Join Yongpei Guan, Director of the University of Florida’s Computational and Stochastic Optimization Lab and Hao Yan, Milton D. Glick Distinguished Professor at ASU, as they discuss Guan’s research on polynomial time algorithms and their relation to power systems.
Seminar: Polynomial Time Algorithms and Strong Formulations for Unit Commitment Problems
Friday, October 26, 2018
Brickyard Engineering Building (BYENG) 210, Tempe Campus [map]
Recent increased renewable energy generation brings challenges for power system operators to perform efficient power generation daily scheduling due to the intermittent nature of the renewable generation and discrete decisions of each generation unit. Unit commitment polytope is fundamental among all aspects considered and is embedded in models at different stages of power systems planning and operations.
In this talk, Yongpei Guan describes the polynomial time algorithms for the unit commitment problems with general convex cost function and piecewise linear cost function, respectively. Then, by exploring its specialized structures, researchers derive strong valid inequalities and explore a new proof technique to prove these inequalities are sufficient to provide convex hull descriptions for certain special cases. We also derive generalized strong valid inequalities for general multi-period cases and further prove that these inequalities are facet-defining under mild conditions.
Moreover, researchers discover efficient polynomial time separation algorithms for these inequalities to improve computational efficiency. Finally, extensive computational experiments are conducted to verify the effectiveness of our proposed inequalities by testing their applications to solve both the network-constrained and self-scheduling unit commitment problems, for which the derived approach outperforms the default CPLEX significantly.
About the Speaker
Yongpei Guan serves as a Professor of Industrial and Systems Engineering and Director of the Computational and Stochastic Optimization Lab at the University of Florida. His research interests include stochastic and discrete optimization, energy system optimization, and supply chain management. His works in these areas have led to NSF Career Award 2008 and Office of Naval Research Young Investigator Award 2010. Yongpei is currently a Department Editor of IISE Transactions and Associate Editor for the Journal of Global Optimization and Computational Optimization and Applications. Guan earned his doctorate from Georgia Tech in 2005.