An intelligent fault detection and classification scheme for distribution lines integrated with distributed generators. (July 2018)

• Record Type: Journal Article
• Authors: Chaitanya, B.K.; Yadav, Anamika
• Is Part Of: Computers & electrical engineering. Volume 69(2018)
• Page Start: 28
• Page End: 40
• Publication Date: 2018-07
• Subjects: Fault detection -- Fault classification -- Fuzzy inference system (FIS) -- Teager energy operator (TEO) -- High impedance faults; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2018.05.025
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: Conventional relays fail to detect the high impedance fault (HIF) in distribution lines, as the change in the current magnitude is very negligible compared to conventional relay settings. Moreover, the incorporation of distributed generators in the distribution lines changes the fault current level, which makes the HIF-detection more complex. In this paper, a fuzzy-based intelligent fault detection and classification scheme is developed for the distribution lines integrated with DGs. Two different fuzzy inference systems (FIS) are modelled in each phase to detect the fault. The first FIS identifies the high magnitude of fault current associated with normal shunt faults; and the second FIS identifies the small magnitude of current owing to occurrence of HIF. The proposed scheme uses the features extracted from the Teager energy operator. An extensive study is conducted and the response time is found to be around ¼-1 cycle. Results validate the efficacy of the proposed scheme.