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Title: Optimal Coordination of Directional Overcurrent Relays Using Hybrid Firefly–Genetic Algorithm
Authors: Foqha, Tareq
Khammash, Maher
Alsadi, Samer
Omari, Osama
Refaat, Shady
Al-Qawasmi, Khaled
Elrashidi, Ali
Keywords: Directional overcurrent relay coordination;Genetic algorithm;Firefly algorithm;Hybrid optimization algorithms;Power system protection
Issue Date: 12-Jul-2023
Publisher: energies journal
Citation: Foqha, T.; Khammash, M.; Alsadi, S.; Omari, O.; Refaat, S.S.; Al-Qawasmi, K.; Elrashidi, A. Optimal Coordination of Directional Overcurrent Relays Using Hybrid Firefly–Genetic Algorithm. Energies 2023,328. 10.3390/en16145328 16, 5
Series/Report no.: 16, 5328;1-28
Abstract: The application of directional overcurrent relays (DOCRs) plays an important role in protecting power systems and ensuring their safe, reliable, and efficient operation. However, coordinating DOCRs involves solving a highly constrained and nonlinear optimization problem. The primary objective of optimization is to minimize the total operating time of DOCRs by determining the optimal values for decision variables such as the time multiplier setting (TMS) and plug setting (PS). This article presents an efficient hybrid optimization algorithm that combines the modified firefly algorithm and genetic algorithm to achieve improved solutions. First, this study modifies the firefly algorithm to obtain a global solution by updating the firefly’s brightness and to prevent the distance between the individual fireflies from being too far. Additionally, the randomized movements are controlled to produce a high convergence rate. Second, the optimization problem is solved using the genetic algorithm. Finally, the solution obtained from the modified firefly algorithm is used as the initial population for the genetic algorithm. The proposed algorithms have been tested on the IEEE 3-bus, 8-bus, 9-bus and 15-bus networks. The results indicate the effectiveness and superiority of the proposed algorithms in minimizing the total operating time of DOCRs compared with other optimization methods presented in the literature.
metadata.dc.identifier.doi: 10.3390/en16145328 16, 5
Appears in Collections:Engineering and Technology Faculty

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