Open AccessLocal measurement‐based technique for estimating fault location in multi‐source DC microgrids
Author(s) -
Meghwani Anju,
Srivastava Suresh C.,
Chakrabarti Saikat
Publication year - 2018
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.2017.1801
Subject(s) - microgrid , fault (geology) , converters , fault detection and isolation , computer science , fault indicator , power (physics) , electrical impedance , electronic engineering , residual , capacitor , engineering , real time computing , electrical engineering , algorithm , physics , quantum mechanics , voltage , seismology , renewable energy , geology , actuator
Quick fault detection and isolation of faulty section are desired in DC microgrid due to the presence of power electronic converters and low cable impedances. Owing to need of fast disconnection, limited time and data are available for online fault distance estimation. Some of the existing techniques consider source capacitors connected at only one end of the cable; therefore, assume that the fault current is contributed by only one end of the cable. This may not be true in the case of multi‐source DC microgrids, where fault current would be supplied from both the ends. Further, existing communication‐based techniques require either data synchronisation or fast communication network. To address these issues, this study proposes an online fault location method for multi‐source DC microgrid without using communication. The mathematical model of faulted cable section connected to sources at both the ends is derived. This model is used along with the measurements to determine the fault distance. The model consistency with the measurements is quantified using the confidence level based on the residual analysis. A ring‐type multi‐source DC microgrid system is considered and simulated on real‐time digital simulator to demonstrate the effectiveness of the proposed algorithm.