Reliable discrimination between power swings and short-circuit faults is essential for secure transmission line protection, since misclassification may lead to unnecessary tripping or delayed fault clearing. Conventional power swing blocking techniques, particularly those based on impedance trajectory analysis, often require system-dependent settings and may exhibit reduced reliability under dynamic operating conditions with increasing renewable generation penetration. This paper proposes a setting-independent method for power swing and fault discrimination based on the Second Central Moment (SCM) of normalized instantaneous voltage and current signals. In this context, setting-independent means that the method does not require line-specific protection settings or case-by-case threshold tuning, although nominal voltage, nominal current, system frequency, and sampling frequency are required for signal normalization and sliding-window implementation. The SCM provides a statistical measure of signal dispersion that enables classification into three operating states: steady-state operation, power swing conditions, and fault events. Common SCM decision boundaries are applied without adjustment across the evaluated transmission lines, operating conditions, fault characteristics, power-swing frequencies, and levels of inverter-based resource penetration. The proposed method is validated through time-domain simulations using the Kundur two-area benchmark system and the IEEE 14-bus network under a wide range of disturbance scenarios, including oscillatory conditions, symmetrical and asymmetrical faults, renewable integration, and swing–fault sequences. For benchmarking purposes, the SCM-based algorithm is compared with a commercial Swing Center Voltage (SCV)-based blocking scheme widely implemented in digital relays. The results show that the proposed method achieves reliable swing–fault discrimination with low computational complexity while providing earlier blocking activation under slow oscillatory conditions and inherent fault discrimination capability. These characteristics support its practical application in real-time transmission line protection.