Detection of Series Arcs Using Load Side Voltage Drop for Protection of Low Voltage DC Systems

Abstract

Low voltage dc distribution grids face issues associated with arc faults, aggravated by the absence of current zero crossing. The focus of this work is to comprehensively develop a method of series arc fault detection at the load side power electronics, based on the electrode dependent initial voltage drop occurring at the arc initiation. The proposed arc detection algorithm is described along with the structure and time constants of the designed bandpass filter. The operational boundaries of the arc detection algorithm are defined for copper electrodes depending on the set threshold voltage and the system parameters, like grid inductance, resistance and the load capacitance. Further, the detection time and the zone of guaranteed positive detection are depicted. These are validated through test simulations on the state space model of the system. Finally, experimental validation of the proposed scheme is carried out, wherein, a series arc is generated in the dc circuit and the programmed micro-controller provides a real time signal upon detecting the arcing event. The results on variation in detection time with set threshold voltage is also presented experimentally.

DC Series Arc Detection Algorithm Based on Adaptive Moving Average Technique

“…A number of algorithms have been proposed to detect the DC series arc using characteristics in various domains. Specifically, methods using time-domain characteristics [3], [6]- [11], frequency-domain characteristics [2], [4], [12], [13], combined time and frequency domain characteristics [5], [14]- [18], artificial intelligence [19]- [23], and techniques using electromagnetic properties during arc generation [24]- [27] have been proposed.…”

A DC Series Arc Fault Detection Method Using Line Current and Supply Voltage

“…However, arc voltage in the line affects both line current and load voltage. In [21], the effects of arc voltage on load voltage under different impedance parameters was analyzed, and DC series arc fault detection method based on the load side voltage decrease at arc initiation is proposed.…”

Binary classification model based on machine learning algorithm for the DC serial arc detection in electric vehicle battery system

“…In view of different types of arc signals, there are many detection methods, which can mainly be divided into time domain analysis, frequency domain analysis and time-frequency analysis [10][11][12][13][14][15][16]. Shekhar et al [10] adopted power electronic device to detect the change of load-side voltage drop, and defined the operating boundary of the detection algorithm of the DC arc according to the system parameters (grid inductor, resistance and load capacitance) and the threshold, then judged the DC arc in the lines. The detection method of DC serial arc based on time domain analysis mainly relies on the jumping signal of voltage and current when the arc occurs, and the proposed algorithm is easy to calculate.…”

“…Due to the limitations of physical methods, more and more signal processing methods have been used to detect DC serial arc in recent years. In view of different types of arc signals, there are many detection methods, which can mainly be divided into time domain analysis, frequency domain analysis and time‐frequency analysis [10–16]. Shekhar et al .…”