A Novel Approach to Automating Overcurrent Protection Settings Using an Optimized Genetic Algorithm

In electrical networks, the coordination and selectivity of protective devices are key to improving reliability and ensuring operational safety. Protections play a fundamental role in maintaining system stability and detecting faults within the power system. This study presents an optimized genetic algorithm (OGA) as a method to optimize the configurations of overcurrent protections in high voltage distribution systems. The OGA obtained the best results in all tested systems, demonstrating its effectiveness in coordinating protections according to IEC 60255-151:2009. In addition, simulations performed with the integration of Python and PowerFactory DigSILENT software validated the correct coordination of the protections, showing that the OGA not only optimizes response times, but also guarantees greater selectivity and reliability in the protection of the electrical system in an efficient way.

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Publication Details

Journal
Energies
Published
2026-01-20
DOI
https://doi.org/10.3390/en19020529
Primary Topic
Power Systems Fault Detection
Type
article
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article

A Novel Approach to Automating Overcurrent Protection Settings Using an Optimized Genetic Algorithm

Eduardo Gómez-Luna, Mario A. Londoño Villegas, Juan C. Vasquez, Luis A. Gallego Pareja
Energies
Power Systems Fault Detection
article

A Novel Approach to Automating Overcurrent Protection Settings Using an Optimized Genetic Algorithm

Eduardo Gómez-Luna, Mario A. Londoño Villegas, Juan C. Vasquez, Luis A. Gallego Pareja
article en

Abstract

In electrical networks, the coordination and selectivity of protective devices are key to improving reliability and ensuring operational safety. Protections play a fundamental role in maintaining system stability and detecting faults within the power system. This study presents an optimized genetic algorithm (OGA) as a method to optimize the configurations of overcurrent protections in high voltage distribution systems. The OGA obtained the best results in all tested systems, demonstrating its effectiveness in coordinating protections according to IEC 60255-151:2009. In addition, simulations performed with the integration of Python and PowerFactory DigSILENT software validated the correct coordination of the protections, showing that the OGA not only optimizes response times, but also guarantees greater selectivity and reliability in the protection of the electrical system in an efficient way.

EnergiesVol. 19(2)
Universidade Estadual de Londrina (BR), Aalborg University (DK), Universidad del Valle (CO)
Affordable and clean energy
Openalex Percentile: Top 82%
Power Systems Fault Detection
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A Novel Approach to Automating Overcurrent Protection Settings Using an Optimized Genetic Algorithm — Eduardo Gómez-Luna, Mario A. Londoño Villegas, et al. · Energies (2026) | TGRS Research Map | TGRS