2024 : 5 : 19
Mahyar Abasi

Mahyar Abasi

Academic rank: Assistant Professor
ORCID: https://orcid.org/0000-0001-5228-6803
Education: PhD.
ScopusId: AAM-8891-2020
Faculty: Engineering
Address: Arak University
Phone: 08632625099


Fault location determination in three-terminal transmission lines connected to industrial microgrids without requiring fault classification data and independent of line parameters
Fault location Industrial microgrids Renewable energy Three-terminal lines Voltage and current phasors PMU
Journal International Journal of Electrical Power & Energy Systems
Researchers Mahyar Abasi ، Arash Rohani ، Farhad Hatami ، Mahmood Joorabian ، Gevork B. Gharehpetian


The connection of large industrial microgrids to three-terminal transmission lines greatly complicates the protection scheme of the lines due to the uncertainty in generating renewable energy sources, the probability of unintentional islanding, the abrupt switching of sensitive and critical loads, the influence of supply and demand management programs, and bidirectional active and reactive power flow. This paper presents a fault location algorithm for three-terminal transmission lines connected to an industrial microgrid that does not need the detection of faulty section, fault classification, and transmission line parameters. The proposed method uses voltage and current phasors of transmission lines measured by phasor measurement units (PMUs). One of the salient features of the proposed algorithm is that it does not need to determine the faulty section before the fault location operation. Furthermore, since power transmission lines are always exposed to changing climatic conditions and aging, their electrical characteristics vary over time in the long run compared to their rated value. Hence, this leads to the malfunction of protection schemes. This is solved in this study as the proposed fault location algorithm is independent of line impedances. On the other hand, the dependence of conventional fault location algorithms on fault classification data reduces the reliability of fault location schemes, making these algorithms dependent on fault classification data. However, the present study overcomes this problem as the algorithm is independent of the data of the faulty phase(s) detection. The proposed scheme is fully implemented in the MATLAB software environment, and the performance of the algorithm is analyzed for various fault types under different conditions. The validity of the algorithm is shown by various tests and sensitivity analyses.