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 Transient and steady-state faults location in intelligent distribution networks compensated with D-STATCOM using time-domain equations and distributed line model
Type Article
Keywords
Distribution network · Smart compensated energy distribution networks · Fault location · Distributed line model · Time-domain equation · D-STATCOM
Journal ELECTRICAL ENGINEERING
DOI https://doi.org/10.1007/s00202-021-01270-0
Researchers abdolrasool fathy (First researcher) , Rahman Dashti (Second researcher) , Mojtaba Najafi (Third researcher) , hamid reza shaker (Fourth researcher)

Abstract

Intelligent electric distribution networks compensated with D-STATCOM are active networks in which data of terminals is important for better distribution of energy. Similar to all electricity network devices, energy distribution lines in such networks are also subject to transient and steady-state AC faults, e.g., short circuit. Sections of the network in which the fault occurs are separated by relays. In such a condition, fault location and restoring the normal status of the network are important. Fault location in these networks is performed based on synchronous data of two terminals because data of all buses are transmitted to the main bus In this paper, a time-domain equation method (TDEM) is proposed for locating faults on smart distribution grid (SDG) using distributed line model based on time-domain equations. The proposed method locates the point of transient and steady-state fault in SDG considering DGs and compensators. In this paper, the D-STATCOM and wind power plant are considered in SDG. The suggested method does not need the D-STATCOM and DGs model for applying the algorithm. It only uses data of less than half of the cycle for executing the algorithm. The numerical simulation confirms that the proposed fault location method is accurate and it provides a reliable solution for automatic fault location problem in distribution networks.