Thesis
Improving the restoration strategy of transmission system under windstorm
Washington State University
Master of Science (MS), Washington State University
05/2020
DOI:
https://doi.org/10.7273/000004242
Handle:
https://hdl.handle.net/2376/124878
Abstract
The weather-related power outages have become the main type of outages in recent decades in the U.S., leading to significant social and economic losses each year. Among multiple extreme weather types, the storm is the most common type causing power system outage. Researchers were trying to analyze weather-related outages and find ways to improve the power system performance under extreme weather. Under such circumstances, resilience, representing the ability of the power system to withstand extreme events, has attracted more attention. According to the National Infrastructure Advisory Council (2009), we can make efforts to three terms to improve power system resilience: robustness, resourcefulness, and rapid recovery. In this thesis, we are trying to improve transmission system recovery under windstorms by considering outage estimation and mutual assistance. We develop our models based on the Transmission-Constrained Unit Commitment (TCUC) model and test them on a 6-bus system and a 24-bus system, respectively. The method we use to solve these problems is Mixed Integer Linear Programming (MILP). The simulation results prove the efficiency of the proposed model. In the future, we are trying to improve our models by considering Distributed Generations (DGs).
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Details
- Title
- Improving the restoration strategy of transmission system under windstorm
- Creators
- Xue Gao
- Contributors
- Feng Zhao (Advisor) - Washington State University, Engineering and Computer Science (VANC), School of
- Awarding Institution
- Washington State University
- Academic Unit
- Engineering and Computer Science (VANC), School of
- Theses and Dissertations
- Master of Science (MS), Washington State University
- Publisher
- Washington State University
- Identifiers
- 99900896419601842
- Language
- English
- Resource Type
- Thesis