Measurement and Analysis of Partial Discharge using an Ultra-High Frequency Sensor for Gas Insulated Structures

Wang, Guoming; Kil, Gyung-Suk

doi:10.1515/mms-2017-0045

Cited by 24 publications

(18 citation statements)

References 2 publications

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“…By contrast, in the back propagation, errors calculated by comparing actual output and desired output propagate from output layer to input layer with update of weights and biases. The back propagation algorithm continuously operated until the allowable error was less than 0.0001 and then the trained weights were updated in the system for real-time lightning warning [17][18][19]. This intelligent algorithm was developed based on the LabVIEW program with the standard state machine design pattern.…”

Section: Artificial Neural Network (Ann)mentioning

confidence: 99%

An Intelligent Lightning Warning System Based on Electromagnetic Field and Neural Network

et al. 2019

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Prediction of lightning occurrence has significant relevance for reducing potential damage to electric installations, buildings, and humans. However, the existing lightning warning system (LWS) operates using the threshold method and has low prediction accuracy. In this paper, an intelligent LWS based on an electromagnetic field and the artificial neural network was developed for improving lightning prediction accuracy. An electric field mill sensor and a pair of loop antennas were designed to detect the real-time electric field and the magnetic field induced by lightning, respectively. The change rate of electric field, temperature, and humidity acquired 2 min before lightning strikes, were used for developing the neural network using the back propagation algorithm. After observing and predicting lightning strikes over six months, it was verified that the proposed LWS had a prediction accuracy of 93.9%.

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Section: Artificial Neural Network (Ann)mentioning

confidence: 99%

An Intelligent Lightning Warning System Based on Electromagnetic Field and Neural Network

et al. 2019

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“…This is because SF 6 has an exceptional combination of physical and chemical properties for high-voltage applications, including high-dielectric strength (three times that of air at atmospheric pressure), arc-quenching capability, thermal conductivity, thermal stability, nonflammability, nontoxicity, nonexplosive, and chemical inertness [1][2][3][4]. As a result, SF 6 -insulated equipment can be designed with reduced size, high reliability, and economic efficiency [5,6]. It is widely employed in space-limited locations such as city substations, offshore plants, or wind-power plants [7].…”

Section: Introductionmentioning

confidence: 99%

“…The global warming potential (GWP) of SF 6 is 23,500 times that of carbon dioxide (CO 2 ) over a 100-year time horizon and is 32,600 times that of CO 2 over a 500-year time horizon. The atmospheric lifetime of SF 6 is 3200 years, whereas that of CO 2 is only 30-90 years [1]. It was reported that 1 kg of SF 6 released into the atmosphere has the equivalent global warming impact as 23.5 tons of CO 2 [13].…”

Section: Introductionmentioning

confidence: 99%

“…Negative impacts have led the power industry to seek an eco-friendly alternative insulation gas to partially or completely replace SF 6 . Studies have been carried out to investigate the potential of natural gases such as CO 2 [19] and nitrogen (N 2 ) [20], and dry air, vacuum, SF 6 gas mixture [20][21][22], and fluorinated gases with reduced GWP such as trifluoroiodomethane (CF 3 I) [4,13,14,23,24], perfluorocarbons (PFCs) [1,25], as well as hydrofluoroolefins (HFOs) [7,26].…”

Section: Introductionmentioning

confidence: 99%

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Green Gas for Grid as an Eco-Friendly Alternative Insulation Gas to SF6: A Review

Pan

Wang²,

Shi

et al. 2020

Applied Sciences

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This paper deals with a review of the state-of-the-art performance investigations of green gas for grid (g3) gas, which is an emerging eco-friendly alternative insulation gas for sulfur hexafluoride (SF6) that will be used in gas-insulated power facilities for reducing environmental concerns. The required physical and chemical properties of insulation gas for high-voltage applications are discussed, including dielectric strength, arc-quenching capability, heat dissipation, boiling point, vapor pressure, compatibility, and environmental and safety requirements. Current studies and results on AC, DC, and lightning impulse breakdown voltage, as well as the partial discharge of g3 gas, are provided, which indicate an equivalent dielectric strength of g3 gas with SF6 after a proper design change or an increase in gas pressure. The switching bus-transfer current test, temperature rise test, and liquefaction temperature calculation also verify the possibility of replacing SF6 with g3 gas. In addition, the use of g3 gas significantly reduces theabovementioned environmental concerns in terms of global warming potential and atmosphere lifetime. In recent years, g3 gas-insulated power facilities, including switchgear, transmission line, circuit breaker, and transformer, have been commercially available in the electric power industry.

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“…At present, in the field of GIS state detection, experts from various countries are devoted to the study of characterization, detection methods, and prevention techniques of partial discharges in GIS. A real-time measurement system for partial discharge defect strength based on phase decomposition was developed by using an ultra-high frequency sensor [9]. A partial discharge sensor diagnosis method based on a silicon photomultiplier (SiPM) was proposed [10]; it promotes the partial discharge process of optical detection from laboratory simulations to practical applications.…”

Section: Introductionmentioning

confidence: 99%

Vibration Feature Analysis for Gas-Insulated Switchgear Mechanical Fault Detection under Varying Current

Feng

2020

Applied Sciences

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As a key component to ensure the safe operation of the power grid, mechanical defect diagnosis technology of gas-insulated switchgear (GIS) during operation is often neglected. At present, GIS mechanical fault detection based on vibration information has not been developed. The main reason is that the excitation current is considerable but uncontrollable in the actual operation of GIS. It is difficult to eliminate the influence of excitation on the vibration amplitude and form an effective vibration feature description technology. Therefore, this paper proposes a unified feature-extraction method for GIS vibration information that reduces the influence of current amplitude for mechanical fault diagnosis. Starting from the GIS mechanical analysis, the periodicity of vibration excitation and the influence of amplitude are discussed. Then, combined with the non-linear characteristics of GIS systems and non-linear vibration theory, the multiplier frequency energy ratio (MFER) is designed to extract vibration-unified features of GIS for diagnosing the mechanical fault under different current levels. The diagnosis results of the experimental data with different feature-extraction methods show the applicability and superiority of the proposed method in the GIS’s mechanical fault-detection field based on vibration information.

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Measurement and Analysis of Partial Discharge using an Ultra-High Frequency Sensor for Gas Insulated Structures

Cited by 24 publications

References 2 publications

An Intelligent Lightning Warning System Based on Electromagnetic Field and Neural Network

An Intelligent Lightning Warning System Based on Electromagnetic Field and Neural Network

Green Gas for Grid as an Eco-Friendly Alternative Insulation Gas to SF6: A Review

Vibration Feature Analysis for Gas-Insulated Switchgear Mechanical Fault Detection under Varying Current

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