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ANALYSIS OF FAILURES IN THE POWER GRID VIA THE PSEUDOINVERSE OF THE ADMITTANCE MATRIX

Recent large-scale power outages demonstrated the limitations of percolationand epidemic-based tools in modeling failures in power grids. Hence, we study the impact of line failures on the flow changes and cascade in the transmission system of the power grid by using a linearized power flow model. We use the pseudo-inverse of the power grid admittance matrix to obtain upper bounds on the flow changes after a failure, develop an efficient algorithm to identify the cascading failure evolution, and develop a simple heuristic to find a set of line failures with the highest impact. Overall, the results demonstrate that the resistance distance and the pseudo-inverse of admittance matrix provide important insights and can support the development of efficient algorithms.