University of Cambridge > Talks.cam > Isaac Newton Institute Seminar Series > Computational Methods for Nonlinear Power Operational Problems: Convex Reformulations and Near-Linear Time Algorithms

Computational Methods for Nonlinear Power Operational Problems: Convex Reformulations and Near-Linear Time Algorithms

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact info@newton.ac.uk.

MESW01 - Flexible operation and advanced control for energy systems

Co-authors: Somayeh Sojoudi (UC Berkeley), Richard Zhang (UC Berkeley), Salar Fattahi (UC Berkeley), Igor Molybog (UC Berkeley), Ming Jin (UC Berkeley), SangWoo Park (UC Berkeley)In this talk, we will study a set of nonlinear power optimization and decision-making problems, namely power flow, optimal power flow, state estimation and topology error detection. We will propose different conic relaxation and approximation techniques to solve these nonconvex problems. We will prove that such conic problems could be solved in near linear time due to intrinsic properties of real-world power networks. We will offer case studies on systems with as high as 14,000 nodes.

This talk is part of the Isaac Newton Institute Seminar Series series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

 

© 2006-2019 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity