Open AccessNovel way for classification and type detection of voltage sag
Author(s) -
Thakur Padmanabh,
Singh Asheesh K.,
Bansal Ramesh C.
Publication year - 2013
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.2012.0435
Subject(s) - voltage sag , computer science , type (biology) , voltage , pattern recognition (psychology) , artificial intelligence , engineering , electrical engineering , power quality , biology , ecology
This study presents a new classification of voltage sags which is based on its types, characteristic voltage and zero‐sequence component of voltage. It is extremely difficult to distinguish between the voltage sags which have same type, same characteristic voltage and same zero‐sequence component of voltage due to load effects and hence such classification is significant. The proposed classification is mathematically justified by introducing two new indices, namely, phase‐to‐neutral and phase‐to‐phase voltage indices. Using the theoretical relation between these two indices, it has been revealed that the voltage sags which have the same type, same characteristic voltage and same zero‐sequence component of voltages, have same mathematical relations. Further, to reveal the accuracy of the proposed classification and type detection, it is validated through recorded waveforms available in IEEE database, Scottish Power, data obtained from Matlab simulation under different conditions of voltage sags and data of real power station. In addition, the proposed classification and type detection are compared with other established algorithms for type detection of voltage sags. The comparative results show that the proposed classification not only removes the existing anomalies in the earlier proposals but also shows its superiority by presenting more accurate and less confusing results.