NATURAL RESOURCE OPTIMIZATION
FOR INTERNATIONAL RENEWABLE
TRANSITION BY 2040
Naomi Arnold
Amanda Lurie
ESD. 124
12/8/2014
AGENDA
„  Question to Investigate
„  Background (Papers and Models)
„  Methodology
„  Projecting Future Demand
„  Pro...
QUESTION TO INVESTIGATE
Which countries can be first to
transition to renewables based on
natural resource supply and cost...
BACKGROUND: PAPERS
„  Regional investigation of renewable
resources and various methodologies
„  Korea (Park, N. B., S. ...
BACKGROUND: MODELS
Aboumahboub,T, et al. (2010).“Optimizing world-wide
utilization of renewable energy sources in the powe...
PROJECTING FUTURE DEMAND
Data Challenge
•  Lack of data projecting energy
consumption in 2040 per
country
•  Usually aggre...
PROJECTING FUTURE SUPPLY
„ Options to calculate supply
„  Geographic Potential
„  Technical Potential
„  Economic Pote...
DETERMINING FUTURE GDP
IIASA Greenhouse Gas Initiative database
„ Projected 2040 GDP per country
„ Most conservative sce...
DETERMINING ENERGY COSTS
Open EI Transparent Cost Database
„ Projected 2040 levelized energy cost per technology
„ Avera...
ANALYSIS
The minimum of the country’s projected demand
and renewable capacity were calculated
This minimum was decreased b...
RESULTS: MOST EXPENSIVE RENEWABLE
TRANSITION COSTS BY COUNTRY
China
28%
United States
16%
India
6%
Russia
5%
Japan
3%
Braz...
RESULTS: WORLD HEAT MAP OF
RENEWABLE TRANSITION FEASIBILITY
„ Percent of GDP required to complete a transition to 100%
re...
RESULTS:THE BEST AND THE WORST
Lowest % GDP Highest % GDP
Smaller, developing countries
in Africa and Asia
Small projected...
SENSITIVITY ANALYSIS
1.  Ample renewable natural resources exist and can
meet world demand in 2040
2.  Cost is the largest...
CONCLUSION
„ High feasibility countries are in developing areas
„ Low feasibility countries depend on oil economies
Top ...
NEXT STEPS
1.  Network flow optimization: trade or sell energy
to neighboring countries and meet grid capacity
constraints...
of 16

Natural Resource Optimization for International Renewable Transition by 2040

Presentation from final term paper for MIT's Energy Systems and Climate Change Mitigation graduate course in Fall 2014 about the possibility and cost implications per country of transitioning to renewable energy by 2040. Measuring climate change mitigation responsibilities based on historical or projected CO2 emissions has proven controversial and created policy stalemates at the international level. Instead, we propose an alternative approach that identifies which countries can be first to transition to renewables based on natural resource supply and cost considerations. Our research revealed that natural resources themselves were not a binding constraint, as ample solar, wind, geothermal, and hydropower potential energy supplies exist worldwide. Cost will be the main factor in the renewable transition, our analysis shows the total cost to switch to renewables will be a significant portion of their GDP for most countries around the world. On a worldwide basis, we estimate the transition to cost 22% of world GDP. This paper highlights the importance of policymakers to allocate more funding for renewable energy R&D and market-based or subsidy programs to support the growth and investment in renewables. The question is not if renewables will be able to supply our future energy needs, but when will the the funds be available to make this transition.
Published on: Mar 3, 2016
Published in: Environment      
Source: www.slideshare.net


Transcripts - Natural Resource Optimization for International Renewable Transition by 2040

  • 1. NATURAL RESOURCE OPTIMIZATION FOR INTERNATIONAL RENEWABLE TRANSITION BY 2040 Naomi Arnold Amanda Lurie ESD. 124 12/8/2014
  • 2. AGENDA „  Question to Investigate „  Background (Papers and Models) „  Methodology „  Projecting Future Demand „  Projecting Future Supply „  Determining Future GDP „  Determining Energy Costs „ Analysis „ Results „ Conclusions „ Next Steps
  • 3. QUESTION TO INVESTIGATE Which countries can be first to transition to renewables based on natural resource supply and cost consideration as a percentage of GDP?
  • 4. BACKGROUND: PAPERS „  Regional investigation of renewable resources and various methodologies „  Korea (Park, N. B., S. J.Yun, and E. C. Jeon) „  Germany (Scholz, R., et al.) „  North Africa (Hawila, D., et al.) „  Global-based supply and demand analysis „  Jacobson, M. Z., et al. "Providing All Global Energy with Wind,Water, and Solar Power” „  Cabal, H., et al. "Review of the World and European Renewable Energy Resource Potentials" „  Cochran, J., et al. "Meta-Analysis of High Penetration Renewable Energy Scenarios”
  • 5. BACKGROUND: MODELS Aboumahboub,T, et al. (2010).“Optimizing world-wide utilization of renewable energy sources in the power sector” Biberacher M, et al.“GIS based model to optimize the utilization of renewable energy carriers and related energy flows.” Haller, M., et al. "Decarbonization Scenarios for the EU and Mena Power System: Considering Spatial Distribution and Short Term Dynamics of Renewable Generation."
  • 6. PROJECTING FUTURE DEMAND Data Challenge •  Lack of data projecting energy consumption in 2040 per country •  Usually aggregated per region Solution •  Extrapolated EIA Primary Energy consumption per country from 2011 •  Applied IEO2013 growth rates •  Includes all sectors and fuels
  • 7. PROJECTING FUTURE SUPPLY „ Options to calculate supply „  Geographic Potential „  Technical Potential „  Economic Potential „  Theoretical Potential Open EI Database NREL Solar Resources Solar Open EI Database NREL Wind Potential Wind EPRI 1978 Geothermal Energy Prospects Geothermal World Atlas Hydropower and Dams Potential Hydropower
  • 8. DETERMINING FUTURE GDP IIASA Greenhouse Gas Initiative database „ Projected 2040 GDP per country „ Most conservative scenario selected „ A2r baseline: High GHG emissions, low GDP projections
  • 9. DETERMINING ENERGY COSTS Open EI Transparent Cost Database „ Projected 2040 levelized energy cost per technology „ Averaged offshore/onshore wind and CSP/PV solar
  • 10. ANALYSIS The minimum of the country’s projected demand and renewable capacity were calculated This minimum was decreased by a fixed percentage (50%) and considered “allocated” The remaining balance of unsatisfied demand calculated Process repeats for the next renewable resource „ Excel model matched country’s demand and supply data „ Allocated renewable resources to fulfill demand
  • 11. RESULTS: MOST EXPENSIVE RENEWABLE TRANSITION COSTS BY COUNTRY China 28% United States 16% India 6% Russia 5% Japan 3% Brazil 2% Iran 2% Saudi Arabia 2% Germany 2% Canada 2% Korea, South 2% France 1% United Kingdom 1% Indonesia 1% South Africa 1% Ukraine 1% Mexico 1% Italy 1% Thailand 1% Australia 1% United Arab Emirates 1% Spain 1% Singapore 1% Egypt 1% Venezuela 1% Argentina 1% Malaysia 1% All other countries 15%
  • 12. RESULTS: WORLD HEAT MAP OF RENEWABLE TRANSITION FEASIBILITY „ Percent of GDP required to complete a transition to 100% renewable resources by 2040 „ Majority of countries in the world (139 out of 181) cost greater than 10% of their GDP to transition
  • 13. RESULTS:THE BEST AND THE WORST Lowest % GDP Highest % GDP Smaller, developing countries in Africa and Asia Small projected demand Various countries in Middle East and Eurasia Prevalence of oil-rich nations
  • 14. SENSITIVITY ANALYSIS 1.  Ample renewable natural resources exist and can meet world demand in 2040 2.  Cost is the largest factor in renewable transition Sensitivity analysis highlights importance of reducing costs „ Learning/experience curves can play major role
  • 15. CONCLUSION „ High feasibility countries are in developing areas „ Low feasibility countries depend on oil economies Top energy consuming countries have the most expensive transitions „ China will account for the largest proportion „  Needs to balance its growing economy with its environmental impact on the rest of the globe
  • 16. NEXT STEPS 1.  Network flow optimization: trade or sell energy to neighboring countries and meet grid capacity constraints over time 2.  Examine energy demand on a by-sector basis: electricity, transportation, etc. 3.  Expand cost accounting with more in depth learning curves and sensitivity analysis 4.  Differentiate levelized costs based on country

Related Documents