LEAP DATA COMPILATION MANUAL BACKGROUND STUDY OF RPJMN LONG-RANGE ENERGY ALTERNATIVES PLANNING SYSTEM

Transcription

1 LEAP LONG-RANGE ENERGY ALTERNATIVES PLANNING SYSTEM DATA COMPILATION MANUAL BACKGROUND STUDY OF RPJMN Directorate of Energy, Mineral and Mining Resources Badan National Development Planning Agency

2 Table of Contents Table of Contents 1 List of Tables 2 1. Data and Data Processing Data Source Data Template Used 4 2. Socio-economy Data Population Data Economy Data Transportation Data Energy Use Data Activity Data Intensity Data Energy Supply Data in BOE Usage Data (Balance Sheet) Energy Supply Data Petroleum Oil and Oil Refinery Data Natural Gas Supply Data Coal Resource, Reserve and Production Data Water Power Potential and Utilization Data Geothermal Power Potential and Utilization Data Electricity Data Other Renewable Energy Data Power Plant Plan 34

3 List of Tables Table 1. Population Data Source... 6 Table 2. Example of Population Data: West Java... 6 Table 3. Example of Population Growth Table: West Java... 7 Table 4. Example of Household Size: West Java... 8 Table 5. National Socioeconomic Survey s Recapitulation Table... 9 Table 6. Population size, population percentage and energy intensity in household sector... 9 Table 7. Economy Data Source Table 8. Example of GDRP Data per Region: West Java Table 9. Example of GDRP Figure per Activity Type: West Java Table 10. Example of GDRP Growth and Inflation: West Java Table 11. Example of Industrial Sector s Added Value: West Java Table 12. Example of Commercial Sector s Added Value: West Java Table 13. Example of Other Sector s Added Value: West Java Table 14. Transportation Sector Data Source Table 15. Amount of Land Transport and Added Value of Air Transport, Sea Transport and Ferry: West Java Table 16. Data on Land Transport Vehicle Amount Growth and Added Value Growth for Air Transport, Sea Transport and Ferry Sector: West Java Table 17. Example of Elasticity Calculation: West Java Table 18. Activity Data and Energy Intensity for Each Sector Table 19. Example of Activity Data for Household, Industry, Commercial, Transportation and Other Sectors: West Java Table 20. Table of Household Sector s Initial Intensity (BOE/capita): West Java Table 21. Table of Commercial Sector s Initial Intensity(BOE/million rupiah): West Java Table 22. Industrial Survey s Raw Data Processing Result: West Java Table 23. Industrial Sector s Initial Intensity (BOE/million rupiah): West Java Table 24. Transportation Sector s Initial Intensity: West Java Table 25. Pertamina s Fuel Sales Data Conversion into BOE: West Java Table 26 PLN s Electricity Sales Data Conversion into BOE: West Java Table 27. Pertamina s LPG Sales Conversion into BOE: West Java Table 28. Natural Gas Conversion into BOE: West Java Table 29. Household Sector Demand in BOE Table 30. Commercial Sector Demand in BOE Table 31. Industrial Sector Demand in BOE Table 32. Transportation Sector Demand in BOE Table 33. Other Sectors Demand in BOE Table 34. Demand and Supply Balance Sheet: West Java Table 35. Goal Seek Result for Household Sector Intensity: West Java Table 36. Final Intensity of Household Sector Table 37. Goal Seek Result for Commercial Sector Intensity: West Java Table 38. Final Intensity of Commercial Sector Table 39. Goal Seek Result for Industrial Sector Intensity: West Java Table 40. Final Intensity of Industrial Sector

4 Table 41. Goal Seek Result for Transportation Sector Intensity: West Java Table 42. Final Intensity of Transportation Sector Table 43. Goal Seek Result for Other Sectors Intensity: West Java Table 44. Final Intensity of Other Sectors Table 45. Demand and Supply Balance Sheet: West Java Table 46. Excel Template for petroleum oil and refinery data Table 47. Natural Gas Data Template Table 48. Coal Data Template Table 49. Water Power Data Template Table 50. Geothermal Data Template Table 51. Electricity Data Template Table 52. Biomass Data Template Table 53. Biofuel Data Template Table 54. Solar Power, Wind Power and Biogas Data Template Table 55. Power Plant Plan: West Java according to RUPTL Table 56. Summary of Power Plant Plan in West Java Table 57. Cumulative Installed Capacity in West Java

5 1. Data and Data Processing 1.1. Data Source For LEAP modeling in Background Study of Energy RPJMN, data used are as follow: No Data National Provincial 1. Statistics Indonesia Province in Figures Handbook of Energy and Economics Statistics of Indonesia Electricity Statistics PLN Statistics National Socio-Economy Survey s Raw Data Industrial Survey s Raw Data Poverty Threshold Data by Statistics Indonesia (BPS) 9. Indonesian Province GDRP according to Business Fields Pertamina s Fuel & Gas Sales Data PGN s gas sales Data 2009 * 12. RUPTL EBTKE Statistics 2011 ** *= Only available for some provinces **= Not all data of EBT Type available to provincial level Data checked only in National column shows that the data presents only national figure and not available at provincial level. Data checked in Province column shows that the data shows only Provincial data. Data checked in both columns shows that the data contains national data which is aggregated into provincial level. Before extracting the data, there are several data that should be processed before being extracted. The mentioned data are Raw Data of National Socio-economic Survey (Susenas) 2011 and Raw Data of Industrial Survey Data Template Used In LEAP modeling for Background Study of Energy RPJMN, there are three data formats for each province. The data formats are as follow: 1. Socio-economy Data, including: Population: Population amount and density, household size, population categorization according to income. GDRP: GDRP per business type, inflation, GDRP growth. Industrial sector s added value, commercial sector s added value, other sector s added value. 4

6 Transportation: amount of cars, motorcycles, buses and trucks, air transport revenue, sea transport and ferry revenue, vehicle amount growth, air and sea transport revenue growth, elasticity of each type of vehicle. 2. Energy Use Data Fuel sales, electricity, natural gas, LPG, coal briquette, and amount of electricity consumers Activity data in Energy use intensity in household sector, commercial sector, industrial sector and transportation sector. Balance sheet between energy use and energy supply 3. Energy Supply Data. Energy source, reserve, distribution (petroleum oil, natural gas, coal, water power, geothermal, biomass, biofuel, and other energy sources). Electricity, including installed capacity, power capacity, electricity production, fuel use, substation data, and distribution station Future electricity plan 5

7 2. Socio-economy Data 2.1. Population Data Table 1 Population Data Source Population Data Data Source Data Processing Population size and density Province in figures 2011 Province Population size 2010 Population growth Province in figures 2011 Household Size Province in figures 2011 Average household members in Province Population size according to income Raw Data of National Socioeconomy Survey Raw Data 2011; Poverty Threshold data by BPS 2010 Population is categorized into: below poverty threshold, bottom 40%, middle and upper (top 20%). To obtain population size according to income, raw data of National Socio-economy Survey 2011 for province is used. The execution steps: 1. Population is distinguished according to domicile: village and city 2. Village and city population is sorted according to to income (capita column) 3. Referring to the poverty threshold and inputted amount of query data, population categorization in below the poverty threshold, bottom 40%, middle and top 20% category can be done and percentage of each category can be obtained. 4. Percentage obtained for each income category is multiplied with province total population. Electrification Ratio per income group Electricity Statistics Electrification Ratio is distributed to four income categories with trial and error method. Population data template in Socio-Economy Data is as follows: Population amount, amount of household (head of family), Area (km 2 ) and population density. The following data is derived from Province in Figures Table 2 Example of Population Data: West Java District/City Population Population size Household Area Density (people) Amount(HH) (km2) (people/km2) Bogor district 4,771,932 2, ,592 Sukabumi district 2,341,409 4, Cianjur district Bandung district 2,171,281 3,178,543 3, , ,809 Garut district 2,404,121 3, Tasikmalaya district 1,675,675 2, Ciamis district 1,532,504 2, Kuningan district 1,035,589 1, Cirebon district 2,067,196 1, ,930 Majalengka district 1,166,473 1, Sumedang district 1,093,602 1, Indramayu district 1,663,737 2, Subang district 1,465,157 2, Purwakarta district 852, Karawang district 2,127,791 1, ,112 Bekasi district 2,630,401 1, ,072 6

8 Bandung Barat district 1,510,284 1, ,131 Bogor city 950, ,506 Sukabumi city 298, ,101 Bandung city 2,394, ,236 Cirebon city 296, ,380 Bekasi city Depok city 2,334,871 1,738, ,932 8,717 Cimahi city 541, ,135 Tasikmalaya city 635, ,446 Banjar city 175, ,339 43,053, ,573,793 37, ,160 Population growth: population growth data is derived from Province in Figures. Several provinces provide population growth down to district/city level, but some only list provincial growth. If Province in Figures only list provincial growth data, population growth for each district/city can be left empty, and provincial growth is filled in the column on bottom side of the table. Table 3 Example of Population Growth Table: West Java District/City Pertumbuhan Jumlah Penduduk (%/tahun) Bogor district -0.63% 3.15% Sukabumi district 1.16% 1.22% Cianjur district 1.59% 1.11% Bandung district -2.56% 2.57% Garut district 1.61% 1.61% Tasikmalaya district -1.92% 1.15% Ciamis district -0.11% 0.47% Kuningan district 0.99% 0.51% Cirebon district 1.59% 0.69% Majalengka district 0.84% 0.40% Sumedang district 1.54% 1.23% Indramayu district 0.94% 0.46% Subang district 0.98% 0.98% Purwakarta district 2.20% 2.01% Karawang district 1.82% 1.77% Bekasi district -2.29% 4.70% Bandung Barat district 1.97% Bogor city 10.70% 2.40% Sukabumi city 7.72% 1.71% Bandung city 0.37% 1.16% Cirebon city 0.66% 0.86% Bekasi city 3.48% Depok city 4.32% Cimahi city 2.06% Tasikmalaya city 1.13% Banjar city 1.14% Province 1.96% 1.90% 7

9 Household Size. The figure for household size is derived from = Population Amount/Head of Household Number. Table 4 Example of Household Size: West Java District/City Family members per Household (people/hh) Province 3.72 Population Amount According to Income and Electrification Ratio To calculate population amount according to income, raw data of National Socio-economic Survey 2011 is used for each province. Figure 1 Example of National Socioeconomic Survey s Raw Data Display per Province: West Java National Socioeconomic Survey s Raw Data as shown above is then processed with the following steps: 1. Households are separated according to Regional Type: 1. City and 2. Village. 2. Households in each city and village are sorted according to capita (using SORT function and MS. Excel). 3. Referring to poverty threshold data from Statistics Indonesia (BPS) for village s poverty threshold and city s poverty threshold. Households with income (capita column) below poverty threshold are categorized into poor household (below PT). 8

10 4. By referring to the data (query) in a province, Lower Middle Households are determined from 40% lowest households according to capita order up to the poverty threshold. 5. Rich households are calculated from 20% households with highest income per capita. 6. Upper middle households are obtained through the boundary between rich households and lower middle households. 7. After succeeding in categorizing the four household categories, number of household members, kerosene consumption, electricity, LPG, natural gas, coal and summed income. Thus, a table with the following appearance is obtained: Table 5 National Socioeconomic Survey s Recapitulation Table Natural Coal Kerosene electricity LPG Village City Gas Briquette City+ Village (BOE/HH/yr) (BOE/HH/yr) (BOE/HH/yr) capita Population Population (BOE/H (BOE/HH/yr) H/year) Under poverty Threshold 6,060 5, , ,137,170 Lower Middle 18,139 7, , , ,093,096,473 Upper Middle 20,572 10, , , ,227,620,008 Top 20% 9,155 4, , , ,423,882, After recapitulating population size and energy consumption of each household category, population percentage according to income can then be calculated. In addition, intensity per capita can also be calculated by dividing energy consumption by population size. Table 6 Population size, population percentage and energy intensity in household sector Coal Kerosene Electricity LPG Natural Gas Percentage Briquette City+ Village Population Intensity Intensity Intensity Intensity (%) Intensity (BOE/capita) (BOE/capita) (BOE/capita) (BOE/capita) (BOE/capita) Below poverty threshold % Lower Middle % Upper Middle % E-05 Top 20% % E % After this data processing, population percentage data is inputted to the population data template: 9

11 Income Category City Village Amount Percentage Population Electrification Ratio Below poverty threshold % 5,938,646 53% 7.31% Bottom 40% % 13,432,815 64% 19.97% Medium % 16,428,266 81% 30.91% Top 20% % 7,254,005 95% 16.01% ,053, % Electrification Ratio: 74.19% In addition, electrification ratio number for each population category is predicted by trial and error method so that the provincial electrification ratio number is approaching the electrification ratio number listed in Electricity Statistics Economy Data Table 7 Economy Data Source Economy Data Data Source Data Processing GDRP Per Region Province in Figures 2011 Constant price GDRP in each district in Province Province GDRP per Activity type GDRP Grwoth and Inflation Province in Figures 2011 Province in Figures 2011 Constant price GDRP according to activity type in Province. Activity type includes: Agriculture, mining, public infrastructure, Manufacture industry, construction service, commercial service, transportation, financial service and social service. GDRP growth is obtained from particular year s GDRP difference with the previous year, which is compared with GDRP in the previous year (in percent) Industrial Sector s Industrial Survey s Raw Data; Added Value Province in Figures Province in Figures 2011; Commercial Sector s Province GDRP according to Added Value Business Field Other Sectors Added Value Province in Figures 2011; Province GDRP according to Business Field Industrial sector added value incorporates added value from each industrial subsector in a particular year in a province (GDRP constant price). Industrial subsectors include: food, textile, timber, paper, chemical, non-metal, metal, machinery and others. Commercial sector added value incorporates added value from financial service, social service and commercial service subsectors in 2010 (GDRP constant price). Other sectors added value incorporates added value from agriculture, mining and construction subsectors in 2010 (GDRP constant price). GDRP data per region. GDRP data per region can be derived from Province in Figures Table 8 Example of GDRP Data per Region: West Java GDRP GDRP/Capita District/City (billion Rp) (million Rp/cap/yr) Bogor district 32, Sukabumi district 8, Cianjur district 8, Bandung district 21, Garut district 11, Tasikmalaya district 5, Ciamis district 7, Kuningan district 3,

12 Cirebon district 8, Majalengka district 4, Sumedang district 5, Indramayu district 14, Subang district 7, Purwakarta district 7, Karawang district 21, Bekasi district 54, Bandung Barat district 8, Bogor city 4, Sukabumi city 1, Bandung city Cirebon city 31, , Bekasi city 15, Depok city 6, Cimahi city 6, Tasikmalaya city 3, Banjar city Province 307, GDRP data per activity type. GDRP data per activity type can be derived from Province in Figures 2011 or Province GDRP according to Business Type GDRP per activity type is stated in million Rupiah. GDRP is usually presented in two values, i.e. current price and constant price. For this activity, GDRP used is constant price. Activity Type Table 9 Example of GDRP Figure per Activity Type: West Java GDRP (constant price 2011) Million Rupiah Agriculture 37,139,985 41,722,076 42,137,486 Mining 6,850,433 7,424,424 7,464,691 Manufacture Industry 133,756, ,432, ,246,774 Public Infrastructure (Utility) 5,985,767 6,839,237 7,315,960 Construction Service 9,730,820 10,299,411 11,810,047 Commercial Service 56,937,923 62,701,714 70,083,413 Transportation 12,233,940 13,209,254 15,352,858 Financial Service 7,750,384 8,307,130 9,216,323 Social Service 4,483,556 4,902,124 6,136, ,869, ,838, ,764,087 GDRP Growth and Inflation Data. GDRP growth is calculated by comparing GDRP increase with GDRP of the previous year. Inflation figures are listed in Province in Figures. Usually, inflation figures are not referring to provincial inflation figures, but inflation figures of several cities in a province. If inflation figures are derived from several cities, then the figures are averaged. 11

13 Table 10 Example of GDRP Growth and Inflation: West Java GDRP Growth 4.35% 6.25% Inflation 6.38% Industrial Sector s Added Value Data, including data on industrial sector s income constant price which is divided in food industry, textile, timber, paper, non-metal, metal, chemical, machinery and other industries. GDRP value of each industrial subsector can be derived from Province in Figures or Industrial Survey. Not all Province in Figures give the detail for GDRP in industrial sector. If Province in Figures does not list GDRP detail of industrial sector, Industrial Sector s raw data processing result can be used. Percentage of each subsector in industrial survey can be used to obtain GDRP value of industrial subsector. Subsector Table 11 Example of Industrial Sector s Added Value: West Java Added Value (Constant Price 2010) %PDRB Food 13,802,269 14,593,464 14,388, % Textile 27,420,706 26,301,087 24,469, % Timber 1,589,552 1,818,574 1,594, % Paper 2,715,706 2,856,221 3,454, % Chemical 11,561,363 11,666,430 10,411, % Non Metal 2,267,875 2,320,724 2,467, % Metal 627, , , % Machinery 68,845,126 65,985,509 73,226, % Others 2,726,795 2,994,700 2,456, % 131,556, ,169, ,072,970 Commercial sector s added value, consists of constant price GDRP value for financial service, commercial service and entertainment service. This figure can be obtained from Province in Figures or Provincial GDRP According to Business Field Table 12 Example of Commercial Sector s Added Value: West Java Added Value (Constant Price 2011) Subsector Financial Service 7,750,384 8,307,130 9,216,323 Commercial Service 56,937,923 62,701,714 70,083,413 Social Service 4,483,556 4,902,124 6,136,535 69,171,863 75,910,968 85,436,271 Other sector s added value, consists of constant price GDRP value for agriculture sector, mining sector and construction service. This figure can be obtained from Province in Figures or Provincial GDRP According to Business Field

14 Table 13 Example of Other Sector s Added Value: West Java Added Value (Constant Price 2011) Subsector Agriculture 37,139,985 41,722,076 42,137,486 Mining 6,850,433 7,424,424 7,464,691 Construction Service 9,730,820 10,299,411 11,810,047 53,721,238 59,445,911 61,412, Transportation Data Table 14 Transportation Sector Data Source Transportation Data Data Source Data Processing Amount of car Statistics Indonesia Amount of cars in 2008, 2009, 2010 Amount of Motorcycle Statistics Indonesia Amount of motorcycles in 2008, 2009, 2010 Amount of Bus Statistics Indonesia Amount of buses in 2008, 2009, 2010 Amount of Truck Statistics Indonesia Amount of trucks in 2008, 2009, 2010 Sea transport and ferry sector s added value Air transport sector s Added value Province GDRP according to Business Field Province GDRP according to Business Field River transport, ferry, and sea transport sector s added value (in million Rupiah) in Banten Province GDRP in 2008, 2009, 2010 and 2011 Air transport sector s added value (in million Rupiah) in Banten Province GDRP in 2008, 2009, 2010 and 2011 Car elasticity Motorcycle Elasticity Bus Elasticity Truck Elasticity Car amount growth and GDRP growth Motorcycle amount growth and GDRP growth Bus amount growth and GDRP growth Truck amount growth and GDRP growth Comparison between car amount growth (in percent) with GDRP growth (in percent) Comparison between motorcycle amount growth (in percent) with GDRP growth (in percent) Comparison between bus amount growth (in percent) with GDRP growth (in percent) Comparison between truck amount growth (in percent) with GDRP growth (in percent) Sea transport and ferry Elasticity Air transport Elasticity Sea transport and ferry sector s added value growth and GDRP growth Air transport sector s added value growth and GDRP growth Comparison between River transport, ferry, and sea transport added value growth (in percent) with GDRP growth (in percent) Comparison between air transport added value (in percent) with GDRP growth (in percent) Amount of vehicle and transportation sector s added value. For land transportation, data on amount of cars, motorcycles, buses and trucks is derived from Statistics Indonesia Data on train (vehicle-km) is derived from the calculation of train mileage in Air transport, sea transport and ferry in this study are calculated by GDRP value derived from Provincial GDRP in Indonesia According to Business Field

15 Table 15 Amount of Land Transport and Added Value of Air Transport, Sea Transport and Ferry: West Java Mode Passenger car (unit) 507, , ,641 Motorcycle (unit) 2,126,612 2,378,188 2,615,527 Bus (unit) 162, , ,578 Truck (unit) 451, , ,412 Train(1000 km) 10,825,409 Ferry Transport (million rupiah) Sea ship (million rupiah) 104,066 66,830 67,526 Airplane (million rupiah ) 596, ,652 1,118,547 Sea transport and ferry (million Rupiah) 104, , , Vehicle amount growth and added value, calculated by comparing the increase/decline of vehicle amount with vehicle amount/added value in the previous year. Table 16 Data on Land Transport Vehicle Amount Growth and Added Value Growth for Air Transport, Sea Transport and Ferry Sector: West Java Growth GDRP 5.33% 5.83% 6.49% Passenger car (unit) 3.73% 4.20% Bus (unit) 11.83% 9.98% Truck (unit) 5.10% 3.85% Motorcycle (unit) 0.11% 3.86% Train (1000 km) 0.00% Ferry Transport (billion Rp) 13.83% % Sea Ship (billion Rp) % 1.04% Airplane (billion Rp) 11.46% 68.29% Sea transport and ferry % 0.68% Calculating elasticity of each vehicle mode. Elasticity calculation is done by comparing the growth of a particular transportation mode with GDRP growth. Vehicle elasticity illustrates the relative vehicle growth on GDRP growth. Table 17 Example of Elasticity Calculation: West Java Elasticity Rata-2 Passenger car (unit) Bus (unit) Truck (unit) Motorcycle (unit) Train (1000 km) Ferry Transport (billion Rp) 2.37 (3.81) (0.72) Sea Ship (billion Rp) (6.14) 0.16 (2.99) Airplane (billion Rp) Sea transport and ferry (6.07) 0.11 (2.98) 14

16 3. Energy Use Data Energy Use Data includes the energy use calculation in household, industry, commercial, transportation and other sectors. Energy use calculation in each sector is verified with energy supply data (fuel, electricity, and gas) in each province. In National LEAP calculation, final energy demand calculation in household, industry, transportation and non-energy sectors uses a simple equation. Demand = Activity Data x Intensity Table 18 Activity Data and Energy Intensity for Each Sector Sector Activity Data Energy Intensity Household Susenas 2011 s Raw Data compilation Population size and categorization based on income of All provinces and Goal seek Industry Industrial Survey (compilation of all Industrial Sector s Added Value in the base year provinces) and Goal Seek Commercial Commercial Sector s Added Value in the base year Guest, Estimate and Goal seek Transportation Vehicle amount in each land transportation mode in Guest, Estimate and Goal seek the base year; Added value of air, sea and ferry transport in the base year. Others Other Sectors Added Value in the base year Guest, Estimate and Goal seek By referring to the above table, it seems that energy demand in each sector can be calculated if all of the data above is available. Ideally, a survey is required to know the energy intensity in each sector. Unfortunately, not all sectors have the survey result to know the magnitude of energy intensity in that particular sector. Therefore, several approaches are needed to obtain the intensity estimation in each sector. For household sector, intensity is calculated based on National Economic Survey s raw data processing result for each province. Industrial sector intensity uses the processing result of Industrial Survey s raw data. Meanwhile, magnitude of intensity for commercial sector, transportation sector and other sectors is determined by guess and estimate (expert judgment). Survey s intensity result and intensity from guess and estimate result are the validated by using energy sales data in each province. If there are differences between energy demand calculation result with energy sales data in the province, intensity adjustment is executed so that the value of energy demand equals to energy sales in the region. This intensity adjustment is called Goal seek. 15

17 Figure 2 Intensity Calculation Flow 3.1. Activity Data Activity data is obtained for energy use data that comes from Socio-economy Template. Activity data takes the base year s data (2010) for household, industry, commercial, transportation and other sectors. Table 19 Example of Activity Data for Household, Industry, Commercial, Transportation and Other Sectors: West Java Population Million Rupiah Income Category 2010 Electrification Ratio Below poverty threshold Poverty threshold to 40% 40% to 80% Top 20% 5,938,646 50% 13,432,815 54% 16,428,266 79% 7,254, % 43,053,732 Industry Food Textile Timber Paper Chemical Non Metal Metal Machinery Others million Rupiah 2010 Percentage 14,388, % 24,469, % 1,594, % 3,454, % 10,411, % 2,467, % 604, % 73,226, % 2,456, % 133,072, % Commercia Commercial Service Financial Service Social Service million Rupiah 2010 Percentage 70,083, % 9,216, % 6,136, % 85,436, %

18 Others million Rupiah 2010 Percentage Agriculture 42,137, % Mining 7,464, % Construction 11,810, % 61,412, % Transportation Mode 2010 Passenger car (unit) 548,641 Motorcycle (unit) 2,615,527 Bus (unit) 177,578 Truck (unit) 469,412 Train (1000 km) Ferry transport (billion Rp) 706 Sea ship (billion Rp) 67,526 Airplane (billion Rp) 1,118,547 Sea transport and ferry 68, Intensity Data Intensity data shows the magnitude of energy use intensity in each sector. Energy intensity is stated in Barrel of Oil Equivalent (BOE) unit per unit. Household Sector Intensity Household sector intensity is derived from processing result of National Socio-economy Survey s data which is processed along with population categorization according to income (see Table 6) Table 20 Table of Household Sector s Initial Intensity (BOE/capita): West Java Multiplier Income Category Kerosene Electricity LPG Natural Gas Charcoal Poor Lower Middle Upper Middle Rich The table above shows the energy intensity in BOE/capita in each household category. Multiplier sign at the top of the table shows that this intensity is the initial intensity before being adjusted to energy sales data. Multiplier number and intensity will change if there was any difference between energy demand with energy sales in the calculated region. Commercial Sector Intensity Commercial intensity is the result of LEAP team s guess and estimate (expert judgment). 17

19 Table 21 Table of Commercial Sector s Initial Intensity(BOE/million rupiah): West Java b. Commercial Sector Sub-sector Diesel Oil Kerosene Electricity LPG Natural Gas Coal Briquette Multiplier Commercial Service Financial Service Social Service The table above shows the energy intensity in BOE/million rupiah in each commercial subsector. Multiplier sign at the top of the table shows that this intensity is the initial intensity before being adjusted to energy sales data. Multiplier figure and intensity will change if there was any difference between energy demand with energy sales in the calculated region. Industrial Sector Intensity Industrial sector intensity is obtained from Industrial Survey 2012 s raw data processing result. The processing result for West Java Province is presented as follow: Industry Type Table 22 Industrial Survey s Raw Data Processing Result: West Java PREMIUM DIESEL KEROSENE COAL PGN GAS LPG ELECTRICITY (BOE) (BOE) (BOE) (BOE) (BOE) (BOE) (BOE) ADDED VALUE (mln IDR) Food Textile Timber Paper Chemical Non Metal Metal Machinery Others To obtain energy intensity in each type of industry, energy demand data is divided by added value, so that the following intensity with BOE/million rupiah unit is generated. 18

20 Table 23 Industrial Sector s Initial Intensity (BOE/million rupiah): West Java Industrial Sector Sub-sector Diesel Oil Fuel Oil Kerosene Electricity LPG Natural Gas Coal Multiplier Food Textile Timber Paper Chemical Non Metal Metal Machinery Others The table above shows the energy intensity in BOE/million rupiah in each industrial subsector. Multiplier sign at the top of the table shows that this intensity is the initial intensity before being adjusted to energy sales data. Multiplier number and intensity will change if there was any difference between energy demand with energy sales in the calculated region. Transportation Sector Intensity Transportation sector intensity for land transport (car, motorcycle, bus and truck) is stated in BOE/vehicle unit. Train uses BOE/km intensity. Meanwhile, intensity for air and sea transport uses BOE/million rupiah intensity. Intensity unit in transportation sector is not uniformed as in other sectors considering the available data for each transportation mode. The following is transportation sector s initial intensity. Transportation Sector Table 24 Transportation Sector s Initial Intensity: West Java Subsector Premium Diesel Oil Natural Gas Fuel Oil Avtur Avgas Electricity Unit Multiplier Passenger car (unit) BOE/unit Motorcycle (unit) BOE/unit Bus (unit) BOE/unit Truck (unit) BOE/unit Train (km) BOE/km Sea Transport (millionrp) BOE/mln Rp Air Transport (million Rp) BOE/mln Rp The value of initial intensity for car, motorcycle, truck and bus is the result of expert judgment which will be adjusted with transportation sector s energy sales data. Train intensity is obtained from the study on train intensity. Sea transport intensity is obtained by dividing 19

21 supply of fuel oil and diesel fuel in sea transport with sector s income in GDRP. Air transport intensity is obtained with avtur and avgas supply in a region with air transport income in GDRP. Other Sectors The following commercial intensity is the result of LEAP team s guess and estimate (expert judgment). Intensity of other sectors only calculates use of diesel fuel. Diesel Subsector Oil Multiplier 1 Agriculture Mining Construction The table above shows the energy intensity in BOE/million rupiah in each household category. Multiplier sign at the top of the table shows that this intensity is the initial intensity before being adjusted to energy sales data. Multiplier number and intensity will change if there was any difference between energy demand with energy sales in the calculated region Energy Supply Data in BOE Energy supply data in BOE consists of fuel, natural gas, LPG supply data as well as electricity sales data. The data are the ones used to confirm the congruity between demand calculation (activity data x intensity) with energy supply in a particular region. The data used is energy sales data in 2010 (base year). Data used are among others: Pertamina s fuel sales data, which is converted from KL to BOE Table 25 Pertamina s Fuel Sales Data Conversion into BOE: West Java 2007 (KL) 2008 (KL) 2009 (KL) 2010 (KL) 2011 (KL) Conversio n Factor 2010 (BOE) 1. Avtur - 3,579 16,003 10,781 12, , Avgas - 4 6,001 1,400 1, , Premium 3,169,746 2,088,060 3,668,173 3,949,929 4,343, ,018,213 a. Land trans 3,166,529 2,084,688 3,644,169 3,946,713 4,330, ,999,472 b. Sea trans c. Industry 3,217 3,370 24,004 3,216 12, , Kerosene 1,985,610 1,429, ,390 92,667 49, ,274 a. Household 1,969,820 1,421, ,410 87, ,078 b. Industry 15,790 7,851 2,980 4,757 5, ,197 20

22 c. Land trans , d. Sea trans Diesel oil 1,919,199 1,792,431 4,204,254 1,910,850 3,015, ,800,029 a. Land trans 1,348,678 1,510,767 1,633,514 1,629,455 1,894, ,969,383 b. Sea trans 1,484 13,312 1,818 1,063 10, ,795 c. Industry 540, ,746 2,551, , , ,878 d. Electricity 28, ,606 17, , , , Fuel oil 671, ,432 6,412 76,547 66, ,859 a. Sea trans ,256 b. Industry 671, ,432 5,657 75,792 66, ,603 c. Electricity ,746,127 5,448,271 8,084,233 6,042,174 7,488, ,494,476 PLN s Electricity Sales Data, which is converted from GWh into BOE Table 26 PLN s Electricity Sales Data Conversion into BOE: West Java Customer Group Electricity Sales (GWh) Conversion factor 2010 Household 6, ,151, Social , Public , Industry 5, ,096, Business 1, ,217, , ,826, Pertamina s LPG Sales Data, which is converted from kg into BOE Table 27 Pertamina s LPG Sales Conversion into BOE: West Java Conversion 2010 Factor (BOE) Household 187,651, ,805, ,336, ,621,002 1,079,019, ,299,145 Industry 24,234,450 21,004,900 22,492,077 24,177, ,085 Transportation ,886, ,810, ,828, ,798,084 1,079,019, ,505,231 21

23 PGN s Natural Gas Sales Data, which is converted from MSCF to BOE Table 28 Natural Gas Conversion into BOE: West Java Customer Group Natural Gas Sales (MSCF) Conversion factor 2010 (BOE) Household ,443 Industry 136,072, ,438,531 Commercial 146, ,222 Transportation ,978 Special sectors (Fertilizer & Steel) , ,582,930 Natural gas supply data is not available for all provinces. This data only available for DKI Jakarta, West Java, Banten, East Java, South Sumatera, North Sumatera, Riau and Riau Archipelago. Besides the four supply data, there is another required data i.e. coal briquette sales data in each province. Unfortunately, this data only available for national level, thus the coal briquette supply aggregate data still have to be processed to obtain supply figure for each province Usage Data (Balance Sheet) In usage data, demand data is presented in BOE for each energy user sector. This demand data is the multiplication result between activity data and initial intensity, and then total demand for each sector in BOE is obtained. The following is demand calculation result for each sector (in BOE) Table 29 Household Sector Demand in BOE Income Group Energy Use in 2011 (BOE) Kerosene Electricity LPG Natural Gas Charcoal Below poverty Threshold 15, , , , Poverty threshold to 40% 52, ,036, ,529, , Biomass 40% to 80% 96, ,851, ,872, , Top 20% 39, ,880, ,624, , , ,506, ,354, ,

24 Subsector Table 30 Commercial Sector Demand in BOE Energy use in 2011 (BOE) Diesel Oil Kerosene Electricity LPG Natural Gas Commercial Service 350, , , , , Financial Service , Social service 30, , , , , , ,088, , , Coal Briquette Table 31 Industrial Sector Demand in BOE Subsector Energy use in 2011 (BOE) Diesel Oil Fuel Oil Kerosene Electricity LPG Natural Gas Coal Food 721, , , , , , Textile 767, , , , , , ,516, Timber 27, , , , Paper 28, , , , , Chemical 175, , , , , , , Non Metal 41, , , , , Metal 5, , , Machinery 436, , , ,094, , , , Others 17, , , , , , ,220, , , ,333, , , ,199, Table 32 Transportation Sector Demand in BOE Subsector Premium Energy use in 2011 (BOE) Diesel Fuel Kerosene Avtur Oil Oil Avgas Natural Gas LPG Elect ricit y Passenger car 1,097, , ,372 - Motorcycle 2,615, Bus 177,578 1,775, Truck 469,412 4,694, ,643 - Train Sea ship and ferry - 11,795 5, Airplane ,509 7, ,359,799 6,756,015 5,256-63,509 7,774 3,192-23

25 Subsector Table 33 Other Sectors Demand in BOE Energy use in 2011 (BOE) Premium Diesel Oil Electricity Construction - 93, Agriculture - 100, Mining - 127, , After all demand figures are obtained, the figures are then summarized into a balance sheet which contains energy demand per sector and energy supply in region on work. Table 34 Demand and Supply Balance Sheet: West Java Energy use in 2011 (BOE) Fuel Transportatio Commercia Household Industry n l Others Power plant Supply Avtur , ,509-63,509 Avgas - - 7, ,774-7,774 Premium* - - 4,359, ,359,799 18,658,414 23,018,213 Kerosene 203,339 56, , , , ,274 Diesel Oil - 2,220,269 6,751, ,100 93, ,973 10,397,240 1,998,633 12,395,873 Fuel Oil - 222,027 5, , , ,859 Natural Gas 160, ,543 3,192 35, ,205 24,212,725 24,582,930 LPG 6,354, ,263-86, ,546,210 1,959,021 8,505,231 Coal - 2,199, ,199,632 (2,199,632) Electricity 12,506,752 2,333,394-1,088, ,928,957 (7,102,835) 8,826,121 Biofuel Charcoal (833) 19,226,704 7,306,209 11,190,647 1,723,995 93, ,973 40,492,309 78,481,784 The table above shows energy use (types of fuel) in each sector. We can see that the total demand for West Java by using activity data and intensity data is BOE. Meanwhile, total supply for West Java (right column) is BOE. It shows that the intensity used still needs to be adjusted to make the Energy Use equals to Energy Supply. In order to harmonize the Energy Use with Energy Supply, the first thing to be given attention to is the difference between Energy Use (Demand) with Supply in the green column for each type of fuel. Types of sector that use each type of fuel also should be examined. MS. Excel has a feature called Goal Seek, this feature can be used to alter the intensity so that energy use for each type of fuel equals to the amount of supply. Goal Seek feature in MS. Excel is included in the what-if-analysis option in the data tab. The Goal Seek executed among others are: Premium Goal Seek by altering the multiplier of premium intensity in transportation sector. Kerosene Goal Seek by altering the multiplier of kerosene intensity in household, commercial and industrial sector. 24

26 Diesel oil Goal Seek by altering the multiplier of diesel oil intensity in transportation, industry, commercial and other sectors. Fuel oil Goal Seek by altering the multiplier of fuel oil intensity in industry and commercial sector. Natural Gas Goal Seek by altering the multiplier of natural gas intensity in household, commercial and industrial sector. LPG Goal Seek by altering the multiplier of LPG intensity in household, commercial and industrial sector. Electricity Goal Seek by altering the multiplier of electricity intensity in household, commercial and industrial sector. Goal Seek is not executed for: Avtur Intensity Avgas Intensity Coal intensity, because there is no provincial coal supply data available. Charcoal intensity, because there is no provincial charcoal supply data available. After goal seek is executed, the multiplier value on intensity will change. Household Sector Table 35 Goal Seek Result for Household Sector Intensity: West Java Multiplier Income Category Kerosene Electricity LPG Natural Gas Charcoal Poor Lower Middle Upper Middle Rich By the change of multiplier value, new intensity value is obtained. Final Intensity of Household Sector is as follow: Table 36 Final Intensity of Household Sector Intensitas Pemakaian Energi Tahun 2010 (BOE/kapita/tahun) Income Electricity w/ Category Kerosene Electricity LPG Charcoal Biomass Natural Gas Electrification ratio Poor Middle B Middle A Rich

27 Commercial Sector Table 37 Goal Seek Result for Commercial Sector Intensity: West Java Sub-sector Diesel Oil Kerosene Coal Electricity LPG Natural Gas Briquette Multiplier Commercial serv Financial serv Social serv By the change of multiplier value, new intensity value is obtained. Final Intensity of Commercial Sector in West Java is presented in the following table: Table 38 Final Intensity of Commercial Sector Subsector Energy use intensity in 2011 (BOE/million rupiah/year) Diesel Oil Kerosene Electricity Natural Gas Coal Briquette Comm. Serv Finance serv Social serv Industrial Sector Table 39 Goal Seek Result for Industrial Sector Intensity: West Java Sub-sector Diesel Oil Fuel Oil Kerosene Electricity LPG Natural Gas Coal Multiplier Food Textile Timber Paper Chemical Non Metal Metal Machinery Others By the change of multiplier value, new intensity value is obtained. Final Intensity of Industrial Sector is presented in the following table: 26

28 Table 40 Final Intensity of Industrial Sector Subsector Energy use intensity in 2011 (BOE/million rupiah/year) Diesel Oil Fuel Oil Kerosene LPG Natural Gas Coal Food Textile Timber Paper Chemical Non Metal Metal Machinery Others Transportation Sector Table 41 Goal Seek Result for Transportation Sector Intensity: West Java Fuel Electri Natural Avtur Avgas city Unit Subsector Premium Diesel Oil Gas Oil Multiplier Passenger car (unit) BOE/unit Motorcycle (unit) BOE/unit Bus (unit) BOE/unit Truck (unit) BOE/unit Train (km) BOE/km Sea transport (millionrp) BOE/juta Rp Air transport (millionrp) BOE/juta Rp The intensity value above is multiplied with multiplier figure obtained from goal seek result, the following is the final Intensity of Transportation Sector in West Java. Table 42 Final Intensity of Transportation Sector Energy use intensity in 2010 (BOE/unit/year or BOE/000 km or BOE/hour) Subsector Premium Diesel Oil Fuel Oil Avtur Avgas Natural Gas Electricity Passenger car (unit) Motorcycle (unit) Bus (unit) Truck (unit) Train (1000 km) Sea ship and ferry Airplane (million Rp) Other Sectors (Agriculture, Mining and Construction) Table 43 Goal Seek Result for Other Sectors Intensity: West Java 27

29 Subsector Diesel Oil Multiplier 0.5 Agriculture Mining Construction With the multiplier above, new intensity value is obtained. Final Intensity of Commercial Sector is presented in the following table: Table 44 Final Intensity of Other Sectors Subsector Energy use intensity in 2010 Premium Diesel oil Electricity Agriculture Mining Construction By executing goal seek for each type of fuel, BOE consumption from demand sector will be the same as supply amount. Table 45 Demand and Supply Balance Sheet: West Java Energy use in 2011 (BOE) Fuel Transportatio Commercia Household Industry n l Others Power Plant Supply Avtur , ,509-63,509 Avgas - - 7, ,774-7,774 Premium* ,018, ,018,213-23,018,213 Kerosene 440,614 56,081-52, , ,274 Diesel Oil - 673,507 10,577, ,723 46, ,973 12,395, ,395,873 Fuel Oil - 527,603 5, , ,859 Natural Gas 52,443 24,458,287 45,978 26, ,582,930-24,582,930 LPG 8,197, ,344-86, ,505,231-8,505,231 Coal - 2,199, ,199,632 (2,199,632) Electricity 4,151,365 3,096,533-1,578, ,826,121-8,826,121 Biofuel Charcoal (833) 12,843,162 31,231,987 33,718,510 1,890,728 46, ,973 80,682,250 78,481,784 With intensity adjustment, demand of each type of fuels will be the same or closer with supply amount. From the table above, we can see that goal seek is not executed to coal and charcoal. It is because supply data for coal and charcoal are not available for the province on work (West Java). 28