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Tie-line planning for resilience enhancement in unbalanced distribution networks

Taheri, B ; Sharif University of Technology | 2022

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  1. Type of Document: Article
  2. DOI: 10.1049/gtd2.12347
  3. Publisher: John Wiley and Sons Inc , 2022
  4. Abstract:
  5. Over the past decades, there has been a dramatic increase in the frequency of natural disasters, which are the leading causes of large-scale power outages. This paper, therefore, assesses the significance and role of optimal tie-line construction in improving the service restoration performance of unbalanced power distribution systems in the aftermath of high-impact low-probability incidents. In doing so, a restoration process aware stochastic mixed-integer linear programming model is developed to find the optimal locations for new tie-line construction in unbalanced three-phase distribution systems. In particular, the restoration process of distribution systems, including the fault isolation and system reconfiguration, is contemplated to place tie-lines in the most proper locations to enhance the manoeuvring capability of distribution systems and reducing the customer interruption time. Furthermore, the model is a stochastic one wherein uncertainty associated with potential damages alongside demand uncertainty is captured via a set of likely scenarios. To validate the effectiveness of the proposed stochastic mixed-integer linear programming model, it is tested and verified on the IEEE 13- and 123-bus test systems. © 2021 The Authors. IET Generation, Transmission & Distribution published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology
  6. Keywords:
  7. Disasters ; Integer programming ; Outages ; Probability distributions ; Restoration ; Stochastic models ; Distribution systems ; Large-scales ; Line planning ; Mixed integer linear programming model ; Natural disasters ; Power outage ; Restoration process ; Stochastics ; Tie-line ; Unbalanced distribution networks ; Stochastic systems
  8. Source: IET Generation, Transmission and Distribution ; Volume 16, Issue 5 , 2022 , Pages 1030-1046 ; 17518687 (ISSN)
  9. URL: https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/gtd2.12347