Abstract: 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%

Key words: arc fault, energy storage power station, spectrum sensing, covariance matrix

摘要： 本文主要研究锂电池储能电站直流系统中故障电弧的检测。锂电池直流系统被广泛应用，但传统的直流保护装置无法对设备和电路进行足够的保护。本文建立了一个基于锂电池储能电站的实验平台。在多种条件下完成了正常电流和电弧故障电流的数据采集，接着展示了电弧发生时明显和微弱信号的波形。分析了几种基于频谱感知的常见方法的原理和应用范围，并研究将它们应用于弧故障检测领域的可行性。最后，选择基于协方差绝对值的检测算法，并通过滤除电流的平均值使算法能够应用在电弧故障检测领域。结果显示：在500组实验数据中，检测准确率达到了98%。

关键词: 电弧故障，储能电站，频谱感知，协方差矩阵