07-31, 13:30–14:00 (UTC), Purple Track
Energy and the economy are deeply intertwined yet the models typically employed for energy analysis treat the energy sector in isolation while lacking the capability to robustly represent the U.S. economy. This talk introduces the SLiDE.jl package, which leverages U.S. economic data to assess economic implications of energy infrastructure planning to answer these and other questions.
The Scalable Linked Dynamic Equilibrium (SLiDE) model is an implementation of a computable general equilibrium (CGE) model. CGE models are commonly used for detailed regional economic analysis of inputs, outputs, prices and quantities of various economic sectors to inform policy decisions. This talk will focus on the development of the data management approach with a focus on usability.
We will delve into the inner workings of the SLiDE module to explore the benefits and challenges of using Julia for data science applications. Techniques used to standardize the publicly available blueNOTE dataset include autogenerated and populated structs and powerful multiple dispatch and methods. Discussion will include the design-thinking approach taken to create a user-friendly interface to scale the model in space, time, and sector and encourage further adoption of Julia in policy analysis.
Caroline Hughes is an Energy Data and Simulation Analyst at the U.S. National Renewable Energy Laboratory. Her research focuses on computational modeling and decision-making under uncertainty. A data scientist and user experience designer, she sees the terminal as an interface and has strong opinions about leveraging coding best-practices to write clever and user-friendly code.