Experimental Evaluation of Transformer Internal Fault Detection Based on <i>V</i>–<i>I</i> Characteristics

Zhao, Xiaozhen; Yao, Chenguo; Zhou, Zehong; Li, Chengxiang; Wang, Xianmin; Zhu, Tianyu; Abu-Siada, A.

doi:10.1109/tie.2019.2917368

Cited by 28 publications

(7 citation statements)

References 49 publications

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“…The voltage traveling wave created by 10A fault in overhead line with 300 Ω characteristic impedance is equal to 3000V. Thus with the use of appropriate signal processing technique such as the technique presented in [21] within the TW observers, a high frequency generated faults can be distinguished from the noise.…”

Section: Simulation Results and Analysismentioning

confidence: 99%

Optimal Placement of Synchronized Voltage Traveling Wave Sensors in a Radial Distribution Network

et al. 2021

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A transmission line fault generates transient high frequency travelling waves (TWs) that propagate through the entire network. The fault location can be determined by recording the instants at which the incident waves arrive at various points in the network. In single end-based methods, the incident wave arrival time and its subsequent reflections from the fault point are used to identify the fault location. In heavily branched distribution networks, the magnitude of the traveling wave declines rapidly as it passes through multiple junctions that cause reflection and refraction to the signal. Therefore, detecting the first incident wave from a high impedance fault is a significant challenge in the electrical distribution networks, in particular, subsequent reflections from a temporarily fault may not be possible. Therefore, to identify a high impedance or temporary faults in a distribution network with many branches, loads, switching devices and distributed transformers, multiple observers are required to observe the entire network. A fully observable and locatable network requires at least one observer per branch or spur which is not a cost effective solution. This paper proposes a reasonable number of relatively low-cost voltage TW observers with GPS timesynchronization and radio communication to detect and timestamp the TW arrival at several points in the network. In this regard, a method to optimally place a given number of TW detectors to maximize the network observability and locatability is presented. Results show the robustness of the proposed method to detect high impedance and intermittent faults within distribution networks with a minimum number of observers.

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Section: Simulation Results and Analysismentioning

confidence: 99%

Optimal Placement of Synchronized Voltage Traveling Wave Sensors in a Radial Distribution Network

et al. 2021

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“…However, due to the low voltage, the sweep FRA fails to detect those latent defects only excited at high voltage. Recently, a new technique based on the voltage-current characteristic of transformer is developed in [18,19]. By monitoring the transformer input/output voltages and input current, the winding condition is diagnosed according to the change of the Lissajous patterns using the digital image processing method.…”

Section: Diagnostic Methods For Transformermentioning

confidence: 99%

Fault diagnosis technologies for power transformers during the on‐site inductive oscillating switching impulse voltage withstand test

Zhang

Wang

Guo

et al. 2022

IET Generation Trans & Dist

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Although oscillating switching impulse (OSI) voltage is recommended for the transformer field test, the lack of corresponding fault diagnosis technologies limits its application in the field. In this study, the inductive OSI test technology and diagnostic methods are investigated. The front time and the oscillation frequency of the OSI are altered by changing the additional inductance, whereas the tail time is affected by both the front and tail resistance. The OSI voltage withstand test is carried out on a 110 kV three‐phase double‐winding transformer on site. Furthermore, transfer function (TF) analysis is used for the diagnosis of transformer insulation with high sensitivity during the OSI test. The fault winding is distinguished by comparing the change in the voltage TF and current TF at different voltage levels. The partial discharge (PD) detection method has the highest sensitivity, which realizes the early diagnosis of insulation faults. The insulation status of the windings is ascertained based on the number and amplitude of PDs. The test results prove that the inductive OSI voltage withstand test is easy to perform on site and can successfully diagnose the insulation faults of the transformer in more detail compared with other routine insulation tests.

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“…It is worth mentioning that the experimental measurements in this paper were conducted under ideal conditions in which signal noise and harmonic levels were not substantial. To facilitate the proposed system to function under highly polluted waveforms, a digital noise elimination technique such as the methods presented in [55][56][57] can be adopted. Moreover, the performance of the measurement sensors and other components involved in the system must be checked and calibrated regularly to detect any incipient malfunction and rectify it in a timely manner [58,59].…”

Section: Ishdb Tested With Iot Implementationmentioning

confidence: 99%

Cost-Effective Design of IoT-Based Smart Household Distribution System

Ahmed

Qays

Abu-Siada

et al. 2021

Designs

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The Internet of Things (IoT) plays an indispensable role in present-day household electricity management. Nevertheless, practical development of cost-effective intelligent condition monitoring, protection, and control techniques for household distribution systems is still a challenging task. This paper is taking one step forward into a practical implementation of such techniques by developing an IoT Smart Household Distribution Board (ISHDB) to monitor and control various household smart appliances. The main function of the developed ISHDB is collecting and storing voltage, current, and power data and presenting them in a user-friendly way. The performance of the developed system is investigated under various residential electrical loads of different energy consumption profiles. In this regard, an Arduino-based working prototype is employed to gather the collected data into the ThingSpeak cloud through a Wi-Fi medium. Blynk mobile application is also implemented to facilitate real-time monitoring by individual consumers. Microprocessor technology is adopted to automate the process, and reduce hardware size and cost. Experimental results show that the developed system can be used effectively for real-time home energy management. It can also be used to detect any abnormal performance of the electrical appliances in real-time through monitoring their individual current and voltage waveforms. A comparison of the developed system and other existing techniques reveals the superiority of the proposed method in terms of the implementation cost and execution time.

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Experimental Evaluation of Transformer Internal Fault Detection Based on V–I Characteristics

Cited by 28 publications

References 49 publications

Optimal Placement of Synchronized Voltage Traveling Wave Sensors in a Radial Distribution Network

Optimal Placement of Synchronized Voltage Traveling Wave Sensors in a Radial Distribution Network

Fault diagnosis technologies for power transformers during the on‐site inductive oscillating switching impulse voltage withstand test

Cost-Effective Design of IoT-Based Smart Household Distribution System

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