A voltage drop limited decentralized electric power distribution network


COMPUTERS & OPERATIONS RESEARCH, vol.118, 2020 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 118
  • Publication Date: 2020
  • Doi Number: 10.1016/j.cor.2020.104907
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, PASCAL, ABI/INFORM, Aerospace Database, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, zbMATH, Civil Engineering Abstracts
  • Hacettepe University Affiliated: Yes


We consider a decentralized electric power distribution network design problem in rural areas with no existing infrastructure. While the source facilities can be located anywhere on the continuous space, the demand points are connected to these source facilities on a tree topology. Since excessive voltage drops cause problems with the appliances at the demand points, we employ a limitation on the voltage drop as a constraint in our distribution network design. Given the locations of demand points on a plane, we formulate a mixed-integer quadratically-constrained programming model for our design problem. Since this problem can be solved for only very small instances, we propose seven alternative heuristic methods that initially decompose the set of demand points into clusters that can be served by a single source facility. Then, for each cluster, these methods tackle the problems of locating the source facility on the continuous space and designing the voltage drop-limited minimum spanning tree to serve all demand points in the cluster by a single facility. We select the solution method based on the size of each cluster; alternative methods can be employed for different sized clusters of the same problem. We use numerical examples to demonstrate the benefits of the tree topology networks obtained by each method compared to the star topology distribution networks for the same clusters. (C) 2020 Elsevier Ltd. All rights reserved.