Enhanced Entropy-Based Metric for Characterization of Delayed Voltage Recovery
For power system operators, this provides a more reliable tool for detecting voltage recovery violations, reducing false negatives in critical infrastructure monitoring.
The paper introduces an enhanced voltage recovery violation index (EVRVI) that uses Empirical Mode Decomposition to improve detection of fault-induced delayed voltage recovery. Simulations on the Nordic system with over 245k scenarios show EVRVI significantly reduces false negatives compared to traditional entropy-based methods.
Ensuring accurate violation detection in power systems is paramount for operational reliability. This paper introduces an enhanced voltage recovery violation index (EVRVI), a comprehensive index designed to quantify fault-induced delayed voltage recovery (FIDVR). EVRVI enhances traditional entropy-based methods by leveraging Empirical Mode Decomposition (EMD) to extract key features from the voltage signal, which are then used to quantify over-voltage (OV) and under-voltage (UV) events. Our simulations on the Nordic system, involving over 245k scenarios, demonstrate EVRVI's superior ability to identify and categorize voltage recovery issues compared to the traditional entropy-based measure. EVRVI not only significantly reduces false negatives in violation detection but also provides a reliable framework for over-voltage detection, making it an invaluable tool for modern power system studies.