ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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- Creators: Korad, Akshay Shashikumar
This research presents three topology control (corrective transmission switching) methodologies along with the detailed formulation of robust corrective switching. The robust model can be solved off-line to suggest switching actions that can be used in a dynamic security assessment tool in real-time. The proposed robust topology control algorithm can also generate multiple corrective switching actions for a particular contingency. The solution obtained from the robust topology control algorithm is guaranteed to be feasible for the entire uncertainty set, i.e., a range of system operating states.
Furthermore, this research extends the benefits of robust corrective topology control to renewable resource integration. In recent years, the penetration of renewable resources in electrical power systems has increased. These renewable resources add more complexities to power system operations, due to their intermittent nature. This research presents robust corrective topology control as a congestion management tool to manage power flows and the associated renewable uncertainty. The proposed day-ahead method determines the maximum uncertainty in renewable resources in terms of do-not-exceed limits combined with corrective topology control. The results obtained from the topology control algorithm are tested for system stability and AC feasibility.
The scalability of do-not-exceed limits problem, from a smaller test case to a realistic test case, is also addressed in this research. The do-not-exceed limit problem is simplified by proposing a zonal do-not-exceed limit formulation over a detailed nodal do-not-exceed limit formulation. The simulation results show that the zonal approach is capable of addressing scalability of the do-not-exceed limit problem for a realistic test case.