ERE Seminar: Victor M. Zavala ( University of Wisconsin - Madison)

Monday, May 8, 2017

12:15 pm

Room 104, Green Earth Sciences Building, 367 Panama Street, Stanford Map

Sponsored by:
Energy Resources Engineering

Victor M. Zavala, University of Wisconsin - Madison

Optimization of Energy Systems: Leveraging Models, Data, and Computing

The combination of systems modeling, data analysis, and high-performance computing provides a powerful framework to tackle emerging challenges in energy systems. We discuss how the constantly evolving energy technology landscape as well as interdependencies between infrastructures necessitate of new algorithmic techniques and tools to quickly assess the performance of different technologies under realistic infrastructure and market conditions. In particular, we present modern techniques to make strategic decisions in the face of uncertainty, across multiple spatial and temporal scales, and in the presence of conflicting priorities among stakeholders. We discuss how to use these techniques to analyze the economic performance of concentrated solar power and energy storage technologies under multi-scale electricity markets. We also demonstrate how to use these capabilities to assess the impacts of coordination (or the lack thereof) between natural gas, computing, and electrical power infrastructures. 

Victor M. Zavala is the Richard H. Soit Assistant Professor in the Department of Chemical and Biological Engineering at the University of Wisconsin-Madison. Before joining UW-Madison, he was a computational mathematician in the Mathematics and Computer Science Division at Argonne National Laboratory. He holds a B.Sc. degree from Universidad Iberoamericana and a Ph.D. degree from Carnegie Mellon University, both in chemical engineering.  He is on the editorial board of the Journal of Process Control and Mathematical Programming Computation. His research interests are in the areas of mathematical modeling of energy systems, high-performance computing, optimization under uncertainty, and model predictive control. 

Monday, May 8, 2017
12:15 pm – 1:00 pm
Room 104, Green Earth Sciences Building, 367 Panama Street, Stanford Map

Engineering Seminar 

Faculty/Staff, Students
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