Restricting Involuntary Extension Of Failures In Smart Grids Using Social Network Metrics

Jose Cordova Garcia Stony Brook University, USA
Dongliang Xie State University of New York at Stony Brook, USA
Xin Wang Stony Brook University, USA


Modern communication technologies are expected to be available in the future Smart Grids to enable the control of equipments over the whole power grid. In this paper, we consider such networked control approach to address failures that may occur at any location of the grid, due to attacks or unit malfunction, and provide a wide-scale solution that prevent the failure impacts from spreading over a large area. Different from literature work that focuses on modifying power equations under the standard constraints of the power system, we estimate the impact of controlling different nodes on topological areas of the grid based on social metrics, which are derived from the graph capturing both the topological and electrical properties of the power grid. We propose a failure control algorithm for topological containment of failures in smart grid. Our algorithm also takes careful consideration of the impact the planned control has on the grid to avoid the possibly involuntary failure extension. We show that social metrics can efficiently trade off between the topological and electrical characteristics revealed by the power grid graph representation. We evaluate the performance against networked control strategies that only use power models to determine the actions to be performed at power nodes. Our results show that the proposed control scheme can effectively contain failures within their original location range.

You may want to know: