The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
Dynamic Modeling of Cascading Failure in Power Systems
Open accessAbstract
The modeling of cascading failure in power systems is difficult because of the many different mechanisms involved; no single model captures all of these mechanisms. Understanding the relative importance of these different mechanisms is important for choosing which mechanisms need to be modeled for particular applications. This work presents a dynamic simulation model of both power networks and protection systems, which can simulate a wider variety of cascading outage mechanisms relative to existing quasi-steady-state (QSS) models. This paper describes the model and demonstrates how different mechanisms interact. In order to test the model, we simulated a batch of randomly selected N-2 contingencies for several different static load configurations, and found that the distributions of blackout sizes and event lengths from the simulator correlate well with historical trends. The results also show that load models have significant impacts on the cascading risks. Finally, the dynamic model was compared against a simple dc-power-flow based QSS model; we find that the two models tend to agree for the early stages of cascading but produce substantially different results for later stages.
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Cites
Power System Stability and Control
Kundur, P. (1994) · Cited by 19,639
Complex networks: structure and dynamics
BOCCALETTI, S., LATORA, V, MORENO, Y., CHAVEZ, M., & HWANG, D. (2006) · Physics Reports · doi:10.1016/j.physrep.2005.10.009 · Cited by 11,010
Zimmerman, R. D., Murillo-Sanchez, C. E., & Thomas, R. J. (2011) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2010.2051168 · Cited by 6,756
Power system control and stability.
(1979) · Mathematics and Computers in Simulation · doi:10.1016/0378-4754(79)90142-3 · Cited by 2,574
Structural vulnerability of the North American power grid
Albert, R., Albert, I., & Nakarado, G. L. (2004) · Physical Review E · doi:10.1103/physreve.69.025103 · Cited by 1,415
An introduction to hybrid dynamical systems
van der Schaft, A., & Schumacher, H. (2000) · Lecture Notes in Control and Information Sciences · doi:10.1007/bfb0109998 · Cited by 1,216
Dobson, I., Carreras, B. A., Lynch, V. E., & Newman, D. E. (2007) · Chaos: An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/1.2737822 · Cited by 954
Power System Modelling and Scripting
Milano, F. (2010) · Power Systems · doi:10.1007/978-3-642-13669-6 · Cited by 794
Grainger, J. J., & Stevenson, W. D. (1994) · CERN Document Server (European Organization for Nuclear Research) · Cited by 747
Carreras, B. A., Lynch, V. E., Dobson, I., & Newman, D. E. (2002) · Chaos: An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/1.1505810 · Cited by 542
Cited by
Toward a consensus on the definition and taxonomy of power system resilience
Gholami, A., Shekari, T., Amirioun, M. H., Aminifar, F., Amini, M. H., & Sargolzaei, A. (2018) · IEEE Access · doi:10.1109/access.2018.2845378 · Cited by 294
Metadata
- Authors
- Song, J., Cotilla-Sanchez, E., Ghanavati, G., & Hines, P. D. H.
- Venue
- IEEE Transactions on Power Systems
- Published
- 2016-05
- Volume
- 31
- Issue
- 3
- Pages
- 2085-2095
- ISSN
- 0885-8950 (ISSN-L)
- 1558-0679
- OpenAlex
- W1529547156
- Cited by
- 274
- References
- 29
- FWCI
- 6.90
- Type
- journal article
- Language
- en
- Open access
- green
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