PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1.
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CLEAN DEVELOPMENT MECHANISM PROJECT DESIGN DOCUMENT FORM (CDM-PDD) Version 03 - in effect as of: 28 July 2006
CONTENTS
A. General description of project activity
B. Application of a baseline and monitoring methodology
C. Duration of the project activity / crediting period
D. Environmental impacts
E. Stakeholders’ comments
Annexes
Annex 1: Contact information on participants in the project activity
Annex 2: Information regarding public funding
Annex 3: Baseline information
Annex 4: Monitoring plan
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SECTION A. General description of project activity
A.1 Title of the project activity:
Buenos Aires Wind Farm Version 0. 01/06/2009
A.2. Description of the project activity:
Buenos Aires Wind Farm will be built with the purpose of generating an average of 38.461 GWh per year of clean electric energy, to be injected to the Interconnected National System of Guatemala. The project is being developed by Empresa Eléctrica Buenos Aires, S.A., a Guatemalan private company.
The site of the project has a potential of 40 MW, which will be exploited in stages. During the first stage wind power turbines will be installed with a total capacity of 15 MW, and the capacity of the wind farm will be increased in future stages. Present PDD refers to first stage.
Buenos Aires Wind Farm will contribute to the increment of the electricity offer in Guatemala, with lower and more stable prices, which is compatible with sectorial laws –Ley General de Electricidad y Ley de Energías Renovables (General Law of Electricity and Renewable Energy Law). The legal framework allow free investment in generation with the objective of increasing the electric energy offer, at a minimum cost, in order to meet the demand required for the economic growth of the country.
Its contribution to the sustainable development is summarized in the following way:
Environmental dimension
Exploiting the wind power resource of Guatemala, without significant environmental impacts,
Reducing the emission of approximately 27,961 ton CO2 a year, since it will replace generation power stations that use fossil fuels at the present. Contributing to disseminate knowledge about wind power through an educational program concerning renewable energies, which will be carried out in schools located in communities near to the site of the project.
Economic dimension
Contributing to meet the growing demand of electricity in Guatemala with a minor dependency of fuels imports. It will avoid importing approximately 2,400 gallons of petroleum derived fuel a year. Contributing to the stabilization of electricity prices for final consumers, because the volatility of petroleum prices does not influence its production costs. Allowing the transference of technology and will increase local capacities, since it is the first wind power project of commercial type carried out in the country.
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Social Dimension
Contributing to the improvement of the educational level of children in communities inside the project’s influence area, through a primary level school which is being built in a lot donated by Empresa Eléctrica Buenos Aires, S.A. Currently the Education Ministry is building the school and Empresa Eléctrica Buenos Aires, S.A. will support a permanent program about environmental education, so that children shall develop abilities and attitudes which allow them to develop their future lives in a successful and responsible way.
A.3. Project participants:
Name of party involved Private and/or public The party involved wishes to entity(ies) be a project participant Guatemala (host) Private entity: Empresa No Eléctrica Buenos Aires, S.A.
A.4. Technical description of the project activity:
A.4.1. Location of the project activity:
A.4.1.1. Host Party(ies): Guatemala
A.4.1.2. Region/State/Province etc.: Villa Canales
A.4.1.3. City/Town/Community etc: Santa Elena Barillas
A.4.1.4. Detail of physical location, including information allowing the unique identification of this project activity (maximum one page):
Buenos Aires Wind Farm is located 40 Km. south from Guatemala City and 5 km south from Amatitlán Lake. The access to the site is by the road from Santa Elena Barrillas to Los Dolores community.
Buenos Aires Wind Farm is located in a valley where the conditions of wind power resources are favorable for its energetic exploitation, because prevailing wind accelerates among the elevations of Cerro Grande, Cerro Ajalom and Cerro Gordo, forming a wind tunnel which penetrates into the valley. PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1.
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The coordinates of the site are: 15°88’883” North and 7°65’490”.
Buenos Aires Wind Farm
Figure 1. Location of the project site.
A.4.2. Category(ies) of project activity:
Sectorial scope: Energy industries (renewable sources)
Category: Renewable based grid connected electricity generation
A.4.3. Technology to be employed by the project activity:
The wind power resource was assessed through two measurement towers equipped with RNG meters, one at 15 m and the other at 30 m high, carrying out the monitoring of wind variables during three consecutive years. The study showed that the wind pattern is seasonal during the year; the highest velocities are registered during the months of November to February, when there is a less electricity production with hydroelectric plants in the country.
Wind study is up-dated as of 2009. The purpose of this study is to assess wind resource at 50 m and to validate the previous wind study.
The wind power farm will consist of 10-15 wind-power generators with nominal capacities between 1.5 and 3 MW. The precise quantity of wind-power generators will be defined according to the micro sitting study and turbines availability in the market. PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1.
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The wind power farm will have an installed capacity of 15 MW and an annual energy production estimated in 38.461 GWh. The energy produced will be injected to the Interconnected National System of Guatemala through a transmission line of 69 kV, in a node electrically robust due to be near to the load center of the country. The wind-power generators will be equipped with controllers which guard the quality of the power injected to the grid.
This technology is implemented for first time in the country. The main technical characteristics of the wind turbines are described in the following table.
Table 1. Technical characteristics of the wind turbines.
Number 10-15 Nominal power 1.5 - 3 MW Manufacturer Pending Rotor diameter 75 - 100 m Swept area m2 Hub height 50 - 100 m Rotational speed approx. 22/15 rpm
A.4.4 Estimated amount of emission reductions over the chosen crediting period:
Table 2. Estimated amount of emission reductions
Annual estimation of emission reductions
( t CO2e ) Year 1 2012 27,961 Year 2 2013 27,961 Year 3 2014 27,961 Year 4 2015 27,961 Year 5 2016 27,961 Year 6 2017 27,961 Year 7 2018 27,961
Total estimated reductions (t CO2e) 223,689 Total number of crediting years 7 Annual average over the first crediting period of estimated reductions (t CO2e) 27,961
A.4.5. Public funding of the project activity:
Public funds are not used in any stage of the project.
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SECTION B. Application of a baseline and monitoring methodology
B.1. Title and reference of the approved baseline and monitoring methodology applied to the project activity:
Buenos Aires Wind Farm uses: “Consolidated Baseline Methodology for Grid-connected Electricity from Renewable Sources” (Version 09 of ACM0002) “Tool to calculate the emission factor for an electricity system”, version 01.1.
B.2 Justification of the choice of the methodology and why it is applicable to the project activity:
The ACM0002, version 09, is applicable to the project due the following reasons:
Because Buenos Aires Wind Farm implies an electricity capacity addition from wind sources.
Buenos Aires Wind Farm does not switch from fuel to renewable sources.
The geographic borders and of the grid system are clearly identified, and the data from the Interconnected National System is available.
The proposed methodology is applicable because it is considered the tool for the demonstration and assessment of additionality1.
B.3. Description of the sources and gases included in the project boundary
Table 2 indicates the sources and gases included in the project boundary. The project boundary includes the physical site of the plant and the spatial extend of the project boundary includes all power plants connected to the electricity system and form part of the wholesale electricity market.
Table 2. Sources and gases included in the project boundary.
Source Gas Included? Justification/explanation Fossil fired power CO2 Yes GHG in the baseline are due thermal plants plants connected to CH Yes CH in the baseline corresponds to the Baseline 4 4 the grid, which are emissions due non condensable attributable displaced by the to the operation of the existent plant in
1 EB16 Report, Annex 1. PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1.
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project activity Ahuachapán field.
N2O No Power plants do not produce N2O emissions or are negligible
Construction CO2 No The emissions produced during construction due vehicles and machinery are negligible in relation to the emission reductions that the power plant will produce Project CH No CH is not produced activity 4 4 N O No N O is not produced 2 2 Operation of back-up CO2 Yes Emissions of CO2 due combustion of fossil generation units fuels from back-up generation
CH4 Yes CH4 is not produced N2O No N2O is not produced
B.4. Description of how the baseline scenario is identified and description of the identified baseline scenario:
1. Analysis of national policies and circumstances
With the passing of the General Law for Electricity in 1996, the electricity wholesale market initiated operation administering the energy and power transactions between market agents, under free market conditions. The electricity wholesale market allows energy transactions in the opportunity or spot market; and capacity and energy transactions in the contract market, according to mutually agreed contracts between market agents.
Investment in electric generation plants is free according to competitive market conditions and there is not centralized planning for the expansion of the generation system in Guatemala.
Regarding the operation of the electric system, Guatemala’s General Electricity Law establishes that the generator plants should operate so as to minimize the cost for the joint operations of the electric market2. To attain this objective, the Administration of the Wholesale Market coordinates the operation of the generating plants and makes the economic load dispatch taking as a first priority the merit list of the plants available.
2. Scenario of the baseline
The CO2 emissions per MWh, that would occurs in the baseline of the electric energy sector in Guatemala, are determined taking into consideration national conditions, trends in electricity demand, economic dispatch characteristics, and the technical specifications of the generation facilities in the Interconnected National System.
2 http://www.amm.org.gt/pdfs/AMM-reglamento-amm.pdf . AMM Regulation, page 16. PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1.
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The emissions coefficient of the baseline permit estimate the CO2 emissions produced during the electric energy generation by the operating plants, through the Operating Margin emission factor; and the CO2 emissions that would be produced by those plants that will be added to the grid during the accreditation period, through the Build Margin emission factor.
At present, the baseline of the generation system in Guatemala is characterized by a mix of plants that uses renewable resources, carbon and fuel fired plants, and imports has not been significant until now. Over the last five years the thermal component has experienced an increment due to the additions of GECSA, Electrogeneración, Arizona and Amatex power plants, similarly the hydro component increased due to the addition of El Recreo, Montecristo, Renace and Palín II plants. Cogenerators and geothermal plants also have had capacity additions.
On the other hand, during the 2005, 2006 and 2007 years, both renewable and thermal plants have been built, whose mix of plants indicates the future trend of the capacity additions in the National Interconnected System, condition reflected by the Building Margin emission factor.
The last inversion in thermal plants occurred in 2007 with a 15 MW plant based in motors of internal combustion. The owner of this plan is Generadora Eléctrica Central, S.A. (GECSA), which will increase its capacity installed to 50 MW in March 20083. CNEE have authorized in 2007, two additional thermal plants with a capacity of 57 MW4, which could be installed in the short term.
In November 2007, Electricity National Commission (CNEE, Comisión Nacional de Energía Eléctrica) authorized an international bid call to Union Fenosa, which is owner of two distribution grid in Guatemala (DEOCSA. Through the bid call, Union Fenosa will buy electricity from a 200 MW carbon plant5. The carbon plant must be constructed in Guatemala and the contract term will be 15 years as of 2012. Therefore, the most plausible alternative for inversion projects is a carbon plant in the long term.
As of 2009, Guatemala will import and export electricity to Mexico through a 400 kV transmission system6. The conditions of the trade agreement in not public information, therefore is not possible at the moment of the present analysis to know exactly the influence of the imports in the baseline. The transmission capacity is of 200 MW and the load factor for the present analysis is assumed 0.5 for electricity imports.
In order to analyze the baseline, a graph is constructed to illustrate the tendencies and is shown in figure 2. First, it is considered the historical data about the electric energy produced since 2001 until 2006, with different fuels and renewable resources. Then a generation dispatch is simulated with the information available about the new capacity additions, and this situation is called the likely scenerio. The tendency is a projection of the possible conditions as of 2012.
3 Administrador del Mercado Mayorista and GECSA. 4 Annual Report, Table 9, page 16, Comisión Nacional de Energía Eléctrica (CNEEE), http://www.cnee.gob.gt/html/memo/Memoria%20CNEE%202007-optimizado-b.pdf 5 http://www.cnee.gob.gt/pdf/informacion/licitaciones/LICITACION%20UNION%20FENOSA.PDF 6 Plan Puebla Panamá, http://www.planpuebla-panama.org/IME/main-pages/noticias_detalle.php?anterior=2#7 PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1.
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14,000.00
12,000.00
10,000.00 Hydro tendency
New CDM projects 8,000.00 CDM projects under validation CDM projects registered 6,000.00 Imports from Mexico
Fuel fired plants 4,000.00
Composition of energy production (GWh) Cogenerators
2,000.00 Geothermal
Hydroelectric
-
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Histrorical Likely scenario Tendency
Figure 2. Scenerio of the Baseline and project activity
The baseline scenery was constructed assuming: Growth energy demand of 5.5% from 2006 until 2011, and 5% from 2011 until 2015. A load factor of 0.6 for electricity imports, because this is the average load factor of the Guatemalan interconnected national system. The capacity addition from a 300 MW plant, using pet coke. This project is developed in two phases. All renewable additions are developed as CDM projects. The new CDM projects considered in the likely scenery are hydro and wind projects being developed at the present 7. Energy from cogenerators includes electricity generated with bagasse and electricity generated with bunker.
At present, there are several Hydro projects in the feasibility stage, which energy production is marked in violet in figure 2. These projects could not occur if there are not enough incentives to overcome the barriers that they have to overcome.
7 Comisión Nacional de Energía Eléctrica, CNEE. PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1.
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Figure 2 shows that the electricity production of the hydro, geothermal and cogenerator plants constructed to 2006, remains constant, while the production based in fuels combustion is variable according to the demand. In the short and medium term, the demand will be meet through the new plants developed as CDM projects, the electricity imports and the capacity additions on thermal plants.
In conclusion, if there are not inversions in renewable plants in Guatemala, the tendency is to increase the fuel based production. The information available indicates that the conditions of the baseline will remain similar during the first crediting period of Buenos Aires Wind Farm, because the capacity additions in renewable plants will be similar to the new thermal plants and the additions in renewable generation to cover the load base will be compensated by the demand growth.
3. Scenerio of the project’s activity
In absence of Buenos Aires wind plant, the AMM would be required to dispatch a thermal facility equivalent in power and energy to the Buenos Aires, in order to supply the demand and grid losses of the Interconnected National System. Considering the present conditions of demand and installed power prevailing in the crediting period, the replaced thermal plant could correspond to one that uses coal or fossil fuels.
The energy produced by the hydroelectric, geothermal, and must-run plants now installed is not enough to meet the demand of the system, even during the periods of minimum demand of the rainy season8, requiring an additional mix of thermal plants. This mix of thermal plants is set up by the marginal units because of their high operational cost respect to renewable plants.
Under the present conditions of installed capacity and demand in Guatemala; hydro, geothermal and cogenerator plants are the base plants due its low operation costs; and thermal plants are the mid range and marginal plants, as a consequence of the economic management of the load dispatch. Therefore a capacity addition to the system using renewables sources will displace thermal plant, and in this way Buenos Aires Wind Farm shall reduce approximately 27,961 t CO2 per annum.
Through the economic dispatch, the minimum cost plants such as hydroelectric plants, geothermal, cogenerators as well as the wind plants have priority, and then are dispatched successively the plants with a higher cost as thermal plants until covering the demand and the system losses. In the rainy season, when the hydraulic generation is bigger, the marginal thermal block decreases, in contrast, during the dry season increases.
In the following graph, we observe the load demand curves and how the hydraulic and thermal generation meets the demand. Hydraulic generation is base generation while fossil plants are on the margin.
8 See the graphs of generation dispatch, AMM 2007 Statistic Report, page 5; 2007. www.amm.org.gt PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1.
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Date of maximum fuel based generation 14/03/2008
Hydro 25.55% Hours Thermal 74.45%
Date of maximum hydroelectric generation 04/09/2008
Hydro 66.52% Hours Thermal 33.48 %
Figure 3. Demand curve during maximum hydroelectric and fuel based generation.
If Buenos Aires Wind Farm is not counted, the emission reductions to be produced by this plant would not happen, because a thermal power block would be dispatched to cover the demand, since the hydraulic and geo-thermal plants installed at present are not enough to cover the system’s demand, even during the period of minimum demand and during the rainy season9. This trend shall prevail at the short and medium terms, since the demand grows at a rate of approximately 100 MW per annum, and the thermal plants that at present are in reserve shall have to be dispatched in order to meet the demand.
9 See 2007 AMM Statistic Report, page 4, www.amm.org.gt PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1.
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B.5. 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 (assessment and demonstration of additionality):
Demonstration of additionality according to the “Toolkit for the demonstration and assessment of of additionality”, version 05.1:
Step 1. Identification of project activity alternatives consistent with laws and regulations.
1. The project developers could decide not to make the investment, thus continuing with the conditions of the baseline, increasing the utilization factor of the existent thermal plant as the business as usual scenario.
2. To build the project without the MDL financing.
The above alternatives are viable under Guatemalan Laws. The General Electricity Law of Guatemala allows an open and competitive electricity market, and the investment in new electricity generation plants is free.
Step 2. Investment analysis.
Not apply.
Step 3. Barrier Analysis.
Electricity market barriers
Buenos Aires Wind Farm will face up barriers in the wholesales electricity market due to the following reason:
o Due to the variable nature of wind resource, the wind plants can not maintain a firm offer and therefore can not sell capacity. Under this situation, the wind plants are in a competitive disadvantage in the electricity market respect to other technologies.
Buenos Aires Wind Farm with a capacity installed of 15 MW can sell only energy, while a plant with a firm offer of 15 MW could perceive up to $ 110,250010 annually per the capacity available during peak period, additionally to energy sales. This amount not perceived by Buenos Aires is equivalent to 5% of the energy sales11 or approximately 40% of the CERs sales12 in a conservative scenerio.
10 In the contract market, the prices could vary in a range between 4.5 and 9.8 $kW-month. According to AMM , the reference price of the capacity is 9.8 $kW-month. 11 Considering the average energy price in the spot market was $62.19 in 2005. PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1.
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o The wind farms are not dispatchable plants and can not store energy, they only generate when the resource is available. By this reason, Buenos Aires Wind Farm can not take advantage of the spot market, by means of the energy storage during the valley period to sell it during the hours with higher prices, as do other technologies.
o There are not technical and commercial regulations in the wholesales electricity market of Guatemala for wind plants, therefore there is an uncertainty about the charges and penalties associated to the intermittent operation of the plant (for example, charges due to the frequency regulation for the compensation of the variations on the real power output).
Sub-step 3a Identified barriers would not prevent the implementation of the alternative
The plants installed at present or the new projects using known technologies do not face the barriers that have to overcome the wind plants.
Due its characteristics, fuel based, hydroelectric, geothermal and cogenerators plants are able to maintain an offer firm, which has value in the electric market. On the other hand, these plants are dispatchable during peak hours when the electricity prices are high.
Step 4. Analysis of common practice.
Sub-step 4a. Other activities similar to the proposed Project activity.
There are not other similar project activities in Guatemala because this is the first wind farm developed in the country.
Sub-step 4b. Other similar options that are occurring
Other wind projects are being carried out in different sites of Guatemala, and in all cases are considering the MDL financing to overcome barriers. These projects are in the resource assessment phase and the potential of the sites could be between 20 and 40 MW.
Step 5. MDL registration impact
The approval and registration of the project activity as a MDL activity shall allow the developers of the Buenos Aires Wind Farm to sell the reduced CO2 emissions produced by project activity to attain the overcoming of the barriers described in Step 3.
Likewise, the approval and registration of the project activity will allow the financing of the activities focused to contribute to the sustainable development of the communities neighbouring.
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B.6. Emission reductions:
B.6.1. Explanation of methodological choices:
The calculation of the reduced emissions is done following the procedures established in the approved “Tool to calculate the emission factor for an electricity system”, Version 01.113. This tool is applicable because the project activity replaces electricity from the grid and electricity produced with renewable resources is increased due to the project.
The baseline scenario and the emission rate calculation is based on the electricity that otherwise would have been generated by the plants connected to the grid and by addition of future plants.
Step 1. Identify the relevant electric power system
The project electricity system is the spatial extent of the power plants connected to the Salvadorian electric grid and dispatched without significant transmission constraints.
Connection to the electrical grid
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Fig 3. Project electricity system14.
The connected electricity system is formed by the power grids of Guatemala, Honduras, Nicaragua, Costa Rica and Panamá, which are interconnected by the SIEPAC (Sistema de Interconexion Electrica para America Central or Central American Electrical Interconnection System).
For Operating Margin emission factor calculation, the emission factor of imports is considered equal to 0 tCO2 per MWh because the electricity imported comes from connected electricity systems in other countries of Central America.
Step 2. Select an operating margin method
The first option to calculate the Operating Margin should be the Dispatch Data Analysis, which is not used because the post-dispatch information available is not enough to complete the calculation.
The electric energy produced by the low-cost and must run plants during the last fiver represent more than 50% of the generation of the plants connected to the grid, therefore the Simple OM method is no applicable and the suitable option is the Simple Adjusted OM method.
Step 3. Calculate the operating margin emission factor according to the selected method
The simple adjusted OM method is calculated based on data on fuel consumption and net electricity of each power plant (option A).
The Operating Margin emission factor is calculated ex-ante and fixed for the first crediting period. It will be up dated at the renewal of the crediting period. Data vintages are: 2005, 2006 and 2007.
The Operating Margin emission factor, EFgrid,OM-adj,y, is calculated using simple adjusted method as is indicated in equation 1. The detailed formula is shown in equation 6.
Where λ is equal to number of hours per year for which low cost and must-run plants are on the margin divided by the total hours per year. The low-cost plants are the hydroelectric, geothermal and cogenerators power plants connected to the grid.
EFgrid,OM-adj,y = λ (Low cost and must-run plants emission factor) + Eq. 1 (1-λ) (Other plants of the system emission factor)
Lambda is calculated graphically. The number of days that low cost and must-run plants are on the margin is calculated as the intersection of the value of equivalent power of these plants and the load duration curve.
14 Source: INDE, Instituto Nacional de Electrificación. PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1.
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For lambda calculation, is considered the amount of energy supplied to the grid by each cogeneration plant, not the gross production.
The following chart illustrates the calculation of lambda and the load duration curve, according wholesale market demand data from Administrador del Mercado Mayorista, AMM.
900 800 700 600 500 400 300
Demand(MW) Hidro + Geo equivalent power 200 100 0 1 731 1461 2191 2921 3651 4381 5111 5841 6571 7301 8031 Hours
Fig. 4 Lambda factor calculation
Step 4. Identify the cohort of power unit to be included in the build margin (BM)
The sample group of power units used to calculate the build margin consists of the set of power plants in the electricity system that comprise 20% of the system generation and have been built most recently, which are:
For BM calculation is considered the following premises: Power units registered as CDM project activities are excluded from the cohort of power plants a. Capacity additions from retrofits of power plants are not included. BM is calculated ex-ante for the first crediting period based in the most recent information available.
Step 5. Calculate the build margin emission factor
The Build Margin emission factor represents the tendency of the mix of generation and is calculated for the five most recent capacity additions and for the most recent capacity additions that represent the 20% of the power of the system. Project participants will use from the two options the group that comprises the larger annual generation of electricity.
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CDM projects are excluded from calculation. Additionally imports are excluded because at the moment of submit the PDD is not clear the interchange of electricity through the Sistema de Interconexión Eléctrica de los Paises de América Central (SIEPAC).
Step 6. Calculate the combined margin emissions factor
The baseline emission factor is calculated as the weighted average of the OM emission factor and the BM emission factor, where the weight factor for both is the default value equal to 0.5, for the first crediting period. Weight factor will be revised at the renewal of the crediting period.
Data vintages
For the calculation ex-ante of the OM emission factor: 2007, 2007, 2008 For the calculation ex-ante of the BM emission factor: 2008
Justification of conservatism in the project’s baseline methodology.
Additionality. The demonstration of additionally is conservative because it analyzes the national scenario and circumstances to demonstrate that the project activity faces real barriers, and the cost of these barriers for the project are quantified in a conservative manner.
Operating Emission factor. The Operating Emission factor calculation is conservative because this value represents the average of the rate to which CO2 is emitted by the plants generating for the National Interconnected System, taking into consideration all from the most efficient to the least efficient and costly. That is to say, the amount of the emissions displaced is made by function of an average, conservative value, and not based on the marginal plant which is least efficient and with a higher emission factor.
Building Emission factor. This factor is calculated in a conservative manner, since it represents the trend of the composition of the generation mix, and takes into consideration the last generation investments.
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B.6.2. Data and parameters that are available at validation:
Data / Parameter: Electricity by generating units Data unit: MWh Description: Annual energy produced by the plants connected to the grid during 2006, 2007 and 2008 Source of data used: Administrador del Mercado Mayorista, AMM Value applied: Please see table A1, annex 3 Justification of the Electricity generated by the plants data is used to calculate the apparent fuel choice of data or consumed per plant and Operating Margin and Build Margin. description of Electricity is measured through measurement equipment installed in each plant. measurement methods and procedures actually applied : Any comment:
Data / Parameter: Average CO2 emission factor of fuel Data unit: tCO2/TJ Description: Average CO2 emission factor of each type of fuel type used in each generating unit connected to the grid Source of data used: 2006 IPCC Guidelines Value applied: Diesel oil 74.1 Residual fuel oil 77.4 Bituminuos coal 94.6
Justification of the Information about fuels consumed by generating units is not available in choice of data or Guatemala, therefore option B2 of the Tool to calculate the emission factor for description of an electricity system is used. Fuel type is available then so the emission factor measurement methods is determined based on the CO2 emission factor of the fuel used. and procedures actually applied : Any comment:
Data / Parameter: Fuels density Data unit: Tonnes/l Description: Fuels density for type of fuel used by the units connected to the grid Source of data used: EIA PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1.
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Value applied: Refer to table 8 Justification of the By means of the fuel density data is calculated the mass of the fuel consumed. choice of data or description of measurement methods and procedures actually applied : Any comment:
Data / Parameter: Net calorific values Data unit: TJ/103 tonnes Description: Net calorific values Source of data used: 2006 IPCC Guidelines Value applied: Default values Justification of the By means of the net calorific values and the mass of the fuel consumed is choice of data or calculated the apparent fuel consumed during each year by the generating units. description of measurement methods and procedures actually applied : Any comment:
Data / Parameter: Carbon content Data unit: tC/TJ Description: Carbon content for each type of fuel Source of data used: 2006 IPCC Guidelines Value applied: Default values. Please see table A1, annex 3 Justification of the The carbon content is used to calculate the carbon emitted per each type of fuel choice of data or consumed in each plant during 2006, 2007 and 2008. description of measurement methods and procedures actually applied : Any comment:
B.6.3 Ex-ante calculation of emission reductions:
1. Calculation of emissions reductions
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Emissions reductions due project activity are calculated according to equation 1.
ER = BE – GHG emissions by sources – leakages Eq.1 y y
Where:
ER y = Emissions reductions (t CO2)
BE y = Baseline emissions reductions (t CO2)
The baseline emissions reductions per year are calculated using the following equation:
BE (t CO ) = EG (MWh) EF (t CO /MWh) Eq. 2 y 2 y y 2
Where:
BE y = Emissions in the baseline setting (t CO2)
EG y = Energy produced by the Buenos Aires Wind Farm during the year y (MWh)
EF y = Emissions factor (t CO2/MWh) y = year
2. Estimate of GHG emissions by sources
Buenos Aires Wind Farm will not have any GHG emissions because the GHG emissions due the emergency plant for auxiliary services are negligible.
3. Estimated leakage:
The project consists of a wind farm; therefore there is no formula for the calculation of leakage included in this section.
5. Estimated anthropogenic emissions by sources of greenhouse gases of the baseline:
The estimated anthropogenic emissions by sources of greenhouse gases of the baseline are given by emissions factor of the Interconnected National System. This value is calculated conservatively as the average of the emission factors of both Operating Margin and Building Margin, according to equation 4.
EF y (t CO2/MWh) = 0.75 EFOM y + 0.25 EFBM,y Eq. 4
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Where:
EFOM y = Operating Margin emission factor (t CO2/MWh)
EFBM y = Building Margin emission factor (t CO2/MWh)
Operating Margin emission factor
The Operating Margin emission factor represents the CO2 emissions of the plants in operation from the generation mix. This factor excludes both the low-cost and must-run plants, which in Guatemala, is the total energy produced by the hydroelectric and geothermal plants and by the cogenerators using bagasse during the harvest period. San Jose, coal based power plant is considered as a must-run plant. See Item B5.
The Operating Margin emission factor is calculated using Equation 3 and data vintages for a 3-year average, based on the most recent statistics available at the time of PDD submission. It is calculated as the generation-weighted average emissions per electricity units serving the system.
EG EF j,y EL , j,y EGk,y EFEL ,k,y i, j k EFOM ,y 1 Eq. 5 EG j,y EGk,y j k Eq. 5 Where:
EFOM,,y = Operating Margin emission factor (t CO2/MWh).
y = year (s)
λ = Lambda factor
FEEL. i ,j = Average CO2 emissions factor of fuel i, used in power plants j, is given in tCO2/TJ. It is determined using Equation 6.
EFEL, i ,k = Average CO2 emissions factor of fuel i, used in power plants k, is given in tCO2/TJ. It is determined using Equation 6.
EG j,y = The summary of the generation from each relevant source power j (MWh), in the j year y, , according to recorded data by the Administrador del Mercado Mayorista, AMM. These data are the result of the commercial measurement, PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1.
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whose breakdown per generating unit does not appear in the statistics reports, and therefore, they have to be obtained directly from the AMM.
EGk,y = The summary of the generation from each relevant source power k (MWh), in the j year y, , according to recorded data by the Administrador del Mercado Mayorista, AMM. These data are the result of the commercial measurement, whose breakdown per generating unit does not appear in the statistics reports, and therefore, they have to be obtained directly from the AMM.
The calculation of the terms defined previously is as follow:
The emission factor for each group of power plants, FEEL,,j,y and EF EL,k,y, connected to Interconnected National System, SNI, is calculated by using the average CO2 emission factor of fuel type i used in each generating unit and the default efficiencies, as describes the following equation:
EFco2,m,i,y 3.6 EFEL m,,y = Eq. 6 D m,y e Where:
EFEL,m,y = Emission factor of power units m, given in tCO2/MWh
EFCO2,m,i,y= Average CO2 emissions factor of fuel i, used in generating units m (j or k), is given in tCO2/TJ.
3.6 = Energy conversion factor, given in TJ/MWh according to the International System Units.
m,y = Average efficiency factor for each generating unit, given in %.
Default CO2 emissions factor for combustion are obtained from Table 1.4, chapter 1, 2006 IPCC Guidelines for National Greenhouse Gas Inventories, where oxidation factor is equal 1. The type of fuels for each power unit are given by AMM.
Default efficiency factors for power plants are obtained from the annex I of the “Tool to calculate the emission facto for an electricity system”. The efficiency factor is selected according the operation starting year and technology of each generating unit, data given by AMM.
Finally, the denominator of the Operating Margin Equation is:
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EG j,y = The summary of the generation from each relevant source power j (MWh), j during the year y, expressed in MWh.
EGk,y = The summary of the generation from each relevant source power k (MWh), j during the year y, expressed in MWh.
Building Margin emission factor
The Building Margin emission factor represents the trend of the generation mix. It is calculated in similar way to the Operating Margin emission factor for both the five most recent plants and for the most recent plants representing 20% of the energy of the system, taking the value that comprises the larger annual generation.
It is calculated ex-ante using the following equation:
F i,m, y COEFi,m i,m EF Eq. 7 BM , y GEN m, y m
Where:
EFBM,,y = Building Margin emission factor (t CO2/MWh)
F i,m,y = The apparent quantity of fuel i, for each relevant source power m of the National Interconnected System, for the reference year y. Where m is determined among the 5 most recent plants or those recent plants contributing the 20% of the National Interconnected System energy, expressed in TJ/year. El Canada is not included in this set because was registered as a CDM project. This value is calculated using equation 6 for the most recent plants.
y = year
COEFi,m = The CO2 emissions coefficient of the most recent plants (tCO2/TJ), connected to the grid, that use fuel i .
GEN m, y = The summary of the generation of each relevant source power m, during the year j 2008 for the first crediting period, in MWh.
For the first crediting period, the emissions factor is calculated ex-ante as follow:
EFOM,y (t CO2/MWh) = 0.797 PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1.
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EFBM,y (t CO2/MWh) = 0.514
EF y (t CO2/MWh) = 0.75 0.797 + 0.25 0.514
= 0.727 t CO2/MWh
(See Annex 3, Tables A2, A3 and A4)
B.6.4 Summary of the ex-ante estimation of emission reductions:
In conclusion, the emission reductions due Buenos Aires Wind Farm is equal to the energy produced by wind turbines multiplied by the emissions coefficient of the baseline, as indicated in equation 2 and described in table 9, because the activity of the project does not produce GHG emissions and there is not leakages
The calculation ex-ante of the emissions reductions for the first crediting period is summarized in the following table.
Table 10. Emission reductions estimated for the first crediting period.
Estimation of project Estimation of Estimation of activity emission baseline emission Estimation of GHG reductions reductions leakage emissions ( t CO2e) ( t CO2e) ( t CO2e) ( t CO2e) A B C D B – C – D 0.705*EGy Year 1 27,961 27,961 0 0 Year 2 27,961 27,961 0 0 Year 3 27,961 27,961 0 0 Year 4 27,961 27,961 0 0 Year 5 27,961 27,961 0 0 Year 6 27,961 27,961 0 0 Year 7 27,961 27,961 0 0 Total (tCO2) 223,689 223,689 0 0
B.7 Application of the monitoring methodology and description of the monitoring plan:
B.7.1 Data and parameters monitored:
Data / Parameter: Electric energy produced by Buenos Aires Wind Farm PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1.
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Data unit: MWh Description: Net electricity supplied by the project activity to the grid Source of data to be The net electricity registered by the commercial meter installed in the electric used: substation of interconnection to the grid. Value of data applied 38,461 MWh for the purpose of calculating expected emission reductions in section B.5 Description of Electricity produced will be registered by the metering equipment verified by the measurement methods Administrador del Mercado Mayorista, and the measurement methods and and procedures to be procedures applied are according to the AMM Standard of Commercial applied: Measurement System (Standard No. 14). Monitoring frequency - The electricity energy meter integrates active energy every 15 min. and stores the data accumulatively in the massive memory of the principal and back-up meter.
- Hourly and daily by the plant operator.
QA/QC procedures to - Electricity measurement equipment must observe the AMM Standard of be applied: Commercial Measurement System (Standard No. 14)
- Electricity must to be calibrated by manufactured, and subsequently, the equipment accuracy will be audited annually by the Administrador del Mercado Mayorista (AMM), using a reference gauge, as is indicated in the AMM measurement equipment calibration procedure.
- Data from main meter is compared against secondary meter, data registered by the plant operator and data downloaded by AMM.
Any comment: The net energy to the grid is equal to the real energy exported to the grid minus the real energy imported from the grid. Both data are registered by meters in different channels.
Data / Parameter: Fuel consumed by back-up generation units Data unit: gal Description: Fuel consumed by back-up generation units installed in the wind farm. Source of data to be Volume meter on site. used: Value of data applied 0 gal for the purpose of calculating expected emission reductions in section B.5 Description of PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1.
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measurement methods and procedures to be applied: Monitoring frequency Continuosly QA/QC procedures to Data from volume meter is validated against the fuel bills. be applied: The consistency of metered fuel consumption quantities should be cross-checked by an annual energy balance that is based on purchased quantities and stock changes. Where the purchased fuel invoices can be identified specifically for the CDM project, the metered fuel consumption quantities should also be cross-checked with available purchase invoices from the financial records.
Any comment: Back-up generation units could operate when the wind turbines are off-line and there are not electricity imports from the grid. Back-up generation units supply electricity to auxiliary services when the turbines are off-line.
B.7.2 Description of the monitoring plan:
The monitoring plan comprises two parts. The first one refers to the compilation and filling of all the relevant data needed to estimate the emissions reductions by the plant as specified in the decision 17/CP.7, document FCCC/CP/2001/13Add.2.
The second part presents the sustainable development monitoring plan, which is not a CDM project requirement, but it is a tool that will allow auditing the impact of the CDM project on sustainable development.
The monitoring of the emissions reductions will be made according to the operational structure shown in figure 4. The first step is the measuring process, followed by verification of the measurement, the second step is the calculation of the emissions reductions, and finally, review and analysis of results.
The General Manager of Empresa Eléctrica Buenos Aires, S.A will be responsible for the monitoring process.
Plant Manager Measurement of the energy produced
Personnel in charge of CDM process Personnel in charge of Verification of the measurement quality control Calculation of the emissions Verification of the process reductions Internal audit
General Manager Analysis of final report and results PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1.
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Fig. 4 Operational structure of the monitoring plan. The quality control and quality assurance procedures observed during the monitoring stage involve:
Use of electric energy meters with accuracy according to Wholesale Market Administrator (AMM) standards.
Verification of the measurement of the plant used for calculating the emissions reductions against the commercial measurement used by the AMM for the payment of operations in the electricity market.
Development of clear and defined procedures for data recording.
The monitoring plan includes an internal audit procedure and a nonconformance and corrective/prevention actions procedure.
B.8 Date of completion of the application of the baseline study and monitoring methodology and the name of the responsible person(s)/entity(ies)
Date of completing the final draft of this baseline and monitoring methodology section: 01/06/2009
Name of person responsible: Alaide González Leche PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1.
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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:
01/01/2010
C.1.2. Expected operational lifetime of the project activity:
20 years
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:
01/01/2012
C.2.1.2. Length of the first crediting period:
7 years
C.2.2. Fixed crediting period:
C.2.2.1. Starting date:
Not applicable
C.2.2.2. Length:
Not applicable
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SECTION D. Environmental impacts
D.1. Documentation on the analysis of the environmental impacts, including transboundary impacts:
The Environmental Impact Assessment was made in observance to Guatemalan Laws 15. The assessment was approved by the Ministry of the Environment and Natural Resources (Ministerio de Ambiente y Recursos Naturales, MARN) on September 28, 2006.
D.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:
The environmental assessment study concludes the Buenos Aires Wind Farm does not imply significative environmental impacts. Temporal and non-significative impacts will occur during the different stages of the project, which must be mitigated through the implementation of an environmental management program.
Following table describes the temporal and non-significative impacts and their respective mitigation measures.
Environmental Components Impacts - Residual Level of Project Subject to Short Environmental Residual Activites Impacts Description Mitigation Measures Effects Impact * Construction Activities 5.1.7. Tower • Soil and • Soil • Limit vehicles to existing None Minimal construction terrain compaction trails anticipated • Vehicle and • Soil erosion • Avoid slopes of greater than equipment travel 15 percent • Use low-impact trucks
5.1.7. Tower • Local residents • Creation of • Vehicles will be properly Some impact, Minimal construction noise maintained but short construction • Vehicle and • Creation of • Vehicles driven in proper duration equipment travel dust on access manner routes • Trail and gravel roads will be watered down if dust becomes an issue
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• Personal vehicles will be denied access to the site • Reasonable construction hours
Operation Activities 5.2.1.1. Land • Terrain/ • Reduction of • Land occupied by equipment None Minimal use vegetation land for will be less than 1 percent of anticipated agricultural site use • Agricultural activities are possible near turbines
5.2.1.4. Wildlife • Birds • Bird collision • Siting of turbines away from Monitoring to Low disturbance migratory bird corridors and in be done for a area of low topographic relief, minimum of away from potential nesting one year areas and in agricultural area with a low diversity of natural vegetation
• Monitoring of bird collisions using carcass surveys
• Turbines will have a tubular structure, which will deter birds form landing or perching on them
Decommissioning/Abandonment Activities 5.3.1. Turbine • Terrain/ • Reduction of • Plan to remove all above- Underground Minimal removal vegetation land for surface equipment structure left in agricultural but marked use
• Soil • Use of low-impact trucks compaction • Reseeding • Turbine foundations left in but marked
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SECTION E. Stakeholders’ comments
E.1. Brief description how comments by local stakeholders have been invited and compiled:
Project participants interpret the stakeholders consultation as a dynamic process, by this reason the stakeholders opinion has been consulted in different opportunities as is described below.
Public survey The first stakeholder consultation was carried during the environmental impact assessment in 2005, through a public survey. The sample was of 50 persons, which was statistical representative because covered 50% of the urban population and 40% of the rural population of the communities in the influence area of the project. Please EIA Report.
First consultation meeting
A live stakeholder consultation meeting was held on June 11, 2009 at 11:00 hours in the headquarters of Empresa Electrica Buenos Aires. The meeting was attended in an appropriate local language: Spanish.
The main purpose of the consultation was to inform to the stakeholders about the main environmental issues of the project (identified environmental impacts, mitigation plans and its follow up) as well as seeking their feedback.
Participants had the opportunity of present their doubts, concerns, and expose their comments, receiving clear and direct responses to them.
Agenda
The agenda of the stakeholder consultation was informed at the beginning of the meeting (please refer to the public presentation of the project slideshow).
Actual situation of electrical generation in Guatemala Wind generation characteristics Description of the project Public stakeholder consultation
Invitations
The stakeholder consultation meeting was by direct mails and written notification to public institutions and community representatives; informing date, time and location of the event.
Category Type of invitation Date Community Letter June 11, 2009
Municipality Letter June 11, 2009 Institutions Direct mail and letters June 11, 2009
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Next consultation meetings Next meetings will be held with more specific purposes, for example, to inform about jobs opportunities, dates and schedules of machinery transportation, etc.
Next consultation meetings Next meetings will be held with more specific purposes, for example, to inform about jobs opportunities, dates and schedules of machinery transportation, etc.
E.2. Summary of the comments received: >>
E.3. Report on how due account was taken of any comments received: >> PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1.
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Annex 1
CONTACT INFORMATION ON PARTICIPANTS IN THE PROJECT ACTIVITY
Organization: Empresa Eléctrica Buenos Aires, S.A. Street/P.O.Box: Building: Metro 15, Oficina 311 City: Guatemala State/Region: Postfix/ZIP: 01015 Country: Guatemala Telephone: 502 - 23692030 FAX: E-Mail: URL: Represented by: Title: General Manager Salutation: Mr. Last Name: Del Cid Middle Name: First Name: José Luis Department: 502 - 23692030 Mobile: 502 – 53060660 Direct FAX: Direct tel: Personal E-Mail:
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Annex 2
INFORMATION REGARDING PUBLIC FUNDING
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Annex 3
BASELINE INFORMATION
2006
TABLE A1 EGm,2007 i EF CO2,m,i,y ηm EF EL,m,y Average emission Default Energy produced factor of fuel efficiency Emission factor CO2 emissions EF calculation Availble Starting 2007 Fuel Type type i Conversion factor factors of unit m 2007
MW year (GWh) (t CO2/TJ) | % t CO2/MWh t CO2 Conversion factor Inventory EB 35 repan 12, Input from AMM from the AMM Plant data Workbook meth tool, annex Calculated Calculated data International (IPCC, 2006) I System of Units STEAM TURBINES -
Escuintla Vapor 2 24.0 1977 - Fuel Oil No.6 77.4 3.6 38% 0.74 - Laguna Vapor 2 11.0 1959 - Fuel Oil No.6 77.4 3.6 38% 0.74 - Laguna Vapor 4 11.0 1961 - Fuel Oil No.6 77.4 3.6 38% 0.74 - GAS TURBINES 35.84 Tampa 79.3 1995 3.36 Diesel 74.1 3.6 30% 0.89 2,982.0 GGG STEWART & STEVENSON 23.0 1995 23.53 Diesel 74.1 3.6 30% 0.89 20,914.9 Escuintla Gas 5 15.0 1985 1.84 Diesel 74.1 3.6 30% 0.89 1,639.6 Laguna Gas 4 27.0 1989 - Diesel 74.1 3.6 30% 0.89 - Escuintla Gas 3 17.0 1976 3.21 Diesel 74.1 3.6 30% 0.89 2,854.7 Escuintla Gas 4 * 1976 - Diesel 74.1 3.6 30% 0.89 - Laguna Gas 2 17.0 1978 - Diesel 74.1 3.6 30% 0.89 - Escuintla Gas 2 * 1968 - Diesel 74.1 3.6 30% 0.89 - Laguna Gas 1 8.0 1964 3.90 Diesel 74.1 3.6 30% 0.89 3,467.1 INTERNAL COMBUSTION MOTORS 2,427.24 Electrogeneración 15.0 2003 69.53 Fuel Oil No.6 77.4 3.6 40% 0.71 49,023.6 Arizona 160.0 2003 1,024.83 Fuel Oil No.6 77.4 3.6 40% 0.71 722,618.4 Amatex 15.0 2003 8.36 Fuel Oil No.6 77.4 3.6 40% 0.71 5,894.0 La Esperanza 124.0 2000 523.27 Fuel Oil No. 6 77.4 3.6 40% 0.71 368,963.2 Las Palmas 65.0 1998 291.85 Fuel Oil No. 6 77.4 3.6 30% 0.93 270,957.4 Genor 41.6 1998 134.72 Fuel Oil No.6 77.4 3.6 30% 0.93 125,071.3 Lagotex 25.0 1996 71.76 Fuel Oil No. 6 77.4 3.6 30% 0.93 66,623.1 Sedegua 36.0 1995 94.52 Fuel Oil No. 6 77.4 3.6 30% 0.93 87,755.4 PQPC 110.0 1993 154.50 Fuel Oil No. 6 77.4 3.6 30% 0.93 143,435.8 Generadora Progreso 19.0 1993 53.91 Fuel Oil No. 6 77.4 3.6 30% 0.93 50,052.1
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2007
TABLE A1 EGm,2006 i EF CO2,m,i,y ηm EF EL,m,y Default Energy produced Average emission efficiency Emission factor of CO2 emissions EF calculation Availble Starting 2006 Fuel Type factor of fuel type i Conversion factor factors unit m 2006
MW year (GWh) (t CO2/TJ) TJ/MWh % t CO2/MWh t CO2 Conversion factor from EB 35 repan 12, Input from AMM Inventory Workbook AMM Plant data the International meth tool, annex Calculated Calculated data (IPCC, 2006) System of Units I STEAM TURBINES 1,010.47 San José 128.9 2000 1,010.47 Bituminous Coal 94.6 3.6 39% 0.87 882,375.2 Escuintla Vapor 2 24.0 1977 - Fuel Oil No.6 77.4 3.6 38% 0.74 - Laguna Vapor 2 11.0 1959 - Fuel Oil No.6 77.4 3.6 38% 0.74 - Laguna Vapor 4 11.0 1961 - Fuel Oil No.6 77.4 3.6 38% 0.74 - GAS TURBINES 8.46 Tampa 79.3 1995 6.49 Diesel 74.1 3.6 30% 0.89 5,766.5 GGG STEWART & STEVENSON 23.0 1995 0.97 Diesel 74.1 3.6 30% 0.89 858.5 Escuintla Gas 5 15.0 1985 1.01 Diesel 74.1 3.6 30% 0.89 894.5 Laguna Gas 4 27.0 1989 - Diesel 74.1 3.6 30% 0.89 - Escuintla Gas 3 17.0 1976 - Diesel 74.1 3.6 30% 0.89 - Escuintla Gas 4 * 1976 - Diesel 74.1 3.6 30% 0.89 - Laguna Gas 2 17.0 1978 - Diesel 74.1 3.6 30% 0.89 - Escuintla Gas 2 * 1968 - Diesel 74.1 3.6 30% 0.89 - Laguna Gas 1 8.0 1964 - Diesel 74.1 3.6 30% 0.89 - INTERNAL COMBUSTION MOTORS 2,219.66 Electrogeneración 15.0 2003 68.56 Fuel Oil No.6 77.4 3.6 40% 0.71 48,342.1 Arizona 160.0 2003 847.47 Fuel Oil No.6 77.4 3.6 40% 0.71 597,562.7 Amatex 15.0 2003 25.86 Fuel Oil No.6 77.4 3.6 40% 0.71 18,233.0 La Esperanza 124.0 2000 476.74 Fuel Oil No. 6 77.4 3.6 40% 0.71 336,154.1 Las Palmas 65.0 1998 320.92 Fuel Oil No. 6 77.4 3.6 30% 0.93 297,938.4 Genor 41.6 1998 178.23 Fuel Oil No.6 77.4 3.6 30% 0.93 165,469.8 Lagotex 25.0 1996 99.09 Fuel Oil No. 6 77.4 3.6 30% 0.93 91,990.7 Sedegua 36.0 1995 74.64 Fuel Oil No. 6 77.4 3.6 30% 0.93 69,294.4 PQPC 110.0 1993 77.76 Fuel Oil No. 6 77.4 3.6 30% 0.93 72,194.3 Generadora Progreso 19.0 1993 50.40 Fuel Oil No. 6 77.4 3.6 30% 0.93 46,791.1
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2008
TABLE A1 EGm,2007 i EF CO2,m,i,y ηm EF EL,m,y Average emission Default Energy produced factor of fuel type efficiency Emission factor of EF calculation Availble Starting 2007 Fuel Type i Conversion factor factors unit m CO2 emissions 2007
MW year (GWh) (t CO2/TJ) TJ/MWh % t CO2/MWh t CO2 Inventory Conversion factor from EB 35 repan 12, Input from AMM AMM Plant data Workbook the International meth tool, annex Calculated Calculated data (IPCC, 2006) System of Units I STEAM TURBINES 1,037.52 Arizona Vapor 1 2007 0.09 San José 128.9 2000 1,037.52 Bituminous Coal 94.6 3.6 39% 0.87 905,992.4 Escuintla Vapor 2 24.0 1977 - Fuel Oil No.6 77.4 3.6 38% 0.74 - Laguna Vapor 2 11.0 1959 - Fuel Oil No.6 77.4 3.6 38% 0.74 - Laguna Vapor 4 11.0 1961 - Fuel Oil No.6 77.4 3.6 38% 0.74 - GAS TURBINES 16.41 Tampa 79.3 1995 12.46 Diesel 74.1 3.6 30% 0.89 11,078.3 GGG STEWART & STEVENSON 23.0 1995 1.54 Diesel 74.1 3.6 30% 0.89 1,369.0 Escuintla Gas 5 15.0 1985 1.33 Diesel 74.1 3.6 30% 0.89 1,177.8 Laguna Gas 4 27.0 1989 0.53 Diesel 74.1 3.6 30% 0.89 473.3 Escuintla Gas 3 17.0 1976 - Diesel 74.1 3.6 30% 0.89 - Escuintla Gas 4 * 1976 - Diesel 74.1 3.6 30% 0.89 - Laguna Gas 2 17.0 1978 0.22 Diesel 74.1 3.6 30% 0.89 197.4 Escuintla Gas 2 * 1968 - Diesel 74.1 3.6 30% 0.89 - Laguna Gas 1 8.0 1964 0.32 Diesel 74.1 3.6 30% 0.89 285.3 INTERNAL COMBUSTION MOTORS 2,568.42 GECSA 2007 66.05 Electrogeneración 15.0 2003 60.75 Fuel Oil No.6 77.4 3.6 40% 0.71 42,835.3 Arizona 160.0 2003 954.95 Fuel Oil No.6 77.4 3.6 40% 0.71 673,349.6 Amatex 15.0 2003 53.47 Fuel Oil No.6 77.4 3.6 40% 0.71 37,700.8 La Esperanza 124.0 2000 595.47 Fuel Oil No. 6 77.4 3.6 40% 0.71 419,875.2 Las Palmas 65.0 1998 356.07 Fuel Oil No. 6 77.4 3.6 30% 0.93 330,578.4 Genor 41.6 1998 191.69 Fuel Oil No.6 77.4 3.6 30% 0.93 177,964.6 Lagotex 25.0 1996 80.43 Fuel Oil No. 6 77.4 3.6 30% 0.93 74,670.1 Sidegua 36.0 1995 70.94 Fuel Oil No. 6 77.4 3.6 30% 0.93 65,862.6 PQPC 110.0 1993 204.65 Fuel Oil No. 6 77.4 3.6 30% 0.93 189,997.1 Generadora Progreso 19.0 1993 - Fuel Oil No. 6 77.4 3.6 30% 0.93 -
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Operation Margin Calculation
Table A2 2006 2007 2008 Σ Fuel fired plants MWh 2,486,277 3,238,589 3,622,347 9,347,214 Low cost/must run plants MWh Imports MWh 23,190 8,410 8,120 39,720 2,509,467 3,246,999 3,630,467 EG j,y MWh 9,386,934
1-λ 0.929 0.920 0.969
λ 0.071 0.080 0.031 0.773 EFj,OM, y (t CO2/MWh) 2,633,865 2,027,415 0.192 0.813 0.560 EFk,OM, y (t CO2/MWh)
EFOM-adj, y (t CO2/MWh) 0.7180 0.7481 0.542
EFOM-adj, y 0.0137
EFOM-adj, y 0.7317 Weight 0.2673 0.3459 0.3868 0.0512 0.2813 0.2165 EFOM-adj, y weigthened (t CO2/MWh)
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TABLE A4 A B C D E F G Fraction Starting Fuel Carbon Carbon Emissions Generation Emissions Rate Year Consumption Content Build Margin Oxidised TJ/year tC/TJ tC02/year GWh tCO2/MWh Inventory Inventory See table = ( B * C * See Table See table A1 Workbook Workbook = ( D / E ) A1 D ) * 44/12 A1 (IPCC, 2006) (IPCC, 2006) Option 1. Five most recent plants
Palín II 2005 0.00 0.00 - San Diego 2005 16.39 21.10 1.00 1,268.37 5.33 0.238 Pantaleón II 2005 107.56 21.10 1.00 8,321.38 34.98 0.238 Magdalena II 2005 88.36 21.10 1.00 6,836.06 23.66 0.289 Renace 2004 - 0.00 0.00 - 160.12 - 212.31 0.00 0.00 16,425.81 224.09 0.073 Option 2. Additions represents 20% of the 1386.2 system generation
Palín II 2005 - 0.00 0.00 San Diego 2005 16.39 21.10 1.00 1,268.37 5.33 0.238 Pantaleón II 2005 107.56 21.10 1.00 8,321.38 34.98 0.238 Magdalena II 2005 88.36 21.10 1.00 6,836.06 23.66 0.289 Renace 2004 - 0.00 0.00 - 278.97 - Electrogeneracion 2003 642.34 21.10 1.00 49,695.53 69.53 0.715 Amatex 2003 77.23 21.10 1.00 5,974.75 8.36 0.715 Darsa 2003 18.79 21.10 1.00 1,453.81 3.07 0.474 Arizona 2003 8,682.34 21.10 1.00 671,723.38 1,024.83 0.655 9,633.00 745,273.28 1,448.72 0.514
TABLE A5 units equation or source Estimated operating A tCO /MWh Table A2 0.797 margin 2 emission rate Estimated B build margin tCO2/MWh Table A4 0.514 emission rate Estimated C baseline tCO2/MWh ( = (0.75A + 0.25 B) 0.727 emission rate* PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1.
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Annex 4
MONITORING INFORMATION
MONITORING PLAN
The monitoring plan comprises two parts. The first one refers to the compilation and filling of all the relevant data needed to estimate the emissions reductions by the hydroelectric as specified in the decision 17/CP.7, document FCCC/CP/2001/13Add.2.
The second part presents the sustainable development monitoring plan, which is not a CDM project requirement, but it is a tool that will allow auditing the impact of the CDM project financing on sustainable development.
A. Monitoring of the emissions reductions
A.1 Objective:
The objective of the present plan is to assure the complete, consistent, clear, and accurate monitoring and calculation of the emissions reductions, within the Buenos Aires Wind Farm boundaries, during the crediting period.
A.2 Methodology:
Emission reductions are monitored according to “Consolidated monitoring methodology for zero- emissions grid-connected electricity generation from renewable resources”.
A.3 Boundaries
The boundaries of the project activity will remain constant during the entire crediting period as defined in section B4 of the PDD.
A.4 Parameters
The parameters monitored in order to calculate the emission reductions are the net electricity supplied to the grid and the fuel consumed by back-up generating plants. The monitoring reports includes the following information for each parameter:
Data / Parameter : EGy Data unit: MWh Description: Net electricity supplied by the project activity to the grid Source of data: Project activity site: commercial electricity meter. PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1.
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- Equipment description - Equipment identification Equipment - Location - Calibration reports and certificates For each procedure, the monitoring report describes: - Name of the procedure Monitoring and registration - Description of procedures procedures - Responsible - Monitoring frequency - Data registration 1. Provide information to demonstrate that: - Electricity measurement equipment must observe the AMM Standard of Commercial Measurement System (Standard No. 14)
- Electricity is calibrated by the manufacturer, and how the Administrador del Mercado Mayorista (AMM) Quality control audits the equipment accuracy.
2. Report of how data from main meter is compared and validated against secondary meter and the data registered by the plant operator and data downloaded by AMM.
Data storing Description of how data is stored, hard and electronically.
A.5 Calculation of baseline emissions
Baseline emissions are reported in a table as follow:
Variable according to PDD EGy EFgrid,CM.y BEy Net electricity supplied by the Name of Variable Emissions factor Baseline emissions project activity to the grid
Unit MWh t CO2/MWh t CO2 Definition A B A*B Month 1 Month 2 …. Total
PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1.
CDM – Executive Board
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A.6 Calculation of emission reductions
Emissions reductions are reported in a table as follow:
BEy PEy ERBy Baseline Emissions of the Emission emissions project activity reductions
Month t CO2e t CO2e t CO2e Definition A B A - B Month 1 Month 2 …. Total