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Agenda Background Methodology Data and scenario settings Results and discussions Conclusion

30th USAEE/IAAA North American Conference 9th-12th October 2011 Modeling Geothermal as Low C arbon Source in Indonesia Joni Jupesta JSPS-UNU Postdoctoral Fellow United Nations University- Institute of Advanced Studies Yokohama-Japan. Agenda Background Methodology

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Agenda Background Methodology Data and scenario settings Results and discussions Conclusion

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  1. 30th USAEE/IAAA North American Conference 9th-12th October 2011Modeling Geothermal asLow Carbon Source in IndonesiaJoni JupestaJSPS-UNU Postdoctoral FellowUnited Nations University- Institute of Advanced StudiesYokohama-Japan

  2. Agenda • Background • Methodology • Data and scenario settings • Results and discussions • Conclusion

  3. Indonesia at the Glance Indonesia Source: Worldbank and Indonesia‘s Ministry of Energy and Mineral Resources, 2010

  4. Energy Mix Policy in 2006 Shift Oil to Biofuel and Geothermal. Source: Indonesia Ministry of Energy and Mineral Resources,2006

  5. Climate Change in Indonesia Climate Change cause is: Greenhouse Gas (GHG) emissions. GHG emission in 2005: Global 45,667 MtCO2eq. Indonesia 2.055 Mt CO2eq. 78% Source: Indonesia National Climate Change Commission,2010

  6. Energy Vision 25/25 in 2010: Changing Future Energy Mix Source: Indonesia National Energy Agency, 2010

  7. Shift from Oil to Geothermal Source: Indonesia Ministry of Energy and Mineral Resources, 2010

  8. Energy Reserves and Production Source: Indonesia Ministry of Energy and Mineral Resources, 2010

  9. Methodology Methodology: Partial equilibrium (Non linear programming) Tool: GAMS , Model: GEOTHERM (based on GLOBAL 2100 model) Time: 2007-2040 (3years step time) While: Objective function: Max. UTILITY Y0 (RG) = Output in 2007 (million US$) L0 (RG) =Population in 2007 (million) L (T,RG) =Population in t year (million) Subject to: NEGISHI (RG) C (T,RG) = Consumption in t year (mio US$) =Y0(RG)/L0(RG)/SHARE SHARE =sum (RG, Y0 (RG)/L0(RG) BETA (T) = annual discount factor (0.9)

  10. Data and Scenario Setting Scenario: 1. Business As Usual : Follow government energy policy 2. Technology: Including the learning by R&D and economies of scale • source: • a(BPS Statistics Indonesia, 2009); • b source: (Sugiyono, 1995), (Ministry of Energy and Mineral Resources, 2009); • c source: (Manne, 1992)

  11. Supply side (BAU scenario)

  12. Demand side (BAU scenario)

  13. Technological Change of Geothermal 3.4%

  14. GDP, Population and Electricity efficiency

  15. Conclusion • The energy supply increases tenfold up to 1,091 Mtoefrom 2007 to 2040 inthe `Business As Usual` scenario. The highest increment comes from coal, gas, oil, hydro, geothermal, biomass and biofuel respectively. • The energy demand grows in line with the GDP growth. Comparing all these sectors, the highest increment is to come from industry, transportation and other sectors put together respectively. The increments between 2007 to 2040 are 18.6, 6.8 and 3.8 times for industry, transportation and others respectively. • The geothermal could supply in 2040 at value 180 Mtoe under `Technology` scenario compares with 5.9 Mtoeunder`Businessas Usual` scenario. Still, this amount in 2025 is only represent 3.4% from the energy mix, lower than 5% target in Energy Mix Policy. • GDP grow at rate 7.8% per year. The population increases by1% per year resulting in 311million people in 2040 and the electricity efficiency is growing from 0.32 in 2007 to 0.35 in 2040.The CO2 emissions increase from 246 Mtoe to 3,343 Mtoefrom 2007 to 2040 under `Business as Usual` scenario.

  16. Thank you! For further information please contact : Joni Jupesta United Nations University- Institute of Advanced Studies jupesta@ias.unu.edu

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