<![CDATA[The development of power systems and the strengthening of transmission networks can increase short-circuit current levels, potentially reducing equipment safety margins when fault currents approach or exceed the rated breaking capacity. This study aims to identify the factors influencing short-circuit current variations, analyze the relationships among the relevant variables, predict short-circuit current development for the 2026–2030 period, and evaluate the adequacy of 500 kV substation equipment ratings. The proposed solution is an integrated approach that combines data-driven short-circuit current prediction with technical evaluation of equipment ratings, allowing potential increases in fault current levels to be identified before they exceed the interruption capability of installed equipment. The study employs Partial Least Squares Structural Equation Modeling (PLS-SEM) using historical power system data from 2018–2025. The analytical procedure includes the development of the Generation, Network Configuration, System, and Short Circuit constructs, evaluation of the measurement model using outer loading, Composite Reliability, Average Variance Extracted (AVE), and discriminant validity, followed by structural model evaluation using path coefficients, bootstrapping, t-statistics, and p-values. The validated model is subsequently used to generate latent variable scores and project short-circuit current development through 2030. The results indicate that the System variable has a positive and statistically significant effect on Short Circuit, with a path coefficient of 0.173, t-statistic of 2.156, and p-value of 0.016, whereas the direct effects of Generation and Network Configuration on Short Circuit are not statistically significant. The projection results indicate an increasing trend in short-circuit current at several observation points. Further equipment assessment shows that 19 extra-high-voltage substations have predicted short-circuit current levels exceeding the breaking capacity of their installed equipment, indicating the need for further attention in equipment reinforcement and system reliability planning.]]>
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