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Environment General Courses (ENVIRON)

graduate level, taught in Durham

298.22 Understanding Energy Models and Modeling
Energy models are widely used for forecasting, system design, and pedagogical purposes. The availability of cheap computing power has increased both the sophistication and accessibility of these models, providing the policy community with an increasingly broad range of studies as well as the ability to produce its own assessments. Such assessments can provide a reasonably transparent and objective foundation for studies of critical energy-related issues, including the need to mitigate global climate change, improve air quality, prepare for the peaking of petroleum and natural gas production, and ensure sufficient infrastructure capacity.

Like any modeling effort, however, energy models have their limitations and lend themselves to abuse and misinterpretation. Policy analysts and decision makers therefore need to acquire a basic literacy in energy modeling in order to understand the modeling process and critically evaluate the claims others derive from their analyses. What should one look for in order to determine if conclusions are credible? What happens inside the black box of an energy model? How elaborate does a model need to be, and at what point does technical sophistication take on a life of its own? In the end, are energy models actually useful?

This course aims to nurture a basic modeling literacy by focusing on a widely-used class of “bottom-up,” optimization-based, energy models commonly used for economic and environmental assessments. Students will acquire familiarity with the energy modeling literature, obtain a working knowledge of model mechanics and gain experience asking the type of questions needed to evaluate the quality of modeling results. Through class discussion, readings, and student projects, the course will cover the following topics:

  • The history of energy modeling;
  • Types of energy models and approaches to energy modeling;
  • Commonly used energy models;
  • What typically goes into an energy model, what comes out, and what happens in between;
  • The critical need for sensitivity and uncertainty analyses;
  • How modeling results are actually used in the policy process and different ways of interpreting conclusions; and
  • Modeling pitfalls, both deliberate abuses and common misinterpretations.

All students with an interest in becoming good consumers of energy models, as well as those who wish to build the foundation needed to become an actual modeler, are welcome. Comfort with mathematical modeling would be beneficial, but prior experience with optimization techniques is not a prerequisite.

 
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