Spectrum-Sensing Method for Arc Fault Detection in Direct Current System with Lithium Batteries

We mainly study the detection of arc faults in the direct current (DC) system of lithium battery energy storage power station. Lithium battery DC systems are widely used, but traditional DC protection devices are unable to achieve adequate protection of equipment and circuits. We build an experimental platform based on an energy storage power station with lithium batteries. Then, the data collection of normal current and arc-fault current is completed under multiple conditions, and the waveforms of obvious and weak signals as the arc occurs are presented. We analyze the principles and application range of several common spectrum-sensing methods and study the feasibility of applying them to the arc detection field. Finally, the covariance absolute value detection algorithm is selected, and the average value of the current is filtered out to make the algorithm adapt to the arc detection field. The result shows that the detection probability in 500 sets of experimental data has reached 98%.