【Title】 A Case Study of Data-Driven Stochastic Optimization Approaches in Power System Operations 

【Presenter】Dr.Ruiwei Jiang, Assistant Professor, University of Arizona 

【Host】 Dr. Lei Zhao 

【Date】Thursday  June 11, 2015, 15:30 – 16:30 

【Venue】Room 510, Shunde Building 

【Abstract】

The exciting transformation of today’s power systems toward ‘smart grids’ accompanies an incorporation of considerable uncertainty in daily operations. The sources of the uncertainty include renewable energy (e.g., wind, solar, and water), electricity prices in deregulated markets, and so on. For the sake of robustness, power system participants often need to make over-conservative decisions based on incomplete historical data and ambiguous understanding of the uncertainty. In this talk, we apply data-driven stochastic optimization approaches on power system operations, with the objective of making less-conservative decisions and better balancing robustness and cost-effectiveness. Numerical results based on real data will be presented and discussed.

【Bio】

Dr. Ruiwei Jiang is currently an assistant professor in the Department of Systems and Industrial Engineering at the University of Arizona. Previously, Ruiwei received a Ph.D. degree in Industrial and Systems Engineering from the University of Florida, Gainesville, FL, and a B.S. degree in Industrial Engineering from the Tsinghua University, Beijing. His research interests include stochastic optimization, integer programming, power system operations, and healthcare operations.