May 6, 2024
Rahman Dashti

Rahman Dashti

Academic Rank: Associate professor
Address:
Degree: Ph.D in electrical engineering
Phone: +98-7731222752
Faculty: Faculty of Intelligent Systems and Data Science

Research

Title Fault location in power grids using substation voltage magnitude differences: A comprehensive technique for transmission lines, distribution networks, and AC/DC microgrids
Type Article
Keywords
Fault Location Transmission Line Distribution Network Hybrid Microgrid Voltage Magnitude Difference D-STATCOM
Journal MEASUREMENT
DOI https://doi.org/10.1016/j.measurement.2023.113403
Researchers mohammad daisy (First researcher) , Rahman Dashti (Second researcher) , hamid reza shaker (Third researcher) , shahram javadi (Fourth researcher) , mahmood hoseini aliabadi (Fifth researcher)

Abstract

Power grids are highly susceptible to various types of faults and their associated consequences. In recent years, numerous fault location methods have been proposed for different types of power networks. Generally, these methods determine the location of a fault by measuring current and voltage data on one or both sides of the line. However, the use of current data can result in calculation errors due to the saturation state of the current transformer and the bidirectional fault current. Moreover, the use of measuring devices in different nodes can lead to increased costs and the need for advanced telecommunication systems and data synchronization. In this paper, we propose a comprehensive technique for fault location in power networks that incorporates the presence of D-STATCOM and considers the effect of line capacitors. Our method estimates the distance and faulty branch by measuring the difference in fault voltage magnitude at the substation and comparing it with simulated faults in other branches. Unlike other methods that rely on current data, our proposed technique is independent of current data, resulting in higher accuracy and faster fault detection. Furthermore, our method offers significant cost savings compared to other fault location methods. To evaluate the performance of our technique, we conducted simulations on a 32-node power network in MATLAB/SIMULINK and an 8-node network in a power system simulator. We tested the sensitivity of our method to various fault locations, resistances, and DG penetration levels. The results of our simulations demonstrate the high accuracy and speed of our proposed technique, making it a promising alternative to other fault location methods in the field.