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final draft ----------------------- do not cite or quote
BUSINESS AS USUAL SCENARIO OF
YOGYAKARTA ENERGY MODEL AND DATABASE
FINAL DRAFT
CAREPI TECHNICAL TEAM OF YOGYAKARTA
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Table of ContentsChapter 1 DESCRIPTION OF SPECIAL REGION OF YOGYAKARTA PROVINCE...1
1.1 Macro and Social Economic description......................................................................11.2 Economic Activities in Each Sector.............................................................................3
1.2.1 Household Sector ...................................................................................................31.2.2 Commercial Sector.................................................................................................31.2.3 Industrial Sector......................................................................................................41.2.4 Transportation Sector.............................................................................................5
Chapter 2 PRIMARY ENERGY SUPPLY............................................................................62.1 Domestic Energy Sources .............................................................................................62.2 Energy Export and Import.............................................................................................62.3 Regional Energy Potential ............................................................................................6
Chapter 3 ENERGY TRANSFORMATION .......................................................................113.1 Transmission and Distribution....................................................................................11
Chapter 4 FINAL ENERGY DEMAND..............................................................................124.1 Final Energy Demand by Type...................................................................................124.2 Final Energy Demand by Sector.................................................................................12
4.2.1 Household Sector .................................................................................................124.2.2 Commercial Sector...............................................................................................144.2.3 Industrial Sector....................................................................................................164.2.4 Transportation Sector ...........................................................................................174.2.5 Other Sector..........................................................................................................18
Chapter 5 DEVELOPMENT of ENERGY SECTOR .........................................................205.1 Assumptions of Macro Economy ...............................................................................20
5.1.1 GDP Growth .........................................................................................................205.1.2 Population and Population Growth .....................................................................215.1.3 Structure and Growth of Commercial Sector .....................................................255.1.4 Structure and Growth of Industrial Sector..........................................................265.1.5 Growth of Transportation Sector.........................................................................285.1.6 Structure and Growth of Other Sector ................................................................30
5.2 LEAP Result of Baseline Scenario.............................................................................325.2.1 Projection of Household Energy Demand ..........................................................325.2.2 Projection of Commercial Sector Energy Demand............................................36
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5.2.3 Projection of Industrial Sector Energy Demand.................................................385.2.4 Projection of Transportation Sector Energy Demand ........................................405.2.5 Projection of Other Sector Energy Demand .......................................................415.2.6 Projection of Final Energy Demand....................................................................43
5.3 Energy Supply..............................................................................................................45
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List of AbbreviationsADO : Automotive Diesel Oil
BAU : Business as Usual
BOE : Barrel Oil Equivalent
BBM : Fossil Oil FuelDIY : Province of Yogyakarta
GRDP : Gross Regional Domestic Product
IDO : Industrial Diesel Oil
IDR : Currency of Indonesia
JAMALI: Electrical Network Interconnection of Java-Madura-Bali
LPG : Liquefied Petroleum Gas
PLN : National Electricity Company
RUED : Regional Energy Plan Policy
RUKD : General Plan of Regional Electricity
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Chapter 1DESCRIPTION OF SPECIAL REGION OF YOGYAKARTA PROVINCE
1.1 Macro and Social Economic descriptionThe Province of Yogyakarta (DIY, Daerah Istimewa Yogyakarta/Special Region of
Yogyakarta) is located in the middle-southern part of Java Island. The province has administrative boundaries with the Province of Central Java in the northern, western and eastern part, while in the southern part, Yogyakarta has a border with Indonesian /Indian Ocean or in local words “Laut Selatan”. The total provincial area of Yogyakarta is about 3,186.25 m2 andconsists of four regencies and one municipality, i.e. Kulonprogo, Bantul, Gunungkidul, Sleman and Yogyakarta. Demographic information such as total area of each regency, total population , households and population density in Yogyakarta is described in Table 1.1.
Table 1. 1. Demographic overview of province DIY, 2005
No. Regency/Municipality Total Population Number of Household Area (km2)
Population density
(persons/km2)1 Kulonprogo 386,686 106,896 586.72 659 2 Bantul 823,734 240,522 506.85 1.625 3 Gunungkidul 695,748 200,800 1,485.36 468. 4 Sleman 955,124 318,423 574.82 1.661 5 Yogyakarta 420,508 151,420 32.50 12.938
Total in Province 3,281,800 1,018,061 3,186.25 1,029 Source: BPS Yogyakarta
The total population in Yogyakarta is distributed at 59.11% in urban area and 40.89 % in rural. In gender perspective, male and female proportion of Yogyakarta population is almost the same in both urban and rural areas. Data of total population and its structural percentage of Yogyakarta province can be found in Table 1.2 and 1.3.
Table 1. 2. Population distribution in gender and residence (urban-rural area), 2005
Urban RuralRegency/Municipality Male Female Total Male Female Total Total
Kulonprogo 37,944 36,828 74,772 155,044 156,870 311,914 386,686 Bantul 289,872 314,760 604,632 111,300 107,802 219,102 823,734 Gunungkidul 19,832 16,576 36,408 321,030 338,310 659,340 695,748 Sleman 409,464 394,236 803,700 73,346 78,078 151,424 955,124 Yogyakarta 197,505 223,003 420,508 - - - 420,508 Provinsi D.I.Y 954,617 985,403 1,940,020 660,720 681,060 1,341,780 3,281,800 Source : BPS Yogyakarta
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Table 1. 3. Percentage of Population Structure in Yogyakarta Province in 2005
Urban RuralRegency/Municipality Male Female Total Male Female Total
Kulonprogo 50.75% 49.25% 19.34% 49.71% 50.29% 80.66%Bantul 47.94% 52.06% 73.40% 50.80% 49.20% 26.60%Gunungkidul 54.47% 45.53% 5.23% 48.69% 51.31% 94.77%Sleman 50.95% 49.05% 84.15% 48.44% 51.56% 15.85%Yogyakarta 46.97% 53.03% 100.00% 0.00% 0.00% 0.00%Provinsi D.I.Y 49.21% 50.79% 59.11% 49.24% 50.76% 40.89%Source : BPS Yogyakarta
Economic activities in Yogyakarta are mainly concentrated on commercial services with about 23% of the total Gross Regional Domestic Product (GRDP). It is then followed by theagricultural sector which is about 19%. A detail of Yogyakarta’s GRDP information is illustrated in Figure 1.1.
19%
1%
14%
1%8%23%
10%
10%
14% Agriculture
Mining
Manufacture Industry
Utility
Construction
Commercial Service
Transportation
Financial Service
Other Services
Figure 1. 1. GRDP in several sectors of Yogyakarta Province in 2005
The GRDP growth in 2005 decreased compared to GRDP growth in 2004. In 2005, inflation rate was higher than the rate in 2004. GRDP growth and inflation rate of Yogyakarta province is given in Figure 1.2. From this figure, it is shown that GRDP reduced from 5.12 % in 2004 to 4.74 % in 2005, while inflation rate rose significantly from 6.95 % (2004) to 14.98 % (2005).
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0
2
4
6
8
10
12
14
16
2001 2002 2003 2004 2005
Percent
GRDP Growth (%)
Inflation (%)
Figure 1. 2. GRDP growth and inflation rate in Yogyakarta Province
1.2 Economic Activities in Each Sector1.2.1 Household Sector
As mentioned above, the share of total population in Yogyakarta who lives in urban is more than 50 %. However, from Table 1.2 and 1.3, population in Kulonprogo and Gunungkidul regency is dominantly living in rural areas with about 80.66% and 94.77%, respectively. Population in Bantul and Sleman regency who are living in rural are about 26.60% and 15.85%. Composition of population based on gender is almost similar for each regency and municipality. This same composition is also found in urban and rural area.
1.2.2 Commercial SectorBased on type of business and their contribution to the GRDP of Yogyakarta, commercial
sector is divided into six sub-sectors; i.e. hotel, shopping center, restaurant, financial services, entertainment and social service. Added value in each sub-sector over 2001-2005 is shown in Figure 1.3.
Figure 1. 3. Added value in commercial sector
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From Figure 1.3, one can notice that restaurant; financial service and shopping center sub-sectors have the highest level of added value with each sector at about 1,662,981; 1,623,210and 1,462,659, million IDR (million Rp.) respectively. Other sub-sectors have lower levels of added value. Economic details by subsector in the commercial sector are presented in Table 1.4.
Table 1. 4. Added value in commercial sector from 2001 to 2005
Added Value (Constant Price in 2000) (in million IDR)No. Subsector
2001 2002 2003 2004 20051 Hotel 289,057 304,147 322,629 340,362 319,188 2 Shopping center 1,218,785 1,247,964 1,307,280 1,374,914 1,462,659 3 Restaurant 1,256,282 1,362,114 1,467,971 1,564,148 1,662,981 4 Financial service 1,227,184 1,314,860 1,408,894 1,500,542 1,623,210 5 Entertainment 55,106 56,772 57,919 65,442 67,681 6 Social service 374,290 374,515 377,920 387,807 405,129
Total 4,420,704 4,660,371 4,942,613 5,233,216 5,540,848 Source : BPS Yogyakarta
1.2.3 Industrial SectorThe industrial sector in Yogyakarta is divided into eight subsectors, i.e. food, textile,
wood, paper, chemical, non-metal, mechanical and other industrial subsectors. Added value in each subsector for 2001-2005 is shown in Figure 1.4. Its contribution to Yogyakarta’s GRDP is two times smaller than the commercial sector.
Figure 1. 4. Added value in Industrial Sector of Yogyakarta province in 2005
From Figure 1.4, growth in food industry increased significantly between 2001-2005. Other subsectors grew less or remained almost constant. Detailed information related to levels of added value is described in Table 1.5.
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Table 1. 5. Added value in industrial sector from 2001 to 2005
Added Value (Constant Price in 2000) (in million IDR)No. Subsector2001 2002 2003 2004 2005
1 Food 696,555 695,205 742,507 800,848 845,594
2 Textile 465,973 489,219 502,380 508,391 510,219 3 Wood 311,451 316,500 316,920 323,944 323,919 4 Paper 115,899 112,777 122,742 124,966 129,735 5 Chemical 103,019 109,942 110,043 112,353 114,892 6 Non Metal 117,875 139,423 121,658 126,292 129,566 7 Mechanical 224,906 239,015 235,737 225,655 226,719 8 Others 164,222 159,805 173,250 178,328 182,586
Total 2,199,898 2,261,886 2,325,236 2,400,776 2,463,230 Source: BPS Yogyakarta
1.2.4 Transportation SectorIn transportation sector, detailed information related to vehicle stock growth for each
transportation mode in Yogyakarta is described in Table 1.6.Table 1. 6. Transportation sector growth for each transportation mode
No. Type of Mode 2001 2002 2003 2004 20051 Passenger Car (unit) 67,309 70,203 74,728 78,817 82,705 2 Motorcycle (unit) 539,448 597,143 666,941 755,101 843,077 3 Bus (unit) 6,591 7,400 8,039 9,968 14,685 4 Truck (unit) 27,745 30,816 32,520 34,031 35,670 5 Train (1000 Km) 498 561 765 997 798 6 Aeroplane (1000 Km) 3,472 4,141 6,652 8,454 6,650
Source: BPS, Airport, and PT. KAITransportation mode of passenger vehicle/car and motorcycle increases annually with
5.28 % and 11.81 % on average over 2001-2005. Transportation mode of train and airplane decreased over 2004-2005 although there was growth before. For bus and truck, these modes increased with 22.17 % and 6.48 % on average per year, respectively.
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Chapter 2PRIMARY ENERGY SUPPLY
2.1 Domestic Energy SourcesIn order to conduct the economic activities in Yogyakarta province, primary energy has
been supplied from outside sources (Central Java province) particularly for fossil liquid fuel (BBM) and electricity. Fossil liquid fuel is supplied to Yogyakarta from the Pertamina Depot of Rewulu. This Pertamina Depot does not only supply the fuel for Yogyakarta but also for regencies in Central Java which are located near Yogyakarta.
Electricity demand of Yogyakarta is supplied through interconnection with the transmission grid of Java-Madura-Bali (JAMALI). From the JAMALI transmission grid, electricity is connected to PLN customers through the distribution network of Yogyakarta province. The distribution network of Yogyakarta consists of eight electrical relay stations (gardu induk) with each station servicing certain areas in Yogyakarta.
For remote areas which are not accessed by PLN (off grid), the electricity demand is supplied by solar cell photovoltaic electricity generating systems (PLTS). Currently, a PLTS program has installed more than 175 units that are distributed in four regencies, i.e. kabupaten :Sleman, Bantul, Gunungkidul and Kulonprogo.
2.2 Energy Export and ImportIn order to supply the energy needs, the regional government of Yogyakarta needs to
import almost of all primary energy. Fossil liquid fuel is imported from Pertamina Depot of Rewulu while for electricity; it is supplied from the transmission grid at Ungaran, Central Java with the electricity coming from the electrical generator in Cilacap, Central Java.
2.3 Regional Energy PotentialYogyakarta has identified that it does not have any non-renewable energy sources such as
liquid fossil fuels, coal and natural gas. Consequently, these energies must be supplied from other provinces in Indonesia. However, regional government, research institutions, universities and NGO have initiated to focus on the development and use of renewable energy sources such as solar, wind, ocean wave, hydro and biomass.
Until now, several areas are observed that have potential sources of renewable energy. Some of them are not used anymore, for example there was a microhydro power generator but this system is not in operation anymore because there was no maintenance and operating funds available from the DINAS. The renewable energy sources are follow as:
Water/Hydro River/open channel flows is one of the energy sources that can be used to produce
electricity with a generator driven by a turbine in the hydropower plan system (PLTAS). Several data should be considered in order to evaluate the potential energy in such rivers/channels, i.e. debit (volume per time unit, Q), minimum daily flow, daily flow duration and topography area. Thus, the energy potential can be obtained from debit (Q) and water pressure (head, h).
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Currently, several potential locations have been already identified in Kulonprogo andSleman regency. Energy potential sources from hydro and water in Yogyakarta are listed in Table 2.1.
Table 2. 1. Energy Potential from Water/Hydro in Yogyakarta Province
No. Name LocationEstimated Potential/
Caapcity (kW)1 Saluran Kalibawang Kedungrong 1 902 Saluran Kalibawang Kedungrong 2 1003 Saluran Kalibawang Semawung 2004 Saluran Kalibawang Tempel, Pendoworejo, Girimulyo 355 Saluran Kalibawang Kemukus, Tanjungharjo, Nanggulan 5.36 Selokan Kamal Kamal, Giripurwo, Girimulyo 347 Sel. Van Der Wicjk-3 Klagaran, Sedangrejo, Mingir 228 Sel. Van Der Wicjk-4 Kajoran, Banyuredjo, Sayegan, 259 Sel. Van Der Wicjk-5 Kedungprahu, Sendangrejo, Minggir 14.710 Sel. Mataram-1 Gasiran, Banyuredjo, Sayegan 9.511 Sel. Mataram-2 Bluran, Tirtonadi, Mlati 3112 Sel. Mataram-3 Trini, Trihanggo, Gamping 2313 Sel. Mataram 4 Gemawang 3.514 Sel.Mataram 8 Candisari, Kalasan 4.715 Kali Buntung Kricak, Tegalrejo 12.416 Bendung Tegal Tegal, Kebonagung, Imogiri 10617 Sel. Van Der Wicjk-4 Desa Kajoran, Banyuredjo, Sayegan, 2518 Sumber Cincin Guling 1 Gedad, Banyusoco, Playen 3.519 Sumber Cincin Guling 2 Gedad, Banyusoco, Playen 320 Sumber air tejun Slumpret Mengguran, Bleberan, Playeng 41
Total 788.6Source: Dinas Disperindagkop
In Kulonprogo regency, hydropower potential source is found in the irrigation open channels of Kalibawang, which has a relative medium debit flows during a year. This facility is not optimality maintained thus this potential is not used yet. In Sleman regency, hydropower potential sources are from Van der Wijck and Mataram channel.
Other hydropower source is a Sermo Dam. Information from Balai Pengelolaan Sumber Daya Air Progo, Opak and Oyo, said that the Sermo Dam has a main function for irrigation (3,004 Ha) with water debit of 0.13 m3/second, flood protection and water resource in dry season(minimum elevation = 113.70 m). Besides that, Sermo Dam is planned for electricity production (PLTA) with debit of flows 76.62 m3/s and the estimated capacity is about 400 kW. Main constraint of this hydropower source is related to the high fluctuation on debit along years.
Solar EnergySolar energy density in atmosphere is estimated from 1 to 1.4 kW/m2. 30 % from that
density is reflected and 19 % is absorbed by atmosphere components itself such as carbondioxide (CO2), dust and cloud. The rest of energy is absorbed by earth (47%).
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Energy that is absorbed by the earth ultimately is returned to the atmosphere through various processes such as evaporation (± 33%), kinetic energies form of waves, sea flows and wind (± 0.215%), and the form of infrared radiation (± 14%). Meanwhile, only small part (± 0.023%) is still used in the process of photosynthesis to the earth, the need for human metabolism, as well as other purposes such as heating, mobility and mechanization.
It can be said in practice that the intensity of solar energy received by the atmosphere from the sun is about 1353 Watt/m2, while the effective part received by the earth is about 1 kW/m2. It means that if there is an area of 1 m2 which gets effective sunlight on the earth, then the potential energy is approximately 1 kWatt. This energy potential is then decreased significantly when there is a cloud covering the sunlight. The amount of received energy depends on the duration of sunlight which is measured in kWh. Solar energy can be converted into another type of energy by three different ways, i.e. thermal excitation (solar thermal collectors for hot water production), the Photovoltaic (PV for electricity) and the chemical reaction (photosynthesis for biological processes).
Wind EnergyThe wind occurs because of the temperature difference between hot and cold air. In the
equatorial regions (likes Indonesia) with only hot season (dry or wet), air will expand becoming light air and then it moves towards the poles where the air is becoming cold. Energy of the wind energy is kinetic energy; therefore, the wind power is proportional with area (A) and speed of the air (v3).
In order to convert wind energy into electricity, it needs a wind turbine. Until now, there are two types of wind turbine based on the axle position, i.e. horizontal axis wind turbines (HWAT) and vertical axis wind turbine. Advantage of vertical axis wind turbine compared to HWAT is able to receive winds from any directions. The minimum speed for wind turbines that can be used to generate electricity is equal to 3 m/s.
The Province of Yogyakarta has wind energy potential because of its geographic position which is located in the coastal area of southern Java. Detailed data on wind speed and direction per month in Yogyakarta can be seen in Table 2.2 and 2.3.
Table 2. 2. Wind Energy Potential in Yogyakarta
No. Location Wind Speed(m/s) Potential Capacity (MW)
1 Coastal area of Yogyakarta
2.5 - 4 up to 10
2 Sundak, Srandakan, Baron, Samas beach
4 - 5 10 - 100
Source: Dinas Disperindagkop
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Table 2. 3. Wind Speed in Yogyakarta per month
No. Month Wind Direction (degree) Average Wind Speed (m/s)1 January 240 5.142 February 240 4.633 March 120 4.634 April 120 4.635 May 240 4.126 June 240 4.637 July 220 4.638 August 240 5.149 September 240 5.14
10 October 240 5.1411 November 240 5.1412 December 240 5.14
In Yogyakarta, average wind speed is in the ranges of 4.12 to 5.14 m/s. In practice, those speed ranges can be used to operate wind turbines to generate electricity.
BiomassBiomass is an organic fuel can be produced from human activities, animals and plants.
Bioenergy technology allows biomass to be used to generate electricity with a variety of capacities. Bioenergy technology is a technology that uses the resources of renewable biomass to produce a number of related-energy products such as electricity, liquid fuel, solid and gas, heat, chemical materials, etc. Biomass potential in Yogyakarta comes from waste of plantation/agricultural products, which can be seen in Table 2.4.
Table 2. 4. Biomass Potential from Agricultural Waste
Biomass Potential (ton)No. Regency/Municipality
Rice Corn Coconut Sugar Cane1 Kulonprogo 90,886.19 13,315.25 22,525.00 2,176.382 Bantul 128,437.94 17,649.82 11,119.19 5,474.763 Gunungkidul 233,381.07 202,163.16 8,399.05 158.634 Sleman 217,157.97 15,763.29 8,457.83 4,569.225 Yogyakarta 839.83 68.48 80.72 -
Total 670.703.00 248,960.00 50,581.79 12,378.99Sources; BPS
Yogyakarta has also biomass potential from municipal waste. Based on the waste management office, in 2002, there is about 5,703 m3/day of municipal waste production. Almost 35 % of the waste is transferred to the final waste disposal/landfill (TPA) in Yogyakarta. One of the largest TPA is Piyungan is located in Bantul. The area of the disposal location is about 12 hectares and can accommodate 2.7 million cubic meters of waste. Potential urban waste data in each location districts in Yogyakarta is shown in Table 2.5.
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Table 2. 5. Municipal Waste in Yogyakarta
No. Regency/City Waste Production (m3/day)
Carried Waste (m3/day)
Service Ratio
1 Kota Yogyakarta 1,724 1,321 77%2 Sleman 1,268 285 22%3 Bantul 1,145 178 16%4 Kulonprogo 585 78 13%5 Gunungkidul 981 158 16%
Total 5,703 2,020 35%
Animal waste from livestock such as cow, buffalo and goats contains high concentration of cellulose. In addition, it is also formed as liquid waste that can be used as a raw material for biogas. Protein, fat and carbohydrate content in the animal waste are one of the key factors in biogas production. A number of factors, such as temperature, anaerobe condition, acetone bacteria and methane bacteria, influences biogas production from animal wastes. These factors decompose organic materials into biogas. The bacteria will grow rapidly in the temperature of 36.7 - 54.4 oC. Methane bacteria will effectively work in the pH range of 6.8 to 8. Solid concentration in the water is around 3-10 % while reaction time of bacteria is about 10 to 30 days. Practically every cow can produce about 600 liters biogas per day with an energy content of approximately 22.5 MJ per liter of gas. Table 2.6 shows the number of animal that potentially can be used to generate biogas in Yogyakarta.
Table 2. 6. Number of Animals in Yogyakarta
Biogas Potential (#animal)No. Regency/ MunicipalityCow Goat Poultry Pig Buffalo Sheep
1 Kulonprogo 44,478 73,580 2,061,720 - - 1,304 2 Bantul 48,157 33,150 1,895,801 - 2 12,4183 Gunungkidul 109,187 127,112 1,888,063 - - 177 4 Sleman 45,007 30,627 4,856,340 - 44 12,531 5 Yogyakarta 181 212 61,764 3,929 38 3,311
Total 247,010 264,681 10,763,688 3,929 84 29,741 Source: BPS
Biomass potential can also be converted to biofuel from the Casava and Sugar Cane plant. The amount of Casava and Sugar Cane plant in Yogyakarta is shown in Table 2.7.
Table 2. 7. Biofuel Potential
Biofuel Potential (ton)No. Regency/Municipality Cassava Sugar Cane
1 Kulonprogo 47,763.76 2,176.382 Bantul 43,090.56 5,474.763 Gunungkidul 811,028.07 158.634 Sleman 18,996.26 4,569.225 Yogyakarta 30.35 -
Total 920,909.00 12,378.99Source: BPS
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Chapter 3ENERGY TRANSFORMATION
3.1 Transmission and DistributionThe electricity system in Yogyakarta province is part of the electrical power
interconnection system of Madura Jawa Bali (JAMALI), which covers seven provinces in Java and Bali. This system is an interconnection system with extra high voltage of 500 kV which is extending along the Java-Bali Island. This system is the biggest electricity system in Indonesia, which consumes almost 80 % of electricity production. PT. PLN (persero) Yogyakarta APJ has a duty to serve the electricity needs of the community in Yogyakarta. Total consumption of electricity in the Yogyakarta province is about 1,469.34 GWh which is supplied by the eight electrical relay stations with a total capacity of 556 MW. Table 3.1 shows the number, operation and capacity of the electrical relay stations located at Yogyakarta. The completed system JAMALI interconnection in Province of Central Java and Yogyakarta is illustrated in Figure 3.1.
Table 3. 1. Electrical relay Stations in Yogyakarta
No. Name Location Voltage (kV) Power (MVA)1 Kentungan Kabupaten Sleman 150 902 Bantul Kabupaten Bantul 150 1203 Gejayan Kota Yogyakarta 150 1204 Wirobrajan Kota Yogyakarta 150 605 Godean Kabupaten Sleman 150 606 Medari Kabupaten Sleman 150 307 Wates Kabupaten Kulonprogo 150 468 Semanu Kabupaten Gunungkidul 150 30Source: PLN 2006
The distribution network of Yogyakarta has a load factor of 65 % (RUKD DIY, 2004) and a transmission and distribution loss of 8.78% in 2005.
Figure 3. 1. Interconnection system of JAMALI
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Chapter 4FINAL ENERGY DEMAND
4.1 Final Energy Demand by TypeTo reach the 2005 GRDP and to support the activities of households, there are 6 types of
energy used, which are oil fuel, electricity, LPG, biomass, coal, and coal briquette. The amount of each type of energy that has been used can be seen in table 4.1.
Table 4. 1. Final energy demand by type
Type Quantity UnitOil fuel 3.7755 Million BOEElectricity 0.9007 Million BOELPG 0.3702 Million BOEBiomass 0.0033 Million BOECoal 0.0015 Million BOECoal briquette 0.0026 Million BOE
Figure 4. 1. Final energy demand by type
Form table 4.1 and figure 4.1 can be seen that the largest use of energy is oil fuel (BBM) with 3.775 million BOE, and then followed by electricity with 0.9007 million BOE, biomass with 0.0033 million BOE, coal briquette with 0.0026 million BOE, and coal with 0.0015 million BOE.
4.2 Final Energy Demand by Sector4.2.1 Household Sector
The energy demand of household sector is dominated by kerosene, followed by electricity, LPG, coal briquette, and biomass. Kerosene is used for several applications like cooking and lighting. Electricity - if it is used - serves for lighting and communication mainly. The other fuels are mainly for cooking and hot water production. Energy demand by type of household sector is shown in table 4.2 and figure 4.2.
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Tabel 4. 2. Energy demand by type of household sector in Yogyakarta Province, 2005
ruralEnergy demand 2005 (BOE)
No. Income ClassKereosene Electricity LPG Coal
Briquette Biomass
1 Under Poverty Line 9,658.55
15,145.22
-
176,35
171.53
2 Under 1.5 poverty line
45,541.90
40,835.39
-
713,97
579.08
3 Middle
117,981.04
79,717.27
24,134.51
229,35
1.034.58
4 Top 20%
74,112.49
51,200.70
39,783.78
-
479.18
Total
247,293.98
186,898.58
63,918.29
1,119.66
2,264.38
urbanEnergy demand 2005 (BOE)
No. Income ClassKereosene Electricity LPG Coal
Briquette Biomass
1 Under Poverty Line 27,516.92
15,043.16
-
170.11
175.60
2 Under 1.5 poverty line
77,320.87
38,493.28
2,775.44
1,012.33
258.45
3 Middle
301,496.82
180,884.24
140,494.73
299.47
503.48
4 Top 20%
78,335.77
125,606.36
137,175.15
38.15
70.02
Total
484,670.37
360,027.05
280,445.33
1,520.06
1,007.54
Gambar 4. 2. Energy demand by type of household sector in Yogyakarta Province, 2005
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Energy demand of household sector by income class is dominated by middle income class, then followed by top 20%, under 1.5 of poverty line, and under poverty line of income class. The energy demand by income class can be shown in figure 4.3.
Figure 4. 3. Energy demand of household sector by income class, 2005
In figure 4.2 can be seen that kerosene is the largest energy demand of household of 731,964.36 BOE and coal briquette is the smallest energy demand of 2,639.72 BOE. In figure 4.3 can be seen that middle income class consumes energy of about 830,000 BOE. This income class has the largest energy demand compared to other income classes.
4.2.2 Commercial SectorEnergy demand of commercial sector by subsector and by type of energy is shown in
table 4.3.Table 4. 3. Energy demand of commercial sector, 2005
Energy Consumption in 2005 (BOE)No. Subsector
ADO Kerosene Electricity LPG Total1 Hotel and Lodging 34,596.82 75.89 43,906.71 3,677.94 82,257.36 2 Wholesale and Retail - - 45,297.13 2,525.64 47,822.78 3 Restaurant - 2,254.21 117,770.32 15,802.11 135,826.64 4 Financial Services 4,040.00 - 12,237.22 18.21 16,295.42 5 Amusement Services 1,031.05 - 23,513.28 34.58 24,578.91 6 Social Services 1,592.30 - 11,043.14 17.24 12,652.69
Total 41,260.16 2,330.10 253,767.81 22,075.72 319,433.79
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Figure 4. 4. Energy demand of commercial sector by type, 2005
In table 4.3 and figure 4.4 can be seen that electricity has the largest energy demand of commercial sector with 253,767.81 BOE and energy demand of kerosene is the smallest with 2,330.10 BOE.
Figure 4. 5. Energy demand of commercial sector by subsector, 2005
In figure 4.5 can be seen that restaurant is the subsector that consumes the largest amount of energy with 135,826.69 BOE while social services consume the smallest amount of energy with 12,652.69 BOE.
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4.2.3 Industrial SectorEnergy demand of industrial sector by type of energy and by subsector of industry is
given in table 4.4.Tabel 4. 4. Energy demand by subsector in industry, 2005
Energy Consumption in 2005 (BOE)No. Subsector
ADO IDO Kerosene Fuel Oil Electricity LPG Coal Total
1 Food 32,675.96 37.91 15,534.26 21,252.25 12,562.97 1,721.58 - 83,784.93 2 Textile 32,378.11 2,423.19 15,392.66 15,724.53 56,478.75 879.38 1,510.44 124,787.04 3 Wood 764.87 2.09 363.62 589.53 3,111.39 145.29 - 4,976.80 4 Paper 220.79 - 104.96 27.31 1,522.85 5.04 - 1,880.95 5 Chemical 6,872.23 22.75 3,267.08 521.34 5,025.58 16.41 - 15,725.38 6 Non Metal 16,352.61 11.18 7,774.08 4,732.51 5,093.15 865.30 - 34,828.84 7 Machinery 1,423.03 - 676.51 104.74 12,178.30 68.67 - 14,451.26 8 Other 5,388.99 92.92 2,561.94 764.12 4,037.69 50.00 22.10 12,917.76
Total 96,076.59 2,590.03 45,675.12 43,716.34 100,010.67 3,751.66 1,532.54 293,352.96
Gambar 4. 6. Energy demand of industrial sector by type of energy, 2005
In table 4.4 and figure 4.6 it can be seen that electricity is the largest energy consumed by industrial sector with 100,010.67 BOE while coal is the smallest energy with 1,532.54 BOE. Energy demand of industrial sector by subsector of industry is shown in figure 4.7. In figure 4.7 it can be seen that textile industry has the largest demand of energy compared to other subsectors of industry. Energy demand of textile industry in 2005 is 124,787.04 BOE. Paper industry has the smallest energy demand of 1,880.95 BOE.
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Gambar 4. 7. Energy demand of industrial sector by subsector of industry, 2005
4.2.4 Transportation SectorEnergy demand of transportation sector by transportation mode can be shown in table
4.5.Table 4. 5. Energy demand of transportation sector, 2005
Energy Consumption in 2005 (BOE)No. SubsectorPremium ADO Avtur Total
1 Passenger Car (unit) 891,208.84 50,211.14 - 941,419.98 2 Motorcycle (unit) 845,500.91 - - 845,500.91 3 Bus (unit) - 127,870.69 - 127,870.69 4 Truck (unit) 268,154.21 315,775.73 - 583,929.94 5 Railway (1000 Km) - 4,507.51 - 4,507.51 6 Aeroplane (1000 Km) - - 243,109.19 243,109.19
Total 2,004,863.96 498,365.07 243,109.19 2,746,338.22
Figure 4. 8. Energy demand of transportation sector by type of energy, 2005
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In table 4.5 and figure 4.8 it can be seen that premium is the largest energy demand of transportation sector. The amount of premium in 2005 for transportation sector is 2,004,863.96BOE while avtur that is used by air transport, is the smallest energy demand with 243,109.19 BOE.
Figure 4. 9. Energy demand of transportation sector, 2005
Energy demand of transportation sector by transportation mode can be shown in figure 4.9. Energy demand of passenger car is the largest of 941.419,98 BOE while train consumed the smallest energy demand of 14,874.78 BOE.
4.2.5 Other SectorEnergy demand of other sector by type of energy and by subsector shown in table 4.6.Table 4. 6. Energy demand of other sector, 2005
Energy Consumption in 2005 (BOE)No. SubsectorKerosene ADO Total
1 Construction - 30,620.40 30,620.40 2 Agriculture 105.90 23,743.13 23,849.02 3 Mining - 699.65 699.65
Total 105.90 55,063.17 55,169.07
In table 4.6 and figure 4.10 can be seen that demand of ADO as energy type is dominating the energy demand of other sector. ADO is used as fuel for off-road vehicles and machinery. The demand of ADO in other sector for 2005 of 55,063.17 BOE while energy demand of kerosene of105.90 BOE.
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Figure 4. 10. Energy demand of other sector by type of energy, 2005
Figure. 11. Energy demand of other sector by subsector, 2005
The energy demand of other sector by subsector can be seen in figure 4.11. Construction subsector has the largest energy demand of 30,620.40 BOE while mining subsector has the smallest energy demand of 699.65 BOE.
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Chapter 5DEVELOPMENT of ENERGY SECTOR
5.1 Assumptions of Macro EconomyThe specification of energy model has base year of 2005 and the end of projection year of
2025. The assumptions of the energy model will be described in the following sections. For the Business As Usual scenario (BAU) described here, the general approach is that it mainly assumes the continuation of the current situation and of trends observed over 2001-2005. It also assumes no change in policy nor any targets related to bio-energy or fuel switch. Also no assumptions about autonomous efficiency improvements or behavioral changes are incorporated. .This means that end use fuel intensities remain constant over the whole projection period. As such it is quite a conservative approach, but well defined to represent a BAU.
The fuel intensities are expressed per unit of activity of the respective sector, e.g. per inhabitant for households, per value added for commercial, industrial and other sectors’’ activities. Final energy consumptions is obtained by multiplying the demand level activity with these fuel intensities. Therefore, a lot of attention has been given to a valid demand level projection for the BAU scenario.
5.1.1 GDP GrowthThe Gross Regional Domestic Product (GRDP) is the total income of population in
economic activity or the total expenditure for goods and services in economic activity of a province or region. GRDP is the best indicator of a province or state economy. Sectoral production that compose the GRDP are agriculture, mining, manufacturing industry, utility, construction, commercial services, transportation, financial services, and other services.
With the assumption that social, economy, politic, and national security are in normal condition, GRDP growth to the end of the projection year is assumed at about 5% per year, while GRDP growth of base year 2005 was 4.75%. GRDP growth assumption is produced by simple regression method based on the time series data of GRDP form 2001 to 2005. The result of regression of GRDP growth can be shown in figure 5.1.
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Figure 5. 1. GRDP growth based on regression method from 2005 to 2025
In figure 5.1 can be seen that the average growth of GRDP from 2006 to 2025 is 4.96%.
5.1.2 Population and Population GrowthPopulation growth for each regency and city in Yogyakarta Province is calculated by
time series data analysis using a linear regression method. The population growth by the end of the projection period is shown in table 5.1.
Table 5. 1. Population growth in regency and city
regency/manucipality 2005 2025Kulonprogo 0.15% 0.10%Bantul 1.99% 0.90%Gunungkidul 0.33% 0.13%Sleman 1.87% 1.38%Yogyakarta 1.82% 1.47%
In table 5.1 can be seen that population growth rate in each regency and city by the end of projection period is decreasing.
The shift of rural and urban composition of the population also has been calculated by linear regression method. The result of composition shift calculation is given in table 5.2.
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Table 5. 2. Composition shift of rural and urban population
Regency/manucipality 2005 2010 2015 2020 2025Kulonprogo rural 82.04% 75.66% 67.08% 59.19% 51.90%
urban 17.96% 24.34% 32.92% 40.81% 48.10%Bantul rural 29.94% 27.90% 26.38% 25.24% 23.09%
urban 70.06% 72.10% 73.62% 74.76% 76.91%Gunungkidul rural 93.33% 92.38% 91.85% 90.84% 89.54%
urban 6.67% 7.62% 8.15% 9.16% 10.46%Sleman rural 20.92% 17.39% 13.70% 10.54% 7.11%
urban 79.08% 82.61% 86.30% 89.46% 92.89%Yogyakarta urban 100.00% 100.00% 100.00% 100.00% 100.00%
In table 5.2 can be seen that the composition of urban population is getting bigger along projection period in all regency except for Yogyakarta city where there is only urban population.
Household activity growth is represented by the growth of population. In the baseline scenario of the energy model LEAP, the growth of household activity is projected for each regency and city in Yogyakarta Province that is shown in figure 5.2.
Figure 5. 2. Growth of household activity for each regency and city
In figure 5.2 it can be seen that Sleman regency has the biggest population compared to other regencies or city while Kulonprogo regency has the smallest population along the projection period. The detail of population growth for each regency and city is shown in table 5.3.
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Table 5. 3. Growth of household activity for each regency and city
Population (thousand People)Regency/municipality2005 2010 2015 2020 2025
Kabupaten Kulonporgo 386.69 389.45 391.99 394.30 396.37 Kabupaten Bantul 823.73 901.76 974.04 1,038.07 1,091.50 Kabupaten Gunungkidul 695.75 706.25 715.12 722.30 727.73 Kabupaten Sleman 955.12 1,044.06 1,134.42 1,225.19 1,315.27 Kota Yogyakarta 420.51 459.01 498.88 539.89 581.76 Total 3,281.80 3,500.52 3,714.44 3,919.75 4,112.64
Household activity for each regency and city is categorized in rural and urban population. Each rural and urban population is classified in four income classes, which are:
1. Under poverty line (class A)2. Under 1.5 of poverty line (class B)3. Middle Income (class C)4. Top 20% of Income (class D)
The poverty line along projection year is assumed to increase, therefore the composition of income classes for rural and urban in each regency and city remains constant in the BAU scenario.
Growth of household activity for rural and urban in each regency and city can be shown in figure 5.3 and figure 5.4.
Figure 5. 3. Growth of rural household activity
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Figure 5. 4. Growth of urban household activity
In figure 5.3 can be seen that rural population has decreased by the end of projection year. The decreasing of rural population is caused by urbanization along projection period. As the result, population in urban area will increase by the end of projection year. This can be seen in figure 5.4. Detail of activity growth in rural and urban area can be shown in table 5.4 and table 5.5.
Table 5. 4. Growth of rural household activity
Population (thousand People)Regency/Municipality2005 2010 2015 2020 2025
Kabupaten Kulonporgo 317.09 290.02 262.44 234.29 205.72 Kabupaten Bantul 247.12 254.93 258.61 257.65 252.03 Kabupaten Gunungkidul 649.34 652.43 653.91 653.61 651.61 Kabupaten Sleman 199.81 182.40 159.05 129.38 93.52 Kota Yogyakarta - - - - -Total 1,413.36 1,379.78 1,334.00 1,274.93 1,202.87
Tabel 5. 5. Growth of urban household activity
Population (thousand People)Regency/Municipality2005 2010 2015 2020 2025
Kabupaten Kulonporgo 69.60 99.43 129.55 160.01 190.65 Kabupaten Bantul 576.61 646.83 715.43 780.42 839.47 Kabupaten Gunungkidul 46.41 53.82 61.21 68.69 76.12 Kabupaten Sleman 755.31 861.66 975.37 1,095.81 1,221.75 Kota Yogyakarta 420.51 459.01 498.88 539.89 581.76 Total 1,868.44 2,120.75 2,380.45 2,644.82 2,909.76
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5.1.3 Structure and Growth of Commercial SectorCommercial sector is divided into six subsectors, which are hotel and lodging, wholesale
and retail, restaurant, financial services, amusement services, and social services. Structural change of commercial sector is calculated by linear regression method based on time series data collection from 2001 to 2005. The result of the linear regression calculation is shown in figure 5.5.
Gambar 5. 5. Structural change in commercial sector form 2005 to 2025
Based on the calculation result presented in figure 5.5, it can be seen that there are changes in all commercial subsectors. The detail change of commercial structure along projection period is given in table 5.6.
Table 5. 6. Structural change of commercial sector
Percentager of value addedSub Sector2005 2010 2015 2020 2025
Hotel and Lodging 5.76% 5.17% 4.58% 4.00% 3.41%Restaurant 26.40% 24.78% 23.16% 21.55% 19.93%Trading 30.01% 31.78% 33.54% 35.30% 37.07%Financial & Business Service
29.30% 30.79% 32.28% 33.77% 35.26%
Amusement Service 1.22% 1.20% 1.17% 1.15% 1.12%Social Service 7.31% 6.29% 5.26% 4.24% 3.21%Total 100.00% 100.00% 100.00% 100.00% 100.00%
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Commercial sector growth is assumed correlated with GRDP growth. From the historic data over 2001-2005, a growth elasticity of 1.227 can be determined. This elasticity has been used in the projection of the whole commercial sector’s activity. The growth of commercial sector for each subsector can be shown in figure 5.6 and table 5.7.
Figure 5. 6. Value added growth of commercial sector
In figure 5.6 it can be seen that restaurant subsector has the biggest value added. The detail of value added growth of commercial sector can be seen in table 5.7.
Table 5. 7. Value added growth of commercial sector (in 1.000.000 juta rupiah)
Value added (1.000.000 juta rupiah)Sub Sector 2005 2010 2015 2020 2025
Hotel and Lodging
0.32
0.38
0.45
0.53
0.60
Restaurant
1.46
1.83
2.28
2.84
3.53
Trading
1.66
2.34
3.30
4.66
6.57
Financial & Business Service
1.62
2.27
3.18
4.45
6.25
Amusement Service
0.07
0.09
0.12
0.15
0.20
Social Service
0.40
0.46
0.52
0.56
0.57
Total
5.54
7.37
9.84
13.19
17.73
5.1.4 Structure and Growth of Industrial SectorIndustrial sector is divided into eight subsectors, which are food, textile, paper, chemical,
Non-metal, machinery, and other industry. Structural change in industrial sector is also calculated by linear regression method. The result of linear regression calculation is shown in figure 5.7.
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Figure 5. 7. Structural change in industrial sector from 2005 to 2025
In figure 5.7 can be seen that progressive change occur in food industry while other sectors will have decreasing contributions to the industrial sector economic value along the projection period. The detail on the structural change of industrial sector can be seen in table 5.8.
Table 5. 8. Structural change in industrial sector
Percentage of Value Added (%)Sub Sector 2005 2010 2015 2020 2025
Chemistry 34.33% 38.42% 42.51% 46.60% 50.69%Textile 20.71% 19.75% 18.78% 17.82% 16.85%Wood 13.15% 11.95% 10.75% 9.56% 8.36%Paper 5.27% 5.26% 5.25% 5.24% 5.23%Chemistry 4.66% 4.47% 4.29% 4.10% 3.91%Non Metal 5.26% 4.75% 4.25% 3.75% 3.24%Machinery 9.20% 8.00% 6.80% 5.61% 4.41%Others 7.42% 7.39% 7.37% 7.34% 7.31%Total 100.00% 100.00% 100.00% 100.00% 100.00%
Activity growth of industrial sector is assumed correlated with GDP growth. From the historic data over 2001-2005, a growth elasticity of 0.606 related to GRDP growth can be determined. This elasticity has been used in the projection of the whole industrial sector’s activity. The growth of industrial sector for each subsector of industry is shown in figure 5.8.
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Figure 5. 8. Value added growth of industrial sector
In figure 5.8 can be seen that food industry has more value added than other subsector of industry. Detailed value added growth for each subsector of industry is given in table 5.9.
Table 5. 9. Value added growth of industrial sector
Value added (1.000 juta rupiah)Sub Sector2005 2010 2015 2020 2025
Chemistry
845.63
1,091.85
1,396.37
1,772.54
2,236.82
Textile
510.13
561.27
616.89
677.82
743.55
Wood
323.91
339.61
353.12
363.64
368.91
Paper
129.81
149.48
172.45
199.32
230.79
Chemistry
114.79
127.03
140.92
155.95
172.54
Non Metal
129.57
134.99
139.60
142.64
142.97
Machinery
226.62
227.35
223.37
213.39
194.60
Others
182.77
210.02
242.09
279.19
322.57
Total
2,463.23
2,841.89
3,284.80
3,803.73
4,412.75
5.1.5 Growth of Transportation SectorTransportation sector consist of land transportation and air transportation. Land
transportation mode consists of road transportation, which is passenger car, motor cycle, bus, truck, and railway. The growths of transportation sector modes are calculated by:
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)).(1(1 ttt GUU eq. 1
where Ut is the number of transportation activity in year t, Ut-1 is the number of transportation activity in previous year, ε is the elasticity of transportation activity to GRDP, and Gt is GRDP growth in year t.
The initial elasticity is based on analysis of historic data, however plain extrapolation of these elasticities in the demand function lead to unrealistic values by 2025, i.e. more motorcycles than inhabitants for Yogyakarta. Therefore, a relaxation of the elasticities was introduced in order to result in a growing but maturing transportation demand.
Along the projection year, elasticity of each transportation modes are assumed as in table 5.10.
Tabel 5. 10. Elasticity of transportation sector
ElasticityTransportation Mode2005 2010 2012 2025
Passenger car 1.117 1.000 0.800 0.500 Motor Cycle 2.495 1.000 0.800 0.500 Bus 4.871 1.000 0.800 0.500 Truck 1.376 1.000 0.800 0.500 Railway 3.133 1.000 0.800 0.500 Airplane 4.524 1.000 0.800 0.500
The growth of transportation activity of road transportation based on equation 1 and the elasticity in table 5.10 is shown in figure 5.9.
Figure 5. 9. Growth of road transport activity
In figure 5.9 can be seen that transportation activity along projection year is still dominated by motorcycle. Detail of road transport activity growth can be shown in table 5.11.
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Table 5. 11. Growth of road transport activity
Number of Vehicle (unit)Type of Vehicle2005 2010 2015 2020 2025
Passenger car 82.70 105.61 127.51 149.62 171.08 Motor Cycle 843.08 1,217.37 1,469.85 1,724.67 1,971.99 Bus 14.69 25.95 31.33 36.76 42.04 Truck 35.67 46.63 56.30 66.06 75.53
Transportation activity growth of railway and airplane based on equation 1 and elasticity in table 5.10 can be shown in figure 5.10.
Figure 5. 10. Growth of transportation activity of railway and airplane
In figure 5.10 can be seen that airplane activity in the end of projection year is tripled and railway activity is doubled from base year activity level. Policy plans to increase airport capacity and transport underpin these assumptions. The detail of railway and airplane activity growth can be shown in table 5.12.
Table 5. 12. Railway and airplane activity growth
Vehicle-Km (million Km)Transportation Mode2005 2010 2015 2020 2025
Railway 0.80 1.22 1.47 1.73 1.97 Airplane 6.65 11.42 13.79 16.18 18.50
5.1.6 Structure and Growth of Other SectorOther sector consists of three subsectors, which are construction, farming, and mining.
Structural change of other sector is determined by linear regression method based on time series data collection from 2001 to 2005. The result of the linear regression of structural change in other sector can be seen in figure 5.11.
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Figure 5. 11. Structural change of other sector form 2005 to 2025
In figure 5.11 it can be seen that there will be an opposite change between construction and farming subsector. This shows a shift from farming fields to construction land area along the projection period. For the mining subsector, the percentage is almost remaining constant. The detailed structural change of other sector can be shown in table 5.13.
Table 5. 13. Structural change in other sector
Percentage of Value AddedSub Sector2005 2010 2015 2020 2025
Construction 29.66% 37.99% 46.31% 54.64% 62.97%Agriculture 67.74% 59.80% 51.87% 43.94% 36.00%Mining 2.60% 2.21% 1.82% 1.42% 1.03%
The growth of other sector activity (in million thousand rupiah) is shown in figure 5.12. In this figure can be shown that construction subsector is progressing to increase along projection period while agriculture and mining subsector remaining constant. Detailed growth of other sector activity can be shown in table 5.14.
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Figure 5. 12. Growth of other sector activity
Tabel 5. 14. Growth of other sector value added
Value added (1.000.000 juta rupiah)Sub Sector2005 2010 2015 2020 2025
Construction 1.39 2.21 3.34 4.90 7.05 Agriculture 3.18 3.48 3.74 3.94 4.03 Mining 0.12 0.13 0.13 0.13 0.12 Total 4.70 5.82 7.21 8.97 11.19
5.2 LEAP Result of Baseline Scenario5.2.1 Projection of Household Energy Demand
Energy demand of household sector is categorized into rural and urban area with five type of energy being projected, which are kerosene, electricity, LPG, wood, and coal briquette. Each rural and urban area energy demand is also projected by income class. The projection result of energy demand of household sector in Yogyakarta Province by type of energy is shown in figure 5.13. In this figure it can be seen that energy demand of household in the province is dominated by demand for kerosene with 950.37 thousand BOE in 2025; kerosene being the main fuel for cooking as well as for lighting applications. Detailed of energy demand in Yogyakarta Province by type of energy is shown in table 5.15.
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Figure 5. 13. Energy demand projection of household sector by type of energy in Yogyakarta Province
Table 5. 15. Energy demand in household sector by type of energy in Yogyakarta Province
energy demand (thousand BOE)type of energy2005 2010 2015 2020 2025
Kerosene 731.95 787.92 843.62 898.10 950.37 Electricity 546.90 654.01 768.93 849.81 928.52 LPG 344.36 380.43 417.21 454.30 491.24 Wood 3.27 3.38 3.47 3.55 3.61 Coal Briquette 2.64 2.81 2.99 3.16 3.32 Total 1,629.12 1,828.56 2,036.23 2,208.91 2,377.06
Energy demand projection by type of energy for rural and urban area can be shown in figure 5.14 and figure 5.15. As highly urbanized area, there is little fire wood consumption in Yogyakarta
Figure 5. 14. Energy demand projection by type of energy for rural area
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Figure 5. 15. Energy demand projection by type of energy for urban area
It can be seen, in figure 5.14, that total energy demand of rural area slightly increasesfrom 2005 to 2015 and start to decrease until 2025. This phenomenon occurs as a result of population shift form rural to urban area. The urbanization causes increase of energy demand in urban area. This can be seen in figure 5.15. Based on this assumption, urban activity will increase along projection year causing increasing energy demand of urban area. Detailed energy demand projection by type of energy for rural and urban area is shown in table 5.16 and table 5.17.
Table 5. 16. Energy demand by type of rural area
energy demand (thousand BOE)type of energy2005 2010 2015 2020 2025
Kerosene 247.36 240.69 231.84 220.74 207.35 Electricity 186.95 201.28 211.99 218.17 219.01 LPG 63.97 63.49 62.31 60.39 57.71 Wood 2.28 2.21 2.16 2.08 1.97 Coal Briquette 1.10 1.08 1.04 0.99 0.93 Total 501.64 508.75 509.34 502.37 486.97
Tabel 5. 17. Energy demand by type of rural area
energy demand (thousand BOE)type of energy2005 2010 2015 2020 2025
Kerosene 484.59 547.22 611.77 677.35 743.04 Electricity 359.94 452.73 556.95 631.64 709.52 LPG 280.41 316.94 354.90 393.91 433.52 Wood 1.00 1.16 1.32 1.48 1.63 Coal Briquette 1.53 1.73 1.95 2.16 2.37 Total 1,127.47 1,319.79 1,526.88 1,706.52 1,890.10
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In table 5.16, it can be seen that energy demand of all type of energy in rural area is decreasing except for electricity. The increasing of electricity demand in rural area is caused by the assumed 100% electrification ratio to be reached in 2025 for all income classes. For urban energy demand, in table 5.17, all types of energy are increasing along the projection period.
Energy demand projection of household sector in Yogyakarta Province by income classes for rural and urban area can be shown in figure 5.16 and figure 5.17.
Figure 5. 16. Energy demand projection of rural area by income classes
Figure 5. 17. Energy demand projection of urban area by income classes
In both figure of figure 5.16 and figure 5.17, it can be seen that middle income class has the largest energy demand in rural and urban area, followed by top 20% income class, 1.5 of
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poverty line income class, and under poverty line income class. Detailed energy demand projection by income classes can be shown in table 5.18 and table 5.19.
Table 5. 18. Energy demand projection of rural area by income classes
energy demand (thousand BOE)Jenis Energi2005 2010 2015 2020 2025
Under Poverty Line 25.15 27.51 29.70 31.63 33.28 Under 1.5 of Poverty Line 87.69 91.27 93.82 95.16 95.11 Middle Income 223.16 227.27 227.65 223.63 214.55 Top 20% of Income 165.65 162.72 158.18 151.97 144.03 Total 501.64 508.75 509.34 502.37 486.97
Tabel 5. 19. Energy demand projection of urban area by income classes
energy demand (thousand BOE)Jenis Energi2005 2010 2015 2020 2025
Under Poverty Line 42.90 53.11 64.26 76.29 89.10 Under 1.5 of Poverty Line 119.85 144.07 170.30 198.27 227.62 Middle Income 623.63 736.11 858.98 950.94 1,044.44 Top 20% of Income 341.11 386.52 433.35 481.03 528.94Total 1,127.47 1,319.79 1,526.88 1,706.52 1,890.10
5.2.2 Projection of Commercial Sector Energy DemandTypes of energy that are projected in commercial sector are kerosene, ADO, LPG, and
electricity. Projection of commercial energy demand is determined by value added of commercial sector that represents the commercial sector’s activity and the energy intensity of commercial sector for each type of energy (in BOE per value added). As explained before, for the BAU a constant fuel intensity level of 2005 is assumed. Energy demand by type of energy along projection period is shown in figure 5.20.
Figrue 5. 18. Projection of commercial sector energy demand by type of energy
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In figure 5.20, it can be seen that use of electricity dominates the energy demand along projection period. Energy demand of electricity in 2025 will reach an amount of 640.16 thousand BOE. Total energy consumption in the commercial sector triples over 2005-2025 as does its contribution to GRDP. Detailed energy projection of commercial sector is given in table 5.20.
Tabel 5. 20. Projection of commercial sector energy demand by type of energy
energy demand (thousand BOE)type of energy2005 2010 2015 2020 2025
kerosene 2.34 3.28 4.60 6.46 9.09 ADO 41.26 50.14 60.61 72.72 86.38 electricity 253.73 335.23 444.50 591.49 789.90 LPG 22.07 29.89 40.61 55.36 75.72 Total 319.40 418.54 550.31 726.03 961.08
Energy projection of commercial sector by subsector is shown in figure 5.21. In this figure, it can be seen that restaurant has the largest demand of energy compared to other subsectors. Energy demand of restaurant in 2025 is 435.18 thousand BOE, near half of the total. Detailed projection of commercial energy demand can be shown in table 5.21.
Figure 5. 19. Projection of commercial energy demand by subsector
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Table 5. 21. Projection of commercial energy demand by subsector
energy demand (thousand BOE)Sub Sector2005 2010 2015 2020 2025
Hotel and Lodging 82.25 98.26 116.28 135.85 155.85 Wholesale and Retail 47.83 59.73 74.55 92.92 115.58 Restaurant 135.82 191.31 269.61 380.28 536.97 Financial Services 16.30 22.79 31.89 44.71 62.78 Amusement Services 24.55 31.99 41.81 54.83 72.13 Social Services 12.65 14.47 16.17 17.44 17.78 Total 319.40 418.54 550.31 726.03 961.08
5.2.3 Projection of Industrial Sector Energy DemandThe types of energy that are projected in the industrial sector are coal briquette, LPG,
electricity, fuel oil, IDO, ADO, and kerosene. Projection of industrial energy demand is determined by the forecast of value added of industrial sector that represent the industrial sector’s activity and the energy intensity of industrial sector for each type of energy (in BOE per value added). Projection of industrial sector energy demand along projection period can be seen in figure 5.22.
Figure 5. 20. Projection of industrial sector energy demand by type of energy
In figure 5.22, it can be seen that ADO has the largest demand of energy type of 251.92 thousand BOE, closely followed by electricity with 220.89 thousand BOE. Fuel oil use of 126.39 thousand BOE, kerosene of 119.77 thousand BOE, LPG of 10.34 thousand BOE, IDO of 5.56 thousand BOE, and coal briquette of 3.24 thousand BOE are the other consumption levels. Detailed projection of industrial energy demand can be shown in table 5.21.
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Table 5. 22. Projection of industrial sector energy demand by type of energy
energy demand (thousand BOE)type of energy2005 2010 2015 2020 2025
Kerosene 45.67 52.84 61.24 71.11 82.71 ADO 96.07 111.14 128.81 149.57 173.98 IDO 2.59 2.86 3.15 3.48 3.84 fuel oil 43.71 51.88 61.64 73.31 87.29 Electricity 100.00 111.10 123.46 137.23 152.56 LPG 3.75 4.40 5.16 6.07 7.14 coal briquette 1.53 1.69 1.86 2.04 2.24 Total 293.33 335.89 385.31 442.80 509.77
Projection of industrial energy demand by subsector is shown in figure 5.23.
Figure 5. 21. Projection of industrial energy demand by type of energy
Table 5. 23. Projection of industrial energy demand by type of energy
energy demand (thousand BOE)Sub Sector2005 2010 2015 2020 2025
Food 83.78 108.18 138.35 175.62 221.62 Textile 124.77 137.24 150.88 165.74 181.86 Wood 4.98 5.22 5.43 5.59 5.67 Paper 1.88 2.17 2.50 2.89 3.35 Chemistry 15.71 17.40 19.26 21.33 23.62 Non Metal 34.83 36.33 37.53 38.29 38.43 Machinery 14.44 14.50 14.25 13.60 12.40 Others 12.93 14.86 17.11 19.74 22.82 Total 293.33 335.89 385.31 442.80 509.77
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In figure 5.23, it can be seen that in 2025 food industry will has the largest energy demand in industrial sector with 221.62 thousand BOE. The growth of energy demand in food industry is inline with the growth of GRDP in food industry. Detailed projection of industrial energy demand by subsector are shown in table 5.23.
5.2.4 Projection of Transportation Sector Energy DemandTypes of energy that will be projected in transportation sector are premium as passenger
car and motorcycle fuel, ADO as fuel for passenger car, truck, bus, and train, and avtur as airplane fuel. Energy projection of road transportation is determined by unit of vehicle that represent road transportation activity and energy intensity of road transportation (BOE per unit vehicle). Railway and airplane energy projection are determined by vehicle-km that represent transportation activity and also its energy intensity (BOE per vehicle-km). The result of energy projection of transportation sector by type of energy can be shown in figure 5.24.
Figure 5. 22. Projection of transportation sector energy demand by type of energy
In figure 5.24, it can be seen that use of premium will dominate transportation energy demand along projection year. In 2025 the use premium has the amount of 2,865.39 thousand BOE. Detailed energy projection of transportation sector by type of energy is shown in table 5.24.
Table 5. 24. Projection of transportation sector energy demand by type of energy
energy demand (thousand BOE)type of energy2005 2010 2015 2020 2025
Premium 2,004.89 2,709.47 3,271.42 3,838.55 4,389.02 ADO 508.73 725.58 876.06 1,027.94 1,175.35 Avtur 244.72 420.19 507.34 595.29 680.66 Total 2,758.34 3,855.23 4,654.82 5,461.78 6,245.02
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Projection of transportation energy demand by transportation mode is shown in figure 5.25.
Figure 5. 23. Projection of transportation sector energy demand by transportation mode
In figure 5.25, it can be seen that motorcycle and passenger car will dominate energy demand in transportation sector along projection period. In 2025, they will consume an amount of energy of 1,947.33 thousand BOE and 1,977.71 thousand BOE respectively. Detailed energy demand of transportation sector by transportation mode is shown in table 5.25.
Table 5. 25. Projection of transportation sector energy demand by transportation mode
energy demand (thousand BOE)mode of transportation 2005 2010 2015 2020 2025Passenger Car (unit) 941.42 1,202.14 1,451.47 1,703.10 1,947.33 Motorcycle (unit) 845.52 1,220.90 1,474.12 1,729.67 1,977.71 Bus (unit) 127.87 225.96 272.83 320.13 366.03 Truck (unit) 583.93 763.34 921.65 1,081.43 1,236.51 Train (1000 Km) 14.87 22.70 27.41 32.16 36.78 Airplane (1000 Km) 244.72 420.19 507.34 595.29 680.66 Total 2,758.34 3,855.23 4,654.82 5,461.78 6,245.02
5.2.5 Projection of Other Sector Energy DemandTypes of energy that will be projected in other sector are ADO and kerosene. Projection
of energy demand in the other sectors is determined by their value added that represents other sector activity and the energy intensity of other sector for each type of energy (in BOE per value added). Projection of other sector energy demand along projection period is shown in figure 5.26.
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In figure 5.26, it can be seen that energy type of ADO will dominate energy demand of other sector along projection period. ADO is the main fuel of the off-road vehicles and machines used in these sectors. In 2025, demand of ADO to run other sector activity will have an amount of 185.27 thousand BOE and kerosene of 0.13 thousand BOE. Detailed energy demand projection of other sector by type of energy is shown in table 5.26.
Figure 5. 24. Projection of other sector energy demand by type of energy
Tabel 5. 26. Projection of other sector energy demand by type of energy
energy demand (thousand BOE)type of energy2005 2010 2015 2020 2025
kerosene 0.11 0.11 0.12 0.13 0.13 ADO 55.06 75.16 101.97 137.70 185.27 Total 55.17 75.28 102.10 137.83 185.41
Projection of other sector energy demand by subsector is shown in figure 5.27. In this figure, it can be seen that construction subsector has the largest energy demand in 2025 of 154.60 thousand BOE, followed by agriculture of 30.15 thousand BOE, and mining of 0.66 thousand BOE. Detailed energy demand projection of other sector by subsector is shown in table 5.27.
Tabel 5. 27. Projection of other sector energy demand by subsector
energy demand (thousand BOE)Sub Sector2005 2010 2015 2020 2025
Construction 30.62 48.50 73.33 107.59 154.60 Agriculture 23.85 26.04 28.01 29.50 30.15 Mining 0.70 0.73 0.75 0.73 0.66 Total 55.17 75.28 102.10 137.83 185.41
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Figure 5. 25. Projection of other sector energy demand by subsector
5.2.6 Projection of Final Energy DemandProjection of final energy demand in Yogyakarta Province from 2005 to 2025 by type of
energy is shown in figure 5.28.
Figure 5. 26. Projection of final energy demand in Yogyakarta Province by type of energy
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In figure 5.28, it can be seen that demand of energy type of premium will still dominate along projection year. Demand of energy type of premium is used to run the transportation sector and in particular motorcycles and cars. In 2025, premium will have a demand of 4,389.02 thousand BOE. Detailed projection of final energy demand by type of energy is shown in table 5.28.
Tabel 5. 28. Projection of final energy demand in Yogyakarta Province by type of energy
energy demand (thousand BOE)type of energy2005 2010 2015 2020 2025
Premium 2,004.89 2,709.47 3,271.42 3,838.55 4,389.02 Kerosene 780.06 844.15 909.58 975.79 1,042.31 ADO 701.12 962.02 1,167.45 1,387.92 1,620.99 IDO 2.59 2.86 3.15 3.48 3.84 Fuel Oil 43.71 51.88 61.64 73.31 87.29 Electricity 900.64 1,100.34 1,336.90 1,578.53 1,870.98 LPG 370.19 414.72 462.99 515.72 574.10 Wood 3.27 3.38 3.47 3.55 3.61 Coal briquette 4.17 4.50 4.84 5.20 5.55 Avtur 244.72 420.19 507.34 595.29 680.66 Total 5,055.35 6,513.49 7,728.77 8,977.35 10,278.34
Projection of final energy demand by sector is shown in figure 5.29. In this figure, it can be seen that transportation sector will dominate final energy demand along projection period. Transportation energy demand in 2025 will reach 6,245.02 thousand BOE. Detailed projection of final energy demand is shown in table 5.29.
Figure 5. 27. Projection of final energy demand in Yogyakarta Province by sector
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Tabel 5. 29 Projection of final energy demand in Yogyakarta Province by sector
energy demand (thousand BOE)Sector2005 2010 2015 2020 2025
Household 1,629.12 1,828.56 2,036.23 2,208.91 2,377.06 Commercial 319.40 418.54 550.31 726.03 961.08 Industrial 293.33 335.89 385.31 442.80 509.77 Transportation 2,758.34 3,855.23 4,654.82 5,461.78 6,245.02 Other Sector 55.17 75.28 102.10 137.83 185.41 Total 5,055.35 6,513.49 7,728.77 8,977.35 10,278.34
5.3 Energy SupplyAs Yogyakarta has no own energy resources, all energy consumed in the final demand
sectors is imported. As such, supply is equal to demand, except for electricity where grid losses play a minor role since also electricity is imported from the JAMALI grid. In this BAU, no exploration of the utilization of Yogyakarta’s renewable energy resources has been done, this is part of the regional energy policy scenario (RUED) will be developed in the Regional Energy Outlook Report.