Saleh Soltan and Guy Grebla Win Best Poster Award in Yearly DTRA Review

August 19, 2014

Saleh Soltan and Dr. Guy Grebla have received the Best Poster Award in the yearly program review of the Defense Threat Reduction Agency (DTRA). Saleh is a Ph.D. student in the WiMNet Lab under the supervision of Prof. Gil Zussman and Guy is a Postdoctoral Research Scientist co-advised by Prof. Zussman and Prof. Dan Bienstock (IEOR Dept.).

The poster - entitled “Cascading Failures in the Power Grid – Analytical Properties and Control with Imperfect Observations” summarizes research results in [1] and [2], which focus on analyzing the evolution of failures in the transmission system of the power grid and developing control algorithms to stop cascading failures. Recent large-scale power outages demonstrated the limitations of percolation- and epidemic-based tools in modeling failures in power grids. Hence, [1] studies the impact of line failures on the power flow changes and cascade in the transmission system of the power grid using a linearized power flow model. The pseudo-inverse of the power grid admittance matrix is used to obtain upper bounds on the power changes after a failure, develop an effi cient algorithm to identify the cascading failure evolution, and develop a simple heuristic to find a set of line failures with the highest impact. In [2], control algorithms that stop power grid cascading failures by minimally shedding load (i.e., reducing demand) are developed. The control is computed at the beginning of the cascade and applied as the cascade unfolds on the basis of real-time measurements. The algorithms operate in an environment where measurements are noisy, missing, or erroneous, and are shown to be robust to these measurements imperfections. More details are available here.

[1] S. Soltan, D. Mazauric, G. Zussman, “Cascading Failures in Power Grids – Analysis and Algorithms,” in Proc. ACM e-Energy’14 , June 2014.

[2] D. Bienstock, G. Grebla, and G. Zussman, “Optimal Control of Cascading Power Grid Failures with Imperfect Flow Observations,” presented in SIAM Workshop on Network Science, July 2014.