Home / Current Issue / Paper 1709133
Improvement of Power System Stability using Optimized Digital Relay Coordination
Subject area: Science,Engineering and Technology · Area of research: Power System Stability
Abstract
The increasing complexity of power systems, particularly in developing nations, necessitates the development of robust and adaptable relay coordination strategies. Traditional relay coordination methods, relying on manual adjustments and time-current settings, are often inadequate for addressing dynamic conditions in modern networks. This leads to prolonged fault clearance times and increased risk of cascading outages. This research uses a genetic algorithm (GA) based approach to optimize digital relay coordination for the 3x15MVA, 33/11kV M2 injection substation in Jabi, Nigeria. The study involves modelling the substation and its key components within MATLAB/Simulink, enabling a simulated environment to test and refine the GA-optimized relay configurations under diverse fault conditions. A multi-objective optimization framework is used to improve fault detection speed, system stability, and relay selectivity. The GA-optimized coordination strategy is anticipated to yield faster fault clearance times and enhanced relay selectivity, establishing a foundation for scalable and adaptable relay protection systems. The results demonstrate a notable improvement in power system stability, with the fitness value decreasing from 0.0615 to 0.0565 over 10 generations. This research advances digital relay coordination practices, offering a valuable tool for bolstering power system resilience in evolving, renewable-integrated grids. The methodology implemented significantly enhances the reliability and efficiency of power grids by minimizing fault clearance times and reducing the risk of cascading failures. The findings of this study can be applied to similar substations in Nigeria and other regions facing reliability challenges. By leveraging GA-based optimization, this research provides a promising solution for improving power system stability and reliability.
Keywords
Coordination, Fault, Genetic Algorithm (GA), Inductor (L), Relay, Stability.
References
[1] S. O. Oyedepo and others, “Towards a sustainable electricity supply in Nigeria: The role of decentralized renewable energy system,” European Journal of Sustainable Development Research, vol. 3, no. 4, p. em0092, 2019.
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[3] O. E. Olabode and others, “Optimal allocation of FACTS devices in deregulated electricity market using JAYA algorithm,” Journal of Electrical Systems and Information Technology, vol. 7, no. 1, pp. 1–18, 2020.
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[6] T. Van Cutsem and C. D. Vournas, Voltage stability of electric power systems, 2nd ed. Springer, 2018.
How to cite this paper
@article{1709133,
author = {Joseph Abom Ikawu, Mohammad Uthman, Ejimofor Chijioke },
title = {Improvement of Power System Stability using Optimized Digital Relay Coordination},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {8},
number = {12},
pages = {811-831},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1709133.pdf},
abstract = {The increasing complexity of power systems, particularly in developing nations, necessitates the development of robust and adaptable relay coordination strategies. Traditional relay coordination methods, relying on manual adjustments and time-current settings, are often inadequate for addressing dynamic conditions in modern networks. This leads to prolonged fault clearance times and increased risk of cascading outages. This research uses a genetic algorithm (GA) based approach to optimize digital relay coordination for the 3x15MVA, 33/11kV M2 injection substation in Jabi, Nigeria. The study involves modelling the substation and its key components within MATLAB/Simulink, enabling a simulated environment to test and refine the GA-optimized relay configurations under diverse fault conditions. A multi-objective optimization framework is used to improve fault detection speed, system stability, and relay selectivity. The GA-optimized coordination strategy is anticipated to yield faster fault clearance times and enhanced relay selectivity, establishing a foundation for scalable and adaptable relay protection systems. The results demonstrate a notable improvement in power system stability, with the fitness value decreasing from 0.0615 to 0.0565 over 10 generations. This research advances digital relay coordination practices, offering a valuable tool for bolstering power system resilience in evolving, renewable-integrated grids. The methodology implemented significantly enhances the reliability and efficiency of power grids by minimizing fault clearance times and reducing the risk of cascading failures. The findings of this study can be applied to similar substations in Nigeria and other regions facing reliability challenges. By leveraging GA-based optimization, this research provides a promising solution for improving power system stability and reliability.},
keywords = {Coordination, Fault, Genetic Algorithm (GA), Inductor (L), Relay, Stability.},
month = {June},
}