Fault location on high voltage transmission line by applying support vector regression with fault signal amplitudes

Fei, Chunguo; Qi, Guoyuan; Li, Chunxin

doi:10.1016/j.epsr.2018.02.005

Cited by 34 publications

(12 citation statements)

References 19 publications

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“…where H n (t) is the magnetic field that leaves conductor n and H s (t) is the magnetic field that is measured by sensor s. Considering (24) and the propagation of the magnetic fields from the phase conductors to the sensor, it is possible to calculate the estimated distance of the fault as in…”

Section: ) Distance From the Sensor To The Transmission Linementioning

confidence: 99%

“…Feature extraction processes may rely upon on the Wavelet Transform, as presented in [20], the Discrete Fourier Transform, as in [21], and/or the energy of the signal [22]. The choice of the most suitable artificial intelligence algorithm may consider Artificial Neural Networks, as described in [22], [23], Support Vector Machines, as in [24], Fuzzy Logic, as in [25], and Petri Nets, as in [26].…”

Section: Introductionmentioning

confidence: 99%

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Fault Location in Overhead Transmission Lines Based on Magnetic Signatures and on the Extended Kalman Filter

Neto¹,

Sartori

Manassero

2021

IEEE Access

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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.

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Section: ) Distance From the Sensor To The Transmission Linementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fault Location in Overhead Transmission Lines Based on Magnetic Signatures and on the Extended Kalman Filter

Neto¹,

Sartori

Manassero

2021

IEEE Access

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show abstract

“…This has resulted in the rapid development of transmission lines in length and numbers since 1945 [1]. Faults frequently occurring on power transmission lines may result in power supply interruption and damage to the customer equipment [2]. Hence, fast detection and accurate estimation of fault location help to rapid fault clearance which ultimately ensures restoration of power supply in minimum time.…”

Section: Introductionmentioning

confidence: 99%

Wigner distribution function and alienation coefficient‐based transmission line protection scheme

Ola

Saraswat

Goyal

et al. 2020

IET Generation, Transmission & Distribution

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“…The solution of quadratic programming problem is easily obtained by proposing a dual set of variables a i and a i *. A Lagrange-like function is formed using the objective function and the corresponding constraints with few mathematical manipulations as given below (Fei et al 2018;Yusuff et al 2014):…”

mentioning

confidence: 99%

A Real-Time Synchronized Harmonic Phasor Measurements-Based Fault Location Method for Transmission Lines

Mallikarjuna

Gopakumar

Roy

et al. 2019

J Control Autom Electr Syst

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In this paper, a real-time synchronized harmonic phasor measurements-based fault location (RT-SHPM-FL) method for transmission lines is proposed. At transmission line protection center (TPC), the synchronized harmonic phasor measurements are obtained from all phasor measurement units (PMU) deployed in a power system. At each bus, the PMU estimates time-tagged 100 and 150 Hz phasors of 3-ɸ current signals in addition to fundamental phasor (50 Hz). The proposed RT-SHPM-FL method detects and locates a fault using the magnitude of 100 and 150 Hz phasors of 3-ɸ currents and equivalent harmonic phasors (EHPs), respectively. These EHPs are calculated from the magnitude of time-tagged 50, 100 and 150 Hz three-phase current phasors. For estimating the fault distance, the RT-SHPM-FL method has employed support vector regression (SVR), because of its mimicking nature, generalization and robustness. The functioning of the proposed fault location method has been validated in real-time on a scaled-down laboratory model of 400 kV extra high voltage (EHV) transmission line of 400 km long. The experimental results and discussions show that the proposed method locates transmission line faults accurately. Further, a comparative study of the proposed fault location method using SVR and adaptive neuro-fuzzy inference system has revealed that the former one is more reliable in fault location than the latter one since the error is within ± 1%.

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Fault location on high voltage transmission line by applying support vector regression with fault signal amplitudes

Cited by 34 publications

References 19 publications

Fault Location in Overhead Transmission Lines Based on Magnetic Signatures and on the Extended Kalman Filter

Fault Location in Overhead Transmission Lines Based on Magnetic Signatures and on the Extended Kalman Filter

Wigner distribution function and alienation coefficient‐based transmission line protection scheme

A Real-Time Synchronized Harmonic Phasor Measurements-Based Fault Location Method for Transmission Lines

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