Real-time grid topology modeling and optimization for power transmission systems
| dc.contributor.advisor | Zhu, Hao, (Ph. D. in electrical and computer engineering) | |
| dc.contributor.committeeMember | Santoso, Surya | |
| dc.contributor.committeeMember | Caramanis, Constantine | |
| dc.contributor.committeeMember | Topcu, Ufuk | |
| dc.contributor.committeeMember | Hanasusanto, Grani | |
| dc.creator | Zhou, Yuqi | |
| dc.date.accessioned | 2024-02-27T23:11:12Z | |
| dc.date.available | 2024-02-27T23:11:12Z | |
| dc.date.created | 2022-12 | |
| dc.date.issued | 2022-12-01 | |
| dc.date.submitted | December 2022 | |
| dc.date.updated | 2024-02-27T23:11:12Z | |
| dc.description.abstract | Accurately modeling and tactfully switching power grid topology are not only crucial for routine power system operational tasks but also play a critical role in system emergency responses under extreme events. The modern power grids have recently witnessed more frequent occurrences of unintentional topology changes. These changes can be caused by misoperations of substation protection systems, malicious cyber attacks, or natural disasters. Although strategically altering the grid topology through transmission switching can effectively relieve network congestion and thus has the potential to mitigate the impact of these events, the optimal decision is in general difficult to attain due to the uncertainty and variability therein. Therefore, this motivates us to devise efficient algorithms for achieving real-time power grid topology monitoring and optimization. This dissertation first focuses on efficient modeling and monitoring of the bus split event, which is a type of grid topology change caused by circuit breakers in substations. We perform sensitivity analysis to evaluate the grid-wide impact of such events under the bus-branch representation, for which a synchrophasor data enabled identification problem is presented by matching the changes in the measurements. Inspired by this, we next explore the transmission switching problem that can incorporate the substation-level topology changes. Furthermore, to perform reliable and cost-effective transmission switching under the renewable uncertainty, we study the distributionally robust chance-constrained problem, which can provide superior robustness guarantees over the traditional chance-constrained formulation. Finally, to provide effective system responses under extreme weather events, we will also investigate scalable optimization and learning algorithms for quick power grid restoration. | |
| dc.description.department | Electrical and Computer Engineering | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | https://hdl.handle.net/2152/123818 | |
| dc.identifier.uri | https://doi.org/10.26153/tsw/50612 | |
| dc.subject | Power systems | |
| dc.subject | Transmission switching | |
| dc.subject | Grid topology | |
| dc.subject | Bus splits | |
| dc.subject | Optimization | |
| dc.title | Real-time grid topology modeling and optimization for power transmission systems | |
| dc.type | Thesis | |
| dc.type.material | text | |
| local.embargo.lift | 2024-12-01 | |
| local.embargo.terms | 2024-12-01 | |
| thesis.degree.department | Electrical and Computer Engineering | |
| thesis.degree.discipline | Electrical and Computer Engineering | |
| thesis.degree.grantor | The University of Texas at Austin | |
| thesis.degree.level | Doctoral | |
| thesis.degree.name | Doctor of Philosophy |
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