- Email: [email protected]
Geo-enabled Decision Support System for Potential Clean Energy Mix for Bali, Indonesia
Available online at www.sciencedirect.com
ScienceDirect Energy Procedia 103 (2016) 333 – 338
Applied Energy Symposium and Forum, REM2016: Renewable Energy Integration with Mini/Microgrid, 19-21 April 2016, Maldives
Geo-enabled decision support system for potential clean energy mix for Bali, Indonesia Bhuwneshwar Prasad Saha* a
Asian Development Bank (ADB), 6 ADB Avenue, Mandaluyong City 1550, Metro Manila, Philippines
Abstract Five types of clean energy sources have been assessed, and spatial distribution mapped for energy mix analysis using desa, a village or the smallest government administrative unit in Indonesia, as the unit of analysis. The results show that the total technical potential of clean energy in Bali is 100,664 GWh/yr. They show that there is great potential to enhance the share of clean energy in electricity generation, and meet demand projected to be 4,993 GWh/yr. in Bali in 2019. These results can be used for policy analysis to help Indonesia to meet, and even exceed, the targeted 23% share of clean energy in total power generation by 2025, establish mini/micro gird power generation plants, and formulate feed-in tariffs for the main electricity grid. © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license © 2016 The Authors. Published by Elsevier Ltd. (http://creativecommons.org/licenses/by-nc-nd/4.0/). Selection and/or peer-review of under responsibility of REM2016 Peer-review under responsibility the scientific committee of the Applied Energy Symposium and Forum, REM2016: Renewable Energy Integration with Mini/Microgrid. Keywords: Clean Energy, Potentiality, Decision Support System, GIS, Mini/micro Grid
1. Introduction The Government of Indonesia aims to expand energy access to all citizens, with the provision of up to 1,200 kWh/yr per capita by 2019 from the current level of 843 kWh/yr per capita (ADB, 2015) [1]. The Government also has a plan to bolster domestic energy security by increasing the utilization of clean energy and scaling up energy efficiency. The current target is to increase the share of clean energy to 23% of all energy generated/used/distributed by 2025. The local government in Bali is particularly promoting increased clean energy use, which is one of Indonesia’s tourism hubs.
* Corresponding author. Tel.: +63-2- 632- 4531; fax: +63-2-636-2198. E-mail address: [email protected]. Disclaimer: The views expressed in this paper are those of the author and do not necessarily reflect the views and policies of the Asian Development Bank (ADB) and the Ministry of Energy and Mineral Resources (ESDM), Government of Republic of Indonesia.
1876-6102 © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the scientific committee of the Applied Energy Symposium and Forum, REM2016: Renewable Energy Integration with Mini/Microgrid. doi:10.1016/j.egypro.2016.11.295
334
Bhuwneshwar Prasad Sah / Energy Procedia 103 (2016) 333 – 338
There is appetite among developers, investors, and researchers to develop viable solutions to tap clean energy from both the technical and economic aspects to fulfill the ever-increasing demand in Indonesia for electricity (ADB, 2015) [2], (Lopez et al., 2012) [3]. The availability and amount of clean energy on hand depend on the location, geophysical, and climatic conditions of a given area, among other things. It is therefore important for development and utilization of clean energy sources to quantify and map their spatial distribution. In this study, the technical potential of five energy sources – solar, wind, biomass, hydropower, and geothermal – have been estimated. 2. Materials and Methods Geospatial and statistical data, for Bali, which is the study site, collected from secondary sources comprise the bulk of data and materials used in this study. Software employed included Quantum GIS (QGIS), a free and open source geographic information system and Geographic Resources Analysis Support System (GRASS), a plugin tool for raster data processing. These software were used for (i) data compilation, integration, and processing for the extraction of the required data, and (ii) geospatial analysis and development of required plugin tools for specific energy potentiality and suitability calculations. Topographic, accessibility, and land cover constraints were applied in the analysis of technical potential. 2.1. Topographic, political boundaries and statistical data The base topographic data include land cover, contour and digital terrain models, road and river networks, and political boundaries (i.e., province, district, and desa) collected from the Badan Informasi Geospasial (BIG) or geospatial information agency, Indonesia. The number of households connected to the grid was obtained for each desa from the Perusahaan Listrik Negara, or state electricity company. The tabular statistical data on agriculture, plantation and forestry production, and their area in hectares was extracted and computerized from the Badan Pusat Statistics, or statistics Indonesia agency, reports from the year 2013. All the data were checked and integrated into the GIS database after editing. A desa is the smallest administrative unit for which population and other statistical data are available. 2.2. Energy source data The Energi dan Sumber Daya Mineral (ESDM), or ministry of energy and mineral resources, has identified the existence of five sources of clean energy in Bali. These are solar, wind, hydropower, geothermal, and biomass. Data for the first four energy sources were obtained from ESDM. For solar and wind energy, ESDM used one-degree Global Data Assimilation System data from National Oceanic and Atmospheric Administration/National Centers for Environmental Prediction and utilized the atmospheric general circulation model (AGCM) for interpolation followed by further downscaling to a 5-km resolution, with the technical assistance from the National Research Center of the Bandung Institute of Technology, Indonesia. By utilizing 1:25,000 scale topographic datasets, and with input from the Department of Public Works, Indonesia, ESDM estimated the run-of-river hydropower potential from potential-head of the delineated basins. Data for the geothermal energy technical potential for Bali was extracted from ESDM’s Geological Agency estimation dataset conducted across the country. For biomass energy, computerized tabular data on agricultural, plantation and forest production, and biomass residuals were integrated with desa political boundary data. Typographical errors in the names of desas were corrected based on the names and identification numbers of corresponding desas in the desa boundary layer.
335
Bhuwneshwar Prasad Sah / Energy Procedia 103 (2016) 333 – 338
2.3. Mapping potential of energy sources 2.3.1. Biomass energy The sources of biomass were identified. The heating values of residual byproducts from agriculture, plantation, and forest production have been compiled under this study in consultation with ESDM, the Center for Energy Resources Development Technology (CERDT), and the Badan Pengkajian dan Penerapan Teknologi (BPPT) or agency for the assessment and application of technology. Table 1 shows that burning biomass residuals generates heat energy, described as heating value in MJ/kg, with values dependent on their type and quality. By utilizing the heating value and integrated production of biomass residual desa- level data and potential energy conversion parameters and formula, given in Table 2, the technical potential density of biomass energy generation in GWh/yr/ha has been estimated. Figure 1 shows the resulting spatial distribution of biomass energy.
Fig. 1. Biomass, run-of-river mini/micro hydropower and geothermal energy technical potential in Bali Table 1. Heating Value of Biomass Residuals (compiled by CERDT, BPPT, Indonesia, Jan, 2016) Biomass Types
Byproducts residuals-may be used as Energy source 1
Rice Rice Husk (t) Maize Cobs (t) Sugarcane Bagasse (t) Coconut Shell (t) Cocoa Shell (t) Candlenut Candlenut shell (t) Cassava Stem/leaves (t) Peanuts Peanuts shell (t) Coffee Coffee hulls (t) Rubber wood Total biomass waste (t) Forest Wood waste of production forest (t) 3.6 MJ equivalent to 1 kWh electric energy
2 Straw (t) Husk (t) Hay top cane (t) Fiber (t)
Cassava Peel (t)
Acacia wood waste (t)
Heating Value (MJ/Kg) 3
Blotong (t)
Onggok (t)
1
2
14.5 17 14.4 18.2 17 21.96 18.42 19.2 12.38 14.98 18.84
15.7 19.66 17.62 16.7
18.42
3
17.62
18.42
18.84
2.3.2. Solar and wind energy Grid solar irradiance data were categorized into five classes. The total annual irradiance was calculated for daily sunshine hours. The results show that irradiance varies from 1490 to 1776 kWhm2/year; thus, confirming that the entire island of Bali has potential access to solar energy (Castillo et al., 2016) [4].
336
Bhuwneshwar Prasad Sah / Energy Procedia 103 (2016) 333 – 338
ESDM wind data also show that the average wind speed ranges from 3.65 to 5 m/s confirming therefore that there is wind energy potential available for power generation. Technical potential was calculated for both solar and wind energy using the conversion parameters (see Table 2) and by considering topography, land cover, and accessibility conditions of the area. The following criteria were used: - Topography: slope 30 %; - Accessibility: distance from the nearest road 5000 m; and, - Eligible land cover types: herbs and grasses, open fields – bare land, savannas, and bushes and shrubs - Ineligible land cover types: lakes, buildings not used as homes, seasonal crops in wetland areas, seasonal crops in dry land areas, lowland forest, highland forest, mangrove forest, plantations, garden and plant mixes, salt/brackish water, rivers, and settlements The technical potentials of solar and wind energy are illustrated in Figure 2 (a) and Figure 2 (b) respectively.
Fig. 2. Technical potential (a) solar and (b) wind energy in Bali
2.3.3. Hydropower and geothermal energy ESDM point data show the location distribution of hydropower (mini/micro) and geothermal potential and the value of potential energy for each. Five sites were identified which had total geothermal potential of 329 MW (ranging from 10 to 226 MW each). A further 143 sites were identified for potential hydropower, with have potential energy each ranging from 0.1 MW to 1.075 MW. The total energy from these potential sites is 14.8 MW. The technical potential for hydropower and geothermal energy was computed using conversion parameters and formula shown in Table 2 and their spatial distribution presented in Figure 1 above.
2.4. Energy mix estimation Using all the criteria described in sub-section 2.3, a new plugin tool for QGIS has been developed and deployed for energy mix estimation.
337
Bhuwneshwar Prasad Sah / Energy Procedia 103 (2016) 333 – 338 Table 2. Potential Energy Conversion Parameters (source: based on consultation meeting with ESDM, Feb 3, 2016) Energy Generation Energy Source
Value [A]
Units
Plant Factor (Efficiency) [B]
Operation (hours) [C]
Area [D]
Maintenance [E]
GWh/year
0.95
([A]*[B]*[D]*[E]*365)/1000000
Solar
kWh/m2
0.15
NA
Wind Hydro (mini and micro) Geothermal
kW
0.30
24.00
NA
0.80
([A]*[B]*[C]*[E]*365)/1000000
kW
0.50
24.00
NA
0.80
([A]*[B]*[C]*[E]*365)/1000000
kW
0.80
24.00
NA
0.80
([A]*[B]*[C]*[E]*365)/1000000
Biomass
kWh
0.20
NA
NA
0.80
([A]*[B]*[E]*365)/1000000
3. Results and discussion The total theoretical potential from solar and wind energy is approximately 1,376,275 GWh/yr (1,376,187 GWh/yr of solar potential and 88 GWh/yr of wind potential); however the technical potential of solar and wind combined is 98,762 GWh/yr as presented in Table 3. The energy mix from all five sources show a total technical potential in Bali is 100,664 GWh/yr (Table 3). The summary of computed technical potential of clean energy sources in Bali (Table 3) shows that there is sufficient clean energy potential, specifically solar energy, that can be tapped to meet electricity demand of 4,993 GWh/yr by 2019 and even beyond that time. However, without proper policy and market intervention, it would be difficult to harness this potential. The estimated quantified energy mix, along with spatial distribution at desa level can be effectively used for different sizes and types of energy generation planning, specifically for small rooftop or backyard solar or hybrid photovoltaic and mini and micro grids. In this context, a geo-enabled decision support system may assist decision makers in selecting the appropriate technologies. Table 3. Projected Energy Demand and Technical Potential of Clean Energy in Bali Technical Potential Clean Energy (GWh_Yr)
No. of Household
Population
Demand 2019 (GWh/yr)
Bangli
66,144
258,623
310.35
47.16
1,991.46
0.00
9.62
121.94
12,170
Gianyar
102,957
402,562
483.07
254.28
1,500.74
0.62
13.41
0
1,769
Denpasar City
131,193
512,965
615.56
31.61
1,724.91
1.11
0
0
1,758
Badung
165,781
648,204
777.84
143.96
9,110.45
0.79
10.53
0
9,266
84,541
330,555
396.67
97.62
10,303.34
10.40
1.77
0
10,413
Karangasem
127,129
497,074
596.49
7.72
9,872.67
3.57
15.29
0
9,899
Buleleng
207,436
811,075
973.29
199.27
34,073.37
1.57
11.5
42.05
34,328
Tabanan
128,802
503,616
604.34
284.61
2,175.68
0.82
10.5
527.7
2,999
50,111
195,934
235.12
70.87
17,985.63
5.58
0
0
18,062
1,064,094
4,160,608
4,993
1,137
24
73
692
100,664
District
Jembrana
Klungkung Total
Biomass
Solar
98,738
Wind
Hydrop ower
Geothe rmal
Total
338
Bhuwneshwar Prasad Sah / Energy Procedia 103 (2016) 333 – 338
4. Conclusion Technical potential of five types of clean energy sources were quantified and their spatial distribution successfully mapped using a GIS platform. The results show that Bali has theoretical potential of 1,378,100 GWh/yr and technical potential of 100,664 GWh/yr from aggregated clean energy sources. The result may be useful for various analyses, including policy formulation to increase the share of clean energy for power generation. Acknowledgements The author would like to extend his gratitude to Mr. Muhammad Irsan and his team at the Research and Development Center for Electricity and New-Renewable Energy Technology, ESDM, Indonesia, for providing the bulk of data for this study. He is also thankful to Dr. Kemal Prakoso, Castelrock Consulting, Indonesia and Dr. Rohmadi Ridlo, BPPT, Indonesia for their assistance in the collection and pre-processing some of the required data. Input and suggestions from ADB staff, Yongping Zhai, Technical advisor (Energy), Pradeep Tharakan, Senior Climate Change Specialist, Jiwan Acharya, Senior Energy Specialist, Priyantha Wijayatunga, Principal Energy Specialist and Naoki Sakai, Senior Knowledge Sharing and Services Specialist, helped to shape this paper. Finally, he is thankful to resource person Mr. Rodolfo Palencia, GIS/ICT Expert, of PASCO Philippines Corporation for his assistance in analyzing most of the data and devising the plug-in-tool for QGIS. References [1]
ADB
2015,
Sustainable
and
Inclusive
Energy
Program-SIEP
(49043-001
Subprogram
1),
(http://www.adb.org/projects/49043-001/main?page-1=1#project-pds) [2]
ADB
2015,
Renewable
energy
developments
and
potential
in
the
Greater
Mekong
Subregion,
(http://www.adb.org/sites/default/files/publication/161898/renewable-energy-developments-gms.pdf) [3] Lopez A, Roberts B, Heimiller D, Blair N, Porro G, 2012, U.S. Renewable Energy Technical Potentials: A GIS -Based Analysis (http://www.nrel.gov/docs/fy12osti/51946.pdf) [4] Castillo CP, eSilva FB, Lavalle C. An assessment of the regional potential for solar power generation in EU-28. Energy Policy 2016;88:86–99.
Biography Bhuwneshwar Prasad Sah is an Infrastructure Specialist at the Asian Development Bank. He is also an Associate Professor (Project) at the Center for Spatial Information Science, University of Tokyo. He holds a Ph.D. in Civil Engineering and has 25 years of work and research experience using geospatial science and engineering for natural resource planning and management.
ScienceDirect Energy Procedia 103 (2016) 333 – 338
Applied Energy Symposium and Forum, REM2016: Renewable Energy Integration with Mini/Microgrid, 19-21 April 2016, Maldives
Geo-enabled decision support system for potential clean energy mix for Bali, Indonesia Bhuwneshwar Prasad Saha* a
Asian Development Bank (ADB), 6 ADB Avenue, Mandaluyong City 1550, Metro Manila, Philippines
Abstract Five types of clean energy sources have been assessed, and spatial distribution mapped for energy mix analysis using desa, a village or the smallest government administrative unit in Indonesia, as the unit of analysis. The results show that the total technical potential of clean energy in Bali is 100,664 GWh/yr. They show that there is great potential to enhance the share of clean energy in electricity generation, and meet demand projected to be 4,993 GWh/yr. in Bali in 2019. These results can be used for policy analysis to help Indonesia to meet, and even exceed, the targeted 23% share of clean energy in total power generation by 2025, establish mini/micro gird power generation plants, and formulate feed-in tariffs for the main electricity grid. © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license © 2016 The Authors. Published by Elsevier Ltd. (http://creativecommons.org/licenses/by-nc-nd/4.0/). Selection and/or peer-review of under responsibility of REM2016 Peer-review under responsibility the scientific committee of the Applied Energy Symposium and Forum, REM2016: Renewable Energy Integration with Mini/Microgrid. Keywords: Clean Energy, Potentiality, Decision Support System, GIS, Mini/micro Grid
1. Introduction The Government of Indonesia aims to expand energy access to all citizens, with the provision of up to 1,200 kWh/yr per capita by 2019 from the current level of 843 kWh/yr per capita (ADB, 2015) [1]. The Government also has a plan to bolster domestic energy security by increasing the utilization of clean energy and scaling up energy efficiency. The current target is to increase the share of clean energy to 23% of all energy generated/used/distributed by 2025. The local government in Bali is particularly promoting increased clean energy use, which is one of Indonesia’s tourism hubs.
* Corresponding author. Tel.: +63-2- 632- 4531; fax: +63-2-636-2198. E-mail address: [email protected]. Disclaimer: The views expressed in this paper are those of the author and do not necessarily reflect the views and policies of the Asian Development Bank (ADB) and the Ministry of Energy and Mineral Resources (ESDM), Government of Republic of Indonesia.
1876-6102 © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the scientific committee of the Applied Energy Symposium and Forum, REM2016: Renewable Energy Integration with Mini/Microgrid. doi:10.1016/j.egypro.2016.11.295
334
Bhuwneshwar Prasad Sah / Energy Procedia 103 (2016) 333 – 338
There is appetite among developers, investors, and researchers to develop viable solutions to tap clean energy from both the technical and economic aspects to fulfill the ever-increasing demand in Indonesia for electricity (ADB, 2015) [2], (Lopez et al., 2012) [3]. The availability and amount of clean energy on hand depend on the location, geophysical, and climatic conditions of a given area, among other things. It is therefore important for development and utilization of clean energy sources to quantify and map their spatial distribution. In this study, the technical potential of five energy sources – solar, wind, biomass, hydropower, and geothermal – have been estimated. 2. Materials and Methods Geospatial and statistical data, for Bali, which is the study site, collected from secondary sources comprise the bulk of data and materials used in this study. Software employed included Quantum GIS (QGIS), a free and open source geographic information system and Geographic Resources Analysis Support System (GRASS), a plugin tool for raster data processing. These software were used for (i) data compilation, integration, and processing for the extraction of the required data, and (ii) geospatial analysis and development of required plugin tools for specific energy potentiality and suitability calculations. Topographic, accessibility, and land cover constraints were applied in the analysis of technical potential. 2.1. Topographic, political boundaries and statistical data The base topographic data include land cover, contour and digital terrain models, road and river networks, and political boundaries (i.e., province, district, and desa) collected from the Badan Informasi Geospasial (BIG) or geospatial information agency, Indonesia. The number of households connected to the grid was obtained for each desa from the Perusahaan Listrik Negara, or state electricity company. The tabular statistical data on agriculture, plantation and forestry production, and their area in hectares was extracted and computerized from the Badan Pusat Statistics, or statistics Indonesia agency, reports from the year 2013. All the data were checked and integrated into the GIS database after editing. A desa is the smallest administrative unit for which population and other statistical data are available. 2.2. Energy source data The Energi dan Sumber Daya Mineral (ESDM), or ministry of energy and mineral resources, has identified the existence of five sources of clean energy in Bali. These are solar, wind, hydropower, geothermal, and biomass. Data for the first four energy sources were obtained from ESDM. For solar and wind energy, ESDM used one-degree Global Data Assimilation System data from National Oceanic and Atmospheric Administration/National Centers for Environmental Prediction and utilized the atmospheric general circulation model (AGCM) for interpolation followed by further downscaling to a 5-km resolution, with the technical assistance from the National Research Center of the Bandung Institute of Technology, Indonesia. By utilizing 1:25,000 scale topographic datasets, and with input from the Department of Public Works, Indonesia, ESDM estimated the run-of-river hydropower potential from potential-head of the delineated basins. Data for the geothermal energy technical potential for Bali was extracted from ESDM’s Geological Agency estimation dataset conducted across the country. For biomass energy, computerized tabular data on agricultural, plantation and forest production, and biomass residuals were integrated with desa political boundary data. Typographical errors in the names of desas were corrected based on the names and identification numbers of corresponding desas in the desa boundary layer.
335
Bhuwneshwar Prasad Sah / Energy Procedia 103 (2016) 333 – 338
2.3. Mapping potential of energy sources 2.3.1. Biomass energy The sources of biomass were identified. The heating values of residual byproducts from agriculture, plantation, and forest production have been compiled under this study in consultation with ESDM, the Center for Energy Resources Development Technology (CERDT), and the Badan Pengkajian dan Penerapan Teknologi (BPPT) or agency for the assessment and application of technology. Table 1 shows that burning biomass residuals generates heat energy, described as heating value in MJ/kg, with values dependent on their type and quality. By utilizing the heating value and integrated production of biomass residual desa- level data and potential energy conversion parameters and formula, given in Table 2, the technical potential density of biomass energy generation in GWh/yr/ha has been estimated. Figure 1 shows the resulting spatial distribution of biomass energy.
Fig. 1. Biomass, run-of-river mini/micro hydropower and geothermal energy technical potential in Bali Table 1. Heating Value of Biomass Residuals (compiled by CERDT, BPPT, Indonesia, Jan, 2016) Biomass Types
Byproducts residuals-may be used as Energy source 1
Rice Rice Husk (t) Maize Cobs (t) Sugarcane Bagasse (t) Coconut Shell (t) Cocoa Shell (t) Candlenut Candlenut shell (t) Cassava Stem/leaves (t) Peanuts Peanuts shell (t) Coffee Coffee hulls (t) Rubber wood Total biomass waste (t) Forest Wood waste of production forest (t) 3.6 MJ equivalent to 1 kWh electric energy
2 Straw (t) Husk (t) Hay top cane (t) Fiber (t)
Cassava Peel (t)
Acacia wood waste (t)
Heating Value (MJ/Kg) 3
Blotong (t)
Onggok (t)
1
2
14.5 17 14.4 18.2 17 21.96 18.42 19.2 12.38 14.98 18.84
15.7 19.66 17.62 16.7
18.42
3
17.62
18.42
18.84
2.3.2. Solar and wind energy Grid solar irradiance data were categorized into five classes. The total annual irradiance was calculated for daily sunshine hours. The results show that irradiance varies from 1490 to 1776 kWhm2/year; thus, confirming that the entire island of Bali has potential access to solar energy (Castillo et al., 2016) [4].
336
Bhuwneshwar Prasad Sah / Energy Procedia 103 (2016) 333 – 338
ESDM wind data also show that the average wind speed ranges from 3.65 to 5 m/s confirming therefore that there is wind energy potential available for power generation. Technical potential was calculated for both solar and wind energy using the conversion parameters (see Table 2) and by considering topography, land cover, and accessibility conditions of the area. The following criteria were used: - Topography: slope 30 %; - Accessibility: distance from the nearest road 5000 m; and, - Eligible land cover types: herbs and grasses, open fields – bare land, savannas, and bushes and shrubs - Ineligible land cover types: lakes, buildings not used as homes, seasonal crops in wetland areas, seasonal crops in dry land areas, lowland forest, highland forest, mangrove forest, plantations, garden and plant mixes, salt/brackish water, rivers, and settlements The technical potentials of solar and wind energy are illustrated in Figure 2 (a) and Figure 2 (b) respectively.
Fig. 2. Technical potential (a) solar and (b) wind energy in Bali
2.3.3. Hydropower and geothermal energy ESDM point data show the location distribution of hydropower (mini/micro) and geothermal potential and the value of potential energy for each. Five sites were identified which had total geothermal potential of 329 MW (ranging from 10 to 226 MW each). A further 143 sites were identified for potential hydropower, with have potential energy each ranging from 0.1 MW to 1.075 MW. The total energy from these potential sites is 14.8 MW. The technical potential for hydropower and geothermal energy was computed using conversion parameters and formula shown in Table 2 and their spatial distribution presented in Figure 1 above.
2.4. Energy mix estimation Using all the criteria described in sub-section 2.3, a new plugin tool for QGIS has been developed and deployed for energy mix estimation.
337
Bhuwneshwar Prasad Sah / Energy Procedia 103 (2016) 333 – 338 Table 2. Potential Energy Conversion Parameters (source: based on consultation meeting with ESDM, Feb 3, 2016) Energy Generation Energy Source
Value [A]
Units
Plant Factor (Efficiency) [B]
Operation (hours) [C]
Area [D]
Maintenance [E]
GWh/year
0.95
([A]*[B]*[D]*[E]*365)/1000000
Solar
kWh/m2
0.15
NA
Wind Hydro (mini and micro) Geothermal
kW
0.30
24.00
NA
0.80
([A]*[B]*[C]*[E]*365)/1000000
kW
0.50
24.00
NA
0.80
([A]*[B]*[C]*[E]*365)/1000000
kW
0.80
24.00
NA
0.80
([A]*[B]*[C]*[E]*365)/1000000
Biomass
kWh
0.20
NA
NA
0.80
([A]*[B]*[E]*365)/1000000
3. Results and discussion The total theoretical potential from solar and wind energy is approximately 1,376,275 GWh/yr (1,376,187 GWh/yr of solar potential and 88 GWh/yr of wind potential); however the technical potential of solar and wind combined is 98,762 GWh/yr as presented in Table 3. The energy mix from all five sources show a total technical potential in Bali is 100,664 GWh/yr (Table 3). The summary of computed technical potential of clean energy sources in Bali (Table 3) shows that there is sufficient clean energy potential, specifically solar energy, that can be tapped to meet electricity demand of 4,993 GWh/yr by 2019 and even beyond that time. However, without proper policy and market intervention, it would be difficult to harness this potential. The estimated quantified energy mix, along with spatial distribution at desa level can be effectively used for different sizes and types of energy generation planning, specifically for small rooftop or backyard solar or hybrid photovoltaic and mini and micro grids. In this context, a geo-enabled decision support system may assist decision makers in selecting the appropriate technologies. Table 3. Projected Energy Demand and Technical Potential of Clean Energy in Bali Technical Potential Clean Energy (GWh_Yr)
No. of Household
Population
Demand 2019 (GWh/yr)
Bangli
66,144
258,623
310.35
47.16
1,991.46
0.00
9.62
121.94
12,170
Gianyar
102,957
402,562
483.07
254.28
1,500.74
0.62
13.41
0
1,769
Denpasar City
131,193
512,965
615.56
31.61
1,724.91
1.11
0
0
1,758
Badung
165,781
648,204
777.84
143.96
9,110.45
0.79
10.53
0
9,266
84,541
330,555
396.67
97.62
10,303.34
10.40
1.77
0
10,413
Karangasem
127,129
497,074
596.49
7.72
9,872.67
3.57
15.29
0
9,899
Buleleng
207,436
811,075
973.29
199.27
34,073.37
1.57
11.5
42.05
34,328
Tabanan
128,802
503,616
604.34
284.61
2,175.68
0.82
10.5
527.7
2,999
50,111
195,934
235.12
70.87
17,985.63
5.58
0
0
18,062
1,064,094
4,160,608
4,993
1,137
24
73
692
100,664
District
Jembrana
Klungkung Total
Biomass
Solar
98,738
Wind
Hydrop ower
Geothe rmal
Total
338
Bhuwneshwar Prasad Sah / Energy Procedia 103 (2016) 333 – 338
4. Conclusion Technical potential of five types of clean energy sources were quantified and their spatial distribution successfully mapped using a GIS platform. The results show that Bali has theoretical potential of 1,378,100 GWh/yr and technical potential of 100,664 GWh/yr from aggregated clean energy sources. The result may be useful for various analyses, including policy formulation to increase the share of clean energy for power generation. Acknowledgements The author would like to extend his gratitude to Mr. Muhammad Irsan and his team at the Research and Development Center for Electricity and New-Renewable Energy Technology, ESDM, Indonesia, for providing the bulk of data for this study. He is also thankful to Dr. Kemal Prakoso, Castelrock Consulting, Indonesia and Dr. Rohmadi Ridlo, BPPT, Indonesia for their assistance in the collection and pre-processing some of the required data. Input and suggestions from ADB staff, Yongping Zhai, Technical advisor (Energy), Pradeep Tharakan, Senior Climate Change Specialist, Jiwan Acharya, Senior Energy Specialist, Priyantha Wijayatunga, Principal Energy Specialist and Naoki Sakai, Senior Knowledge Sharing and Services Specialist, helped to shape this paper. Finally, he is thankful to resource person Mr. Rodolfo Palencia, GIS/ICT Expert, of PASCO Philippines Corporation for his assistance in analyzing most of the data and devising the plug-in-tool for QGIS. References [1]
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(http://www.adb.org/projects/49043-001/main?page-1=1#project-pds) [2]
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(http://www.adb.org/sites/default/files/publication/161898/renewable-energy-developments-gms.pdf) [3] Lopez A, Roberts B, Heimiller D, Blair N, Porro G, 2012, U.S. Renewable Energy Technical Potentials: A GIS -Based Analysis (http://www.nrel.gov/docs/fy12osti/51946.pdf) [4] Castillo CP, eSilva FB, Lavalle C. An assessment of the regional potential for solar power generation in EU-28. Energy Policy 2016;88:86–99.
Biography Bhuwneshwar Prasad Sah is an Infrastructure Specialist at the Asian Development Bank. He is also an Associate Professor (Project) at the Center for Spatial Information Science, University of Tokyo. He holds a Ph.D. in Civil Engineering and has 25 years of work and research experience using geospatial science and engineering for natural resource planning and management.