Worst-Case Probabilistic Network Outage Identification Under Physical Disturbances
This letter presents a mathematical optimization model to identify the worst-case probabilistic network outage scenario induced by physical disturbances. That is, we seek to find the outage scenario with the maximum combined likelihood and impact on the network. This is a challenging combinatorial problem, as the search domain exponentially grows with the size of the network and the impact of outages on the network is not usually explicitly quantifiable. In this letter, we develop an iterative algorithm to tackle these challenging issues by formulating it as a mixed-integer programming problem and tightening the search domain by bounding upper and lower bounds of the solution using the upper bound estimates of outage scenario probabilities. We also apply the proposed model to identify the worst-case outage scenarios in power networks, where the impacts of outage scenarios are calculated using the security-constrained optimal power flow problem. The numerical studies, conducted on two test power networks, demonstrate the efficiency and proven convergence of the proposed model in identifying the worst-case probabilistic outage scenario.
Network failure, power grid resilience, mixed-integer programming, Frechet probability inequalities, reliability.