November 22, 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 A Novel Fault Location Methodology for Smart Distribution Networks
Type Article
Keywords
Smart distribution network , distributed generation , load estimation , section estimation
Journal IEEE Transactions on Smart Grid
DOI 10.1109/TSG.2020.3031400
Researchers hamid mirshekali (First researcher) , Rahman Dashti (Second researcher) , Ahmad Keshavarz (Third researcher) , Amin Torabi Jahromi (Fourth researcher) , hamid reza shaker (Fifth researcher)

Abstract

Power distribution networks (PDNs) has played a crucial role in expediting transition towards cleaner and better distributed energy sources. Nowadays, more and more distributed generations (DGs) are used in PDNs which complicates the automatic fault location. This article presents an accurate impedance-based method to determine the fault location for smart PDN in the presence of DGs. In addition, phase domain equations of distributed line parameters are used to enhance the accuracy of fault location. Two types of networks are considered. The first type of network is assumed to be fully observable with μPMU and in the second type there are only a few μPMUs with data loggers on the rest nodes. Load impedances of all nodes are estimated using pre-fault recorded information by present μPMUs and data loggers. The proposed algorithm might suggest several points as possible fault locations for a PDN. To find out the actual location of fault same fault type is simulated for all suggested points. A matching value which is mathematically defined in the article, is calculated using recorded and simulated voltage to determine the actual fault point among all the suggested candidates. The accuracy of suggested method is analyzed against various conditions.