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Resilience-oriented distribution network optimal planning to improve the continuity of power supply

Ghaffarpour, R ; Sharif University of Technology | 2020

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  1. Type of Document: Article
  2. DOI: 10.1080/01430750.2018.1451373
  3. Publisher: Taylor and Francis Ltd , 2020
  4. Abstract:
  5. A widely dispersed asset, electric grid has enormous impacts on people’s lives. Recently occurred various high-impact low-probability (HILP) threats have raised the concerns about the classical reliability-oriented view. Therefore, withstanding unexpected and less frequent severe situations still remain a significant challenge. As a critical infrastructure (CI), power systems are more and more expected to be resilient to HILPs. So, utilities put their endeavours to harden enough their networks against HILPs. In this regard, there is a great need to a methodology able to optimise the hardening programme investments. This scheme could potentially save a large amount of money, as well as increase the resilience of the programme. So, this paper is organised to provide a comprehensive study on optimal resilient planning of distribution networks aiming to find an optimal solution for simultaneous optimal feeder routing problem and substation allocation, finding types of installed conductors and cost-effective hardening of the lines considering the deliberate attacks on urban CIs, costs and operational parameters in normal and resilient modes of distribution networks. Voltage limitation and thermal limit of feeders are modelled using fuzzy set theory. To validate the effectiveness of the proposed scheme, simulations are carried out on a relatively large-scale distribution network. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group
  6. Keywords:
  7. Genetic algorithm ; Hardening ; Optimal Resilient Distribution network Planning ; Resiliency ; Cost effectiveness ; Electric power systems ; Genetic algorithms ; Hardening ; Investments ; Distribution network planning ; Large-scale distribution ; Operational parameters ; Optimal planning ; Optimal solutions ; Oriented distributions ; Voltage limitation ; Fuzzy set theory
  8. Source: International Journal of Ambient Energy ; Volume 41, Issue 4 , 2020 , Pages 466-474
  9. URL: https://www.tandfonline.com/doi/abs/10.1080/01430750.2018.1451373