电力电子设备存在下低压配电系统中电弧/火花放电现象的表征

The increasing complexity of modern electrical loads challenges traditional arc fault detection methods, which require sophisticated approaches for reliable identification. This study investigates the arc/spark discharge behavior in low-voltage distribution systems, particularly under the influence of modern domestic appliances embedded with power electronic components. A nonlinear equivalent circuit model of arc/spark discharge was developed, empirically derived from experimental observations and guided by physical principles such as voltage-current hysteresis and energy balance considerations. The model incorporates dynamic parameters, including the arc time constant and carbon bridge resistance, to analyze their influence on the discharge characteristics. Extensive laboratory experiments involving representative appliances, such as rheostats, mixers, laptops, microwave ovens, and vacuum cleaners, were performed to analyze the arc discharge behavior under realistic load conditions. To characterize and differentiate arcs from non-arc conditions, temporal features were extracted using L-moment statistics, which offer improved resilience to outliers and capture higher-order distributional behavior. The resulting features demonstrate strong discriminatory capability across load types, enabling robust arc fault detection. This integrated modeling and feature-extraction framework contributes to the development of safer and more reliable arc detection systems suited to modern low-voltage electrical environments.