Open AccessVoltage sag assessment using type‐2 fuzzy system considering uncertainties in distribution system
Author(s) -
Mitra Rituparna,
Goswami Arup Kumar,
Tiwari Prashant Kumar
Publication year - 2017
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2016.0816
Subject(s) - voltage sag , fault (geology) , voltage , monte carlo method , fuzzy logic , electric power system , control theory (sociology) , reliability engineering , power (physics) , computer science , power quality , engineering , electrical engineering , mathematics , statistics , biology , artificial intelligence , physics , paleontology , control (management) , quantum mechanics
Power quality (PQ) is the key concern in every corner of the world today. Regarding PQ voltage sag is one of the most relevant issues. The causes of faults in distribution system resulting voltage sag are impact of wind speed on conductors and attachments, faults caused by cattle, animal, mice, rat, birds, bat, snakes and vagaries of weather seems to be definite but found unpredictable in quantum. Considering the intensity and the impacts of these uncertainties as an input interval type‐2 fuzzy system is applied to ascertain fault rates of individual lines in distribution systems. The fault rate of each line is calculated using type reduction Karnik–Mendel algorithm. Selection of the location of fault is done by Monte Carlo simulation to assess voltage sag in each bus of the distribution system. This approach is applied to IEEE 30‐bus system and Barak Valley 37‐bus distribution system for validation.