A High-Speed Fault Detection, Identification, and Isolation Method for a Last Mile Radial LVDC Distribution Network

Abstract

The day-by-day increase in digital loads draws attention towards the need for an efficient and compatible distribution network. An LVDC distribution network has the capability to fulfill such digital load demands. However, the major challenge of an LVDC distribution network is its vulnerability during a fault. The need for a high-speed fault detection method is inevitable before it can be widely adopted. This paper proposes a new fault detection method which extracts the features of the current during a fault. The proposed fault detection method uses the merits of overcurrent, the first and second derivative of current, and signal processing techniques. Three different features are extracted from a time domain current signal through a sliding window. The extracted features are based upon the root squared zero, second, and fourth order moments. The features are then set with individual thresholds to discriminate low-, high-, and very high-resistance faults. Furthermore, a fault is located through the superimposed power flow. Moreover, this study proposes a new method based on the vector sum of positive and negative pole currents to identify the faulty pole. The proposed scheme is verified by using a modified IEEE 13 node distribution network, which is implemented in Matlab/Simulink. The simulation results confirm the effectiveness of the proposed fault detection and identification method. The simulation results also confirm that a fault having a resistance of 1 m Ω is detected and interrupted within 250 μ s for the test system used in this study.

Development of New Protection Scheme in DC Microgrid Using Wavelet Transform

“…I wave_rms2 (t) in Cases 3-6 are not presented because this value is not used to judge the fault section in Cases 3-6. In these Cases, a comparison of I wave_rms1 (t) calculated by (14) in Cases 1, 2, 4, and 6 is shown in Figure 11. Cases 3 and 5 are not presented because Case 4 is a representative case of DC line faults.…”

“…Using (14), it is primarily determined whether there is a line fault (fault 3 ), bus fault (fault 4 ), AC/DC converter side fault (fault 1 ) or PV side fault (fault 2 ). In the algorithm shown in Figure 9, α is a threshold value used to distinguish between the fault types.…”

“…In [13], a mathematical morphology-based protection method was proposed using the features from fault currents with capacitor discharge characteristics or highimpedance faults with arcing phenomenon. In [14], a fault detection method was proposed using the advantages of overcurrent, primary and secondary differentiation of current, and signal processing techniques. In [15], a protection method in a ring-bus LVDC microgrid with intelligent electronic equipment and a solid-state circuit breaker was proposed.…”

Fault detection and location estimation forLVDCmicrogrid using self‐parametric measurements

“…A technique of fault detection in a section for LVDC systems has been developed by using capacitive discharge current. 24 Fault detection methods in LVDC have been proposed [25][26][27][28][29] using signal processing method and rolling mean technique respectively. A fault detection for multi-terminal DC systems is presented.…”

“…26,27 A graph theory-based fault detection and fault line identification method has been developed that uses the BIBC and network theory. 28 A modular protection system has been proposed for fault detection and selective fault clearing 30 that uses a communication-based scheme, but these methods [22][23][24][25][26][27][28][29][30] remain silent about fault location.…”