumb-Mercedes-Zarum. 27.986 r6 43.0%CT Calana 61.085 r6 43.0% 163.770 Tr6 42.98% Source: Own production with COES list of plants. Setting these NECs for the baseline estimation assumes that the technology opted per fuel type in the SEIN is going to keep the same. I.e. Up to 2003 the R6 plants in the SEIN used a diesel engine and not a heat turbine so its NEC was closer to 43% than to 32% - see reference Table above. Likewise, usually R-500 plants in the SEIN used a heat turbine so that their NEC was closer to 32% and not to 43%. As COES recently decided to publish NECs from this year, for the monitoring real NECs published by COES will be used to assure the best quality in measured ER-this is explained in the MP.



Justification of the usage of COES information system data for baseline calculation: The baseline calculation disregarded the data that is not registered by COES and deemed COES data to be the best approximation of total SEIN data about both generation and installed capacity additions, and also the best data to allow a good monitoring practice because of three reasons: -There is not as good quality data of the SEIN production as what COES registers. The information of plants connected to the SEIN but not registered in COES regarding generation and installed capacity additions is provided by the plants’ management periodically to the MINEM, but this data does not pass through a verification or validation process or is required to comply with technical standards as rigorously as COES requires from their power plants members. - Limitation on MINEM final annual reports and data availability would not allow good monitoring practice. - The generation of these other plants connected to the SEIN but not registered by COES, is irrelevant, only 1% of total SEIN electricity generation in 2003, as the table bellows shows.

SEIN (GWh) COES (GWh) COES/SEIN Not recorded by COES2003 20,999 20,689 0.99 0.01 2002 20,018 19,658 0.98 0.02 2001 18,755 18,463 0.98 0.02 Anuario Estadistico MINEM (2001-03) and Estadistico de Operaciones COES (2001-03)

Source: Taken from Public Poechos I PDD– based on MINEM Annual Statistic 2003 and COES Annual Statistics 2003.



SEIN Capacity Additions from 1988-2003 (all categories)

Additions to SEIN Situation Additions in Installed Capacity (MW)1988C.H. CARHUAQUERO Newly built 75.1CHARCANI (I-V) Newly built 136.81993TG VENTANILLA 2 Newly built 100.0TG VENTANILLA 1 Newly built 100.01995CALANA Newly built 19.21996

WESTINGHOUSE Newly built 127.71997C.H. PARIAC Interconnection 5.2GD PACASMAYO Interconnection 10.1C.H. GALLITO CIEGO Newly built 34.0TG MALACAS Interconnection 45.0GD CHICLAYO OESTE Interconnection 9.3CH YAUPI Interconnection 108.0CH OROYA Interconnection 21.3CH MALPASO Interconnection 54.4TG VENTANILLA Newly built 184.0TV SAN NICOLAS Interconnection 63.6MOLLENDO MIRLESS Newly built 31.7ILO (TV1) Interconnection 154.0ILO TG Interconnection 81.7ILO (CATKATO) Interconnection 3.31998AGUAYTIA 1 Newly built 86.3AGUAYTIA 2 Newly built 86.3C.H. CARHUAQUERO Upgrade 19.9GD SULLANA Upgrade 3.2TV TRUPAL Upgrade 6.8CHARCANI (I-V) Upgrade 8.1HERCCA Interconnection 1.0SAN RAFAEL Interconnection 11.2MOQUEGUA Interconnection 1.0TG MALACAS Newly built 102.21999SAN GABAN II Newly built 55.0C.H. GALLITO CIEGO Upgrade 4.1C.H. CAHUA Upgrade 1.6CALANA Newly built 6.4GD PACASMAYO Interconnection 14.5C.H. CALLAHUANCA Upgrade 3.3GD PAITA Upgrade 2.8GD SULLANA Upgrade 1.3C.H. MATUCANA Upgrade 8.6MOLLENDO TGM Newly built 90.02000SAN GABAN II Newly built 58.1ILO2 TVC Newly built 145.0C.H. MOYOPAMPA Upgrade 24.6C.H. CAÑON DEL PATO Upgrade 92.7C.H. CHIMAY Newly built 156.0C.H. YANANGO Newly built 42.32001C.H. CAÑON DEL PATO Upgrade 10.0TUMBES Newly built 18.3MACHUPICCHU Rehabilitation 92.3SAN NICOLAS CUMMINS Interconnection 1.32002C.H. CAÑON DEL PATO Upgrade 4.2C.H. HUANCHOR Newly built 18.92003YARINACOCHA Newly Built 25.6ARCATA Interconnection 5.1

Source: Taken from Pubic Poechos I PDD - based on COES annual statistics.



Installed capacity per power plant of the SEIN, as of December 31st, for 1996-2003 1996 1997

PLANT INSTALLED CAPACITY (MW) PLANT INSTALLED CAPACITY (MW)AGUAYTIA ENERGY S.A. AGUAYTIA ENERGY S.A.

CAHUA S.A. CAHUA S.A.C.H. CAHUA 41.5 C.H. CAHUA 41.5

C.H. PARIAC 5.2CNP ENERGIA S.A. CNP ENERGIA S.A.

GD PACASMAYO 10.1C.H. GALLITO CIEGO 34.0

EDEGEL EDEGELC.H. HUINCO 258.4 C.H. HUINCO 258.4C.H. MATUCANA 120.0 C.H. MATUCANA 120.0C.H. CALLAHUANCA 71.0 C.H. CALLAHUANCA 71.0C.H. MOYOPAMPA 63.6 64.7 C.H. MOYOPAMPA 63.0C.H. HUAMPANI 31.4 C.H. HUAMPANI 31.4

TG STA. ROSA WESTINGHOUSE 127.7 TG STA. ROSA WESTINGHOUSE 127.7TG STA. ROSA UTI 109.8 TG STA. ROSA UTI 109.8TG STA. ROSA BBC 52.2 TG STA. ROSA BBC 52.2EEPSA EEPSA

45 TG MALACAS 36.0

EGENOR S.A. EGENOR S.A.C.H. CAÑON DEL PATO 153.9 C.H. CAÑON DEL PATO 153.9C.H. CARHUAQUERO 75.1 C.H. CARHUAQUERO 75.1TG CHIMBOTE 63.4 TG CHIMBOTE 63.4TG PIURA 24.3 TG PIURA 24.3TG TRUJILLO 22.8 TG TRUJILLO 22.8GD PIURA 26.3 GD PIURA 26.3GD CHICLAYO 17.3 26.61 GD CHICLAYO OESTE 21.0

CHICLAYO NORTE 7.5GD PAITA 8.3 GD PAITA 8.3GD SULLANA 8.0 GD SULLANA 8.0TV TRUPAL 12.0 TV TRUPAL 12.0

ELECTROANDES S.A.CH YAUPI 108.0CH OROYA 9.0

12.28 CH PACHACHACA 12.0CH MALPASO 54.4

ELECTROPERU ELECTROPERUC.H. MANTARO 798.0 C.H. MANTARO 798.0C.H. RESTITUCION 210.4 C.H. RESTITUCION 210.4

ETEVENSA ETEVENSA

TG VENTANILLA 200.0 TG VENTANILLA 519.2

SHOUGESA63.6 TV SAN NICOLAS 62.5

EGASA EGASACHARCANI (I-V) 165.16 CHARCANI I 168.82

31.7 MOLLENDO MIRLESS 32.09

CHILINA TV 22 CHILINA TV 22CHILINA CC 20 CHILINA CC 20CHILINA SULZER 10.4 CHILINA SULZER 10.4EGEMSA EGEMSA

MACHUPICCHU 109.90 MACHUPICCHU 109.90DOLORESPATA 15.62 DOLORESPATA 15.62

BELLAVISTA 8.60 BELLAVISTA 7.83

TAPARACHI 6.60 TAPARACHI 7.80EGESUR EGESURARICOTA I, II 35.70 ARICOTA I, II 35.70CALANA 19.20 CALANA 19.20

PARA 2.50 PARA 2.50ENERSUR

154 ILO (TV1) 176.00ILO TG 81.69ILO (CATKATO) 3.30

Source: Taken from Pubic Poechos I PDD.



Continue: Installed capacity per power plant of the SEIN, as of December 31st, for 1996-2003 1998 1999

PLANT INSTALLED CAPACITY (MW) PLANT INSTALLED CAPACITY (MW)AGUAYTIA ENERGY S.A. AGUAYTIA ENERGY S.A.AGUAYTIA 1 101.3 AGUAYTIA 1 86.29AGUAYTIA 2 101.3 AGUAYTIA 2 86.29CAHUA S.A. CAHUA S.A.C.H. CAHUA 41.5 C.H. CAHUA 43.1C.H. PARIAC 5.2 C.H. PARIAC 5.2CNP ENERGIA S.A. CNP ENERGIA S.A.GD PACASMAYO 10.1 24.62 GD PACASMAYO 24.8C.H. GALLITO CIEGO 34.0 C.H. GALLITO CIEGO 38.1

EDEGEL EDEGELC.H. HUINCO 258.4 C.H. HUINCO 258.4C.H. MATUCANA 120.0 C.H. MATUCANA 128.6C.H. CALLAHUANCA 71.0 C.H. CALLAHUANCA 74.3C.H. MOYOPAMPA 63.0 C.H. MOYOPAMPA 64.7C.H. HUAMPANI 31.4 C.H. HUAMPANI 30.2

TG STA. ROSA WESTINGHOUSE 127.7 TG STA. ROSA WESTINGHOUSE 127.7TG STA. ROSA UTI 109.8 TG STA. ROSA UTI 109.8TG STA. ROSA BBC 52.2 TG STA. ROSA BBC 52.2EEPSA EEPSATG MALACAS 147.2 TG MALACAS 147.2VERDUN 2.2 VERDUN 2.3EGENOR S.A. EGENOR S.A.C.H. CAÑON DEL PATO 153.9 C.H. CAÑON DEL PATO 153.9C.H. CARHUAQUERO 95.0 C.H. CARHUAQUERO 95TG CHIMBOTE 63.4 TG CHIMBOTE 63.8TG PIURA 24.3 TG PIURA 24.3TG TRUJILLO 22.8 TG TRUJILLO 22.8GD PIURA 26.3 GD PIURA 26.3GD CHICLAYO OESTE 25.3 GD CHICLAYO OESTE 26.61

GD PAITA 8.3 GD PAITA 11.1GD SULLANA 11.2 GD SULLANA 12.5TV TRUPAL 18.8 TV TRUPAL 15ELECTROANDES S.A. ELECTROANDES S.A.CH YAUPI 108.0 CH YAUPI 108CH OROYA 9.0 CH OROYA 9CH PACHACHACA 12.0 CH PACHACHACA 12.3CH MALPASO 54.4 CH MALPASO 54.4ELECTROPERU ELECTROPERUC.H. MANTARO 798.0 C.H. MANTARO 798C.H. RESTITUCION 210.4 C.H. RESTITUCION 210.4

ETEVENSA ETEVENSA

TG VENTANILLA 561.6 TG VENTANILLA 549.3

SHOUGESA SHOUGESATV SAN NICOLAS 62.50 TV SAN NICOLAS 63.586

EGASA EGASACHARCANI I 176.89 CHARCANI 176.89MOLLENDO MIRLESS 31.7 MOLLENDO MIRLESS 31.71

MOLLENDO TGM 90CHILINA TV 22 CHILINA TV 22CHILINA CC 20 CHILINA CC 20CHILINA SULZER 10.4 CHILINA SULZER 10.4EGEMSA EGEMSAHERCCA 1.02 HERCA 1.02

DOLORESPATA 15.62 DOLORESPATA 15.62SAN GABANSAN GABAN II 55

TINTAYA 17.96 TINTAYA 17.96BELLAVISTA 8.60 BELLAVISTA 8.6SAN RAFAEL 11.16 SAN RAFAEL 11.16TAPARACHI 8.80 TAPARACHI 8.8EGESUR EGESURARICOTA I 35.70 ARICOTA 35.7CALANA 19.20 CALANA 25.6MOQUEGUA 1.00 MOQUEGUA 1PARA 2.50 PARA 2.5ENERSUR ENERSUR ILO (TV1) 176.00 ILO 1 176ILO TG 79.29 ILO 1 TG 79.29ILO (CATKATO) 3.30 ILO 1 CATKATO 3.3





PLANT INSTALLED CAPACITY (MW) PLANT INSTALLED CAPACITY (MW)AGUAYTIA ENERGY S.A. AGUAYTIA ENERGY S.A.AGUAYTIA 1 86.294 AGUAYTIA 1 86.294AGUAYTIA 2 86.294 AGUAYTIA 2 86.294CAHUA S.A. CAHUA S.A.C.H. CAHUA 43.6 C.H. CAHUA 43.6C.H. PARIAC 5.216 C.H. PARIAC 5.216CNP ENERGIA S.A. CNP ENERGIA S.A.GD PACASMAYO 24.562 GD PACASMAYO 24.591C.H. GALLITO CIEGO 38.147 C.H. GALLITO CIEGO 38.147

EDEGEL EDEGELC.H. HUINCO 258.4 C.H. HUINCO 258.4C.H. MATUCANA 128.578 C.H. MATUCANA 128.578C.H. CALLAHUANCA 75.059 C.H. CALLAHUANCA 75.059C.H. MOYOPAMPA 89.25 C.H. MOYOPAMPA 89.25C.H. HUAMPANI 31.36 C.H. HUAMPANI 31.36C.H. YANANGO 42.3 C.H. YANANGO 42.3C.H. CHIMAY 156 C.H. CHIMAY 156

TG STA. ROSA WESTINGHOUSE 127.7 TG STA. ROSA WESTINGHOUSE 127.7TG STA. ROSA UTI 109.8 TG STA. ROSA UTI 109.8TG STA. ROSA BBC 52.2 TG STA. ROSA BBC 52.2EEPSA EEPSATG MALACAS 141.296 TG MALACAS 173.2VERDUN 2.319 VERDUN 2.319EGENOR S.A. EGENOR S.A.C.H. CAÑON DEL PATO 246.582 C.H. CAÑON DEL PATO 256.55C.H. CARHUAQUERO 95.02 C.H. CARHUAQUERO 95.02TG CHIMBOTE 63.833 TG CHIMBOTE 63.833TG PIURA 24.3 TG PIURA 24.3TG TRUJILLO 22.8 TG TRUJILLO 22.8GD PIURA 26.715 GD PIURA 27.277GD CHICLAYO OESTE 26.61 GD CHICLAYO OESTE 26.61

GD PAITA 11.112 GD PAITA 11.112GD SULLANA 12.5 GD SULLANA 12.5TV TRUPAL 15 TV TRUPAL 15ELECTROANDES S.A. ELECTROANDES S.A.CH YAUPI 108 CH YAUPI 108CH OROYA 9 CH OROYA 9CH PACHACHACA 12.282 CH PACHACHACA 12.282CH MALPASO 54.4 CH MALPASO 54.4ELECTROPERU ELECTROPERUC.H. MANTARO 798 C.H. MANTARO 798C.H. RESTITUCION 210.4 C.H. RESTITUCION 210.4

TUMBES 18.339

ETEVENSA ETEVENSA

TG VENTANILLA 549.316 TG VENTANILLA 384

SHOUGESA SHOUGESATV SAN NICOLAS 63.586 TV SAN NICOLAS 63.586

SAN NICOLAS CUMMINS 1.25

EGASA EGASACHARCANI 176.89 CHARCANI 176.89MOLLENDO MIRLESS 31.71 MOLLENDO MIRLESS 31.71MOLLENDO TGM 90 MOLLENDO TGM 90CHILINA TV 18 CHILINA TV 18CHILINA CC 20 CHILINA CC 20CHILINA SULZER 10.4 CHILINA SULZER 10.4EGEMSA EGEMSAHERCA 1.02 HERCA 1.02

MACHUPICCHU 92.25DOLORESPATA 15.62 DOLORESPATA 15.62SAN GABAN SAN GABANSAN GABAN II 110 SAN GABAN II 112.9TINTAYA 17.96 TINTAYA 17.96BELLAVISTA 8.6 BELLAVISTA 8.6SAN RAFAEL 11.16 SAN RAFAEL 11.16TAPARACHI 8.8 TAPARACHI 8.8EGESUR EGESURARICOTA 35.7 ARICOTA 35.7CALANA 25.6 CALANA 25.6MOQUEGUA 1 MOQUEGUA 1

ENERSUR ENERSURILO 1 154 ILO 1 154ILO 1 TG 81.69 ILO 1 TG 81.69ILO 1 CATKATO 3.3 ILO 1 CATKATO 3.3ILO2 TVC 135 ILO2 TVC 145





PLANT INSTALLED CAPACITY (MW) PLANT INSTALLED CAPACITY (MW)AGUAYTIA ENERGY S.A. TERMOSELVAAGUAYTIA 1 86.294 AGUAYTIA 1 86.294AGUAYTIA 2 86.294 AGUAYTIA 2 86.294CAHUA S.A. CAHUA S.A.C.H. CAHUA 43.6 CAHUA 43.600C.H. PARIAC 5.216 PARIAC 5.216CNP ENERGIA S.A. E. PACASMAYOGD PACASMAYO 24.545 PACASMAYO 24.617C.H. GALLITO CIEGO 38.147 GALLITO CIEGO 38.147

ARCATA 5.098

EDEGEL EDEGELC.H. HUINCO 258.4 HUINCO 258.400C.H. MATUCANA 128.578 MATUCANA 128.578C.H. CALLAHUANCA 75.059 CALLAHUANCA 75.059C.H. MOYOPAMPA 89.25 MOYOPAMPA 89.250C.H. HUAMPANI 31.6 HUAMPANI 31.360C.H. YANANGO 42.3 YANANGO 42.300C.H. CHIMAY 156 CHIMAY 156.000C.H. HUANCHOR 18.86 HUANCHOR 18.860TG STA. ROSA WESTINGHOUSE 127.7 SANTA ROSA WTG 127.700TG STA. ROSA UTI 109.8 SANTA ROSA UTI 109.800TG STA. ROSA BBC 52.2EEPSA EEPSATG MALACAS 173.2 ##### MALACAS 173.2VERDUN 1.001EGENOR S.A. EGENORC.H. CAÑON DEL PATO 260.73 CAÑON DEL PATO 260.730C.H. CARHUAQUERO 95.02 CARHUAQUERO 95.020TG CHIMBOTE 63.833 CHIMBOTE 63.833TG PIURA 24.3 TG PIURA 24.300TG TRUJILLO 22.8 TRUJILLO 22.800GD PIURA 27.85 PIURA 27.850GD CHICLAYO OESTE 26.61 CHICLAYO OESTE 26.610

GD PAITA 11.12 PAITA 11.112GD SULLANA 12.5 SULLANA 12.500TV TRUPAL 15 TRUPAL 15.000ELECTROANDES S.A. ELECTROANDESCH YAUPI 108 YAUPI 108.000CH OROYA 9 OROYA 9.000CH PACHACHACA 12.282 PACHACHACA 12.282CH MALPASO 54.4 MALPASO 54.400ELECTROPERU ELECTROPERUC.H. MANTARO 798 COMPLEJO MANTARO - MANTARO 798.000C.H. RESTITUCION 210.4 COMPLEJO MANTARO-RESTITUCION 210.400TUMBES 18.339 18.34 TUMBES 18.244

YARINACOCHA 25.600

ETEVENSA ETEVENSA

TG VENTANILLA 384 VENTANILLA 384

SHOUGESA SHOUGESATV SAN NICOLAS 63.586 SAN NICOLAS TV 1-2-3 63.586SAN NICOLAS CUMMINS 1.25 SAN NICOLAS CUMNIS 1.25

EGASA EGASACHARCANI 176.89 CHARCANI 176.890MOLLENDO MIRLESS 31.71 MOLLENDO MIRLESS 31.710MOLLENDO TGM 90 MOLLENDO TGM 90.000CHILINA TV 18 CHILINA TV 18.000CHILINA CC 20 CHILINA C.C 20.000CHILINA SULZER 10.4 CHILINA SULZER 10.400EGEMSA EGEMSAHERCA 1.02 HERCA 1.020MACHUPICCHU 92.25 MACHUPICCHU 92.250DOLORESPATA 15.62 DOLORESPATA 15.620SAN GABAN SAN GABANSAN GABAN II 112.9 SAN GABAN II 113.098TINTAYA 17.96 TINTAYA 17.960BELLAVISTA 8.6 BELLAVISTA 8.600SAN RAFAEL 11.16TAPARACHI 8.8 TAPARACHI 8.800EGESUR EGESURARICOTA 35.7 ARICOTA 35.7CALANA 25.6 CALANA 25.6MOQUEGUA 1 MOQUEGUA 1

ENERSUR ENERSURILO 1 154 ILO 1 TV 154.000ILO 1 TG 81.69 ILO 1 TG 81.690ILO 1 CATKATO 3.3 ILO 1 CATKATO 3.300ILO2 TVC 145 ILO 2 TVC1 145.000




Detail of LRMC variables In detail, Ii: Sum of Equivalent Annual Costs of the New Capacity Investments ($ millions) for year i. Parameters considered for each Annuity were:

14% discount rate; expected life of thermal plants = 30 years; expected life of hydroelectric plants=40 years; depreciation method: sinking fund The Investment Cost considers: a) Additional generation plants that start operations in years 2007-2017. Plants to be built were assumed to use the most attractive technology for generation available in the market, natural gas. Their size and technological characteristics were determined by the WASP Program (Wien Automatic System Planning Package) out of the following options given:

Alternatives Technologies considered for the WASP Optimization Model Alternative Unit name Observations

GT 100 MW G100 O.C GT 100 MW NG Outside Lima - Camisea NG

GT 150 MW G150 O.C GT 150 MW NG Outside Lima - Camisea NG

CC 2 GT 100+1 HT 100 CC300 CC 300 MW -NG 2 GT of 100 MW - Camisea NG 1 HT of 100 MW - Camisea NG

CC 2 GT 150 + 1 HT 150 CC450 CC 450 MW –NG 2 GT of 150 MW - Camisea NG 1 HTof 150 MW - Camisea NG

Source: Peru’s Baseline Study 2003.

Other fossil fuel technologies were not given as options because their levelized costs are higher, as shows the graph below80:

Load Factors Source: Peru’s Baseline Study 2003.

80 Only the large hydropower plant project Platanal (270MW) shows a lower Levelized Cost- because of its economies of scale.



The WASP generates sequences of projects that comply with the limit values for maximum and minimum reserves, and maximum number of units of the alternatives given.

The WASP determines also the O&M Cost as a function of the hydro supply and SEIN demand for each year in question (2007-2017)

b) Prices of gas turbines – were based on publications in the magazine World Gas Turbine and Installation costs were based and MINEM estimations c) SEIN Interconnection costs - elevator transformers (keys yard), 1 exit substation, a short transmission line, and transmission-line-interconnection cells.

Natural Gas-fired plants Investment Costs Considered

Alternative Code Power (MW) Total ($000) GT 100 MW G100 368 36,790 GT 150 MW G150 336 50,457

CC 2 GT 100+1 HT 100 CC300 475 142,376 CC 2 GT 150 + 1 HT 150 CC450 434 195,267


The WASP results for capacity additions were the following:

Additional Generation Plants Considered for 2007-2017

Year Generation Unit added Power MW Observations

2007 1 GT 150 MW Natural Gas - CC 150

2008 1 GT 150 MW + 1 HT 150 MW Natural Gas – CC 300

Both are complemented: 450 MW CC








Total: 1,800 MW in new units with Natural Gas technology- all of them CC. Source: Peru’s Baseline Study 2003. O&Mi: Annual O&M costs (including fuel) to attend the additional demand for year I, includes O&M of

both existent and new plants that get to satisfy the incremental demand, according to a dispatch simulation made for each year (of the period 2007-2017). The Costs of O&M, basically fuel



costs, were not calculated in a direct manner with a load factor, but instead, they were the result of a Dispatch Simulation. The dispatch simulation considered monthly load factor variations and monthly hydro supply variations. The dispatch simulation also considered temporal shutting down of plants’ operations for maintenance purposes. Thus, in each month of the period in question, the production of fossil fuel fired plants is a function of the hydroelectric supply (function of the hydrological projected conditions) and the demand.

O&M Composition: a) Variable Costs of Fuel (US$/MWh) Fuel price (c$/106 Kcal) and specific caloric consumption (Kcal/KWh). The latter was obtained from the specific fuel consumption (g/kWh) and the caloric value of the fuel in question (Kcal/Kg) – the specific caloric consumption at minimum charge and the incremental consumption were obtained from statistics of engines’ power and performance trials recorded by COES

The Fuel prices81 taken were the 2002’s, because after that year the prices are biased by the War with Irak:

Liquid-Fuel Prices used for the LRMC Calculation

Plant Fuel Type Soles82/Gln $/Gln $/Barrel $/Ton Kg/Gln (density)

D2 2.94 0.84 35.28 258.62 3.248 R6 2.43 0.69 29.16 192.22 3.612 Callao

R500 2.38 0.68 28.56 185.03 3.675 D2 2.93 0.84 35.16 257.74 3.248 Mollendo R500 2.42 0.69 29.04 188.14 3.675 D2 2.96 0.85 35.52 260.38 3.248 Ilo R6 2.46 0.70 29.52 194.59 3.612


Non-Liquid Fuel Prices used for the LRMC Calculation Coal Price ILO2 is the only coal-fired thermal plant in Peru. It uses imported coal, which price is a

function of standard coal with superior calorific power of 6,240 Kcal/Kg. The coal price assigned to this plant by COES and OSINERG is $38.9/MT

Natural Gas Price

Malacas TG-4 and Aguaytia Gas Prices considered were those of the 2003 projection made by OSINERG, which was $2.199/MMBTU - the price of the Camisea Gas considered was $2.03/MMBTU, and it was assumed that future gas-fired power plants will consume the Camisea Gas.


b) Non-Fuel Variable Costs These costs were taken from OSINERG reports. These cost comprise Variable Costs of additives, lubricants, spares, materials and other maintenance expenses - all expressed in US$/MWh.

81 Do not include Selective Consumption Tax (ISC), because ISC is exonerated for electricity generators. V.A.T is not included because this is recovered by the generating company as a fiscal credit when it sells its energy produced. 82 Exchange rate: 3.5 Soles/$.



c) O&M Fixed Costs These costs were taken from MINEM reports. These costs comprise fixed costs of payroll expenses for employees in charge of the plant operation, plant supervision, plant maintenance, plant security and other general expenses-all expressed in US$/KW- month.

O&M for new plants

Units Code Max. Power

Min Power

Specific Caloric

Consumption Fuel Cost O&M Costs

Max Min Incremental Min Domestic Fixed Cost V. Cost

KW Kcal/kWh c$/10^6Kcal $/KW-month $/MWh

GT 100 MW G100 100 25 2300 3340 856.3 1 4 GT 150 MW G150 150 38 1960 3424 856.3 0.7 3

CC 2 GT 100 + 1 HT 100

C300 300 150 1400 2013 856.3 1.4 2.4

CC 2 GT 150 + 1 HT 150

C450 450 225 1250 1851 856.3 0.98 1.8

Source: Peru’s Baseline Study 2003. NSEi: Non-served energy in year I (assumed to be zero, because this effect was incorporated in the Di

variable) Di: Additional Demand in year i

Projections for 2007-2017 were based on OSINERG projections from 2003-2007 and the following assumptions: a) Both GDP and population growth will maintain their average growth of the 2003-2007 period. b) Price of electricity generation will maintain the 2003-2007 OSINERG Projection c) Energy losses in distribution and transmission will be kept at levels projected for 2007 by OSINERG. The generation shown is the LRMC charts is before any distribution or transmission losses occur, as it is necessary to account for these losses to satisfy the demand.

d) Demand will be equal to OSINERG projection for the 2007, and from 2008 to 2017, the demand from mining projects will increase at 5% annually.

e) The future interconnection with Ecuador will cause exports from Peru to Ecuador only. The demand of Ecuador is added to the demand of Peru in wet months, from December to April up (147 GWh) for all the period 2007-2017

The results for the projected demand are:

SEIN Demand Projection

Year Power MW Energy GWh Power Growth Rate Energy Load Factor



2007 3480 24062 3.22% 3.63% 78.9% 2008 3603 24935 3.55% 3.63% 79.0% 2009 3731 25789 3.55% 3.42% 78.9% 2010 3864 26681 3.55% 3.46% 78.8% 2011 3999 27588 3.51% 3.40% 78.7% 2012 4143 28549 3.58% 3.48% 78.7% 2013 4291 29539 3.59% 3.47% 78.6% 2014 4445 30563 3.57% 3.47% 78.5% 2015 4602 31618 3.55% 3.45% 78.4% 2016 4766 32710 3.55% 3.45% 78.4% 2017 4935 33839 3.55% 3.45% 78.3%

Source: Peru’s Baseline Study 2003. N: Number of years in the period of analysis (i = 1, ....,n)

Period = 2007-2017

Illustrative Gas Price Sensitivity Analysis in the LRMC This analysis shows what would be the LRMC if the gas price rises up to $3/MMBTU (a high figure for the gas price in Peru – As of August 1st 2005, the Camisea gas price was $2.0658/MMBTU). The Camisea gas price considered in the LRMC was $2.03/MMBTU so for this sensitivity the O&M Cost of the power plants considered for the LRMC calculation was increased in 48%. The resulting LRMC (“LRMC magnified”) taking a gas price of $3/MMBTU is $33.32/MWh (considering a 14% discount rate). By taking the LRMC magnified (with the gas price of $3/MMBTU), the same sensitivities run in Sub-Step 2d of the additionality tools, under Section B.3 of the PDD, will be run herewith for illustrative purposes only. For the SEIN LRMC ($/MWh)83: a) Equivalent Annual Investment cost b) Discount Rate For the project levelized cost ($/MWh): a) Load Factor b) The Initial Investment Cost c) Discount Rate

a) and b) - Sensitivity run for the magnified SEIN LRMC ($33.32/MWh)

83Note that a load factor sensitivity analysis can not be performed for the LRMC, because in the LRMC calculation the load factor varied per plant, per month, and per year.



Values as of April 1st 2008

DataY 12% 14% 16% r=0% 90% 100% 110% 12% 14% 16% 12% 14% 16% 12% 14% 16%

2007 867 871 875 843 27,573 30,636 33,700 28,365 28,491 28,615 31,517 31,656 31,794 34,668 34,822 34,974 2008 1,576 1,555 1,535 1,716 45,543 50,603 55,664 41,832 41,280 40,745 46,480 45,867 45,273 51,128 50,454 49,800 2009 2,108 2,043 1,982 2,570 78,222 86,914 95,605 64,150 62,194 60,329 71,278 69,104 67,033 78,406 76,015 73,736 2010 2,535 2,415 2,302 3,462 104,997 116,663 128,330 76,882 73,230 69,810 85,425 81,367 77,567 93,967 89,503 85,323 2011 2,856 2,673 2,504 4,369 127,861 142,068 156,275 83,593 78,225 73,286 92,881 86,917 81,429 102,169 95,608 89,572 2012 3,111 2,860 2,633 5,329 155,367 172,629 189,892 90,693 83,380 76,768 100,770 92,644 85,298 110,847 101,908 93,828 2013 3,294 2,975 2,692 6,320 198,555 220,617 242,679 103,485 93,471 84,576 114,984 103,857 93,974 126,482 114,243 103,371 2014 3,418 3,033 2,697 7,344 220,687 245,208 269,729 102,697 91,132 81,038 114,107 101,258 90,042 125,518 111,383 99,046 2015 3,490 3,042 2,659 8,399 247,940 275,489 303,038 103,017 89,812 78,487 114,463 99,791 87,208 125,909 109,770 95,928 2016 3,521 3,016 2,590 9,491 288,627 320,697 352,766 107,073 91,711 78,764 118,970 101,901 87,516 130,867 112,091 96,268 2017 3,518 2,960 2,498 10,620 323,249 359,165 395,082 107,068 90,098 76,045 118,965 100,109 84,495 130,861 110,120 92,944

30,293 27,443 24,967 60,463 908,855 823,023 748,464 1,009,839 914,470 831,627 1,110,823 1,005,917 914,790 90%*I

12% 30.00 15.12 14% 29.9916% 29.98

100%*I12% 33.3414% 33.3216% 33.31

110%*I12% 36.6714% 36.6516% 36.64

100%*I90%*I

SENSITIVITY ANALYSIS FOR THE SEIN LRMC (2007-2017)-MAGNIFIED

NPV of Annual Investments=

110%*IIncremental GWh

r=0%EAC=I Discount Rate Sensitivity

Source: Sensitivities are based on Sectoral Baseline Study (2003) and chart model taken from Public Poechos I PDD. From the chart above it can be observed that the LRMC magnified is basically not affected by changes in discount rates, but only by changes in the equivalent annual costs84.

a) - Sensitivity run for the project ($41.06/MWh)

Change in Load Factor (LF*%)LF l else constant

100% 90% 95% 100% 105% 110%Capacity MW $49.00 $49.00 $49.00 $49.00 $49.00 $49.00 Total Investment $Million $52.01 52.01 52.01 $52.01 52.01 52.01Annual Cost:Capital $Million $7.32 7.32 7.32 $7.32 7.32 7.32O&M $Million $4.28 4.28 4.28 $4.28 4.28 4.28Total Annual Cost $Million $11.60 11.60 11.60 $11.60 11.60 11.60Plant Factor % 65.82% 59.24% 62.53% 65.82% 69.11% 72.40%Generation MWh 282,528 254,275 268,402 282,528 296,654 310,781 Levelized Cost $/MWh 41.06 45.62 43.22 41.06 39.11 37.33

40 years of payment

14% Discount Rate

LEVELIZED COST FOR THE PROJECT

Source: Single parameters were provided by the Sponsor, calculations are own production From the chart above it can be observed that the project levelized cost continues being higher than the LRMC magnified, under load factor sensitivities of +/-10% change.

a), b) and c) - Sensitivity run for the project ($41.06/MWh) against a) and b) sensitivities run for the magnified LRMC ($33.32/MWh)

84 The values in the chart above (costs and GWh.) have bee re-expressed to reflect their present value as of October 1st 2009 (date of the project commissioning) to allow comparison with the project levelized cost figures involved.



In the chart below it can be observed the project’ sensitivity analysis matrix. In this matrix, the project’s load-factor sensitivity run was +/-10%, the project’s initial-investment-cost sensitivity run was +/-10%, and the project’s discount-rate sensitivity run was +/- 2 basis points.

90% 95% 100% 105% 110%

Equivalent Annual Investment Cost ("EAIC") 46.81 I*90% 12% $5.68 $5.68 $5.68 $5.68 $5.6814% $6.59 $6.59 $6.59 $6.59 $6.5916% $7.51 $7.51 $7.51 $7.51 $7.51

52.01 I*100% 12% $6.31 $6.31 $6.31 $6.31 $6.3114% $7.32 $7.32 $7.32 $7.32 $7.3216% $8.34 $8.34 $8.34 $8.34 $8.34

57.21 I*110% 12% $6.94 $6.94 $6.94 $6.94 $6.9414% $8.05 $8.05 $8.05 $8.05 $8.0516% $9.18 $9.18 $9.18 $9.18 $9.18

Annual O&M $4.28 $4.28 $4.28 $4.28 $4.28Equivalent Annual Cost ("EAC") 46.81 I*90% 12% $9.96 $9.96 $9.96 $9.96 $9.96

14% $10.87 $10.87 $10.87 $10.87 $10.8716% $11.79 $11.79 $11.79 $11.79 $11.79

52.01 I*100% 12% $10.59 $10.59 $10.59 $10.59 $10.5914% $11.60 $11.60 $11.60 $11.60 $11.6016% $12.62 $12.62 $12.62 $12.62 $12.62

57.21 I*110% 12% $11.22 $11.22 $11.22 $11.22 $11.2214% $12.33 $12.33 $12.33 $12.33 $12.3316% $13.46 $13.46 $13.46 $13.46 $13.46

Levelized Cost 46.81 I*90% 12% 39.17 37.11 35.25 33.57 32.05 (Total Equivalent 14% 42.75 40.50 38.47 36.64 34.97

Annual Cost$/GenerationMWh) 16% 46.37 43.93 41.73 39.74 37.94 52.01 I*100% 12% 41.65 39.46 37.48 35.70 34.08

14% 45.62 43.22 41.06 39.11 37.33 16% 49.65 47.04 44.68 42.56 40.62

57.21 I*110% 12% 44.13 41.81 39.72 37.83 36.11 14% 48.50 45.95 43.65 41.57 39.68 16% 52.93 50.15 47.64 45.37 43.31

Load Factor Sensitivity

Source: Single parameters were provided by the sponsor, calculations are own production

Considering the magnified LRMC, the project would not be additional at only 9 out of 135 cases (7%). The unlikelihood of these 9 cases is discussed in the chart below. Comparison of the project’s levelized costs against the not efficient scenario for the benchmark:


46.81 I*90% 12% Additional Additional Not Additional Not Additional Not Additional36.64 14% Additional Additional Additional Not Additional Not Additional

16% Additional Additional Additional Additional Additional110% Investment Cost 52.01 I*100% 12% Additional Additional Additional Not Additional Not Additional


57.21 I*110% 12% Additional Additional Additional Additional Not Additional14% Additional Additional Additional Additional Additional16% Additional Additional Additional Additional Additional

Benchmark- Not efficient MarketChange in Load Factor (LF*%)

for the ProjectDiscount Rate

Source: Single parameters were provided by the sponsor, calculations are own production -It is not likely that the investment price is reduced by 10%, prices in general tend to go up, thus the 5 scenarios that occur when the investment is reduced by 10% are not likely -The 6th and 7th scenario of this chart are not likely since it joins 2 extreme events, hydrological favourable conditions as well as a discount rate of 12%. -The 8th scenario of this chart is not likely since it is grounded on a extremely favourable hydrological condition, and that is not likely to keep stable over time.



Comparison of the project’s levelized costs against the base scenario for the benchmark: Benchmark- Base Scenario for the Market Change in Investment Discount Rate

for the Project for the Project 90% 95% 100% 105% 110%46.81 I*90% 12% Additional Additional Additional Additional Not Additional

33.31 14% Additional Additional Additional Additional Additional16% Additional Additional Additional Additional Additional

100% Investment Cost 52.01 I*100% 12% Additional Additional Additional Additional Additional14% Additional Additional Additional Additional Additional16% Additional Additional Additional Additional Additional



Source: Single parameters were provided by the sponsor, calculations are own production -The 9th, scenario can be seen in this chart and it attains and extremely favourable hydrological condition, a 10% reduction in the investment cost and a discount rate of 12%. It is not likely that the investment price is reduced that much, and is less likely that the 3 most positive scenarios occur altogether. Comparison of the project’s levelized costs against the efficient scenario for the benchmark:

Benchmark- Most efficient Market Change in Investment Discount Ratefor the Project for the Project 90% 95% 100% 105% 110%






Source: Single parameters were provided by the sponsor, calculations are own production -At the magnified LRMC most efficient market scenario, the project is additional at all load factors, discount rates and investment costs considered.



Abbreviations

APFR Annual plant fuel requirement (TJ) Baseline emissions Product of the EFy times EGy BM Build Margin Emission Factor BM2 Build Margin Emission Factor – Option 2 C Carbon Content (tC/TJ) Factor - 1996 IPCC worldwide values CDM Clean Development Mechanism CERs Certified Emission Reductions CM Combined Margin Emission Factor COEF tCO2/MWh COES Committee of Economical Operation of the SEIN (Dispatch Center) DOE Designated Operational Entity DDA-OM Dispatch Data Analysis Operating Margin Emission Factor ECL Peru’s Electric Concessions Law of 1992 ECLR Peru’s Electric Concessions Law Regulation of 1993 EFy Baseline Emission Factor (tCO2/MWh) EGy The Project annual generation (MWh) ERs Green House Gases Emissions Reductions GHG Green House Gases GWh Gigawatts hours HP Hydropower plant (s) HT Heat Turbine – Thermal power plant (s) LRMC Long Run Marginal Cost of the SEIN MINEM Peru’s Ministry of Energy and Mines MP Monitoring Plan MWh Megawatts hours NEC Net Efficiency Conversion O Oxidation Factor - 1996 IPCC worldwide values OM Operating Margin Emission Factor OSINERG Peru’s Energy Investment Supervisory Agency (Regulatory Entity) REP Red de Energía del Perú S.A. (Transmission System Operator) SEIN National Interconnected Electric Grid tCO2e Tons of carbon dioxide equivalent The Operator Tarucani Generating Company (The project operator) The Sponsor Tarucani Generating Company (The project sponsor) TP Thermal fossil fuel-fired plant(s)

Source: Own production.



Annex 4 MONITORING PLAN

THE MONITORING PLAN

TABLE OF CONTENTS

I. Background information II. Purpose of the Monitoring Plan III. Use of the Monitoring Plan by the Operator IV. Organizational, Operational and Monitoring Obligations

A. Obligations of the Operator B. Emissions Reductions Calculation Procedure and Required Spreadsheets

V. Sustainable Development Monitoring Plan

A. Environmental Sustainability B. Socio-Economic Sustainability

VI. Annexes



I. Background Information The baseline methodology and monitoring methodology for Tarucani (“the project”) are in accordance with the approved consolidated baseline methodology for grid connected electricity generation from renewable sources ACM0002 (“the methodology”). The project’s installed capacity and estimated yearly average generation is as follows:

Project name Installed capacity (MW) Generation (GWh/yr) Tarucani 49 282,528

Source: The sponsor. The project is a hydroelectric power plant located in Peru, in the south-western Arequipa department. The project is expected to displace 153,957 tCO2e per year, which accounts for 1,077,699 tCO2e for the first crediting period (7 years). The spatial extent of the project boundary is the National Interconnected Electric Grid (SEIN). The project is connected to SEIN through the Cerro Verde Substation - which belongs to Red de Energía del Perú S.A. (REP). The 282,528 GWh expected annual electricity generation will be sell to private industrial clients. Until now, neither electricity exports from the SEIN nor electricity imports to the SEIN have taken place; but will be monitored if any occur in accordance with the methodology. II. Purpose of the Monitoring Plan This report presents the monitoring plan (“the MP”) for the project. The MP defines a standard against which the performance in terms of the project’s ERs will be monitored and verified, in conformance with all relevant requirements of the CDM of the Kyoto Protocol. The MP is part of the Emissions Reductions Purchase Agreement (ERPA) document and, after its validation, will be an integral part of the contractual agreement between the buyer, and the project’ sponsor (“the sponsor”). For the MP, the sponsor will be treated as if it were the project’s operator (“the operator”), and solely responsible for the ERs delivery, if the operator becomes a third party it should be noted to the verifier the transference of all the responsibilities regarding ERs delivery. Both the project’s baseline and the MP are subject to verification procedures. III. Use of the Monitoring Plan by the operator This report, the MP, identifies key performance indicators of the project and sets out the procedures for metering, monitoring, calculating and verifying the ERs generated by the project, annually. Adherence to the instructions in the MP is necessary for the operator to successfully measure and track the impact of the project on the environment and prepare all data required for the periodic audit and verification process that must be undertaken to confirm the achievement of the corresponding ERs. The MP is thus the basis for the production of ERs and delivery of ERs to the buyer. Specifically, the MP provides the requirements and instructions for: (i) establishing and maintaining the appropriate monitoring system including spreadsheets for the calculation of ERs, (ii) checking whether the project meets key sustainable development indicators, (iii) implementing the necessary measurement and management operations, and (iv) preparing for the requirements of independent third party verifications and audits. The MP can be updated and adjusted to meet operational requirements. The verifier approves such modifications during the process of initial or periodic verification. In particular, any shifts in the baseline scenario may lead to such amendments, which may be mandated by the verifier. Amendments may also



be necessary as a consequence of new circumstances that affect the ability to monitor ERs as described here or to accommodate new or modified CDM rules. I.V. Organizational, Operational and Monitoring Obligations A. Obligations of the Operator Monitoring performance of the project requires the fulfilment of operational data collection and processing obligations from the operator. The operator has the primary obligation of ensuring that sufficient and accurate information is available to calculate ERs in a transparent manner and of allowing for a successful verification of accounted ERs. The operator must gather and process information needed to monitor ERs. It is required that the operator calculate its ERs based on most recent available information, following the ERs Calculation Procedure (“ERCP”) presented in this report. All data required for the MP will come from COES information system. Data gathering and processing should be done monthly by the operator, as follows:

Monthly Data Collection At the end of each month:

COES (Data Provider)

-Report of hourly generation of the SEIN’s units (measurement: 15’ or 30’ 85). As the project will be an active member of COES all data will come from COES. -Report of weekly dispatch merit orders for “hours of maximum demand 86” -Real NECs per power plant in the SEIN.

Operator (Data processor)

-Back up of any claims with receipt of sales -Monthly data filling in all the spreadsheets required, following the ERCP -Monthly report to the buyer.

Source: Public Poechos I PDD served as example to build this chart. The operator should calculate ERs on the basis of this MP (following the ERCP) for the purpose of claiming ERs credits. It is believed that the MP approach presented here will result in an accurate, yet conservative calculation of ERs. However some uncertainties may lead to a deviation of monitored ERs and the verified ERs, especially errors in the data monitoring and processed system. The operator is expected to prevent such errors and the verification audits are expected to uncover any possible errors. The Certified Emissions Reductions (“CERs”) would be granted ex-post verification. B. Emissions Reductions Calculation Procedure and Required Spreadsheets The Emissions Reductions Calculation Procedure (ERCP) is the basic instrument for gathering, recording and processing information that will result in the measured ERs. The operator shall keep the project ERCP as a manual. The ERCP should contain: i) data gathered from COES and ii) data processed by the operator. All data processing should be done in Excel. The ERCP is designed for monthly calculation, based on final monthly COES reports. Although it will only be possible to know the ERs at the end of each year (March 31st for the project), filling data monthly in the required spreadsheets will provide time to review formulas, minimize errors and have data readily available for the verifier in any period of the

85 Half an hour measurement is still acceptable if total SEIN production calculated with it, does not deviate greatly (i.e. less than 1%) from total SEIN Production calculated with the 15-minute measured data 86 (6pm to 11 pm) to set a standard - weekly merit orders for hours of maximum, minimum and medium demand are similar



year. There are only 2 required spreadsheets to update with new data: Tarucani DDA-OM.xls and Tarucani BM2.xls. The names of these files should be kept but should also reflect the date for which the latest adjustment is made. DDA-OM Spreadsheet: This excel file contains all data and formulas necessary to calculate the Dispatch Data Analysis Operating Margin. The data’s year is the year of project generation (April1st-March31st). 14 worksheets compose the DDA-OM Spreadsheet: -Worksheet #1: COEFs (tCO2/MWh) to assign to each unit of the SEIN along the first crediting period87. -Worksheet #2: Calculation of monthly grid dispatch merit order for all thermal units of the SEIN. -Worksheet #3 to Worksheet #14: One worksheet per month of the year; they contain the SEIN units hourly generation.

Worksheet #1

Table # 1: COEF by Technology88 Current Technologies in the SEIN Future Technologies in the SEIN

Type of Fuel COEF(tCO2/MWh) Type of Fuel COEF (tCO2/MWh)Coal 1.01 MIX weigthed average of fuel COEFs

Oil based 0.80 Change fuel type each month (first week of the month)Diesel 2 0.76 Diesel CC 0.48

Residual 6 0.64 Residual CC 0.50R500 0.84 Gas Dry CC 0.37Gas 0.61 Gas PM CC 0.35Dry 0.62 Coal CC 0.61

Pure Methane 0.59 Diesel Cogeneration 0.33Hydro 0.00 Residual Cogeneration 0.34

Residual 6 and Diesel 2 0.66 Gas Dry Cogeneration 0.25Pure Methane or Diesel 2 DEPENDS Gas PM Cogeneration 0.24

ILO TV2 Cogeneration Plant 0.34 Coal Cogeneration 0.42 Source: Taken from Pubic Poechos I PDD. COEFs numbers showed in the two charts above are only an example; they were used for the baseline estimation only. In the monitoring, COEFs should vary according to real NECs per power plant to be published by COES. Annual real NECs average per technology will have to be considered for the COEFs per technology calculation. Table#1’COEFs will be updated yearly according to real NECs published in COES Statistics. The formula to use to calculate the COEFs per technology for Table 1 is: COEFs per technology = [3.6 x (44/12) x C x O] / [103 x NEC average per technology]. Future technologies in the SEIN should be updated as well with real NECs data of the future. The following table relates each unit of the SEIN to a COEF, according to the technology the unit uses. The assignation of COEFs, shown in Table #2, is to be taken from Table#1.

Table#2: Name Plant / Technology/Assigned COEF

Table #2, holds up to 100 units (no more than 34 HPs and 66 TPs), 81 that operated in 2003 (27 HPs and 54 TPs) and 19 future units (7 HPs and 12 TPs) that are set aside a space. Future units’ data should be filled as the arrows in Table#2 indicate, as they enter the SEIN. Units that did not dispatch in any hour of

87 COEF will vary according to published NECs per plant. Annual real NECs average per technology will have to be considered for the COEFs per technology calculation. 88Combined cycle technology is named “CC”.



the year in question should not be considered for the DDA-OM calculation at all, so that they do not occupy extra-space, unnecessarily. Table#2 below shows the technical name of the SEIN unit (the way COES has it registered), complete name of the plant, technology and assigned COEF. Table #2 COEFs that show “DEPENDS” indicates the plant that changes the fuel it burns in several weeks of the year. For this plant the fuel that was burned in the first week of the month was taken as an assumption for the plant’s fuel burned for the month, and the COEF related to that type of fuel was taken for the month.



ag_tg1 AGUAYTIA 1 (2) Dry 0.62ag_tg2 AGUAYTIA 2 (2) Dry 0.62arcata Arcata Hydro 0.00aricota CH ARICOTA Hydro 0.00bvista1 BELL MAN 1,2 Diesel 2 0.76bvista2 BELL MAN 1,2 Diesel 2 0.76cahua Cahua Hydro 0.00calana123 CALANA 123 Residual 6 0.64calana4 CALANA 4 Residual 6 0.64call CH Callahuanca Hydro 0.00ccomb C. COMBINADO Diesel 2 0.48chariii CH CHARCANI Hydro 0.00chariv CH CHARCANI Hydro 0.00charv CH CHARCANI Hydro 0.00charvi CH CHARCANI Hydro 0.00chi_slz12 SULZER CHILINA Diesel 2 0.76chicl_o DS CHICLAYO OESTE-D Diesel 2 0.76chiltv1 chiltv1 R500 0.84chiltv2 TV2 CHILINA R500 0.84chiltv3 TV3 CHILINA R500 0.84chimay CH Chimay Hydro 0.00chimb TG1 CHIMBOTE Diesel 2 0.76cnp_mann DS PACAS-MAN Residual 6 and Diesel 2 0.66cnp_slz DS PACAS-SULZER Residual 6 0.64cpato CH Cañón del Pato Hydro 0.00cqro CH Carhuaquero Hydro 0dolores1 DOL ALCO 1-2 GM 1-2-3 Diesel 2 0.76dolores2 DOL ALCO 1-2 GM 1-2-3 Diesel 2 0.76gciego CH Gallito Ciego Hydro 0herc CH HERCA Hydro 0hp1 HP1 Hydro 0hp2 HP2 Hydro 0hp3 HP3 Hydro 0hp4 HP4 Hydro 0hp5 HP5 Hydro 0hp6 HP6 Hydro 0hp7 HP7 Hydro 0hpni CH Huampaní Hydro 0huanchor CH Huanchor Hydro 0huin CH Huinco Hydro 0ilo1catk KATCATO (ENERSUR) Diesel 2 0.76ilo1tg1 TG1 ILO Diesel 2 0.76ilo1tg2 TG2 ILO Diesel 2 0.76ilo1tv1 ILO TV1 R500 0.84ilo1tv2 ILO TV2 R500 0.34ilo1tv3 ILO TV3 R500 0.84ilo1tv4 ILO TV4 R500 0.84ilo2_carb TV CARBON ILO II Coal 1.01machup CH MACHUPICCHU Hydro 0mal_tg1 TG1 Pure Methane or Diesel 2 DEPENDSmal_tg2 TG2 Pure Methane or Diesel 2 DEPENDSmal_tg3 TG3 Pure Methane or Diesel 2 DEPENDSmal_tg4 TGN4 Pure Methane 0.59malp CH Malpaso Hydro 0man CH MANTARO Hydro 0mat CH Matucana Hydro 0moll123 MOLLENDO 1,2,3 R500 0.84molltg1 TGM1 MOLLENDO Diesel 2 0.76molltg2 TGM2 MOLLENDO Diesel 2 0.76moq12 MOQUEGUA Diesel 2 0.76moy CH Moyopampa Hydro 0oro_p CH Oroya-Pachac. Hydro 0paita1 DS PAITA1 Diesel 2 0.76paita2 DS PAITA2 Diesel 2 0.76pariac Pariac Hydro 0piura1 DS PIURA1 Diesel 2 0.76piura2 DS PIURA2 Diesel 2 0.76ron CH RESTITUCION Hydro 0sgab2 CH SAN GABAN Hydro 0shcummins CUMMINS Diesel 2 0.76shou_tv1 TV1 SHOUGESA R500 0.84shou_tv2 TV2 SHOUGESA R500 0.84shou_tv3 TV3 SHOUGESA R500 0.84sullana DS SULLANA Diesel 2 0.76taparachi TAPARACHI Diesel 2 0.76tg_piu TG PIURA Diesel 2 0.76tintaya TINTAYA Diesel 2 0.76tp55 TP55 Unknown 0tp56 TP56 Unknown 0tp57 TP57 Unknown 0tp58 TP58 Unknown 0tp59 TP59 Unknown 0tp60 TP60 Unknown 0tp61 TP61 Unknown 0tp62 TP62 Unknown 0tp63 TP63 Unknown 0tp64 TP64 Unknown 0tp65 TP65 Unknown 0tp66 TP66 Unknown 0truji TG TRUJILLO Diesel 2 0.76trupal TRUPAL Residual 6 0.64tumbes TUMBES Residual 6 0.64uti_5 TG S.ROSA UTI5 Diesel 2 0.76uti_6 TG S.ROSA UTI6 Diesel 2 0.76vent3 TG VENTANILLA-3 Diesel 2 0.76vent4 TG VENTANILLA-4 Diesel 2 0.76westin TG WESTINGHOUSE Diesel 2 0.76yanan CH Yanango Hydro 0yarinac Yarinacocha (5) Residual 6 0.64yaupi CH Yaupi Hydro 0

← Start filling from HP7 to HP1. COEFs remain 0 for the seven HPs. ← Start filling from TP55 to TP66. COEFs remain 0 for yet to exist TPs.

Source: Taken from Pubic Poechos I PDD – based on COES data of plants and type of fuel.



Worksheet #2: Monthly Merit order Calculation

The 52 weekly merit orders89 for “hours of maximum demand” should be averaged in this Worksheet #2:

Unit Name Sta Rosa Eq-C (S/KWh) Unit Name Sta Rosa EC (S/KWh) Unit Name Sta Rosa EC (S/KWh)Sorted by name x Sorted by name Monthly Average Merit Order Name Sorted by Monthly Average Merit Order

Unit Name Sta Rosa Eq-C (S/KWh) Visible Average FunctionSorted by name x

Unit Name Sta Rosa Eq-C (S/KWh)Sorted by name x

Unit Name Sta Rosa Eq-C (S/KWh)Sorted by name x

April - 3rd Week most recent year

April - 4rd Week most recent year

April-most recent year April-most recent yearApril - 1st Week most recent year

April - 2nd Week most recent year

….. 12 monthly merit orders need to be obtained from April through March. Source: Public Poechos I PDD served as example to build this chart.

Worksheet #3 to Worksheet #14: Hourly Generation of the SEIN Units 12 monthly worksheets that contain the SEIN units’ hourly production in each month of the most recent year (June-May) of project generation should be identical in # of columns, formulas, “general organization” but in data. Worksheets #3’ – Worksheet #14’ columns C to CY should be organized as follow:

COEFs: 0 0 0 0 0 0.34 0.76 0 0TECHNOLOGY: hydro hydro hydro hydro hydro r-500 diesel unknown unknown

Hours of the month HP 1… ...HP7 CH Mantaro … Canhon del Pato ILO T2 Cog Dolores TP55 T661

.

.

.744

Future HPs Existing HPs Existing TPs Future TPs

There is an unchangeable pre-defined order for existing

and future HPs - for all the crediting period

Existing TPs should be placed according to

grid dispatch merit order, future TPs are placed last Source: Taken from Pubic Poechos I PDD.

Hydropower plants’ (existent and future) hourly generation should occupy the D to AK columns only. Thermal plants’ (existent and future), the AL to CY columns only. The predefined order for HPs is shown below (Where the “-1 position” =D column and “27th position” =AK column). This order should hold for the first crediting period. TPs should be sorted according to their grid dispatch monthly merit order calculated. As future HPs (max.7) are kept a space (columns) in the left extreme of columns D to AK; future TPs (max. 12) should be kept a space (columns) in the right extreme of columns AL to CY (like they were occupying the least monthly merit order of grid system dispatch). Finally, the SEIN units’ associated COEFs should be placed in the first row of the corresponding unit’s column. For yet-to-exist plants COEF=0.

89 The merit order is given by the Santa Rosa Equivalent Cost (Soles/MWh) assigned to a unit, according to its efficiency.



Predefined order from left to right (D to AK) for all HPs90 -7 hp1 HP1-6 hp2 HP2-5 hp3 HP3-4 hp4 HP4-3 hp5 HP5-2 hp6 HP6-1 hp7 HP71 Hydro CH MANTARO2 Hydro CH RESTITUCION3 Hydro CH Huinco4 Hydro CH Matucana5 Hydro CH Yaupi6 Hydro CH Oroya-Pachac.7 Hydro CH Malpaso8 Hydro Cahua9 Hydro Pariac

10 Hydro Arcata11 Hydro CH Gallito Ciego12 Hydro CH Callahuanca13 Hydro CH Moyopampa14 Hydro CH Huampaní15 Hydro CH Chimay16 Hydro CH Yanango17 Hydro CH Huanchor18 Hydro CH Carhuaquero19 Hydro CH ARICOTA20 Hydro CH CHARCANI21 Hydro CH CHARCANI22 Hydro CH CHARCANI23 Hydro CH MACHUPICCHU24 Hydro CH HERCA25 Hydro CH SAN GABAN26 Hydro CH CHARCANI27 Hydro CH Cañón del Pato

Source: Taken from Pubic Poechos I PDD – Based on COES data. The formula component of each monthly worksheet (W#3–W#14) is given by columns CZ to FD (not shown in this report). Formulas will use data entered in columns D to CY and will bring a resulting DDA-OM. The only data column in this set is EE which should be filled with the project hourly generation. The resulting DDA-OM will show up at the low end of column EE in W# January (same as W#14). The BM2 Spreadsheet: This excel file, composed by four worksheets, contains all the calculations necessary to update the BM2. The data’s year is the year of the project generation. -Worksheet #15: SEIN Installed Capacity as of March 31st of every year of the crediting period. -Worksheet #16: New units built’ annual generation in the year of the project generation. -Worksheet #17: The BM2 calculation in the year of the project generation. -Worksheet #18: The Baseline Emission Factor and ERs in the year of the project generation.

90 The only difference between negative and positive positions is that negatives' are for inexistent plants as of today. Even when they start to exist they should keep that position. Note that Future HPs are kept a space (column) on the left extreme of Worksheet #3-Worksheet #14.



Worksheet #15: 2008-2015 SEIN Installed Capacity



SEIN Installed Capacity March 2003 …PLANT INSTALLED CAPACITY (MW)TERMOSELVAAGUAYTIA 1 86.294AGUAYTIA 2 86.294CAHUA S.A.CAHUA 43.600PARIAC 5.216E. PACASMAYOPACASMAYO 24.617GALLITO CIEGO 38.147ARCATA 5.098

EDEGELHUINCO 258.400MATUCANA 128.578CALLAHUANCA 75.059MOYOPAMPA 89.250HUAMPANI 31.360YANANGO 42.300CHIMAY 156.000HUANCHOR 18.860SANTA ROSA WTG 127.700SANTA ROSA UTI 109.800

EEPSAMALACAS 173.2

EGENORCAÑON DEL PATO 260.730CARHUAQUERO 95.020CHIMBOTE 63.833TG PIURA 24.300TRUJILLO 22.800PIURA 27.850CHICLAYO OESTE 26.610

PAITA 11.112SULLANA 12.500TRUPAL 15.000ELECTROANDESYAUPI 108.000OROYA 9.000PACHACHACA 12.282MALPASO 54.400ELECTROPERUCOMPLEJO MANTARO - MANTARO 798.000COMPLEJO MANTARO-RESTITUCION 210.400TUMBES 18.244YARINACOCHA 25.600

ETEVENSAVENTANILLA 384SHOUGESASAN NICOLAS TV 1-2-3 63.586SAN NICOLAS CUMNIS 1.25

EGASACHARCANI 176.890MOLLENDO MIRLESS 31.710MOLLENDO TGM 90.000CHILINA TV 18.000CHILINA C.C 20.000CHILINA SULZER 10.400EGEMSAHERCA 1.020MACHUPICCHU 92.250DOLORESPATA 15.620SAN GABANSAN GABAN II 113.098TINTAYA 17.960BELLAVISTA 8.600

TAPARACHI 8.800EGESURARICOTA 35.7CALANA 25.6MOQUEGUA 1

ENERSURILO 1 TV 154.000ILO 1 TG 81.690ILO 1 CATKATO 3.300ILO 2 TVC1 145.000

TOTAL SEIN Inst Capacity 4794.928

3/2015 SEIN Installed Capacity

Source: Public Poechos I PDD served as example to build this chart.



The project staff should classify SEIN’s yearly capacity additions as follow:

Newly Built = Only when new units are added - interconnectionof units less than 5 years old are included

Interconnection = Old unit that gets interconnected to SEIN

Rehabilitation = Reconstruction of a plant that was broken down

Upgrade = Same unit that increases its installed capacityby technological improvements or adjustments

Classification of SEIN Addition in Installed Capacity (MW)


Worksheet #16: Capacity Additions from 1988-201591

91 Only the plants that fall in the Newly Built Classification should be considered “Capacity Addition” for the BM2 calculation.



SEIN Additions in Inst.Cap:

Years Techn Addition Install.Cap. 2001 Gen 2002 Gen 2003 Gen2015 Gen Annual Generation

Category Added (MW) (GWh) (GWh) (GWh) ...(GWh) (GWh)

1988C.H. CARHUAQUERO HYDRO Newly built 75.1 469.27 479.41 458.78 469.16CHARCANI (I-V) HYDRO Newly built 136.80 842.17 641.80 660.24 714.741993TG VENTANILLA 2 D2 Newly built 100 2.40 2.45 1.54 2.13TG VENTANILLA 1 D2 Newly built 100 2.40 2.45 1.54 2.131995CALANA R6 Newly built 19.2 33.02 25.72 45.81 34.851996STA. ROSA WESTING D2 Newly built 127.7 9.41 5.61 11.60 8.881997C.H. GALLITO CIEGO HYDRO Newly built 34.0 183.53 149.71 121.79 151.68TG VENTANILLA D2 Newly built 184.0 4.41 4.51 2.83 3.92MOLLENDO MIRLESS R500 Newly built 31.7 10.98 9.53 35.37 18.631998AGUAYTIA 1 GAS Newly built 86.3 230.80 412.26 466.80 369.95AGUAYTIA 2 GAS Newly built 86.3 216.30 332.89 367.97 305.72TG MALACAS PM GAS Newly built 102.2 206.23 181.35 274.30 220.631999SAN GABAN II HYDRO Newly built 55.0 357.38 376.19 356.34 363.30CALANA R6 Newly built 6.4 11.01 8.57 15.27 11.62MOLLENDO TGM D2 Newly built 90.0 0.73 0.86 1.43 1.012000SAN GABAN II HYDRO Newly built 58.1 377.51 397.38 376.41 383.76ILO2 TVC COAL Newly built 145.0 338.78 845.93 859.44 681.38C.H. CHIMAY HYDRO Newly built 156.0 724.76 752.96 825.87 767.86C.H. YANANGO HYDRO Newly built 42.3 214.60 239.13 202.28 218.672001TUMBES R6 Newly built 18.3 22.38 20.73 27.99 24.362002C.H. HUANCHOR HYDRO Newly built 18.9 - 36.86 144.64 144.642003

YARINACOCHA R6 Newly Built 25.6 - - 56.88 144.972004New Plants 2004 - - - 2005

New Plants 2005 - - - 2006New Plants 2006 - - - 2007

New Plants 2007 - - - 2008New Plants 2008 - - - 2009New Plants 2009 - - - 2010 - - - New Plants 2010 - - - 2011 - - - New Plants 2011 - - - 2012New Plants 2012 - - - 2013New Plants 2013 - - - 2014New Plants 2014 - - - 2015New Plants 2015 - - -

Source: Taken from Pubic Poechos I PDD – based on COES data.



Only columns and rows highlighted in blue (empty low rows, empty right columns) should be updated. The year of annual generation of the capacity addition is the year of the project generation92. Information of the capacity additions (MW and technology) from 1988 through 2003 should not be recalculated but taken from Worksheet #16 (rows filled). It will be necessary to know the yearly installed capacity of the plant the unit added belongs in order to obtain the unit added participation in the total generation produced by the plant.

Worksheet #17: Build Margin 2 Calculation

Table#1: Selection of the sample group Year Plant Plant Most recent year Filter most Most recent 20% Filter 5 most 5 Most recent

Name Type generation(GWh) recent 20% units generation recent units units generation2003 YARINACOCHA r6 145 1 145 1 1452002 C.H. HUANCHOR Hydro 145 1 145 1 1452001 TUMBES r6 24 1 24 1 242000 C.H. YANANGO Hydro 219 1 219 1 2192000 C.H. CHIMAY Hydro 768 1 768 1 7682000 ILO2 TVC Coal 681 1 681 0 02000 SAN GABAN II Hydro 384 1 384 0 01999 MOLLENDO TGM d2 1 1 1 0 01999 CALANA r6 12 1 12 0 01999 SAN GABAN II Hydro 363 1 363 0 01998 TG MALACAS gas 221 1 221 0 01998 AGUAYTIA 1 gas 370 1 370 0 01998 AGUAYTIA 2 gas 306 1 306 0 01997 C.H. GALLITO CIEGO Hydro 152 1 152 0 01997 TG VENTANILLA d2 4 1 4 0 01997 MOLLENDO MIRLESS r500 19 1 19 0 01996 TG STA. ROSA WESTINGHOUSE d2 9 1 9 0 01995 CALANA r6 35 1 35 0 01993 TG VENTANILLA 2 d2 2 1 2 0 01993 TG VENTANILLA 1 d2 2 1 2 0 01988 C.H. CARHUAQUERO Hydro 469 0 0 0 01988 CHARCANI (I-V) Hydro 715 0 0 0 0

T/. 5,044 20 3,860 5 1300First sample comprises: 19.69% of SEIN generation

SEIN Annual Gen= 19,603The sample list would be composed by …. most recent 20% 20% of SEIN Gen= 3,921as it represented greater gen. addition

3,860 > 1,300 Source: Taken from Pubic Poechos I PDD. Any new unit recorded in Worsheet#16 will origin an additional row in Worksheet #17’s. In Worksheet #17, empty cells/columns highlighted in blue should be updated. New units (rows) are to be incorporated as the arrow above indicates. The first filter (5th column composed by 1s and 0s) helps keeps track that the sample’s annual generation comprises the most recent 20% in generation added to the SEIN. The second filter (7th column) counts up to 5 most recent plants. One automatic check is included in this table; it checks whether the 5 most recently built plants’ generation is greater than first sample’s generation (latest 20% in generation added) and indicates which sample should be selected for the BM2 calculation.

92 In case the addition was not an entire plant but rather a unit of an existent plant, only this new unit added to the SEIN should be considered in the sample. If not publicly available, its generation should be estimated by the % that this unit capacity represents in the total plant capacity times the annual generation of the plant it belongs.



Table # 2: BM2 Calculation Clusters the generation of the selected sample by technology, and gets a tCO2/MWh weighted average.

Technologies in Selected Sample Most Recent Year Gen (GWh) % per technology APFR C O 44/12 CO2 Emissions(tCO2)

Coal 681.38 18% 7,433.28 #### ### 3.67 689,124d2 18.06 0% 186.12 #### ### 3.67 13,647r6 215.80 6% 1,807.54 #### ### 3.67 138,445

r500 18.63 0% 204.82 #### ### 3.67 15,688Dry Gas 675.68 18% 7,484.40 #### ### 3.67 417,776

Pure Methane Gas 220.63 6% 2,443.85 #### ### 3.67 129,282Dry Gas CC 0.00 0% 0.00 #### ### 3.67 0

Hydro 2,029.91 53% 0.00 0.00 ### 0.00 0Total 3,860.08 100% 1,403,961

BM2= 0.36371 tCO2//MWh Source: Taken from Pubic Poechos I PDD. APFR=Annual Plant Fuel Requirement (TJ) = Gen (KWh) x 3.6 x 10^6/(NEC x 10^12); C= Carbon Content (tC/TJ); O=Oxidation Factor; 44/12 = Mass Conversion (tCO2/tC). Empty columns and cells highlighted in blue should be updated. The arrow shows insertion of new technologies (new rows) that enter the SEIN. The NECs to use in the APFR formula, and the C and O factors should be extracted accordingly from Table #3, of this Worksheet #17.

Table # 3: NECs & IPCC 1996 values that hold for the first crediting period COEF(tCO2/MWh)

Type of Fuel D2 R6 R500 Gas Dry Gas PM CoalNEC 34.93% 42.98% 32.74% 32.50% 32.50% 33.00%

C Content 20.20 21.10 21.10 15.30 14.50 25.80Oxidation Factor 0.99 0.99 0.99 0.995 0.995 0.98

COEF(tCO2/MWh) 0.76 0.64 0.84 0.62 0.59 1.01

Open Cycle

COEF(tCO2/MWh)

Type of Fuel D2 R Gas Dry Gas PM CoalNEC 55.00% 55.00% 54.00% 55.00% 55.00%

C Content 20.20 21.10 15.30 14.50 25.80Oxidation Factor 0.990 0.990 0.995 0.995 0.980

COEF(tCO2/MWh) 0.48 0.50 0.37 0.35 0.61

Combined Cycle

COEF(tCO2/MWh)

Type of Fuel D2 R Gas Dry Gas PM CoalNEC 80% 80% 80% 80% 80%

C Content 20.20 21.10 15.30 14.50 25.80Oxidation Factor 0.990 0.990 0.995 0.995 0.980

COEF(tCO2/MWh) 0.33 0.34 0.25 0.24 0.42

Cogeneration

Source: Taken from Pubic Poechos I PDD. Figures shown in the chart above are only an example; these figures were used in the baseline calculation only. The (ex-post) monitoring should use Real NECs (and therefore real COEFs) data, which is to be published by COES from this year forward. Average real NECs per technology need to be calculated separately every year; Table #3, of this Worksheet #17 will show updated NECs per technology calculated with yearly real data from COES. This will allow the most accurate TJ-estimation consumed per technology. COEFs will be updated automatically as NECs are updated; both rows are linked by the following COEFs formula:



COEFs per technology = [3.6 x (44/12) x C x O] / [103 x NEC average per technology]93.

Worksheet #18: Combined Margin and ERs of the year Worksheet #18 shows the ERs of the year calculated with the 2 spreadsheets’ results for DDA-OM and BM2. Empty cells highlighted in blue should be updated at the end of the year (December 31st).94

Project MWh in the yearTarucani 58,500.00

Ers of the Year (DDA-OM - BM2):Project MWH in the year*Combined MarginTarucani 31,878

DDA-OM= 0.72614BM2= 0.36371CM= 0.54493

Source: Public Poechos I PDD served as example to build this chart. V. Sustainable Development Monitoring Plan (“SDMP”): Being a CDM activity, the project must meet the requirements of The Kyoto Protocol Article 12 for CDM projects, which states that the CDM activity must assist the host country in achieving sustainable development. The Government of Peru has endorsed the project as a CDM-eligible activity. This part of the MP explains why it can be taken for granted that the project will contribute to environmental sustainability as well as development in Peru over its lifetime. The sustainable development objective applies also to projects, where not only positive but also negative environmental and social effects are conceivable. The MP for the project specifies sustainable development indicators and targets, which must be monitored and met by the operator and the area to which these indicators and targets will be applied. The SDMP can be seen in the annex section of this MP. A. Environmental Sustainability In addition to mitigate emission of CO2, the project will reduce emissions of local pollutants (particularly SO2, NOx and particulates). The sustainable development contribution of the project is considered fulfilled as long as the project is operating. In the project’s EIA no major impacts were identified. Construction impacts will be well managed through proper environmental practices. The area is not a migratory bird habitat, and no impact is expected on the local bird population. There is no impact on vegetation either if the Environmental Management Plan (“EMP”) is applied by the sponsor. The project will operate using the current and future water requirements for irrigation, potable water and ecological flow. The total flow is determined by the local Agricultural Authority of the region, not by the project’s sponsor. The water concession is based upon the use of the flow required for agricultural needs. 93 COEFs per technology obtained for this Worksheet#17-Table#3 should be the same as COEFs obtained for Worksheet#1-Table#1, as they both will use the latest information publicly available from COES. 94 The margins are rounded to the 5th decimal.



B. Socio-Economic Sustainability No negative social impacts are predicted as a consequence of the project. Water user rights will be respected, as energy generation receives a lower priority than agricultural use. During operation, the project will hire local labor for operation and maintenance. The sponsor has created a broad social plan for Querque, which is the closest town to the project site. This broad social plan for Querque will be monitored in the SDMP, shown in the annex section of this MP.



VI. Annexes Sustainable Development Monitoring Plan (“SDMP”)

The SDMP will cover the project’s direct and indirect area of influence95 and their habitants. The following sustainable development indicators and targets framework will facilitate the measurement of progress towards sustainability. The indicators will be revised annually by the verifier to check compliance with targets. The targets will be progresses96 registered by the indicators. The following indicators have been established:

SDMP Indicators and Targets Framework Goal 1: Environmental Sustainability

Initiative Indicator97 Target Environment Donations to Querque in regards of the environment98:

-Enlargement and repairing of the water channel system. -Truchas nest to foster truchas reproduction. -Reforestation project which includes reforestation of eucalipt, quenhua, intimpa, and other local vegetation. -Program of reproduction of vicuñas.

Positive

New Initiative In case the sponsor desires to incorporate a new initiative to this environmental-sustainability-initiative list, it will have to be approved by the verifier

N/A99

Goal 2: Socio-Economic Sustainability

Initiative Indicator100 Target Number of employees hired from local population Positive Economic

standards Purchases from local suppliers Positive

95 Defined in the EIA. 96 Progresses meaning positive results of the indicators. 97 Yearly flow or yearly change. 98 Until complying with investments committed with Querque - according to the act signed by Querque and the sponsor. 99 Target will be set when indicator is created and also needs to be approved by the verifier. 100 Yearly flow or yearly change.



Donations to Querque in regards of social development101: -Electrification of Querque. The investment will consist of an electricity-fed line of 22.9/0.22 kV and 50 KVA that will go from the Tarucani Substation to the Querque community. -Financing for the creation of the local administration system for the town. -Bridges over the Huasamayo and Querque hills. -Driving road to join Querque and Huasamayo. -Road to allow entrance to the ruins “Llacctapata”. -Cheese-maker factory. -Installation of public phones to be property of Querque. -Installation of Internet to be property of Querque. -Installation of parabolic satellite to be property of Querque -Installation of public light to be property of Querque. -Construction of school rooms for the local school. -Improvement in a local hospital stand. -Implementation of a small basic drugstore. -Exploitation of the tourism potential of Llacctapata ruins. -Basic training in hospitality and providing of financing for the business of tourists’ accommodations.

Positive

New Initiative In case the sponsor desires to incorporate a new initiative to this socio-economic-sustainability-initiative list, it will have to be approved by the verifier

N/A102

Source: Public Poechos I PDD served as example to build this chart. To provide evidence of listed indicators’ progresses, the project should provide the verifier the following: (a) Receipts of expenses incurred for the socially and environmentally responsible action. (b) Documents related to socially and environmentally responsible action. (c) The compliance form signed annually by all members of the compliance committee (described below). The Compliance Committee: The compliance committee will be formed to enforce further the SDMP. The compliance committee will be composed by a representative from: - The project’s direct area of influence: Mr. Gerardo Casa, Deputy Mayor of Querque. - The project’s indirect area of influence: Mr. Jacinto Neyra Jacobo, Mayor of Lluta District. The compliance committee will meet annually to: - After reviewing evidence [(a) and (b) described above], reviewing a written summary of the

environmentally and socially responsible actions taken in the semester - to be prepared by the sponsor- and being left convinced by this evidence about the indicators’ progresses’ accuracy claimed by the project, sign the attached form annexed below (“compliance form”); and

101 Until complying with investments committed with Querque - according to the act signed by Querque and the sponsor. 102 Target will be set when indicator is created and also needs to be approved by the verifier.



- Review progresses, identify stoppages and suggest solutions regarding listed indicators, to the sponsor, represented by Project Manager Engineer. Miguel Suazo and/or Engineer Jose Melendez, who will be present at the meeting.



Annual Compliance Committee Meeting - Compliance Form Goal 1: Environmental Sustainability

Initiative Indicator103 Annual Cumulative Progress Environment Donations to Querque in regards of the environment104 As of March 31st New Initiative In case the sponsor desires to incorporate a new initiative to

this environmental-sustainability-initiative list, it will have to be approved by the verifier

N/A105

Source: Public Poechos I PDD served as example to build this chart.

Goal 2: Socio-Economic Sustainability Initiative Indicator106 Annual Cumulative Progress

Number of employees hired from local population As of March 31st = Purchases from local suppliers As of March 31st =

Economic standards Donations to Querque in regards of social development107 As of March 31st = New Initiative In case the sponsor desires to incorporate a new initiative to

this socio-economic-sustainability-initiative list, it will have to be approved by the verifier

N/A108

Source: Public Poechos I PDD served as example to build this chart. Identified stoppages, suggested solutions and other observations brought up in the meeting: __________ ______________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________ (Annex extra-paper if necessary). _______________________________ _______________________________ Direct area of influence representative Indirect area of influence representative _________________________________ The sponsor Date of the Compliance Committee Meeting: Period of the year monitored:

103 Yearly flow or yearly change. 104 Until complying with investments committed with Querque - according to the act signed by Querque and the sponsor. 105 Target will be set when indicator is created and also needs to be approved by the verifier. 106 Yearly flow or yearly change. 107 Until complying with investments committed with Querque - according to the act signed by Querque and the sponsor. 108 Target will be set when indicator is created and also needs to be approved by the verifier.



MP Steering CommitteeMP Steering CommitteeL. VieiraL. CostaF. Liu

L. VieiraL. CostaF. Liu

Miguel Suazo

JoséMeléndez

ERCP ManagementERCP ManagementRuben Napa

Operating Margin Calculation - Responsible

Operating Margin Calculation - Responsible

Build Margin Calculation - Responsible

Build Margin Calculation - Responsible

RubenNapa

LuisLandeo

SupportSupportMauricio Buitron

Monitoring Plan (MP) – Emissions Reductions Calculation Procedure

ERCP Organizational Structure



Monitoring Plan (MP) – Emissions Reductions Calculation ProcedureERCP Quality Control

Operating Margin CalculationOperating Margin Calculation Build Margin CalculationBuild Margin Calculation

Which data comes? All of the aboveBy what means does it come? By E-mail/ CDHow does it come? In ExcelHow frequently does it come? MonthlyFrom whom does it come? From COES (Programacion Semanal)To whom does it comes? Ruben Napa and Luis Landeo

The Project hourly generation data: “A”SEIN units hourly generation data: “B”Weekly Merit order for hours of maximum demand: “C”Real NECs

COES most recent year operations statistics (Tables: 2.6, 4.3, 12.1): “D”

New units that enter the SEIN annuallyReal NECs

Data

Quality of DataCollection

Quarterly Cross-checkingQuarterly Corrective actionsCheck calibration of electricity meters, periodicallyMake coordination with COES to be able to implement this document

Original DataOrganized DataEntered DataProcessed DataResult

Quality ofData Processing

Prevent Excel versioning problem, by keeping “a new” Excel software package every year in PCs used for the OM and BM calculationsKeep all data for 2 years after the first crediting period (9 years) –Each responsible should assign a password to his excel spreadsheetsSave the document with the last date in which an alteration was made, i.e. “OM at xx”, so that old versions are kept in diskKeep all written documentation in a folder per Margin/Responsible

Quality ofData Storage

Provide to the verifier e-mails /CD through which the data provider (COES) delivered the original data Provide to the verifier receipt of sales to final clientsProvide to the verifier all calculations made (all steps of data processing) by showing all preliminary versions of spreadsheets saved in disk

Quality ofData Delivery

Which data comes? All of the aboveBy what means does it come? By E-mail/ CDHow does it come? In ExcelHow frequently does it come? YearlyFrom who does it come? From COES (EE. Economicos)To whom does it comes? Ruben Napa and Luis Landeo

Original DataOrganized DataEntered DataProcessed DataResult

• Monthly calculation involves 5 steps• Follow ERCP• Beware of alerts –

presented in training• Quarterly cross-check by BM responsible• Yearly consolidation of C.Margin

• Yearly calculation involves 5 steps• Follow ERCP• Beware of alerts –

presented in training• Yearly c-check by OM responsible• Yearly consolidation of C.Margin

CLEAN DEVELOPMENT MECHANISM PROJECT DESIGN DOCUMENT FORM ... · PDF filepallasca motil chauall...

Documents

Transcript of CLEAN DEVELOPMENT MECHANISM PROJECT DESIGN DOCUMENT FORM ... · PDF filepallasca motil chauall...