Differential current‐based fault protection with adaptive threshold for multiple PV‐based DC microgrid

Abstract

A new differential current-based fast fault detection and accurate fault distance calculation is proposed for photovoltaic (PV)-based DC microgrid. A multiterminal direct current (MTDC) distribution network is studied as an adequate solution for present low-voltage utility grid scenario, where local distributed generators (DGs) are incorporated primarily by power electronics based DC-DC converters, DC-AC voltage-source converters (VSCs). PV and diesel generator (as auxiliary source) are considered for cascaded common DC bus, and AC utility bus integration is achieved by VSC unit for the proposed MTDC network. DC microgrid protection is quite significant research focus due to the absence of well-defined standards. Poleto-pole, pole-to-ground, PV-side DC series and ground arc faults are basically considered as DC distribution network hazards. A discrete model differential current solution is considered to detect, classify and locate the faults by modified cumulative sum average approach. A comprehensive case study is presented with different DC loadings, to deliberate effectiveness of the proposed protection scheme in terms of percentage error and trip time (Ts). The result verification is conducted in MATLAB environment as well as TMS320C6713 digital signal processor-based test bench with the proposed multiple DGs based DC microgrid.

Series DC Arc Simulation of Photovoltaic System Based on Habedank Model

“…The impact of PV system on arc was analyzed in frequency domain. In [33], a PV-based DC microgrid model containing arcs was built in MATLAB. In [34], 10 different arc models were used to model series arcs in a PV system.…”

“…In [34], 10 different arc models were used to model series arcs in a PV system. Unfortunately, both [33] and [34] only presented the fault signals within 2 seconds, because the purpose of the systems Arc-fault detection mainly focuses on the changes of PV systems within 2 s after arc ignition according to the suggestion of UL 1699b, while the long-time response of PV systems addresses less attention of researchers. In fact, in order to have a profound understanding of the interactions between arc and PV system, both short-and long-time arc-caused reaction of PV systems should be well studied.…”

“…In [34], 10 different arc models were used to model series arcs in a PV system. Unfortunately, both [33,34] only presented the fault signals within 2 s, because the purpose of the systems was to verify the proposed fault detection or arc location algorithm. Therefore, a more suitable model should be proposed to study how the arc and PV system affect each other over a long time.…”

Kalman filter and a fuzzy logic processor for series arcing fault detection in a home electrical network

“…In order to reconcile simplicity and efficiency, the strategy adopted in this work relies on an adaptive thresholding logic. The main part of the decision making is constituted by a Fuzzy logic processor largely used in recent years in fault diagnosis in photovoltaic and robotic systems [30][31][32][33] .…”

Line-to-Line Fault Analysis and Location in a VSC-Based Low-Voltage DC Distribution Network

“…For instance, the same fault occurs in the DC system, and the peak currents of VSC are I p1 = 0.850 kA, I p2 = 0.720 kA and I p3 = 1.470 kA, respectively. According to Equations (26) and (27), the distances of the fault to VSC1, VSC2 and VSC3 are 1.45 km, 2.01 km and 0.63 km, respectively (Data in detail are given in appendices). According to step p2, the operation instructions of switches connected to Bus1 and Bus2 should be blocked.…”