MEV Mechatronics, Electrical Power, and Vehicular Technology 04 (2013) 89-98 Mechatronics, Electrical Power, and Vehicular Technology e-ISSN:2088-6985 p-ISSN: 2087-3379 Accreditation Number: 432/Akred-LIPI/P2MI-LIPI/04/2012 www.mevjournal.com © 2013 RCEPM - LIPI All rights reserved doi: 10.14203/j.mev.2013.v4.89-98 ECONOMIC ANALYSIS OF CIKASO MINI HYDRO POWER PLANT AS A CDM PROJECT FOR INCREASING IRR Irhan Febijanto * Centre for Technology of Energy Resources Development, Deputy for Technology of Informatic, Energy and Mineral- BPPT, Cluster 5 of Energy Building, Puspiptek Serpong, Tangerang Selatan 15314 Received 18 August 2013; received in revised form 31 October 2013; accepted 31 October 2013 Published online 24 December 2013 Abstract Renewable energy fueled power generations are few developed by private sector in Indonesia. High-cost investment and low electricity selling price to PT PLN as a single buyer is main barriers for private sector to involve in the development of renewable energy fueled power generations. In this project, the economic feasibility of Mini Hydro Power Plant of Cikaso with capacity of 5.3 MW, located at Sukabumi Regency, West Java province was assessed. This project utilized revenue generated from carbon market to increase the economic feasibility. Procedure to register the project to United Nation for Climate Change Convention (UNFCCC) as a Clean Development Mechanism project was explained in detail. Approved Consolidation Methodology (ACM) 0002 Version 12.3.0 was used to calculate grid emission factor in Jawa-Bali-Madura the grid electricity system. It was calculated that the grid emission factor is 0.833 (t-CO2/MWh), and the carbon emission reduction generated for this project is 21,982 ton/year. From the analysis result, it can be proven that the additional revenue from carbon credit could increase the project IRR from 10.28% to 13.52%. Key words: mini hydro power plant, Clean Development Mechanism, emission factor, IRR. I. INTRODUCTION A. Background Renewable energy potential in Indonesia is quite large. Hydro energy potential in Indonesia is around 75 GW scattered over islands in Indonesia. Until now, only 4000 kW from the potential has been utilized as a power plant [1]. The utilization of mini hydro (over than 1 MW), micro hydro (10 kW – 1 MW) and pico hydro (below 10 kW) is suitable for remote areas and the area where PT Perusahaan Listrik Negara (hereinafter referred as to ”PLN”) Persero’s electric grid is not yet built. PLN is the state- owned electric power company, which has a role as a single buyer in the electricity business in Indonesia [2]. Indonesia government has targeted ratio of renewable energy to be 2.5% from all energy consumption in 2025. Regarding Green House Gas (hereinafter referred as to ”GHG”) Reduction, Indonesia’s government has planned to reduce 26% of GHGs in 2020 [3]. Despite policy and target for supporting renewable energy development have been implemented. Investors of renewable energy power plants still get a constrains on economic problems within the project. Unlike other countries, although the incentive for supporting renewable energy development has been implemented, however, the benefit still not be felt by investors. The incentive for renewable energy regarding electricity tariff for selling to PLN was determined by Regulation of Ministry of Energy and Mineral Resources in the year of 2002, 2006, and 2009 [4, 5, 6]. Despite the electricity tariff determined in 2009 relative closes to the economic price of the renewable energy project. However, it is not applicable to a hydro power plant project. Renewable energy based power plant is not economic. It is one reason why private sector is not interested to involve in it an investment in * Corresponding Author.Tel: (021) 75791355 E-mail: irhan.febijanto@gmail.com http://dx.doi.org/10.14203/j.mev.2013.v4.89-98 I. Febijanto / Mechatronics, Electrical Power, and Vehicular Technology 04 (2013) 89-98 90 Indonesia. Development of the hydro power plants in remote areas needs high investment cost. Besides that the electricity selling price must compete with the electricity selling price of fossil fuel based power plant that gets a subsidy. This is another reason, why renewable energy based power plant is not a lot of built in Indonesia [7]. Clean Development Mechanism (hereinafter referred as to ”CDM”) is one of the mechanism of Kyoto Protocol as an attempt to reduce Green House Gasses [8] (hereinafter referred to as ”GHG”) such gas of CO2, N2O, CH4, and so on. The reduction emission amount refers to the GHG amount generated by every country during a year of 1990. CDM has been implemented throughout the world since 1997, however, the implementation number in Indonesia is less compared to other countries in Asia such as India and China. Ratification of CDM by Indonesian government has been done in 2004, signed by the President of Republic of Indonesia. Through CDM, developed countries (member of ANNEX I) collaborate with these countries to reduce GHGs emission. The benefit of CDM program for developing countries includes: (1) flow of the foreign fund which could help financial of a domestic project; (2) participation of foreign investors for the project which could minimize the risk to local developers; (3) possibility of transfer technology that could help domestic technology development in domestic; (4) loan rate from a foreign bank usually that has a lower rate compared to domestic bank rate. Among the benefits of CDM project above, lower bank loan rate is the most interesting factor for the local developers. For developed countries, CDM is the mechanism for reducing GHG with low cost compared to develop the project activity in their country. CDM itself has procedures determined by United Frameworks for Convention Climate Change (hereinafter referred as to”UNFCCC”). The procedures should be conducted in order for approved officially by UNFCCC as an entity that provides a certificate for CDM project. Each step conducted in the CDM procedures may need a time more than one year. Basically, all procedures implemented on the project should be clarified whether the project can reduce GHG emission exactly and in line with the determined methodology. One of the conditions that a project can be implemented as CDM project, if the project economic can be increased using additional revenue from selling carbon credit. Project economic is a value of Internal Rate Return (hereinafter referred as to ”IRR”). CDM is one of the mechanisms that can reduce unfeasible economic factors of the renewable power generation project. The renewable power generation is a project than can reduce carbon emission generated from fossil- fuel power generation plant connected by the grid electricity system in a certain area. Revenue from selling carbon credit can be extra revenue, and usually for hydro power plant the additional revenue increases IRR value around 1-2% more, and also grosses revenue around 10-20%. PT Bumiloka Cikaso Energi has conducted the investigation of hydro power potential and found the hydro potential in Curug Luhur water fall in Cikaso River, in West Java Province. The investigation result concluded that the river in that area has a potential to generate electric power. This project utilizes potential energy generated from height differences between Cikaso River and Curug Luhur (Luhur Waterfall) (see Figure 1). After reaching the optimum head, the flow is returned to the Cikaso River from the river bank having height differences of 40 m with the Cikaso River. Using penstock the water flow is returned to the river through turbine. The potential energy is converted to mechanical energy by three units of turbines, and then it is converted to the electric energy by three units of generators. Table 1 shows the specification of Cikaso Small Scale Hydro Power Plant (hereinafter referred to as ”SSHPP”). The lowest of turbine capacity of 0.8 MW is used especially in the dry season when the water flow decrease drastically. During the rainy season, all of three turbines can be operated at full capacity of 5.3 MW. Rocky condition of the site leads to high investment cost, especially the cost for developing water channel toward to turbine became several times higher compared to the normal condition. Based on Feasibility Study Figure 1. Site condition I. Febijanto / Mechatronics, Electrical Power, and Vehicular Technology 04 (2013) 89-98 91 Report that has been completed in 2009, it can be concluded that this project has IRR value of 10.28%. It is lower than a benchmark that determined based on the lowest rate of Working Capital rate of 12.22% issued by Bank of Indonesia in 2009. The project investment is Rp 122.2 billion funded by 100% owner equity. In order to increase the feasibility level to the project, it is needed to add additional revenue through CDM mechanism for this project. For this purpose, this project activity would be submitted as CDM project and it was planned to be registered in UNFCCC. Certification of this project activity can be sold, and it can generate additional revenue besides the main revenue from selling electricity to PLN. B. Purpose This paper describes the grid emission factors (hereinafter referred as to ”EF”) calculation for Jawa-Bali-Madura grid electricity system (hereinafter referred as to ”JAMALI system”). Using the EF, the GHG reduction generated from this project activity can be calculated annually. The economy of Cikaso Small scale Hydro Power Plant (hereinafter referred as to ”SSHPP”) as the CDM project is calculated by considering the additional revenue from selling credit carbon. The economic condition with and without the additional revenue are compared. The economic feasibility of the project is compared using the conservative benchmark at that time. II. METHODOLOGY A. Green House Gas Calculation Grid EF in this project activity is calculated using methodology determined by UNFCCC. Two methodologies are category of I-D:”grid connected renewable electricity generation” [8], ver. 16 and ACM (Approved Consolidation Methodology) 0002 version 12.3.0, “Consolidated methodology for grid-connected electricity generation from renewable sources” [9]. Using both methodologies, the electricity amount exported to the grid is converted to the emission reduction amount, and then based on the carbon market price, the additional revenue is calculated. Project boundary is determined based on the methodology as illustrated in Figure 2 [8]. This figure indicates that the emission reduction activity is limited to the activities related to the Cikaso SSHPP only. In this project activity, small part of generated electricity is utilized for auxiliary equipments and the remaining is exported to the grid owned by PLN of West Java region. The difference between both electricity amounts is net electricity that used in the in the emission reduction calculation. The data used during the determination of EF is all electricity generated by all power plants connected by the JAMALI system and all fuel consumption used in the all power plant during 2001-2005 [10-15]. Based on ACM 0002 [9], EF value is calculated by average value of the latest three years of data used during the determination of EF, 2003-2005 [12-15]. JAMALI system is the interconnection electricity system in Jawa, Madura and Bali Island. Based on AMS-I.D [8], Baseline Emission, BEy, is obtained by multiplying net of electricity, EGy, by the grid emission factor within the system, EFy. Equation of BE is indicated in Equation (1). 𝐵𝐵𝐸𝐸𝑦𝑦 = 𝐸𝐸𝐺𝐺𝑦𝑦 𝑥𝑥 𝐸𝐸𝐹𝐹𝑦𝑦 (1) where BEy is baseline emission (tCO2 e) in year y, EGy is quantity of net electricity generation that is produced and fed through the system as a result of the implementation of the CDM project Table 1. Cikaso SSHPP specification Item Unit Value Installed total capacity MW 5.3 Installed capacity each unit MW 2 x 2.25 1 x 0.8 Average of exported energy to the grid annually MWh 26,390 Capacity factor % 58 Head m 40 Water flow m3/s 16.5 Unit number - 3 Turbine type - Horizontal Francis Figure 2. Project boundary Project Boundary Electricity Stream Electricity to JAMALI grid Electricity to end-user Cikaso SSHPP Auxiliary Consumption I. Febijanto / Mechatronics, Electrical Power, and Vehicular Technology 04 (2013) 89-98 92 activity in the year y, and EFy is Emision factor (tCO2 e). Prior BEy calculation, parameters used in the steps below should be determined [16]. 1) Step 1; Determination of Operating Margin Emission Factor Simple Operating (OM) is selected for the emission factor calculation with the reason as follows. • Dispatch data analysis emission factor is unable to be implemented, because required data cannot be published • Number of plants which includes the category of “Low-Cost and Must-Run/LCMR” power generation plan is below of 50% compared to total of power generations connected to JAMALI system during five years (2005-2009). In this case, numbers of LCMR power plants are five units of power plant in 2005 and 2006, six units of power plant in 2007 and 2008, and seven units of power plant in 2009. Calculation of simple operating margin (EFOM ,y) uses Equation (2) as follows. 𝐸𝐸𝐹𝐹𝑂𝑂𝑂𝑂,𝑎𝑎𝑣𝑣𝑣𝑣𝑣𝑣𝑎𝑎𝑣𝑣𝑣𝑣 ,𝑦𝑦 � 𝑡𝑡𝑡𝑡𝑂𝑂2 𝑂𝑂𝑀𝑀ℎ � = ∑ (𝐸𝐸𝐺𝐺𝑚𝑚 ,𝑦𝑦 𝑥𝑥 𝐸𝐸𝐹𝐹𝐸𝐸𝐸𝐸 ,𝑚𝑚 ,𝑦𝑦 )𝑚𝑚 ∑ 𝐸𝐸𝐺𝐺𝑚𝑚 ,𝑦𝑦𝑚𝑚 (2) where EGm,y, is net quantity of electricity generated and delivered to the grid by power unit m in the year y (MWh), EFEL,m,yis CO2 emission factor of power unit m in the year y (tCO2/MWh), m is power unit included in the operated margin, and y is most recent historical years for which power generation data is available. 2) Step 2; Calculation of Build Margin Emission Factor Build Margin Emission Factor (EFBM,y) calculation indicates an amount of CO2 reductions in the absence of fossil fuel based power plant or on the delay to the development. In the EFBM,y, calculation, the most recently developed a set of power plant having the highest electricity production annually is selected according to the following procedures. • The set of five power units that have been built most recently, or • The set of power capacity additions to the electricity system that comprise 20% of the system generation (in MWh) and that have been built most recently. The set of power units that comprises the larger annual generation is selected, and then Build Margin Emission Factor is calculated using the following Equation (3). 𝐸𝐸𝐹𝐹𝐵𝐵𝑂𝑂,𝑦𝑦 � 𝑡𝑡𝑡𝑡𝑂𝑂2 𝑂𝑂𝑀𝑀ℎ � = ∑ 𝐹𝐹𝑖𝑖,𝑚𝑚 ,𝑦𝑦𝑖𝑖,𝑚𝑚 ∙ 𝑡𝑡𝑂𝑂𝐸𝐸𝐹𝐹𝑖𝑖,𝑚𝑚 ∑ 𝐺𝐺𝐸𝐸𝐺𝐺𝑚𝑚 ,𝑦𝑦𝑚𝑚 (3) where Fi,m,y, COEFi,m and GENm,ycan be analogous as the same parameters which are used throughout the operating margin emission factor calculation for a set of power units, m. 3) Step 3; Calculation of Baseline Emission Factor Combined Margin Emission Factor (EFy) is using Equation (4). 𝐸𝐸𝐹𝐹𝑦𝑦 = 𝑤𝑤𝑂𝑂𝑂𝑂 𝑥𝑥 𝐸𝐸𝐹𝐹𝑂𝑂𝑂𝑂,𝑦𝑦 + 𝑤𝑤𝐵𝐵𝑂𝑂 𝑥𝑥 𝐸𝐸𝐹𝐹𝐵𝐵𝑂𝑂,𝑦𝑦 (4) where the ratio for wOM and wBM, is 50% respectively (wOM= wBM= 0,5). 4) Step 4. Calculation of Baseline Emission Baseline emission (BEy) is calculated using Equation (5): 𝐵𝐵𝐸𝐸𝑦𝑦 = 𝐸𝐸𝐺𝐺𝑦𝑦 𝑥𝑥 𝐸𝐸𝐹𝐹𝑦𝑦 (5) Where EGy is quantity of net electricity generation and EFy is Emision factor. 5) Step 5. Calculation of Emission Reduction Calculation of Emission Reduction (ERy) is using Equation (6): 𝐸𝐸𝐸𝐸𝑦𝑦 = 𝐵𝐵𝐸𝐸𝑦𝑦 − 𝑃𝑃𝐸𝐸𝑦𝑦 − 𝐸𝐸𝑦𝑦 (6) This project activity is a renewable energy based power generation. Therefore, there is no leakage, Ly=0, and Project Emission, PEy=0. B. Economic Analysis The aim to submit the project activity as CDM project is to increase the economic feasibility of the project. The Internal Rate Return (hereinafter referred as to ”IRR”) is used as an economic parameter. The value is lower than the selected benchmark. The lowest bank loan rate over the year of 2009 is taken as the benchmark. The feasibility study was completed in 2009. Sensitivity analysis is calculated using ±10% of change of the following parameters, • Investment cost • Electricity selling prive • General administration and O&M cost The change of ±10% is considered can be represented the changes due to inflation, increase over the prices, change of water debit and other parameters that able to change parameter of (i) investment cost, (ii) selling electricity price and (iii) generation administration cost and O&M cost. The IRR project is re-calculated using the additional revenue generated from selling carbon credit and then the economic feasibility of the project is re-analyzed. I. Febijanto / Mechatronics, Electrical Power, and Vehicular Technology 04 (2013) 89-98 93 III. RESULTS AND DISCUSSIONS A. Green Houses Gasses Emission Green houses gasses emitted from power generation plant activity is Carbon Dioxide (hereinafter referred as to ”CO2”), mainly. The amount of the GHG in JAMALI system rises year by year along with the increase of the coal- fired power plant number as a result of implementation of the Crash Program I. The increase of CO2 is shown in Figure 3. Figure 3 indicates that CO2 rose sharply in 2006. The increase is caused by Cilacap and Tanjung Jati B coal-fired power plants started to operate in that year. Even, there is no new power plant operated. The consumption of coal increased gradually that resulted CO2 emissions increased, in the following years. According to the methodology [8], emission factor shall be calculated using the average of the last three years of 2007, 2008 and 2009. B. Calculation of Emission Factor EF of JAMALI system is calculated using Equations (1), (2) and (3). Coefficient Emission calculation (COEF) of CO2 for each fuel is shown in Table 2. The total amount of generated electricity within five years in the system is indicated in Table 3. Table 4 shows the ratio number between Low Cost Must Run (hereinafter referred as to ”LCMR”) [16] power plants and total power plant connected with the system. In the table, it is indicated that within five years (2001-2005) consecutive, the ratio of LCMR power plant is lower than 50%. Therefore, according to the tool, the calculation of EFOM shall use a simple OM [16]. Table 5 shows the loss generated from own consumption and generated from sub stations. The lost data used is only for 2005 and 2006, because in the following years, a net electricity production of each power plant was published. The net electricity production is an amount of Figure 3. CO2 Emitted from coal fired power plant in JAMALI system during 2004-2010 [17] Table 2. Fuel specification Fuel Type (A) (B) ( C) (D) (E) (F) (G) Calorie Value Carbon Content Standard Oxidized Carbon Factor Standard Carbon Emissin, CO2 Specific Gravity Emission CO2 (A)x(B)x(C) (D) x 44/12 (E) x (F) TJ/kt fuel (tC/TJ) - tC/kt fuel tCO2/kt fuel kt/k l tCO2/kl fuel Sources Pertamina MEM IPCC IPCC IPCC - - - MFO 41.02 21.1 1 865.50 3,173.51 0.00099 3.142 HSD 42.73 20.2 1 863.12 3,164.77 0.000845 2.674 Coal 24.03 26.20 1 629.61 2,308.56 Natural Gas 48.00 15.30 1 734.40 2,692.80 Note. : HSD: High Diesel Speed, MFO: Marine Fuel Oil, IPCC: Intergovernmental Panel on Climate Change; PERTAMINA: Perusahaan Pertambangan Minyak dan Gas Bumi Negara/State-Owned Oil Company of Indonesia, kt fuel: kilo tonne fuel; tC: tonne carbon, TJ: Terra Joule, kl fuel : kilo litre fuel I. Febijanto / Mechatronics, Electrical Power, and Vehicular Technology 04 (2013) 89-98 94 electricity generated deducted by the loss generated from own consumption and generated from sub stations. Fuel consumption of each power plant during five years, 2005-2009 is shown in Table 6. Amount of GHG emitted from each kind of fuel is shown in Table 7. Table 8 shows EFsimpleOM derived from the amount of CO2 emission and total amount of electricity generated during the last three years, 2007, 2008, and 2009. The value of EFsimpleOM was calculated using Equation (4), and the result is 0.9583 (tCO2/MWh). Table 3. Electricity generated in JAMALI system based on the fuel type (MWh nett) Source of plant Operation year 2005 2006 2007 2008 2009 fuel GWh Hydro 7,023 5,309 5,930 6,251 6,635 Diesel Oil 128 101 87 173 121 Gas Turbine Gas 2,603 2,038 2,126 3,073 4,688 Oil 2,547 2,087 1,958 2,191 3,275 Geothermal 6,185 6,183 6,672 7,337 8,188 Steam Coal 45,477 51,826 57,206 54,140 56,965 Gas 646 669 941 690 563 Oil 6,673 7,171 7,685 8,274 7,301 Combined Cycle Gas 16,559 6,193 17,929 18,953 20,301 Oil 8,980 8,444 7,192 10,505 7,527 Total Net Production 96,821 100,021 107,726 111,586 115,564 Tabel 4. Ratio of low cost and must run power of power plant in the last 5 years (2005 - 2009) Item Units 2005 2006 2007 2008 2009 Total Generation Net GWh (net) 83,436 88,351 95,124 97,999 100,741 Low Cost and Must-run generation GWh (net) 13,385 11,670 12,603 13,588 14,823 Low Cost and Must-Run Generation/ Total Generation % 16% 13% 13% 14% 15% Table 5. Lost ratio Year 2005 2006 Average losses in Java-Bali system due to own consumption 3.94% 4.21% Table 6. Fuel consumption in the grid during 2005-2009 Fuel Type unit 2005 2006 2007 2008 2009 HSD kilo litre 4,406,883 3,623,332 3,498,197 4,031,017 2,781,649 MFO kilo litre 1,944,142 2,054,365 2,225,317 2,374,577 2,150,386 IDO kilo litre 4,074 2,343 2,306 4,401 - Gas MMBTU 136,744,924 141,147,996 145,991,700 167,844,288 219,008,065 Coal ton 24,524,261 26,860,205 29,584,714 28,353,988 29,409,721 Table 7. CO2 emission in JAMALI grid system during 2005-2009 Year 2005 2006 2007 2008 2009 Fuel type t-CO2 HSD 11,785,015 9,689,620 9,354,980 10,779,863 7,438,768 MFO 6,108,049 6,454,344 6,991,436 7,460,377 6,756,020 IDO 11,142 6,408 6,307 12,037 - Gas 8,093,881 8,354,497 8,641,195 9,934,641 63,006 Coal 6,615,701 62,008,365 68,298,053 65,456,849 67,524,209 TOTAL 82,613,788 6,513,234 93,291,971 93,643,767 94,682,002 I. Febijanto / Mechatronics, Electrical Power, and Vehicular Technology 04 (2013) 89-98 95 EFBM calculation is conducted after determined the most recently developed a set of power plant having the highest electricity generated annually. Two groups of power plants were determined according to step 2. The first group consisted of five units the most recently developed power plant, and the second group consisted of power plant generating electricity with the amount ratio of 20% from total electricity generated within the system. The highest electricity generated from both groups that consist of power plants producing electricity in amount of 20% from the total in 2009 was selected, as shown in Table 9. Table 10 to Table 12 indicates electricity generated and fuel consumption in 2009 from a group of power plants having electricity generated of 20% from total electricity generated inside the system. Using Equation (2), EFBM is 0.7075 (t-CO2/MWh). Using Equation (3), EF2005 is 0.833 (t-CO2/MWh). C. Emission Reduction, (ERy) ER in this project activity is calculated using Equation (4) and Equation (5). Ly=Pey=0, and then emission reduction of CO2 resulted from operation of Cikaso SSHPP is 21,982 tCO2/yr. D. Economic Analysis The calculation results of sensivity analysis are shown in Figure 4. X-axis and Y-axis indicates the amount of parameter change and IRR value. In the Figure, benchmark line of 12.22%, selling electricity price, investment cost, and general administration cost and O&M cost is indicated by symbol of (X), (■), (◆) and (▲), respectively. The selected benchmark used throughout the calculation is the conservative bank loan rate in 2009 when the Feasibility Study completed. Change of three parameters within the amount of ±10% shows IRR is still below than the benchmark value. It can be concluded that the Figure 4. IRR project and the benchmark 5.00% 6.00% 7.00% 8.00% 9.00% 10.00% 11.00% 12.00% 13.00% -１０％ Base Case ＋１０％ IR R Table 8. Operating margin emission factor during in the last three years (2007-2009) Item Unit 2007 2008 2009 TOTAL Total Emissions tCO2 e 93,291,971 93,643,767 94,682,002 281,617,740 Total Generation MWH (net) 95,123,861 97,998,684 100,741,000 293,863,545 EFOM tCO2 e/MWh 0.958 Table 9. Two groups of power plant using to determine build margin emission factor Sample group (m) Classification “The five power plants that have been built recently” (GWh) “The power plants capacity addition to the electricity system that comprises 20% of system generation ( in GWh) and that have been built most recently” Comments Electricity quantity 12,578.0 25,660 Total generation is 115,564 (GWh) in JAMALI grid Proportion (ratio to total generation in JAMALI grid) 10.88% 22.20% Selected group O I. Febijanto / Mechatronics, Electrical Power, and Vehicular Technology 04 (2013) 89-98 96 change of three parameters doesn’t give an effect to the feasibility of the project to be unfeasible. The assumption of CER (Certified Emission Reduction) is 13 Euro/t-CO2 for 30 years. The calculation results considered the additional revenue from CER shows IRR increased 3.24%, from 10.28% to 13.52% as shown in Table 13. The additional revenue increased the value of IRR of 13.52%. It becomes higher than the benchmark value of 12.22%. IV. CONCLUSION According to the calculation result of economic feasibility of the project, it can be proven that the additional revenue generated from carbon credit could increase the project IRR Table 10. Sample group power plant for build margin calculation (part 1) No. Power Plant Fuel type Opera tion year Capa city Generated Power Thermal Eff. Actual Data Calculation data MW MWh Gj/GW/h Owner Power Plant A C C=AxBx 8760/1000 D 1 PT Java Power Paiton II #6 Steam-Coal 2000 1220 4541.7 0.00 2 PT Geo Dipa Energi Dieng Geothermal 2002 50 93.0 0.00 3 PT Cikarang Listrindo Power Cikarang GT-Gas 2003 150 1043.0 9119.04 4 PT Krakatau Daya Listrik Krakatau Steam-Coal 2003 0 2.0 9235.95 5 Muara Tawar Block 3 & 4 GT-Gas 2004 840 3555.0 9119.04 6 Block 3 & 4 GT-Oil 2004 840 351.0 9119.04 7 PT Sumberenergi Sakti Prima Cilacap #1 Steam-Coal 2006 562 3496.0 9235.95 8 Cilacap #2 Steam-Coal 2006 562 3496.0 0.00 9 Tanjung Jati B unit #1 Steam-Coal 2006 660 8226.0 9235.95 10 unit #2 Steam-Coal 2006 660 8226.0 0.00 11 Cilegon Cilegon CCGT-Gas 2006 740 3916.0 6003.37 12 Indorama Indorama Steam-Coal 2007 50 0.0 9235.95 13 PLN Labuhan Steam-Coal 2009 300 436.0 9235.95 TOTAL 25,659.7 Table 11. Sample group power plant for build margin calculation (part 2) No. Power Plant NCV Fuel Consumption Unit GJ/k t fuel GJ/k ltr fuel Actual data calculation data Owner Power Plant E F G= CxD/E G= 1000x CxD/E 1 PT Java Power Paiton II #6 24,031 - - - - - 2 PT Geo Dipa Energi Dieng - - - 9,014,689 - MMBTU 3 PT Cikarang Listrindo Power Cikarang - - - - 769 ton 4 PT Krakatau Daya Listrik Krakatau 24,031 - - 30,726,000 - MMBTU 5 Muara Tawar Block 3 & 4 - 41 - - 78,820 kltr 6 Block 3 & 4 - - 1,899,271 - - ton 7 PT Sumberenergi Sakti Prima Cilacap #1 24,031 - - - - - 8 Cilacap #2 - - 3,620,231 - - ton 9 Tanjung Jati B unit #1 24,031 - - - - - 10 unit #2 - - - 22,282,040 - MMBTU 11 Cilegon Cilegon - - - - - ton 12 Indorama Indorama 24,031 - - - - ton 13 PLN Labuhan 24,031 - - - - - TOTAL I. Febijanto / Mechatronics, Electrical Power, and Vehicular Technology 04 (2013) 89-98 97 from 10.28% to 13.52%. The additional revenue from carbon credit can increase the economic feasibility of a renewable energy. This mechanism is suitable for Indonesian condition that still doesn’t have incentives to renewable energy power generation development. The other benefit for implementing CDM, the project can be known internationally as the project that contributes in emission reduction of GHG. It can increase the project image as a green project which contributes in GHG emission reduction. REFERENCES [1] Ministry of Energy and Mineral Resources, “Indonesia Energy Outlook 2010”, pp.39, Jakarta, 2010. [2] Fabby Tumiwa, “Switch On/Switch Off: Lesson Learn from the Reform Indonesia Power Sector”, presented at International Conference on “Establishing Dialogue on Fuel and Energy Sector Transparency Initiative” Bishkek, 26-27 September 2011. [3] Bappenas, Guidelines of Local Action Plan for Reducing Green House Gasses (RAN- GRK), Jakarta, 2011. [4] Ministry of Energy and Mineral Resources, Minister Regulation, No: 1122 K/30/MEM/2002 regarding Distributed Energy Power Plant, Jakarta, 2002. [5] Ministry of Energy and Mineral Resources, Minister Regulation, No: 002/2006 Medium Scale of Renewable Energy Generation Power Plant, Jakarta, 2006. [6] Ministry of Law and Human Rights, Indonesian Law, No. 30/2009 on electricity, Jakarta, 2009. [7] Center for Strategic & International Studies, A report of the CSIS Chair for Southeast Asia Studies and the Energy National Security Program,” Sustainable Energy Future in Southeast Asia”, pp.11, Jakarta, December 2012. [8] United Nation for Climate Change Convention, AMS-I D, ver.16, Approved Small Scale Methodologies, http://cdm.unfccc.int/filestorage/C/D/M/CD Table 12. Sample group power plant for build margin calculation (part 3) No. Power Plant Fuel type Operation year Effective CO2 emission factor Emission Reduction (t- CO2/GJ) t-CO2 Owner Power Plant H G= (ExF)xH/1000 G= ExGxH 1 PT Java Power Paiton II #6 Steam-Coal 2000 - 4,968,464 - 2 PT Geo Dipa Energi Dieng Geothermal 2002 0 - - 3 PT Cikarang Listrindo Power Cikarang GT-Gas 2003 0 - 533,576 4 PT Krakatau Daya Listrik Krakatau Steam-Coal 2003 0 1,775 - 5 Muara Tawar Block 3 & 4 GT-Gas 2004 0 - 1,818,661 6 Block 3 & 4 GT-Oil 2004 0 237 - 7 PT Sumber Energi Sakti Prima Cilacap #1 Steam-Coal 2006 - 4,384,579 - 8 Cilacap #2 Steam-Coal 2006 0 - - 9 Tanjung Jati B unit #1 Steam-Coal 2006 - 8,357,517 - 10 unit #2 Steam-Coal 2006 0 - - 11 Cilegon Cilegon CCGT-Gas 2006 0 - 1,318,866 12 Indorama Indorama Steam-Coal 2007 0 - - 13 PLN Labuhan Steam-Coal 2009 - 386,848 - TOTAL - 21,770,522 Table 13. IRR calculation with and without the additional revenue without additional revenue with additional revenue Investment cost Rp 122.2 Billion Benchmark 12.22% Life Time 30 years IRR Project 10.28% 13.52% I. Febijanto / Mechatronics, Electrical Power, and Vehicular Technology 04 (2013) 89-98 98 MWF_AM_2GHDC30TPDJK04LS07SY07 X9MFZRG5/AMS_I.D._ver09.pdf?t=M1V8 bXU0Z3prfDACo-aRwXzWkC4VvptJ0w7q, accessed on October 3, 2013. [9] United Nation for Climate Change Convention, Approved large scale Methodologies, ACM0002 ver.12.3.0, http://cdm.unfccc.int/filestorage/4/W/1/4W1 SCKX3EMPO6AYGRJUTD7BQ8IVN0H/ Consolidated%20baseline%20methodology %20for%20grid- connected%20electricity%20generation%20 from%20renewable%20sources.pdf?t=Ykt8 bXU0aGE5fDDRP6_ZxQO_- 0F407pOidWU, accessed on October 3, 2013. [10] PT Indonesia Power Annual Statistic 2005, Jakarta, 2006. [11] PT Indonesia Power Annual Statistic 2006, Jakarta, 2007. [12] PT Indonesia Power Annual Statistic 2007, Jakarta, 2008. [13] PT Indonesia Power Annual Statistic 2008, Jakarta, 2009. [14] PT Indonesia Power Annual Statistic 2009, Jakarta, 2010. [15] PT PJB, Annual Statistic PT Pembangkit Jawa Bali, 2005-2009, Jakarta 2010. [16] UNFCCC, Methodological tool (Version 01.1) “Tool to calculate the emission factor for an electricity system”, EB 35 Report Annex 12 Page 1, 28 July 2008. [17] Rencana Penyediaan Tenaga Listrik Sistem Jawa-Madura-Bali 2003-2010, Direktorat Transmisi dan Distribusi PT PLN (Persero), Jakarta, September 2003. Introduction Background Purpose Methodology Green House Gas Calculation Step 1; Determination of Operating Margin Emission Factor Step 2; Calculation of Build Margin Emission Factor Step 3; Calculation of Baseline Emission Factor Step 4. Calculation of Baseline Emission Step 5. Calculation of Emission Reduction Economic Analysis Results and Discussions Green Houses Gasses Emission Calculation of Emission Factor Emission Reduction, (ERy) Economic Analysis Conclusion References