Abstract
This paper describes a novel mathematical method for decomposing power system signals obtained from measurements and monitoring of power systems. The technique is characterized as a self-based decomposition since the own system signals generate the basis used in the analysis. The resulting decomposition is sensitive to the system operation and is strongly related to the system operating parameters and power consumption, even when signals are non-purely sinusoidal. Mathematical theory is carefully exposed and three potential applications in power systems are presented to prove the efficiency of the signal processing method: high-impedance fault detection in three-phase distribution systems, single-phase VAR and harmonic compensator and three-phase voltage filtering. The investigation demonstrates that the technique is an effective signal-processing tool for power system applications, such as signal filtering and nonlinear process detection.
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