Enhanced symbiotic organisms search algorithm for arc-flash-aware optimal overcurrent relay coordination

This paper presents an enhanced Symbiotic Organisms Search algorithm (SOSCAP) for arc-flash–aware coordination of overcurrent relays (OCRs) and directional overcurrent relays (DOCRs). SOSCAP integrates comprehensive opposition and adaptive parasitism to improve population diversity and local exploitation. It employs adaptive inverse (AI) time-current curves and treats the IEC curve parameters (α, β) as decision variables, thereby forming the AI and Hybrid-AI strategies. The objective function (OF) minimizes total relay tripping time while enforcing selectivity and incident-energy (IE) screening limits of 40 and 120 Cal/cm² guided by IEEE 1584 and NFPA 70E. Results on three networks demonstrate consistent gains. On the IEEE 8-bus system with a normal inverse (NI), SOSCAP achieves 17.03% and 30.28% lower OF relative to the Imperialist Competitive Algorithm and the Harmony Search Algorithm, respectively. With the AI strategy, SOSCAP reduces OF by 60.72% relative to the Flow Direction Algorithm and by 61.01% relative to the Flower Pollination Algorithm. IE values fall sharply, and no case exceeds 120 Cal/cm². On the IEEE 15-bus system with NI, SOSCAP yields 8.69% lower OF than the Harmony Search Algorithm, and with the AI strategy it achieves 54.77% lower OF than the Flower Pollination Algorithm. Under the AI strategy, the 40 Cal/cm² screening limit is not violated. On a real-world 22 kV distribution network, the AI and Hybrid-AI strategies reduce OF relative to NI by 60.53% and 68.07%, respectively, with no IE exceeding 40 Cal/cm². Overall, SOSCAP with AI and Hybrid-AI provides faster fault isolation and lower IE than the baseline algorithms considered. These findings support deployment in distribution networks with high penetration of distributed generation.