Optimal Reconfiguration of Electrical Distribution System Using Heuristic Methods with Geopositioning Constraints

Edy Quintana, Esteban Inga

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Natural disasters have great destructive power and can potentially wipe out great lengths of power lines. A resilient grid can recover from adverse conditions and restore service quickly. Therefore, the present work proposes a novel methodology to reconfigure power grids through graph theory after an extreme event. The least-cost solution through a minimum spanning tree (MST) with a radial topology that connects all grid users is identified. To this end, the authors have developed an iterative minimum-path heuristic algorithm. The optimal location of transformers and maintenance holes in the grid is obtained with the modified Prim algorithm, and the Greedy algorithm complements the process. The span distance and capacity restrictions define the transformer’s number, where larger spans and capacities reduce the number of components in the grid. The performance of the procedure has been tested in the urban zone Quito Tenis of Ecuador, and the algorithm proved to be scalable. Grid reconfiguration is pushed through a powerful tool to model distribution systems such as CYMDIST, where the voltage drops were minor than 3.5%.

Original languageEnglish
Article number5317
Issue number15
StatePublished - Aug 2022

Bibliographical note

Funding Information:
Universidad Politécnica Salesiana and Smart Grid Research Group (GIREI) founded this work under the project chargeability of the electric distribution grid considering the massive inclusion of electric vehicles.

Publisher Copyright:
© 2022 by the authors.


  • graph theory
  • minimum spanning tree
  • power grids
  • reconfiguration
  • resilience


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