WHAT DID THE 2012 EARLY CAREER AWARD ALLOW YOU TO DO?
The Department of Energy Early Career Research Award was instrumental in helping me launch my scientific career. This award allowed me to explore new and exciting directions in the development of scalable algorithms and software for optimization problems under uncertainty that arise in energy infrastructures.
With the advent of the smart grid, renewable technologies, and carbon emission programs, a key concern is the coordination of national infrastructures such as the electricity, natural gas, and water supply network systems. Scalable high‐performance computing algorithms will aid the design and real‐time dispatch operations of national energy infrastructure systems.
Using our new algorithms and software, we are currently solving optimization problems that we previously thought to be intractable. We have been able to tackle problems of interest to industry and national labs.
Moreover, the research activities and products developed have been used to train a new generation of postdoctoral, graduate, and undergraduate researchers. These researchers are now working in industry, academia, and national labs.
The work developed under this award has also allowed me to catalyze research in other domains. Graph optimization and machine learning currently form the core of the research in my group.
Research supported by my Early Career Award was the basis for my Presidential Early Career Award for Scientists and Engineers. I received the PECASE award in 2019 for contributions to computational strategies for power systems.
Victor M. Zavala is the Baldovin-DaPra Professor in the Department of Chemical and Biological Engineering at the University of Wisconsin-Madison and a Computational Mathematician in the Mathematics and Computer Science Division at Argonne National Laboratory.
SUPPORTING THE DOE SC MISSION:
The Early Career Research Program provides financial support that is foundational to early career investigators, enabling them to define and direct independent research in areas important to DOE missions. The development of outstanding scientists and research leaders is of paramount importance to the Department of Energy Office of Science. By investing in the next generation of researchers, the Office of Science champions lifelong careers in discovery science.
For more information, please go to the Early Career Research Program.
THE 2012 PROJECT ABSTRACT:
Title Next‐Generation Optimization under Uncertainty: Structure‐Oriented Algorithms
With the advent of the smart grid, renewable technologies, and carbon emission programs, a key concern is the coordination of national infrastructures such as the electricity, natural gas, and water supply network systems. Anticipating and mitigating uncertainty of weather, demands, and contingencies in a more integrated environment are necessary to maximize resource efficiency and prevent cascading failures that can ultimately lead to catastrophic shortages of supplies. This project will develop scalable high‐performance computing algorithms that will aid the design and real‐time dispatch operations of national energy infrastructure systems.
K Kim and VM Zavala, “Algorithmic innovations and software for the dual decomposition method applied to stochastic mixed-integer programs.” Mathematical Programming Computation 10, 225 (2018). [DOI: 10.1007/s12532-017-0128-z]
N. Chiang, CG Petra, and VM Zavala, “Structured nonconvex optimization of large-scale energy systems using PIPS-NLP.” IEEE 2014 Power Systems Computation Conference, p.1 (2014). [DOI: 10.1109/PSCC.2014.7038374]
J Jalving, Y Cao, and VM Zavala, “Graph-based modeling and simulation of complex systems.” Computers & Chemical Engineering, 125, 134 (2019). [DOI: 10.1016/j.compchemeng.2019.03.009]
Journal Link: Mathematical Programming Computation Journal Link: IEEE Journal Link: Computers & Chemical Engineering