Abstract
This paper proposes a non-contact method for fault location in transmission lines, which is based on magnetic fields produced by current signals measured using magnetoresistive sensors installed only at transmission line terminals, under the phase conductors of the first transmission tower at both terminals or at the substations portals. The proposed method uses the Extended Kalman filter to process these measurements and is based on a travelling wave approach in order to perform the fault localization. This paper also describes the implementation and testing of the method, firstly introducing its overview, followed by an analysis of the magnetic fields produced by the current signals, as well as considerations on their measurement; secondly, detailing the Extended Kalman filter and the travelling wave approach; and, finally, presenting the results of the method with regards to simulations built using EMTP/ATP to evaluate its robustness under different conditions varying the fault resistance, fault inception angle, phases involved and fault location. The results indicate that the proposed method is robust and accurate.
Highlights
A robust and reliable electric power transmission system can guarantee the availability of energy to meet population growth and industrial development, through the interconnection of several electric power generation stations to large urban consumer centers and to less populated rural regions, constituting large interconnected systems.These systems are subject to abnormal conditions that may occur in different equipment
Algorithms and fault location methods have been proposed in the literature and can be divided into the following main groups, The associate editor coordinating the review of this manuscript and approving it for publication was Bernardo Tellini
MANUSCRIPT STRUCTURE The rest of the paper is divided as follows: section II presents the fault location method proposed by the authors, with respect to its theory and application to the fault location problem; section III presents details regarding its implementation and configuration when used to locate faults in a simulated system; section IV presents a statistical analysis of the method, as well as considerations of its performance when tested against circa ten thousand simulations varying fault resistance, inception angle, distance, phases involved and fault type; and section V presents the authors conclusions
Summary
A robust and reliable electric power transmission system can guarantee the availability of energy to meet population growth and industrial development, through the interconnection of several electric power generation stations to large urban consumer centers and to less populated rural regions, constituting large interconnected systems. Oftentimes, knowledge-based methods harness features from other fault location methods and from parameters of the transmission lines, as well as high frequency components of the voltage and current signals, to provide inputs to machine-learning approaches that can calculate the fault location These methods present basic fault location schemes which are based on feature extraction processes and artificial intelligence algorithms. Due to the use of the Extended Kalman filter (EKF), that estimates the magnetic field behaviour in the vicinity of the transmission line terminals, the proposed method is self-adaptive and is capable of detecting the fault occurrence when the difference between the measured magnetic fields and their estimation surpass a predefined, and self-adaptive, threshold Besides it copes well with noisy input signals. MANUSCRIPT STRUCTURE The rest of the paper is divided as follows: section II presents the fault location method proposed by the authors, with respect to its theory and application to the fault location problem; section III presents details regarding its implementation and configuration when used to locate faults in a simulated system; section IV presents a statistical analysis of the method, as well as considerations of its performance when tested against circa ten thousand simulations varying fault resistance, inception angle, distance, phases involved and fault type; and section V presents the authors conclusions
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