Optimal Coordination of Directional Overcurrent Relays Using a Modified Grey Wolf Optimization Algorithm Considering Multiple Characteristic Curves

The effective coordination of directional overcurrent relays (DOCRs) is essential for maintaining the stability and dependability of power systems. This work presents a modified grey wolf optimization (MGWO) approach for addressing the DOCR coordination problem. The MGWO algorithm improves the original grey wolf optimization (GWO) by increasing convergence characteristics and balancing the exploration and exploitation stages. This equilibrium is attained by a dimension learning-hunting method and a quadratic reduction in the control parameter during the optimization phase. DOCR coordination is optimized using the MGWO method, using decision factors such as pickup current, time dial setting, and curve type. The goal is to reduce the total working time of primary relays while maintaining selectivity and shortening the discrimination time between primary and backup relays. The suggested MGWO technique is evaluated on the IEEE 8 bus system with two scenarios and compared to other optimization approaches. The results reveal that MGWO outperforms previous algorithms, achieving improvements in the objective function ranging from 5.52% to 58.19%. Additionally, the DOCR settings created by MGWO are evaluated using ETAP software to assure compliance with operational requirements and prevent violations of DOCR coordination.Keywords: Directional Overcurrent Relay Coordination, Grey Wolf Optimization, Multiple Curves, Pickup Current, Time Dial Setting.