Seminar by Jean-Paul Watson
On the Rigorous Evaluation of Stochastic Approaches to Power Systems Operations
Discrete Math and Optimization Department
Sandia National Laboratories
While there is significant recent research on stochastic optimization approaches to power systems operations, e.g., unit commitment and economic dispatch, there are still major impediments to their adoption in practice. In our experience, developed over years of attempting to deploy such approaches, one key issue is accurate evaluation of any proposed approach, relative to existing deterministic operational methodologies. In this talk, we discuss the challenges in such evaluation, and report on a novel methodology addressing what we feel to be deficiencies with current approaches. In the talk, we focus on issues relating to data availability and segmentation, probabilistic scenario generation, and the impact of scenarios on operational performance.
Dr. Jean-Paul Watson is a Distinguished Member of Technical Staff in the Discrete Math and Optimization Department at Sandia National Laboratories, in Albuquerque, New Mexico. He has over 14 years of experience applying and analyzing algorithms for solving difficult combinatorial optimization and informatics problems, in fields ranging from logistics and infrastructure security to power systems and computational chemistry. His research currently focuses on methods for approximating the solution of large -scale deterministic and stochastic mixed-integer and non-linear programs, with applications in the domain of electricity grid operations, planning, and resiliency. Previously, he developed solutions for real-world stochastic optimization problems in logistics (Lockheed Martin and the US Army) and sensor placement (US Environmental Protection Agency).