Topological analysis and mitigation strategies for cascading failures in power grid networks

dc.contributor.authorPahwa, Sakshi
dc.date.accessioned2010-07-27T19:32:07Z
dc.date.available2010-07-27T19:32:07Z
dc.date.graduationmonthAugusten_US
dc.date.issued2010-07-27T19:32:07Z
dc.date.published2010en_US
dc.description.abstractIn recent times, research in the field of complex networks has advanced by leaps and bounds. Researchers have developed mathematical models for different networks such as epidemic networks, computer networks, power grid networks, and so on. In this thesis, the power grid has been modeled as a complex network. The power grid is being used extensively in every field today. Our dependence on the power grid has exceeded to an extent that we cannot think of survival without electricity. Recently, there has been an increasing concern about the growing possibility of cascading failures, due to the fact that the power grid is works close to full utilization. Furthermore, the problem will be exacerbated by the need to transfer a large amount of power generated by renewable sources from the regions where it is produced to the regions where it is consumed. Many researchers have studied these networks to find a solution to the problem of network robustness. Topological analysis may be considered as one of the components of analysis of a system's robustness. In the first part of this thesis, to study the cascading effect on power grid networks from a topological standpoint, we developed a simulator and used the IEEE standard networks for our analysis. The cascading effect was simulated on three standard networks, the IEEE 300 bus system, the IEEE 118 bus test system, and the WSCC 179 bus equivalent model. To extend our analysis to a larger set of networks with different topologies, we developed a first approximation network generator the creates networks with characteristics similar to the standard networks but with different topologies. The generated networks were then compared with the standard networks to show the effect of topology on the robustness of power grid networks. A comparison of the network metrics for the standard and the generated networks indicate that the generated networks are more robust than the standard ones. However, even if the generated topologies show an increased robustness with respect to the standard topologies, the real implementation and design of power grids based on those topologies requires further study, and will be considered as future work. In the second part of this thesis, we studied two mitigation strategies based on load reduction, Homogeneous load reduction and Targeted range-based load reduction. While the generic Homogeneous strategy will only mitigate the severity of the cascade when a non-negligible load reduction is performed, our newly proposed targeted load reduction strategy is much more efficient, reducing the load only in a small portion of the grid. The determination of this special portion of the grid is based on an algorithm, which finds the paths supplying power from the generators to the nodes. This algorithm is described in details in the Appendix B. While the Homogeneous strategy is easier to implement, efficient results can be obtained using the targeted strategy.en_US
dc.description.advisorCaterina M. Scoglioen_US
dc.description.degreeMaster of Scienceen_US
dc.description.departmentDepartment of Electrical and Computer Engineeringen_US
dc.description.levelMastersen_US
dc.description.sponsorshipEnergy and Power Affiliates Group, consisting of Burns and McDonnell, Westar Energy, Omaha Public Power District, and Nebraska Public Power District.en_US
dc.identifier.urihttp://hdl.handle.net/2097/4317
dc.language.isoen_USen_US
dc.publisherKansas State Universityen
dc.subjectpower griden_US
dc.subjectrobustnessen_US
dc.subjectcascadingen_US
dc.subjecttopologyen_US
dc.subjectgenerated networksen_US
dc.subjectmitigationen_US
dc.subject.umiEngineering, Electronics and Electrical (0544)en_US
dc.titleTopological analysis and mitigation strategies for cascading failures in power grid networksen_US
dc.typeThesisen_US

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