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Distribution transformer relocation problem: an integer programming solution

Azimi Hosseini, K ; Sharif University of Technology | 2021

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  1. Type of Document: Article
  2. DOI: 10.1049/gtd2.12016
  3. Publisher: John Wiley and Sons Inc , 2021
  4. Abstract:
  5. The short-term expansion planning of the private utilities, as well as the emerging technologies such as photovoltaic panels (PVs), plug-in hybrid electric vehicles (PHEVs), cryptocurrency mining, and storage elements spread, make the long-term load estimation of distribution transformers (DTs) noticeably imprecise. In response, the number of overload and underload transformers is growing in recent years. The utilities normally analyse the loading of their DTs annually to determine the DTs, which should be replaced. It is a common practice for utilities to relocate these DTs to reduce the investment needed to purchase new transformers. Therefore, the utility needs a systematic algorithm to determine the optimal schedule to relocate/replace the DTs with minimum required time and cost. This paper introduces a two-stage procedure to obtain the optimal schedule to replace DTs. In the proposed algorithm, the maximum permitted number of work-hours per day for field workers is considered, which converts the problem to a daily-task based optimisation problem. Also, an useful life investigation of the in-service DTs is considered in the relocation problem. A real case study in Qom province, Iran, has been studied to prove the effectiveness of the proposed algorithm. © 2020 The Authors. IET Generation, Transmission & Distribution published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology
  6. Keywords:
  7. Electric transformer loads ; Electric transformers ; Integer programming ; Photovoltaic cells ; Distribution transformer ; Emerging technologies ; Optimisation problems ; Photovoltaic panels ; Plug-in hybrid electric vehicles ; Relocation problem ; Short-term expansion ; Two stage procedure ; Plug-in hybrid vehicles
  8. Source: IET Generation, Transmission and Distribution ; Volume 15, Issue 1 , 2021 , Pages 108-120 ; 17518687 (ISSN)
  9. URL: https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/gtd2.12016