Changes in Cascading Failure Risk with Generator Dispatch Method and System Load Level

Industry reliability rules increasingly require utilities to study and mitigate cascading failure risk in their system. Motivated by this, this paper describes how cascading failure risk, in terms of expected blackout size, varies with power system load level and pre-contingency dispatch. We used Monte Carlo sampling of random branch outages to generate contingencies, and a model of cascading failure to estimate blackout sizes. The risk associated with different blackout sizes was separately estimated in order to separate small, medium, and large blackout risk. Results from $N-1$ secure models of the IEEE RTS case and a 2383 bus case indicate that blackout risk does not always increase with load level monotonically, particularly for large blackout risk. The results also show that risk is highly dependent on the method used for generator dispatch. Minimum cost methods of dispatch can result in larger long distance power transfers, which can increase cascading failure risk.Comment: Submitted to Transmission and Distribution Conference and Exposition (T&D), 2014 IEEE PE

A Large Mass of H_2 in the Brightest Cluster Galaxy in Zwicky 3146

We present the Spitzer/IRS mid-infrared spectrum of the infrared-luminous (L_(IR) = 4 × 10^(11) L_☉) brightest cluster galaxy (BCG) in the X-ray-luminous cluster Zwicky 3146 (Z3146; z = 0.29). The spectrum shows strong aromatic emission features, indicating that the dominant source of the infrared luminosity is star formation. The most striking feature of the spectrum, however, is the exceptionally strong molecular hydrogen (H_2) emission lines, which seem to be shock-excited. The line luminosities and inferred warm H_2 gas mass (~10^(10) M_☉) are 6 times larger than those of NGC 6240, the most H_2-luminous galaxy at z ≲ 0.05. Together with the large amount of cold H_2 detected previously (~10^(11) M_☉), this indicates that the Z3146 BCG contains disproportionately large amounts of both warm and cold H_2 gas for its infrared luminosity, which may be related to the intracluster gas cooling process in the cluster core

Development of vibration design procedures for representative structural types Final technical report, Sep. 1965 - Jul. 1966

Effects of multimode and damping on random fatigue of cantilever beams and bracket

Cascading Power Outages Propagate Locally in an Influence Graph that is not the Actual Grid Topology

In a cascading power transmission outage, component outages propagate non-locally, after one component outages, the next failure may be very distant, both topologically and geographically. As a result, simple models of topological contagion do not accurately represent the propagation of cascades in power systems. However, cascading power outages do follow patterns, some of which are useful in understanding and reducing blackout risk. This paper describes a method by which the data from many cascading failure simulations can be transformed into a graph-based model of influences that provides actionable information about the many ways that cascades propagate in a particular system. The resulting "influence graph" model is Markovian, in that component outage probabilities depend only on the outages that occurred in the prior generation. To validate the model we compare the distribution of cascade sizes resulting from $n-2$ contingencies in a $2896$ branch test case to cascade sizes in the influence graph. The two distributions are remarkably similar. In addition, we derive an equation with which one can quickly identify modifications to the proposed system that will substantially reduce cascade propagation. With this equation one can quickly identify critical components that can be improved to substantially reduce the risk of large cascading blackouts.Comment: Accepted for publication at the IEEE Transactions on Power System