Advanced Relay Coordination in Power Networks Considering Transformer Inrush and Motor Starting Currents via Weighted Mean Variance Optimizer

More endeavors and attempts are still dedicated to solving the optimal relays coordination problem in power systems due to its complexity and evolvement. Consequently, a novel weighted mean variance (WMV) based methodology is interrogated in this research for attaining the optimal settings of overcurrent (OC) relays in mesh and radial networks. The WMV optimizer is utilized in obtaining the best objective function (OF) among various algorithms for solving the nominated problem in benchmark study cases. Three test cases, including one practical power network, are presented and examined. The WMV algorithm proves its dominance in achieving 20.4% reduction in the total tripping time (TTT) value compared to the best competitors for the 15-bus network. Additionally, it accomplishes in selecting the very inverse along with extremely inverse curves among the several tripping standardized characteristics (CCC). Afterwards, the OF is reformulated incorporating various operating constraints in the optimization process and examined over an isolated practical distribution network. The WMV optimizer attains the best OC relays settings by fine-tuning the tripping CCC above the motors and transformers inrush points and below their damage curves. These discrepant constraints represent a major burden to the optimizer to avoid the false tripping in case of energizing along with fully protecting the network’s components. In this context, WMV optimizer manifests its transcendent performance over the well-renowned particle swarm optimizer by attaining TTT of 1.0489 s with 14.2% reduction. Consequently, the proposed methodology eliminates the technical headaches by solving the OC relays coordination problem fulfilling the practical recommended operating scenarios.