Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Electrical and Electronic Engineering | en_US |
| dc.contributor.advisor | Bu, Siqi (EEE) | en_US |
| dc.creator | Fang, Ce | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/14128 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | en_US |
| dc.rights | All rights reserved | en_US |
| dc.title | Power system resilience assessment and enhancement | en_US |
| dcterms.abstract | Given the importance of energy supply and the changes in extreme weather, maintaining energy security and socioeconomic stability now heavily depends on the power system's robustness. This thesis discusses in depth the evaluation and improvement strategies of power system resilience and improvement methods, aiming at improving the resilience and stability of the power grid in response to disasters, equipment failures, and other emergency accidents. | en_US |
| dcterms.abstract | We use historical datasets documenting an extreme tornado event and tower distribution data by primary modeling to calculate the compound failure probability. The concept and importance of toughness assessment are analyzed in detail. A proposed elastic evaluation method outlines indexes for assessing the power grid's capacity during disasters. Effective distribution network repair is crucial for reducing power loss and restoring normal operation during typhoons. Implementing a strategic emergency repair schedule can improve power supply reliability and stability, while minimizing load loss and social/economic impacts. Emergency repair work for distribution network faults during typhoons is highly significant. A model for repairing distribution networks after a typhoon has been developed to address post-disaster repair work. The model analyzes constraints related to construction teams, material vehicles, branch power flow, radial constraints, and multi-coupling constraints. The simulated annealing algorithm is utilized to solve the nonlinear decision model with the objective of maximizing weighted load recovery. The effectiveness of the model and algorithm is simply demonstrated using the IEEE15-node system as a case study. | en_US |
| dcterms.extent | 1 volume (various pagings) : color illustrations | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2024 | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 8592.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 1.69 MB | Adobe PDF | View/Open |
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