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Mixed-integer nonlinear programming formulation for distribution networks reliability optimization

  • Alireza Heidari*
  • , Zhao Yang Dong
  • , Daming Zhang
  • , Pierluigi Siano
  • , Jamshid Aghaei
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

An optimal placement of protective devices could increase the reliability and quality level of a distribution network. An innovative mixed-integer nonlinear programming model is proposed in this paper to find the type, optimal siting, and number of protective devices to be accurately installed in distribution networks. The customer outage and protective devices costs are considered to derive a value-based reliability equation. To ensure the effectiveness of the proposed formulation economic and technical constraints is considered. Further, this paper aims at aiding decision-makers in providing appropriate protective device allocation by minimizing the expected interruption cost index. Case studies are employed to demonstrate the reliability optimization of a test network and a typical real-size network in which the several cost constraints and protection schemes are assumed to extract the results. Accuracy and effectiveness of the proposed method are assessed and sensitivities analysis is carried out. © 2005-2012 IEEE.
Original languageEnglish
Pages (from-to)1952-1961
JournalIEEE Transactions on Industrial Informatics
Volume14
Issue number5
DOIs
Publication statusPublished - 1 May 2018
Externally publishedYes

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Research Keywords

  • Distribution system reliability
  • mixed-integer nonlinear programming (MINLP)
  • protective device
  • sectionalizing switch placement

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