Abstract:
Loss of stability may eventually lead to blackouts which despite being rare, are extremely costly. However, to ensure system stability is a non-trivial task. First, power systems, by nature, are complex nonlinear dynamical ones so to assess and maintain the system stability is challenging mainly due to the co-existence of multiple equilibria and the lack of global stability. Second, the systems are subject to various sources of uncertainties and disturbances. Unfortunately, the current security assessment may not be sufficient to verify the system stability in the presence of such uncertainties. This talk focuses on new approaches for robust stability assessment. First I will discuss a novel computationally tractable approach for constructing OPF feasibility (convex) subsets. For any inner point of the subset, the power flow problem is guaranteed to have a feasible solution which satisfies all the operational constraints in the corresponding OPF. This inner approximation technique is developed based on Brouwer's fixed point theorem. Simulation results show that the constructed region covers a substantial fraction of the true feasible set. Next, I will introduce another inner approximation technique for estimating the attraction domain of a post-fault equilibrium based on contraction analysis. The technique is scalable as the attraction region can be characterized by analyzing extended virtual systems which are linear in the system states. In the last part of the talk, I will focus on small-signal stability assessment under load dynamic uncertainties. After introducing a generic impedance-based load model which can capture the uncertainties, I propose a new robust small signal stability (RSS) criterion. Semidefinite programming is used to find a structured Lyapunov matrix, and if it exists, the system is provably RSS stable. The criterion can naturally apply to characterize operating regions which are safe from a Hopf bifurcation.

Bio:
Hung D. Nguyen received his B.E. degree in electrical engineering from Hanoi University of Technology, Vietnam, and an M.S. degree with honors in electrical engineering from Seoul National University, Korea. He is a Ph.D. candidate in the Department of Mechanical Engineering at Massachusetts Institute of Technology (MIT). His current research interests include power system operation, control, and optimization; the nonlinear dynamics, and stability of large-scale power systems; Dynamic Security Assessment/Energy Management System; and smart grids. He is a Siebel Scholar class of 2017 on Energy Science. He is working on several joined projects supported by NSF and DOE and in collaboration with ISO New England, LANL, and PNNL. With his advisor, Konstantin Turitsyn, he is developing PowerWolf, one of the first powerful power system analysis software packages in Mathematica. He is currently running Electricity Student Research Group (ESRG) at MIT for students studying electric power systems.