Adaptive framework for accurate phasor characterization of transient and dynamic power system signals

Abstract

PMU data is known for high data resolution and accuracy, is gaining increasing significance in power system monitoring and control. This is especially true with the wide application of machine learning and big data analytics. In this paper, a fast implementation framework of phasor parameter calculation algorithm is discussed. The proposed technique utilizes the most recent frequency estimate, and adaptively adjust algorithms applied to characterize both electromagnetic transients and electromechanical dynamics in the power grid. PSS/E simulation results show that the proposed technique is able to adequately characterize transients and dynamics in terms of accurate and fast phasor parameter calculation.