Optimal Coordination of Directional Overcurrent Relays in Interconnected Networks Using an Improved Multi-Strategy Coati Optimization Algorithm

Syed Muhammad Abdullah Hashmi*, Tahir Mahmood, Muhammad Mansoor Ashraf ()
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Syed Muhammad Abdullah Hashmi*, Tahir Mahmood, Muhammad Mansoor Ashraf: Department of Electrical Engineering, University of Engineering and Technology Taxila, Pakistan

International Journal of Innovations in Science & Technology, 2025, vol. 7, issue 7, 143-157

Abstract: The proper coordination of directional overcurrent relays (DOCRs) in interconnected power systems is essential for selective and time-efficient protection. This study introduces a Tuned Non-inertial T-distribution based Weighted Coati Optimization Algorithm (TNTWCOA) to solve the challenging, highly constrained DOCR coordination problem. The proposed method optimizes time dial settings (TDS) and plug settings (PS) to minimize relay operating times while maintaining selectivity. Coordination is critical for both primary and backup protection devices to prevent fault currents from rising to dangerously high levels too quickly. TNTWCOA uses a chaotic sequence mechanism for better population initialization, a nonlinear inertia weight to balance exploration and exploitation, an adaptive T-distribution strategy to increase diversity and avoid local optima, and an alert update mechanism to improve search adaptability. The algorithm was tested on IEEE 3-bus and 15-bus networks, considering both mid and near-end faults with a normal inverse relay characteristic. A comparative analysis with other advanced metaheuristics shows that TNTWCOA outperforms classical and recent optimization methods by reducing total relay operation time. The results confirm that TNTWCOA helps prevent premature convergence and boosts search efficiency, making it a highly effective solution for DOCR coordination in modern power systems

Keywords: Optimal coordination; Directional overcurrent relays; Power System Protection; Relay Settings; Coati Optimization Algorithm (search for similar items in EconPapers)
Date: 2025
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