An effective method based on time reversal and optimization techniques for locating faults on power grids

Moussa Kafal (1) , Nicolas Gregis (1) , Jaume Benoit (1) , Nicolas Ravot (1)

1 LFIC - Laboratoire Fiabilité et Intégration de Capteurs

Electromagnetic time reversal (EMTR) has recently emerged as a promising technique applied for locating faults in power networks. It directly transposes the idea of focusing energy back to its source introduced in original time-reversal (TR) methods. Accordingly, we present in this paper, FasTR, a method based on the tenets of TR, that estimates the fault location by employing optimization based algorithms for fetching the highest peak amplitude with maximum coherence in space and time. However, it uses an alternative approach for executing the cumbersome TR post-processing, thanks to a simplified analytical model capable of evaluating the voltage (or current) at any position and any instant of the tested network resulting from the back-injection of the recorded time-revered signals. FasTR is shown to accurately locate a fault in a complex network with just a basic knowledge of its topology in no more than a couple tens of seconds. More importantly is its ability to locate multiple faults in non-homogeneous networks. The performance of the proposed method is validated by numerical simulations as well as an experimental setup by making reference to a reduced-scale coaxial cable network where real faults are hardware-emulated.

Keywords: cable; power network; complex network; non-homogeneous network; coaxial cable network; defect; fault location; multiple faults; diagnosis; reflectrometry; transferometry; Electromagnetic time reversal (EMTR); original time-reversal (TR); optimization algorithm; Electromagnetic time reversal; optimization techniques; power system faults; power system transients; power system protection

Domains: Signal and Image Processing; Electromagnetism

Moussa Kafal, Nicolas Gregis, Jaume Benoit, Nicolas Ravot. An effective method based on time reversal and optimization techniques for locating faults on power grids. IEEE Sensors Journal, 2021, 21 (2), pp.1092-1099. ⟨10.1109/JSEN.2020.3000301⟩. ⟨cea-03122180⟩