A Method for Ranking Critical Nodes in Power Networks Including Load Uncertainties

This paper presents a new method for ranking critical nodes in bulk power systems. The proposed approach is able to offer a list of nodes or substations, from which system planners can easily identify those facilities with more urgent investment needs. The ranking process includes both static (via optimal power flow) and dynamic (via transient stability) performance analyses to assess deterministic indices. These indices measure the static and dynamic vulnerabilities of the network. As an extension of the deterministic approach, a new ranking based on the same indices is evaluated through a Monte Carlo simulation, considering several load scenarios modeled through uncertainties and the related generating dispatches. Applications in a test system presenting the rank of critical nodes are provided and discussed.