Optimal Reconfiguration of Electrical Distribution System Using Heuristic Methods with Geopositioning Constraints
Edy Quintana and
Esteban Inga
Additional contact information
Edy Quintana: Department of Posgraduate in Electricity, Universidad Politécnica Salesiana, Quito 170525, Ecuador
Esteban Inga: Department of Posgraduate ICT for Education, Smart Grid Research Group, Universidad Politécnica Salesiana, Quito 170525, Ecuador
Energies, 2022, vol. 15, issue 15, 1-20
Abstract:
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%.
Keywords: power grids; graph theory; minimum spanning tree; reconfiguration; resilience (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
https://www.mdpi.com/1996-1073/15/15/5317/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/15/5317/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2022:i:15:p:5317-:d:868896
Access Statistics for this article
Energies is currently edited by Ms. Agatha Cao
More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().