Abstract
Far distant wind farms are integrated nowadays with the help of Voltage Source Converter (VSC)-based HVDC grids. Rapid fault current is very common in VSC-based HVDC grids and, therefore, quick fault detection and fast executing protection methods are critical for the existence of the HVDC grids. This paper proposes a rise time-based fault detection method using local measurement data and Travelling Wave (TW) characteristics of incoming fault TW. Dominating frequency of the primary wavefront is computed by the rise time of incoming fault TW. With the help of auto-updating transmission line parameters and the dominating frequency of incoming TW, the fault location is identified. The performance of the proposed method has been observed in PSCAD Simulation with a 4-Terminal HVDC test grid in multiple scenarios and compared with the existing fault detection methods on multiple levels. The results show that the proposed method is very fast, and accurate and can complete the whole Fault Location process within a few microseconds just after the Inception of the fault.
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No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
Govind Kant Mishra
Govind Kant Mishra received the BTech degree in instrumentation and control engineering from UPTU in 2012 and MTech degree in power systems from NIT Patna, India in 2014. Currently, he is a research scholar at HBTU Kanpur. His research interests include the design and modelling of power system, distributed generation systems, protection of HVDC systems, power electronics and the design of instrumentation systems.
Yaduvir Singh
Yaduvir Singh obtained an ME in control and instrumentation from MNNIT, Allahabad, India in 1993 and a PhD degree in industrial electronics from Thapar Institute of Engineering and Technology, Patiala, India in 2004. Presently, he is professor in the Department of Electrical Engineering at the School of Engineering, HBTU, Kanpur, India. His research interest includes intelligent systems design, soft computing, automated control systems, artificially intelligent systems, power system modelling and identification, industrial electronics and design of instrumentation systems. Email: [email protected]