Synchrophasor-Based Real-Time Detection for Power System Events With Fast and Slow Dynamics via Dual Windowed Recurrence Quantification Analysis Algorithm

Accurate event detection is critical for power system operators to take appropriate control strategies so as to ensure the system stability under disturbances. Whereas, most existing event detection techniques are conducted under a single analytical window and criterion, which leads to the misdetection for events of different dynamics. Given this background, a synchrophasor-based real-time event detection method using dual windowed recurrence quantification analysis (DWRQA) algorithm is proposed in this article. First, the recurrence quantification analysis algorithm for synchrophasor data is employed to analyze the nonstationary state of power systems, and a recurrence rate-based power system event indicator is presented to reveal the occurrence of power system events. Then, a real-time event detection scheme based on the dual window structure is proposed to monitor both fast and slow dynamic events of power systems. Finally, case studies on the Western Electricity Coordinating Council (WECC) 179-bus power system and the actual Guangdong power system (GDPS) are performed to demonstrate the effectiveness of the proposed method. Simulation results show that the proposed method can detect both fast and slow dynamic events without misdetections and false alarms, and short time delays for detecting events also make it suitable for real-time applications in actual power systems.