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A risk-based resilient distribution system planning model against extreme weather events

Zare Bahramabadi, M ; Sharif University of Technology | 2022

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  1. Type of Document: Article
  2. DOI: 10.1049/rpg2.12503
  3. Publisher: John Wiley and Sons Inc , 2022
  4. Abstract:
  5. Due to the accelerated climate change, it is anticipated that the number and severity of natural disasters such as hurricanes, blizzards, and floods will be increased in the coming years. In this regard, this paper presents a distribution system planning model to improve the system resilience against hurricane. A scenario-based mathematical model is proposed to capture the random nature of weather events. Moreover, a stochastic optimization model is developed to simultaneously harden the distribution lines and place different types of distributed generation (DG) units such as microturbines (MTs), wind turbines (WTs), and photovoltaic cells (PVs). The conditional value at risk (CVaR) is used as a risk index to manage the system risk against different failure scenarios. The problem is formulated as a mixed integer linear programming (MILP) model that can be solved by various commercial solvers. Finally, to illustrate the effectiveness of the proposed model, it is implemented on the IEEE 33 bus system, and various case studies are defined. The results show the effectiveness of our mathematical model in improving the distribution system resiliency and managing the system risk. © 2022 The Authors. IET Renewable Power Generation published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology
  6. Keywords:
  7. Climate change ; Disasters ; Hurricanes ; Integer programming ; Photoelectrochemical cells ; Risk perception ; Stochastic models ; Storms ; Value engineering ; Weather information services ; Distribution system planning ; Extreme weather events ; Natural disasters ; Planning models ; Risk-based ; Scenario-based ; Stochastic optimization model ; System resiliences ; System risk ; Weather events ; Solar cells
  8. Source: IET Renewable Power Generation ; Volume 16, Issue 10 , 2022 , Pages 2125-2135 ; 17521416 (ISSN)
  9. URL: https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/rpg2.12503