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Improving Network Reductions for Power System Analysis


Abstract The power system is the largest man-made physical network in the world. Performing analysis of a large bulk system is computationally complex, especially when the study involves engineering, economic and environmental considerations. For instance, running a unit-commitment (UC) over a large system involves a huge number of constraints and integer variables. One way to reduce the computational expense is to perform the analysis on a small equivalent (reduced) model instead on the original (full) model.

The research reported here focuses on improving the network reduction methods so that the calculated results obtained from the reduced model better approximate the performance of the original model. An optimization-based Ward reduction (OP-W... (more)
Created Date 2017
Contributor Zhu, Yujia (Author) / Tylavsky, Daniel John (Advisor) / Vittal, Vijay (Committee member) / Hedman, Kory (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Subject Electrical engineering / Holomorphic embedding / Network reduction / Power system analysis
Type Doctoral Dissertation
Extent 146 pages
Language English
Copyright
Reuse Permissions All Rights Reserved
Note Doctoral Dissertation Electrical Engineering 2017
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS


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Description Dissertation/Thesis