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- Type of Document: Ph.D. Dissertation
- Language: Farsi
- Document No: 54624 (05)
- University: Sharif University of Technology
- Department: Electrical Engineering
- Advisor(s): Vakilian, Mehdi; Farzin, Hossein; Lehtonen, Matti
- Abstract:
- The number and severity of natural disasters have significantly increased in the recent years. Extreme weather-driven events cause catastrophic damages to power grid components. As a consequence, severe power outages occur in the affected grids. According to the published reports on natural disasters, 90 percent of such outages originate from distribution systems. In addition, the repair process of the damaged elements takes a long duration. Thus, it is necessary to improve the distribution system (DS) resilience against natural disasters. The strategies for resilience enhancement can be classified into two main groups: hardening and operation-oriented measures.Formation of microgrids has been recognized as an effective strategy for improving DS resilience against natural disasters. In this regard, this PhD thesis aims at exploring the effects of microgrid formation in enhancing the resilience of DSs. In this context and in the first step of this thesis, a new two-stage framework is proposed that co-optimizes island formation and repair schedule after a disaster. In addition, the disaster mutual assistance is taken into account in the proposed framework. In the next step, a new three-stage stochastic framework is presentedd to develop necessary islands during two-phase natural disasters. A storm that is followed by flood is handled as a two-stage disaster, and islands are formed in three stages, namely before storm arrival, during and after storm, and after flooding. In addition, stochastic programming method is utilized for modeling the uncertainties. Subsequently, a framework is presented to proactively develop the required islands prior to storm onset, while considering tree-caused failures. Finally, a two-stage stochastic framework is proposed which employs solar-powered charging stations of electric buses for improving DS resilience. It uses electric buses as electric energy resources. In addition, CVaR index is used for controlling the risk imposed by the uncertain parameters. All the presented frameworks have been validated through different case studies
- Keywords:
- Network Resiliance ; Microgrid ; Electricity Distribution Network ; Stochastic Programming ; Storm ; Flood ; Electrical Vehicle ; Conditional Value at Risk
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