Power System Security Monitoring: Quantum Computing Aided Anomaly Detection and Early Warning System

Power system security is a critical concern for modern energy grids, where both natural disturbances and human-made events can lead to system failures or significant disruptions. Effective monitoring is essential to maintain stability, reduce risks, and ensure the system’s reliable operation. This study aims to develop an advanced security monitoring framework for power systems using quantum computing to enhance anomaly detection and establish an early warning system. It focuses on identifying and mitigating disturbances through a robust model that improves system security and resilience. The dataset used for this study is sourced from phasor measurement units (PMUs), which are critical for identifying anomalies. The z-score normalization approach was used to preprocess the dataset. Wavelet transforms and statistical techniques are combined to extract key characteristics, which aids in finding patterns and trends that were necessary for spotting abnormalities. The stochastic fractal search-driven quantum-enhanced scalable support vector regression (SFS-QE-SSVR) is designed to improve prediction accuracy by optimizing support vector regression models. The quantum enhancement boosts the algorithm’s performance by accelerating the search process for optimal parameters. The system detects anomalies based on deviations from normal patterns and triggers early warnings, allowing operators to take preventive actions before critical failures occur. The model demonstrates superior accuracy in detecting anomalies and cyber-attacks, outperforming traditional machine-learning methods. In a comparative analysis, the suggested method is assessed with various evaluation measures, such as [Formula: see text]-score (98.15%), recall (97.10%), precision (98.35%) and accuracy (98%). The result demonstrated that the SFS-QE-SSVR method improves the prediction accuracy by optimizing support vector regression models. The proposed quantum-enhanced approach significantly enhances power system security and efficiency, providing a reliable solution for modern energy grids.