Energy Systems Modeling with High Performance Computing Resources
Climate change coupled with rapid technological innovation is driving large scale change in the global energy system. Computer models of the energy system – referred to as energy optimization system models – provide a way to examine future energy system evolution, test the effects of proposed policy, and explore the role of future uncertainty. Modeling the whole energy system is computationally intensive and requires large input datasets. In addition, in order to deliver insights that are robust to large future uncertainties, it is necessary to iterate the model many times under different scenario assumptions.
In this talk, Dr. Joseph DeCarolis, Professor in the Department of Construction, Civil, & Environmental Engineering at NC State, will highlight ongoing work using Tools for Energy Model Optimization and Analysis (Temoa), an open source energy system optimization model developed at NC State that is designed to conduct rigorous uncertainty analysis and make use of high-performance computing resources.
The Research Computing series is a forum for information sharing about high-performance computing, deep learning, parallel computing, and other relevant topics. This talk is being offered in conjunction with Energy Week.