Voluntary Carbon Standard Project Description

Transcription

1 Voluntary Carbon Standard Project Description Date of VCS PD: 11 September 2009 Version: 3 Table of Contents 1 Description of Project: VCS Methodology: Monitoring: GHG Emission Reductions: Environmental Impact: Stakeholders comments: Schedule: Ownership:

2 1 Description of Project: 1.1 Project title Mobuya Mini Hydro Power Plant 3 x 1000 kw North Sulawesi, Indonesia. Date: September 11, 2009 Version: Type/Category of the project Mobuya Mini Hydro Power Plant 3 x 1000 kw, North Sulawesi, Indonesia (hereafter the project), developed and owned by PT. Cipta Daya Nusantara (hereafter referred to as the project owner), is a run-of-river mini hydropower project that utilizes 5 m3/s water flow from Poigar River. The project consists of three turbines with a capacity of 1,000 kw each. A total of 21,550,000 1 kwh electricity is exported to the Minahasa grid annually. As the project has an installed capacity totaling 3 MW and is connected to the grid, it can be classified as a small-scale grid connected renewable electricity generation project. Based on the small-scale CDM UNFCCC criteria, one approved GHG program by the VCS Board, the project belongs to: Type 1: Renewable energy projects Category I.D: Grid connected renewable electricity generation According to the Voluntary Carbon Standard, the project falls into the renewable energy category (wind, PV, solar thermal, biomass, liquid biofuels, geothermal, and run-of-river hydro). The project is not a debundled project activity. 1.3 Estimated amount of emission reductions over the crediting period including project size: The project activity generates an average of 11,637 credits per annum from 21,550,000 kwh electricity generated. Based on the VCS Program Guidelines , there are three project groups as follow: Micro projects: under 5,000 tco2-e per year Projects: 5,000 1,000,000 tco2-e per year Mega projects: greater than 1,000,000 tco2-e per year The proposed project activity meets the requirement of the Project group, generating emission reduction credits between 5,000 and 1,000,000 tco2-e per year. Emission reduction estimates over a crediting period of 10 (ten) years from 15 June 2007 until 14 June 2017 is provided in the table below: Calendar Year Vintage Year Annual Agreed Volume June June , June June , June June , June June , June June , June June , June June ,637 1 Electricity generated and exported to the grid based on assumption of 80% load factor (3000 kw x 8760 x 80% = 21,024,000 kwh per annum). However, in the PPA, the electricity generation is 21,550,000 kwh. 2

3 June June , June June , June June ,637 Total estimated reductions(tco2e) 116,370 Total number of crediting years 10 years Annual average of the estimated reductions over the crediting period (tco2e) 11,637 *Based on assumption with 80% load factor, referred to Detail Planning Report. 1.4 A brief description of the project: The project activity comprises a run-of-river hydropower station that will export electricity generated to the Minahasa grid, replacing electricity from fossil-fuel-based power plants connected to the Minahasa grid (which is operated and managed by PT. PLN (Persero) Region Suluttenggo) 2. Ergo, the project activity is reducing greenhouse gas emissions. Basic information about the power station is provided in the following table: Name Mobuya Mini Hydro Power Plant 3x1000 kw North Sulawesi, Indonesia Project Owner PT. Cipta Daya Nusantara Installed Capacity (kw) Water head (m) Technology used 3x Francis- Horizontal Turbine 3 Project Location Mobuya Village, Passi Sub-district, Bolaang Mongondow District, North Sulawesi Province Purpose of the project activity The main purpose of the project activity is to generate electricity through sustainable means using run-of-river hydropower resources, selling the generated electricity to the state-owned electricity company (PT. PLN (Persero)). The project activity will contribute to climate change mitigation efforts and to sustainable development goals of Indonesia. Apart from renewable electricity generation, the project activity has also been conceived for the following purposes: to encourage private companies to invest into the development of hydro power stations in the regions, and to reduce the prevalent regulatory risks for this project through carbon finance scheme Contribution of the project activity to sustainable development Based on sustainable development criteria defined by the government of Indonesia, the project activity specifically contributes to following: Social well-being: The project leads to more development in the region. During construction, the project is expected to generate considerable employment opportunities for the local population. Various kinds of mechanical work generate employment on a regular and permanent basis. Economic well-being: The project activity creates jobs in the local area and promotes gender equality, as represented by the female power plant manager. Large investments in a developing region would not have been made in absence of the project. 2 PT. PLN (Persero) is divided into several regions, one of them is PT. PLN (Persero) Region Suluttenggo (see the official website: 3 See Detail Planning Report; Commissioning certificate from Directorate General Electricity and Renewable Energy dated 21 May

4 The generated electricity is fed into regional grids through the local grid, thereby improving the grid stability and availability of electricity to local consumers (villagers and sub-urban inhabitants). Due to increased grid reliability, new opportunities for industries and economic activities arise with a chance for more local employment and better overall development. The project activity leads to diversification of the national energy supply, which is dominated by conventional fuel based generating units. The project activity contributes to economic sustainability around the plant sites and encourages economic power decentralization. Environmental well-being: The project utilizes hydropower to generate electricity, which otherwise would have been generated through fuel- (most likely fossil-fuel-) based power plants. This way it is contributing to a reduction in specific emissions (emissions of pollutant/unit of energy generated), including GHG emissions. As run-of-river hydropower projects produce no end products in the form of solid waste (ash, etc.), they address the problem of solid waste disposal encountered by most other sources of power. Being a renewable energy source, run-of-river hydro energy used to generate electricity contributes to resource conservation. The project has no noteworthy negative impact on the surrounding environment. Technological well-being: The project promotes local products developed in the region when spare parts replacement is needed to support renewable technology development especially for run-of-river hydropower technology. In view of the above arguments, the project participants consider the project activity as profoundly contributing to the region s sustainable development. 1.5 Project location including geographic and physical information allowing the unique identification and delineation of the specific extent of the project: The project site is located in Mobuya Village, Passi Sub-district, Bolaang Mongondow District, North Sulawesi Province, Indonesia. The project is approximately 130 km distant from Manado, the capital city of North Sulawesi Province. The exact location is N, ,9 E 4. 4 See Environmental Management and Monitoring Plan page II-10 conducted by University of Sam Ratulangi, Manado 4

5 1.6 Duration of the project activity/crediting period: The project start date: 21 May 2007 (when the project started commissioning as referred to the commissioning certificate for all three turbines). The crediting period start date: 15 June 2007 (when the project started its operation and electricity generation). The crediting period: 10 (ten) years from 15 June 2007 until 14 June 2017 with 1x renewable. 1.7 Conditions prior to project initiation: Project is a totally new activity at the site, so no prior condition. The project area is a land that that was owned and utilized as plantations by the local people. The project site are located at the riverbank of Poigar River, which is also utilized by other mini hydro power plants, one of them is the Poigar Mini Hydro Power Plant. 1.8 A description of how the project will achieve GHG emission reductions and/or removal enhancements: The project utilizes run-of-river hydro energy source to generate electricity. Fossil-fuel-generated electricity in the grid is replaced by renewable energy. 1.9 Project technologies, products, services and the expected level of activity: The project is utilizing the Poigar river water flow of 5 m 3 /s for its three 1000 kw horizontal Francis turbines with net heads of 71 m. The project is a run-of-river system that consists of a water weir and intake, settling tank, 2.35 km open artificial trapezium channel, penstock, and a powerhouse. Below is a table to show the main technical parameters of the project: 5

6 Parameters Value Source Installed capacity (kw) 3 x 1000 Detail Planning Report Operating time yearly (hour) 7008 (8760 x 80%) Detail Planning Report Expected annual minimum 21,550,000 PPA electricity supplied to the grid (kwh) Water head (m) 71 Detail Planning Report Design flow (m 3 /s) 3 x 1.67 Detail Planning Report Total loss, include parasitic and 20 Detail Planning Report capacity factor (%) Project lifetime (years) 20 PPA The project is connected to the Minahasa grid (known as system in the Tool to calculate the emission factor for an electricity system ). The project is using state of the art but known technology in electricity generation and transmission. The essential equipment used in the project has to be procured from abroad. Prior to project commissioning the project owner has organized a series of training together with the equipment supplier. The training conducted covered mainly the following topics: management of hydropower generation; operation and maintenance of a hydropower plant; operation and maintenance of turbine, generator, and other equipments. The purpose of the training is to enable the local staff to perform regular operation and maintenance Compliance with relevant local laws and regulations related to the project: The project meets all local laws and regulations by the government of Indonesia. The project activity, in using hydropower to generate electricity, is a voluntary action that has not been imposed by the government of Indonesia. The project has a construction permit issued by the Regent of Bolaang Mongondow Regency; a power purchase agreement (PPA) with PT. PLN Persero (the state-owned electricity company); and an Environmental Management and Monitoring Plan (UKL/UPL) Identification of risks that may substantially affect the project s GHG emission reductions or removal enhancements: The project is already operating normally. There are no identified risks that could affect the removal enhancements of the project, which are shown by construction permits and Environmental Management and Monitoring Plan (EMMP) approval from the responsible authorities Demonstration to confirm that the project was not implemented to create GHG emissions primarily for the purpose of its subsequent removal or destruction. Not applicable, the project was not implemented to create GHG emissions primarily for the purpose of its subsequent removal or destruction Demonstration that the project has not created another form of environmental credit (for example renewable energy certificates). The project activity has not applied to any other form of environmental credits Project rejected under other GHG programs (if applicable): N/A 6

7 1.15 Project proponents roles and responsibilities, including contact information of the project proponent, other project participants: Name of the party involved ((host) indicates a host party) Private and/or public entity (ies) project participants (as applicable) Indonesia (host) PT. Cipta Daya Nusantara No Switzerland South Pole Carbon Asset No Management Ltd. (as the carbon credit buyer) Project proponents contact information as follows: Project owner: Organization: PT. Cipta Daya Nusantara Street/P.O.Box: Jl. W. Z. Yohanes No. 12, Bumi Nyiur Building: City: Manado State/Region: North Sulawesi Postfix/ZIP: Country: Indonesia Telephone: FAX: URL: Represented by: Salutation: Ms. Last Name: Ratela Middle Name: First Name: Jeanete O. Mobile: Direct Fax: Direct Tel: Personal Kindly indicate if the party involved to be considered as project participant (Yes/No) Carbon credit buyer: Organization: South Pole Carbon Asset Management Ltd. Street/P.O.Box: Technoparkstrasse 1 Building: City: Zurich State/Region: Postfix/ZIP: 8005 Country: Switzerland Telephone: FAX: info@southpolecarbon.com URL: Represented by: Salutation: Mr. Last Name: Heuberger Middle Name: First Name: Renat Mobile: Direct Fax: Direct Tel: Personal r.heuberger@southpolecarbon.com 7

8 1.16 Any information relevant for the eligibility of the project and quantification of emission reductions or removal enhancements, including legislative, technical, economic, sectoral, social, environmental, geographic, site-specific and temporal information.): N/A 1.17 List of commercially sensitive information (if applicable): N/A 2 VCS Methodology: 2.1 Title and reference of the VCS methodology applied to the project activity and explanation of methodology choices: The category for the project activity according to Appendix B of the UNFCCC s published simplified procedures for small-scale activities is: Project Type: Project Category: I-Renewable energy projects AMS I.D. Grid connected renewable electricity generation (Version 13, 14 th December 2007, EB 36) The simplified baseline and monitoring methodology AMS I.D., version 13 is applicable. For more information about the methodology, please refer to following website: Justification of the choice of the methodology and why it is applicable to the project activity: Appendix B of the simplified modalities and procedures for small-scale CDM project activities provides indicative simplified baseline and monitoring methodologies for the selected small-scale CDM project activity category. As per this document, the project satisfies the applicability conditions of small-scale CDM projects and AMS I.D., version 13: The project activity is a renewable electricity project (run-of-river mini hydro power plant). The project has an output capacity lower than 15 MW (CMP2 paragraph 28 (a): the project has an installed capacity of 3x1000 kw). The electricity generated is supplied to a grid that is or would have been supplied by at least one fossil-fuel-fired generating unit (the Minahasa grid). 2.3 Identifying GHG sources, sinks and reservoirs for the baseline scenario and for the project: As referred to in Appendix B for small-scale project activities AMS I.D, the project boundary for a small-scale hydropower project that provides electricity to a grid encompasses the physical, geographical site of the renewable generation source (see table below). The baseline includes the emissions related to the electricity produced by the facilities and power plants displaced by this hydropower installation. This involves emissions from displaced fossil-fuel use at power plants connected to the Minahasa grid, which covers Minahasa Sector and Kotamobago Branch, as they are called by PT PLN (Persero) (see table below). B a s e Source Gas Included? Justification/Explanation Minahasa grid CO2 Included According to AMS I.D., only CO2 8

9 Project Activity electricity production Mobuya Mini Hydro Power Plant 3x1000 kw North Sulawesi, Indonesia electricity production emissions from electricity generation should be accounted for. CH4 Excluded According to AMS I.D. N2O Excluded According to AMS I.D. CO2 Excluded According to AMS I.D. 2.4 Description of how the baseline scenario is identified and description of the identified baseline scenario: According to the AMS I.D. version 13 as per point no. 9, baseline emissions are calculated by multiplying the energy generated by the hydroelectric plant (in MWh) by the emission factor of the interconnected grid (in tco2e/mwh) calculated in a transparent and conservative manner using one of the following methods: For all other systems, the baseline is the kwh produced by the renewable generating unit multiplied by an emission coefficient (measured in kg CO2e/kWh) calculated in a transparent and conservative manner as: (a) A combined margin (CM), consisting of the combination of operating margin (OM) and build margin (BM) according to the procedures prescribed in the Tool to calculate the emission factor for an electricity system. OR (b) The weighted average emissions (in kg CO2e/kWh) of the current generation mix. The data of the year in which project generation occurs must be used. We choose option (a). The emission factor established in the EF calculation spreadsheet is tco2e/mwh to calculate emission reductions from the project activity. This factor will remain fixed during the selected crediting period. Key information and data used to determine the combined margin can be found as one of the attached files provided to the DOE. 2.5 Description of how the emissions of GHG by source in baseline scenario are reduced below those that would have occurred in the absence of the project activity (assessment and demonstration of additionality): In addition to using a VCS Program approved methodology; the project proponent shall demonstrate that the project is additional using the following test: Test 1- The Project test: Step 1: Regulatory Surplus There is no mandatory law or regulation that would force the project proponent to develop runof-river hydropower electricity generation. There are no national laws or legislations that require the production of run-of-river hydropower energy or impose the target to private entities to invest in renewable power generation in general. Step 2: Implementation Barriers 9

10 The project shall face one (or more) distinct barrier(s) compared with barriers faced by alternative projects. Investment Barrier Technological Barrier Institutional Barrier The project proponents selected investment and first of its kind barriers for the proposed project, as elaborated below in further details w.r.t Appendix B of the simplified modalities and procedures for small-scale CDM project activities. Investment Barrier The likelihood of the development of this project, as opposed to the continued generation of electricity by the existing generation mix operating in the grid will be determined by comparing the project IRR without VCU financing with the benchmark rates available to a local investor. The most appropriate benchmark rate, as per EB 41 of Guidance on the assessment of investment analysis version 05.2 point no. 11, is the local commercial lending rate. With regard to the project, the commercial lending rate given by one local bank (Bank Negara Indonesia or BNI) in September 2005, at when the project developer got a loan approval of IDR 15,000,000,000 of the total project investment that is IDR 54,056,460,000 is chosen to compare with the IRR calculated of the project. The commercial lending rate given by the BNI is %. This value will be used as a discount factor for this project to refer that if the project has IRR below the commercial lending rate, thus the project is indeed needed of additional revenue stream to cover such loan agreement. Calculation and comparison of financial indicators The table below shows the financial analysis for the project activity with and without VCU financing. As shown, the project IRR is lower than the benchmark rate of return applicable, which is % for investment funds in Indonesia special for the proposed project. This therefore indicates that in comparison with other alternative investments, the project is not financially attractive to a rational investor. With the addition of VCU revenues, the IRR increases to get closer to the benchmark, even though the IRR is still low. At the same time, VCU brings many other attendant benefits to the project, as well as additional income, which make the project more attractive, including international recognition, and a green image and associated publicity for the project developer. Therefore, the project owner is assured that VCU could make the unattractive investment becoming more sensible to be developed. Table: Financial Parameters for Mobuya Mini Hydro Power Plant Financial parameter Unit Value Source/Reference Total investment IDR 54,056,460,000 (with Detail Planning IDR Report 15,000,000,000 loan from BNI) Operating costs IDR/MWh 31,756 Detail Planning Report Annual power generation MWh/year 21,550 PPA Company revenue taxes % Tax regulation Depreciation % 5.00 Tax regulation Discount rate % BNI loan agreement The electricity generation assumed in the Detail Planning Report is using 80% load factor from 3000 kw installed capacity. However, in the PPA, 21,550,000 kwh is the agreed value between PT. PLN (Persero) Region Suluttenggo and PT. CDN that will be used as the electricity assumption within the VCS PD calculation. Table: Summary of Project Financial Analysis for 20 years With VCS (2.5 Euro per VCU) Without VCS 10

11 Net Present Value (IDR) -5,713,218,782-6,808,515,214 IRR 12.07% 11.66% Discount rate 14.25% Sensitivity Analysis The sensitivity analysis uses assumptions that are conservative from the point of view of analyzing additionality, i.e. the best-case conditions for the project IRR are assumed. As referred to the Tool for the demonstration and assessment of additionality, version 05.2, EB 39, the sensitivity analysis must show a realistic assumption for the project and covers a range of +10% and -10%, unless this is not deemed appropriate in the context of the proposed project. It is supposed that the project experiences either: a. the original assumptions in the financial analysis; or b. the revenues increase by 10 % (the electricity tariff was increased by 10 %, or operating hours were increased by 10 %); On the contrary, the reduced electricity tariff and operating hours will be lowering the IRR as from the original assumption. Therefore, the -10% tariff reduction and -10% operating hours will not be taken into account in the sensitivity analysis; or c. the operating costs decrease by 10 %. The decreased operating cost would give a possibility of a higher IRR, while on the opposite, the increased operating cost would decrease IRR that is deemed to be even lower than the original assumption of current financial analysis. Thus, +10% increase of operating cost will not be considered in the sensitivity analysis. The results of assumptions that could give a higher IRR compare to original assumptions are shown in the table below. Table: summary of project sensitivity analysis Scenario % change IRR (%) Original (electricity tariff IDR 420 per kwh and 21,550,000 kwh electricity generation) 11.66% Increase in project revenue (increase in tariff) % 13.18% Increase in project revenue (increase in electricity generation) % 13.18% Reduction in Operational Costs % 11.77% The variation in key parameters of +/- 10% is chosen and considered to be conservative, as the parameters are not expected to vary by more than this amount (and are in fact not expected to vary in favour of the project at all) for the following reasons: 1. Project revenue is unlikely to increase more than 10 %, since the power purchase agreement contract was already signed between PT CDN and PLN for 20 years. In addition to that, one clausal in the PPA has also mentioned that the electricity price negotiation would never be occurred within the PPA contract years; 2. Increasing operation (or reducing maintenance hours) is difficult to accomplish more than few percent given the engineering constraints of a hydro power plant. Besides that, the assumption of 80% load factor (or even more, as stated in the PPA is 21,550,000 kwh) has been an optimum and conservative assumption if it is compared to one of other mini hydro power plants that is also connected to the Minahasa grid and using the same river flow that is Poigar mini hydro power plant. The Poigar mini hydro power plant could only achieved 55% load factor based on statistic compilation as shown in the table below. Poigar mini hydro power plant production trend Year Electricity Installed capacity Available Load factor (to 11

12 production (kwh) (kw) installed capacity (kw) ,821, ,320, ,539, ,738, Source: PT. PLN (Persero) Region Suluttenggo Statistic Data year available installed capacity, %) As can be seen from Poigar mini hydro power plant example, an increase in operating hours (or reducing maintenance hours) will never increase the load factor to more that 80%, the conservative load factor used in the project design and also calculation. Besides that, operational costs are also unlikely to decrease by more than 10 %, and even the expectation is for ongoing costs to continue to rise for keeping the power plant running well as expected. Using these (somewhat unrealistic) assumptions the Best Case IRR (without VCU financing) is still exposed to a series of risks (project, country, technology etc.). These results show that even under very favourable circumstances the project IRR is still below the % threshold rate of return for similar investments in the Indonesia. Therefore we can conclude that neither the Best Case IRR nor the proposed project without VCU is financially attractive. Step 3: Common practice The project is the first-mini hydro power plant constructed and operated by an independent power purchaser (IPP) in Sulawesi Island 6. Therefore, the project is not common practice and faced significant competition with fossil fuel power plants in the region connected to the local grid. 3 Monitoring: 3.1 Title and reference of the VCS methodology (which includes the monitoring requirements) applied to the project activity and explanation of methodology choices: As defined in Appendix B of the Simplified modalities and procedures for small-scale CDM project activities, the proposed project activity applies following project type and category: Type : I-Renewable energy projects Project Category : I.D.-Grid-connected renewable electricity generation (Version 13, 14 December 2007, EB 36) Requirements with respect to technology/measure under AMS I.D. Grid connected renewable electricity generation (Version 13, 14 December 2007, EB 36) are justified as follows: The project activity is a small-scale activity with less than 15 MW; its maximum capacity is used for classification, according to the Simplified modalities and procedures for small-scale CDM project activities. The category comprises of renewable energy, including run-of-river hydropower, which supplies electricity to the connected grid. The project activity generates electricity from run-of-river hydropower and supply to the connected grid. This fact justifies an application of type I.D. for the project. 3.2 Monitoring, including estimation, modelling, measurement or calculation approaches: Purpose of monitoring 5 Please see the spreadsheet of Grid emission calculation for Minahasa Grid. 6 Please see the following link: 12

13 To verify the emission reductions, based on actual data recorded by the PP and also verified by the invoice copy given to the PT. PLN (Persero) Region Suluttenggo. Types of data and information to be reported, including units of measurement - Electricity generated by the run-of hydro (MWh) through daily metering and recording. Origin of the data Electricity generated (MWh) daily recoding by the PP (also verified monthly invoice copy given to PT. PLN (Persero) Region Suluttenggo). Monitoring, including estimation, modelling, measurement or calculation approaches Calculation for monitoring will be made on actual generation data (daily recording) with verification from the invoice copy given to the PT. PLN (Persero) Region Suluttenggo. Monitoring times and periods, considering the needs of intended users Monitoring will be done on a yearly basis for entire crediting period. Monitoring roles and responsibilities Project proponent will be actively involved in collecting the monitoring information such as electricity generation and also calibration process of electricity meter. Operator Plant manager VCS manager Operator will collect, record and submit daily data to the plant manager. The plant manager will compile daily data and provide monthly data report to the VCS manager. The VCS manager then will forward yearly data report of electricity generation, calibration certificate once per 3 years and also monthly invoice to South Pole Carbon Asset Management that will calculate the actual emission reductions per annum from the project activity. In case, any modification or emergencies happened, the VCS manager will report and discuss the situation with South Pole Carbon to make any required actions related to the project. Managing data quality All meters and equipments that measure data will be calibrated on regular basis (generally once per 3 years as proposed by the PT. PLN (Persero) Region Suluttenggo). 3.3 Data and parameters monitored / Selecting relevant GHG sources, sinks and reservoirs for monitoring or estimating GHG emissions and removals: Data and parameters that are available at validation Data / Parameter: CO2 emission factor of the Minahasa Grid Data unit: tco2/mwh Description: CO2 emission factor from the Minahasa Grid Source of data: Calculated based on the statistics data from PLN Value applied Justification of the choice of data or This is estimated ex-ante and is based on PLN data description of measurement methods and procedures actually applied: Any comment: Calculated as weighted sum of the OM and BM emission Data / Parameter: Data unit: Description: Source of data: CO2 Operating Margin emission factor of the Minahasa Grid tco2/mwh Average emission factor that is calculated as indicated in the relevant OM baseline method for 3 recent years (2004, 2005 and 2006) Calculated based on the statistics data from PLN 13

14 Value applied Justification of the choice of data or This is estimated ex-ante and is based on PLN data description of measurement methods and procedures actually applied: Any comment: Calculated as indicated in the relevant OM baseline method Data / Parameter: CO2 Build Margin emission factor of the Minahasa Grid Data unit: tco2/mwh Description: Emission factor that is calculated over recently built power plants defined in the BM baseline methodology Source of data: Calculated based on the statistics data from PLN Value applied Justification of the choice of data or This is estimated ex-ante and is based on PLN data description of measurement methods and procedures actually applied: Any comment: Calculated as Data / Parameter: Diesel technology efficiency Data unit: % Description: Average net energy conversion efficiency of power unit in the Minahasa grid Source of data: Statistic data from PLN (see Emission Factor Calculation sheet) Value applied 33 Justification of the choice of data or This data is taken from publicly available data and not description of measurement methods and direct measurement procedures actually applied: Any comment: Obtained from published website: Data / Parameter: Data unit: Description: Source of data: Value applied Justification of the choice of data or description of measurement methods and procedures actually applied: Any comment: CO2 emission coefficient of diesel tc/gj diesel The coefficient for CO2 emissions for combustion of High Speed Diesel in Indonesia power stations IPCC default value tonnes of tc/tj Considering that there is no actual measurement of emission factor, the default value of IPCC guideline 2006 is used In the absence of actual data, IPCC values are used Data / Parameter: Data unit: Description: Source of data: Electricity generation of each power source/plant MWh/year Electricity generation from each power source/plant of low cost must run power plant Statistic data from PLN (see Emission Factor Calculation sheet) 14

15 Value applied Justification of the choice of data or description of measurement methods and procedures actually applied: Any comment: Total Generation Capacity ( , incl. Must-Run (see Emission factor calculation sheet) The low cost/must run in which contributes to Minahasa Grid comprises of Hydro and Geothermal power plant. Obtained from the latest statistic from PLN Data / Parameter: Data unit: Description: Source of data used: Value applied: Justification of the choice of data or description of measurement methods and procedures actually applied : Any comment: Electricity generation in Minahasa Grid MWh The electricity generation by source j in year y connected to Minahasa Grid State-owned electricity company See Emission Factor calculation Sheet Official released statistic; publicly accessible and reliable data source Data and parameters to be monitored Data / Parameter: Data unit: Description: Source of data: Value of data applied for the purpose of calculating expected emission reduction: Measurement procedures (if any): Description of measurement methods and procedures to be applied: QA/QC procedures to be applied: EGy kwh Net electricity delivered to the grid by the project activity. (EGy = EGexp EGimp) Onsite measurement using Project Proponent-PLN revenue meter (electricity sales invoice) 21,550,000 (as per signed PPA) Use electricity meters Electricity produced will be measured by one main watt-hour meter, which can measure both power delivered to the grid and received from the grid. Therefore net electricity export will be measured. The measurement of electricity generation will be conducted on a continuous basis, where daily total electricity measurement will be available. The measurement results will be summarised transparently in regular monthly production reports. The QA/QC will be conducted through cross checking with sales electricity receipts. Meters will be calibrated according to the Standard Operational Procedures explained in the PPA signed between PT. CDN and PLN (load dispatcher) or other documents, which update or replace this SOP. Data measured by meters will be cross checked by electricity sales receipt. The meter (s) will either: i) be read frequently jointly by the project developer and the grid company ii) be only read by the project developer and data will be double checked with the electricity sales receipts iii) be only read by the grid company Any comment: - Data / Parameter: Data unit: Description: EGexp kwh Electricity delivered to the grid by the project activity. 15

16 Source of data: Value of data applied for the purpose of calculating expected emission reduction: Measurement procedures (if any): Description of measurement methods and procedures to be applied: QA/QC procedures to be applied: Onsite measurement using Project Proponent flow meter 21,550,000 (as per signed PPA) Use electricity meters Electricity exported will be measured by a watt-hour meter, which can measure both power delivered to the grid and received from the grid. The measurement of electricity imported will be conducted on a continuous basis, where daily total electricity measurement will be available. The measurement results will be summarised transparently in regular monthly production reports. Meters will be calibrated according to the Standard Operational Procedures explained in the PPA signed between PT. CDN and PLN (load dispatcher) or other documents, which update or replace this SOP. Any comment: - Data / Parameter: Data unit: Description: Source of data: Value of data applied for the purpose of calculating expected emission reduction: Measurement procedures (if any): Description of measurement methods and procedures to be applied: QA/QC procedures to be applied: EGimp kwh Electricity received from the grid by the project activity. Onsite measurement using Project Proponent flow meter 0 kwh (the number is an assumption used in the exante calculation, which could be different during monitoring process) Use electricity meters Electricity imported will be measured by a watt-hour meter, which can measure both power delivered to the grid and received from the grid. The measurement of electricity imported will be conducted on a continuous basis, where daily total electricity measurement will be available. The measurement results will be summarised transparently in regular monthly production reports. Meters will be calibrated according to the Standard Operational Procedures explained in the PPA signed between PT. CDN and PLN (load dispatcher) or other documents, which update or replace this SOP. Any comment: Description of the monitoring plan The Monitoring Plan for this project has been developed to ensure that from the start, the project is well organised in terms of the collection and archiving of complete and reliable data. 1. Monitoring organisation The organisation of the monitoring team will be established prior to the start of the crediting period. Clear roles and responsibilities will be assigned to all staff involved in the VCS project and the prospect of nominating a VCS Manager will be considered. If appointed, the VCS Manager will have the overall responsibility for the monitoring system on this project. For this project, the VCS Manager will document yearly electricity generated from the power plant to the Minahasa Grid. Operator Plant manager VCS manager 16

17 A formal VCS monitoring procedure will be established relevant to the proposed project. A description of these procedures is provided in the power plant. They include issues such as training, data quality assurance and control, and relevant back-up procedures. The procedures will be agreed and signed off by the PT Cipta Daya Nusantara and South Pole Carbon Asset Management Ltd.. The VCS Manager and plant manager will be responsible for ensuring that the procedures are followed on site and for continuously improving the procedures to ensure a reliable monitoring system is established. 2. Monitoring equipment and installation Given the emission factor is calculated ex-ante, and referring to the Monitoring Methodology AMS I.D. version 13, the only data to be monitored is electricity supplied to the grid by the project. Metering of Electricity Supplied to the Grid (Revenue Meter) The location of the main electricity meter for establishing the electricity delivered to the grid is already specified in the Power Purchase Agreement (PPA) between the project developer and the grid operator prior to the start of operation of the project. This electricity meter will be the revenue meter that measures the quantity of electricity that the project will be generating. As this meter provides the main VCS measurement, it will be a key part of the verification process. This meter will be installed at the nearest sub-station. Electricity meters should meet the relevant standards acceptable to the grid company at the time of installation. Before the installation of the meters, it should be calibrated by government agency or other accredited institution and it will be re-calibrated every 3 years. The meters will be installed by either the project developer or the grid company. Records of the meter will recorded as follows: Meter # Serial no. Model and factory Date of calibration Fuji Electric/FF23HTI 4 April Fuji Electric/FF23HTI 4 April Fuji Electric/FF23HTI 4 April 2007 and retained by the plant manager in the power plant control room. Quality Assurance The revenue meter is owned and installed by the grid company. The PPA with the grid company specifies the QA procedure for measurement and calibration to ensure the measurement accuracy of the main meter. Periodic checks should be conducted as described in the PPA. For further details on the VCS data quality control and quality assurance see the VCS Monitoring System Procedures. 3. Data recording procedure The process for collecting the electricity meter data will be detailed in a procedure, which is summarised below: Metering Electricity Delivered to the Grid (the revenue meter) a) At the first day of each month the project developer and the grid company will take a meter reading and record this figure in the operational data record. b) The reading of this revenue meter will be summarized in the Official Report, which will specify: 1. the agreed amount of electricity supplied to the grid 2. the amount of discrepancy between agreed and actual supply 3. the amount of electricity received from the grid These three values will be recorded on the invoice from PT. CDN to the PT. PLN (Persero) Suluttenggo region. The net electricity generation will be summarized from total electricity supplied to the grid subtracted by the total electricity received from the grid. 17

18 4. Data and records management At the end of each month the monitoring data needs to be filed electronically. The electronic files need to have CD back-up and/or print-out. The project developer needs to keep electricity sales and purchase invoices. All written documentation such as maps, drawings, the Environmental Management and Monitoring Plan (EMMP) and the Detail Planning Report, should be stored and should be available to the verifier so that the reliability of the information may be checked. The document management system will be developed as part of an applicable procedure. All the data shall be kept until two years after the end of credit period. For details of the operational and management structure used for the monitoring of the project activity, please see VCS Monitoring System Procedures. This section details the steps taken to monitor on a regular basis the GHG emissions reductions from the Mobuya Mini Hydro Power Plant 3x1000 kw North Sulawesi in Indonesia. The VCS Monitoring Procedures for this project has been developed to ensure that from the start, the project is well organised in terms of the collection and archiving of complete and reliable data. 4 GHG Emission Reductions: 4.1 Explanation of methodological choice: Combined margin CO2 emission factor for grid connected power generation in year y calculated using the latest version of the Tool to calculate the emission factor for an electric system. According to this tool, the following steps are applied: Step 1. Identify the relevant electric power system Step 2. Select an operating margin (OM) method Step 3. Calculate the operating margin emission factor according to the selected method Step 4. Identify the cohort power units to be included in the build margin (BM) Step 5. Calculate the build margin emission factor Step 6. Calculate the combined margin (CM) emission factor Step 1. Identify the relevant electric power system The spatial extent of the proposed project boundary includes the project site and all power plants connected physically to the electricity system that the VCS project power plant is connected to. The project is located in North Sulawesi Province, Indonesia. The North Sulawesi Province is covered by Minahasa grid, according to PT PLN (Persero) Region Suluttenggo. Thus the relevant electric power system is Minahasa Grid. According to PLN s actual grid structure, Minahasa grid covers Minahasa Sector and Kotamobago Branch as they are called by PT PLN (Persero). Currently, the grid mix is composed of diesel power plants fuelled by High Speed Diesel (HSD), hydro, and geothermal power plants. The baseline emission factor (EFy) is calculated as the simple average of the operating margin emission factor (EFOM,y) and the build margin emission factor (EFBM,y) due the data availability. In accordance with AMS I.D., the baseline emission factor can be calculated with the following steps described below. Step 2. Select an operating margin (OM) method The calculation of the operating margin emission factor (EFOM,y) is based on one of the following methods: (a) Simple OM, or (b) Simple adjusted OM, or (c) Dispatch data analysis OM, or (d) Average OM. From 2003 to 2006 among the total electricity generation of Minahasa grid that the project is connected into, the amount of low-cost/must-run resources accounts for 52%, 62%, 53% and 54% respectively with an average of 55.6%; all more than 50%. Therefore method (d), Average OM, is adopted to calculate the operating margin emission factor of Minahasa Grid. 18

19 Besides that, there are other reasons to select Average OM as a method to calculate the operating margin emission factor of Minahasa Grid as follows: There is not a half hourly MWh data sheet for individual power plant at Statistics data. The data for the Dispatch Data Analysis Emission Factor is not available to public. In addition to that, it is also difficult to determine λ in simple adjusted OM because of difficulty in determining total annual generation from low cost must run resources. Total annual electricity generation from the low cost must run resources, which includes hydro and geothermal constitutes more than 50% of the total grid generation in Minahasa Grid. Step 3. Calculate the operating margin emission factor according to the selected method The Average OM emission factor (EFOM,average) is calculated as the generation-weighted average emissions per electricity unit (tco2e/mwh) of all generating sources serving the Grid, including low operating cost and must run power plants: Where: Step 4. Identify the cohort of power units to be included in the build margin The Project Developer chooses to use Option 1 to calculate Build Margin Emission Factor (EFBM,y), which is based on a sample group m that consists of either one of the followings whichever comprises the larger annual generation: a. five power plants that have been built most recently, or b. power plant capacity additions that comprises 20% of the system generation that have been built most recently Option 1. Calculate the Build Margin emission factor EFBM,y ex-ante based on the most recent information available on plants already built for sample m. The sample group m consists of either the five power plants that have been built most recently or the power plant capacity additions in the electricity system that comprise 20% of the system generation (in MWh) and that have been built most recently. It is required to select from those two options that sample group that comprises the larger annual generation. Option 2. For the first crediting period, the Build Margin emission factor EFBM,y must be updated annually ex-post for the year in which actual project generation and associated emissions reductions occur. For subsequent crediting periods, EFBM,y should be calculated ex-ante, as described in option 1. The sample group m consists of either five power plants that have been most recently built or the power plant capacity additions in the electricity system that comprise 20% of the system generation (in MWh) and that have been most recently built-project developer should use from these two options that sample group that comprises the larger annual generation. Among the two options available for calculating the build margin, the first option is selected i.e. calculate the build margin emission factor ex-ante based on the most recent information available on plants already built for sample group m at the time VCS PD submission. 19

20 Step 5. Calculate the build margin emission factor The Build Margin emission factor is calculated ex-ante based on the generation-weighted average emission factor (tco2/mwh) of a sample of power plants m, as follows: Where: Step 6. Calculate the combined emission factor: The combined emission factor is calculated as follow: EF y = w OM EF OM,y + w BM EF BM,y where: EFOM,y = Operating margin CO2 emission factor in year y (tco2e/mwh) EFBM,y = Build margin CO2 emission factor in year y (tco2e/mwh) wom = Weighting of operation margin emission factor (%) wbm = Weighting of build margin emission factor (%) Leakage Emissions According to AMS I-D, the leakage of the proposed project is not considered. No leakage is expected. L y = 0 Baseline Emissions BE y = ( EG y EG baseline ) EF CM,y where: BEy EGy EGbaseline EFCM,y Baseline emissions in year y (tco2e/year) Electricity supplied by the project activity to the grid (MWh) Baseline electricity supplied to the grid in the case of modified or retrofit facilities (MWh)(for new power plants, this value is taken as zero) Combined Margin CO2 emission factor for grid connected power generation in 20

21 year y calculated using the latest version of the Tool to calculate the emission factor for an electricity system Mobuya 3x1000 kw Mini Hydro Power Plant is not a modified, or retrofit facility nor an additional power unit at an existing grid-connected renewable power plant. Mobuya Mini Hydro is a new grid connected renewable power plant. Therefore EGbaseline is zero: BE y = EG y EF CM,y Emission Reductions Emission reduction calculations are as follows: ER y = BE y PE y L y where: ERy PEy BEy Ly Emission reduction in year y (tco2e/year) Project emissions in year y (tco2e/year) Baseline emissions in year y (tco2e/year) Leakage emissions in year y (tco2e/year) 4.2 Quantifying GHG emissions and/or removals for the baseline scenario: Step 1. Identify the relevant electric power system The spatial extent of the proposed project boundary includes the project site and all power plants connected physically to the electricity system that the VCS project power plant is connected to. The project is located in North Sulawesi Province, Indonesia. The North Sulawesi Province is covered by Minahasa grid, according to PT PLN (Persero) Region Suluttenggo. Thus the relevant electric power system is Minahasa Grid. According to PLN s actual grid structure, Minahasa grid covers Minahasa Sector and Kotamobago Branch as they are called by PT PLN (Persero). Currently, the grid mix is composed of diesel power plants fuelled by High Speed Diesel (HSD), hydro, and geothermal power plants. The baseline emission factor (EFy) is calculated as the simple average of the operating margin emission factor (EFOM,y) and the build margin emission factor (EFBM,y) due the data availability. In accordance with AMS I.D., the baseline emission factor can be calculated with the following steps described below. Step 2. Select an operating margin (OM) method From 2003 to 2006 among the total electricity generation of Minahasa grid that the project is connected into, the amount of low-cost/must-run resources accounts for 52%, 62%, 53% and 54% respectively with an average of 55.6%; all more than 50%. Therefore method (d), Average OM, is adopted to calculate the operating margin emission factor of Minahasa Grid. Besides that, there are other reasons to select Average OM as a method to calculate the operating margin emission factor of Minahasa Grid as follows: There is not a half hourly MWh data sheet for individual power plant at Statistics data. The data for the Dispatch Data Analysis Emission Factor is not available to public. In addition to that, it is also difficult to determine λ in simple adjusted OM because of difficulty in determining total annual generation from low cost must run resources. Total annual electricity generation from the low cost must run resources, which includes hydro and geothermal constitutes more than 50% of the total grid generation in Minahasa Grid. Type of Power Plant Fuel type Avrg of 4 recent years Hydro 154, , , , ,960 21