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 Determining an Accurate Fault Location in Electrical Energy Distribution Networks in the Presence of DGs using Transient Analysis
Type Article
Keywords
Journal MEASUREMENT
DOI
Researchers Rahman Dashti (Second researcher) , Mojtaba Najafi (Third researcher) , hamid reza shaker (Fifth researcher)

Abstract

Distributed generation resources are becoming more popular in electric energy distribution networks. As more Distributed generation are integrated into the grid, the system performance is challenged by issues such as manifold power injection to the network or nonlinear behavior when a fault occurs. To address this, fault location in electric energy distribution networks in the presence of distributed generation needs particular attention. This is important to reduce the loss of generated energy, reduce interruptions time, increase the reliability of the network and consequently improve the security of electricity supply. In this paper, a novel fault location method is presented applied to distributed networks with distributed generation. The proposed method is a hybrid two-step method which identifies accurate fault location using information stored in the network at pre- and post-fault time. The proposed method employs voltage and current information at the beginning of the feeder to estimate fault distance in the first step. The estimated distance will be associated with several similar sections considering the topology of the distributed networks. In the second step, the proposed method determines accurate fault location through transient analysis based on the frequency component. In this step, the exact fault location is identified. In order to investigate its performance, a standard IEEE-11 network is simulated in MATLAB. Furthermore, experiments are carried out in a network power simulator, showing good results.