ENERGY SYSTEMS MODELING AND CRITICAL MINERAL SUPPLY CHAINS.

Catalog description

Many of the most pressing energy challenges of our time transcend traditional disciplinary boundaries and necessitate the use of systems models to analyze possible solutions. This course will show how methodological approaches can be applied to construct such energy systems models. Particular emphasis will be devoted to models that combine concepts from engineering, economics, natural sciences, and policy. The featured models will showcase a broad range of methodological approaches, such as optimization, simulation, machine learning, decision analysis, stochastic processes, and dynamical systems. More generally, the course will train students to build mathematical models that represent complex real-world energy system problems. Topics include basics of energy systems engineering, concepts in probability and statistics, spatial representation (e.g. GIS), and more. Graduate students will be expected to have basic programming skills and to produce optimization models in Python and Excel. Graduate students will be expected to be able to apply these skills to existing open-source and commercial grade modeling software, generate and validate new scenarios and produce publication quality visualizations, presentations and reports.