Collaborative Research: Computationally Efficient Solvers for Power System SimulationMariesa Crow, Electrical Engineering, Missouri University of Science & TechnologyMaggie Cheng, Computer Science, Missouri University of Science & TechnologyShuwang Li, Applied Mathematics, Illinois Institute of TechnologyAbstract: Several recent advances in computational methods in a variety of fields have brought the goal of real-time dynamic simulation within reach. Unfortunately, many power system analysis tools do not use algorithms that implement state-of-the-art solution techniques due to the time lag of results percolating from one field to another. Therefore, there is a need to bring together the best of the mathematicians, computer scientists, and power engineers to solve realistic problems. In this project, computationally efficient solution methods will be synergistically developed and applied to the problem of achieving real-time power system simulation. Specifically, recent advances in computational science and theoretical computer science will be extended to the problem of electric power networks. Intellectual Merit: Real-time simulation has long been considered to be a grand challenge in electric power engineering. A realistically sized electric power network problem can generate hundreds of dynamic state variables and 50,000+ algebraic states. The computational complexity of some power system simulations has kept time domain simulation from being used in on-line decision making. If simulations could run in real-time, then power system operators would have situational awareness and could implement on-line control to avoid cascading failures. This tool will assist the operator with proactive measures to limit the extent of the incident, and can significantly improve power system reliability. This project will exploit the expertise and advances in areas of linear solvers from a variety of physical fields and will adapt them for use in power system simulation.Broader Impact: This project will provide an opportunity for educating a diverse STEM workforce in electric power systems, computer algorithms and applied mathematics. The PIs, the graduate students, and the post-doctoral fellow will enter into a close mentoring relationship that will include one-on-one instruction not only in computational methods, but also ethical research practices, communication skills, and international awareness. The results of this research will be incorporated into multiple graduate classes: Computational Methods for Power Systems andApproximation Algorithms. The PIs will also develop undergraduate course material and pre-college hands-on projects.
|Effective start/end date||10/1/16 → 7/31/18|
- National Science Foundation