Probabilistic Framework for Evaluation of Smart Grid Resilience of Cascade Failure

The next generation power grid demands high reliability, robustness and real time communication of control information related to power flow in the grid. This paper proposes a probabilistic framework of smart grid power network with statistical decision theory to evaluate system performance in steady state as well as under dynamical case and identify the probable critical links which can cause cascade failure. Proposed model for cascade failure prediction has been tested on the IEEE 30 bus test bed system. Simulation results validated critical links in probabilistic model of power grid system with deterministic power flow analysis. The key contribution of this paper is, performance evaluation of smart grid power network and identification as well as prediction of critical links which may lead to system blackout. In addition to this, a graphical model has been developed using minimum spanning tree to analyze topology and structural connectivity of IEEE 30 bus system.