Introduction to Energy Modeling (Graduate Course)

  1. Overview

The course aims for a student to understand the entire life cycle of energy modeling process including input, core, and output system of GCAM. In terms of input data system, energy balance table will be explored first. Then rest of sectors will be covered. You will have a chance to take a glimpse idea of utilizing the full version of GCAM. Additional tools for presenting the results in terms of tables and figures such as R-studio will also be provided. Most of the information on this model is accessible through github link provided below. References include a couple of articles you might want to take a look.

As a pre-requisite for “Advances in energy modeling” class, this course introduces the basic concept of energy modeling software system through lectures and practical hands-on computer experience with GCAM (Global Change Assessment Model) energy modeling software.

After the midterm exam, a simplified version of GCAM (GCAM-EML, energy modeling lab.) will be provided and explained. You will find this GCAM-EML easy to manipulate for your exercise and application. You are asked to run this program updating your country case using available information and report the results in terms of thesis proposal including detailed tables and figures. Your performance of the calss will be evaluated based on the final report which will be utilized for your thesis proposal.

Materials uploaded:

    1. Overview
    2. GCAM Work Flow: Installation of GCAM pacakge (data system), Running GCAM, Introduction to Case studies. [pdf] [1] [2] [3] [4]
    3. How to look into outputs from GCAM: How to use Model Interface, Understanding GCAM Energy System Structure. [pdf] [1] [2] [3] [4]
    4. Scenario Run: Exercise: Tehcnology Efficiency , Cost Change [pdf] [1] [2] [3] [4]
    5. Introduction to R: Basic Rules of R (Data Types, Operator, Conditional Statement, Loop, User defined Function, Importing and exporting data, Exercise) [pdf] [1] [2] [3] [4] : [Hint]
    6. Data manipulation & Visualization in R: Useful Packages: tidyr , dplyr, ggplot2 (Reshaping, Joining, Grouping, Filtering, Selecting, Mutating, Plotting, Exercise) [pdf] [1] [2] [3] [4]
    7. Handling GCAM outputs in R: Comparison between historical data and GCAM results [pdf] [1] [2] [3] [4]
    8. Mid-term Period
    9. Overview of GCAM EML and Its Installation File  
    10. Using GCAM EML [pdf]
    11. Using GCAM EML and Scenario Design [pdf] [1] [2] [3] [4]
    12. Building sector [pdf] [1] [2] [3] [4]
    13. Discussion on final project [pdf] [1] [2] [3] [4]
    14. Scenario Development using GCAM EML (video, no live class)
    15. Transportation sector [pdf] [1] [2] [3] [4]
    16. Project submission (Replaces final exam)

New Arrivals

References

  • GCAM: http://www.globalchange.umd.edu/gcam/
  • GCAM: https://github.com/JGCRI/gcam-core
  • R: https://www.r-project.org/about.html
  • Data Science: https://www.datacamp.com/
  1. Brenkert, A.L., Smith, A.J., Kim, S.H., and Pitcher, H., M., 2003, Model Documentation for the MiniCAM, Pacific Northwest National Laboratory, PNNL-14337
  2. Clarke, J.F., Edmonds, J.A., 1993. Modelling energy technologies in a competitive market. Energy Econ. 15, 123–129. doi:10.1016/0140-9883(93)90031-L
  3. Edmonds, J.A., Reilly, J., 1985. Global Energy: Assessing the Future. Oxford University Press, New York.
  4. Kim, S.H., J. Edmonds, J. Lurz, S. J. Smith and M. Wise (2006) The ObjECTS Framework for Integrated Assessment: Hybrid Modeling of Transportation, Energy Journal (Special Issue #2) pp 51-80.
  5. McFadden, D. 1974, “Conditional Logit Analysis of Qualitative Choice Behavior,” in Zarambka, ed. Frontiers of Econometrics, New York: Academic Press
  • Articles for Building Model
  1.  Clarke, L., Eom, J., Hodson Marten, E., et al. 2018. Effects of long-term climate change on global building energy expenditures. Energy Economics 72, pp. 667-677
  2. Yu, S., Eom, J., Evans, M., & Clarke, L.,  (2014). A long-term, integrated impact assessment of alternative building energy code scenarios in China, Energy Policy, 67, 626-639. 
      • Articles for Transportation Model
  1. Kyle, P., & Kim, S. H. (2011). Long-term implications of alternative light-duty vehicle technologies for global greenhouse gas emissions and primary energy demands, Energy Policy, 39(5), 3012-3024.
  2. Chaturvedi, V., & Kim, S. H. (2015). Long term energy and emission implications of a global shift to electricity-based public rail transportation system. Energy Policy, 81, 176-185.
  3. Mishra, G. S., Kyle, P., Teter, J., Morrison, G. M., Kim, S., & Yeh, S. (2013). Transportation module of global change assessment model (GCAM): model documentation. Institute of Transportation Studies, University of California, Davis.
  4. Paladugula, Anantha Lakshmi, Nazar Kholod, Vaibhav Chaturvedi, Probal Pratap Ghosh, Sarbojit Pal, Leon Clarke, Meredydd Evans, et al. “A Multi-Model Assessment of Energy and Emissions for India’s Transportation Sector through 2050.” Energy Policy116 (May 2018): 10–18.
  5. Wise, M., Muratori, M., & Kyle, P. (2017). Biojet fuels and emissions mitigation in aviation: An integrated assessment modeling analysis. Transportation Research Part D: Transport and Environment, 52, 244-253.
  6. Yeh, S., Mishra, G. S., Fulton, L., Kyle, P., McCollum, D. L., Miller, J., … & Teter, J. (2017). Detailed assessment of global transport-energy models’ structures and projections. Transportation Research Part D: Transport and Environment, 55, 294-309.

  7. Yin, X., Chen, W., Eom, J., Clarke, L. E., Kim, S. H., Patel, P. L., … & Kyle, G. P. (2015). China’s transportation energy consumption and CO2 emissions from a global perspective. Energy Policy, 82, 233-248.

  • Articles for Energy policy & Carbon abatement
  1. Brown, M.A., 2001, “Market failures and barriers as a basis for clean energy policies,” Energy Policy, Vol. 29, No. 14, pp. 1197-1207.
  2. Kesicki, F., 2010, “Marginal abatement cost curves for policy making–expert-based vs model-derived curves,” Energy Institute, University College London, pp. 1-8.
  3. McKinsey & Company, 2009, “Pathways to a Low-Carbon Economy: Version 2 of the Global Greenhouse Gas Abatement Cost Curve,” McKinsey & Company, pp. 1-192.
  4. Zhou, S., G. P. Kyle, S. Yu, L. E. Clarke, J. Eom, P. Luckow, and J. A. Edmonds, “Energy use and CO2 emissions of China’s industrial sector from a global perspective”, Energy Policy, Vol. 53, 2013b, pp. 284~294.