Influence Mechanisms of Trace H2O on the Generating Process of SF6 Spark Discharge Decomposition Components

Tang, Ju; Rao, Xiajin; Zeng, Fuping; Cai, Wei; Lin, Cheng; Zhang, Chaohai

doi:10.1007/s11090-016-9764-8

Cited by 21 publications

(13 citation statements)

References 27 publications

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“…Considering the concentration range of SF 6 decomposition components generated in SF 6 -insulated equipment reported in previous studies [4,25], a series of SF 6 decomposition components concentrations, 1, 10, 50, 100, 200, 300, and 400 ppm, were prepared to analyze the gas-sensing performance of the Ni-CNT gas sensor. As shown in Figure 3, the resistance of the gas sensor significantly reduces when it contacts SF 6 decomposition components [26,27,28,29].…”

Section: Resultsmentioning

confidence: 99%

Ni-CNT Chemical Sensor for SF6 Decomposition Components Detection: A Combined Experimental and Theoretical Study

Tao

Zhang

et al. 2018

Sensors

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SF6 decomposition components detection is a key technology to evaluate and diagnose the insulation status of SF6-insulated equipment online, especially when insulation defects-induced discharge occurs in equipment. In order to detect the type and concentration of SF6 decomposition components, a Ni-modified carbon nanotube (Ni-CNT) gas sensor has been prepared to analyze its gas sensitivity and selectivity to SF6 decomposition components based on an experimental and density functional theory (DFT) theoretical study. Experimental results show that a Ni-CNT gas sensor presents an outstanding gas sensing property according to the significant change of conductivity during the gas molecule adsorption. The conductivity increases in the following order: H2S > SOF2 > SO2 > SO2F2. The limit of detection of the Ni-CNT gas sensor reaches 1 ppm. In addition, the excellent recovery property of the Ni-CNT gas sensor makes it easy to be widely used. A DFT theoretical study was applied to analyze the influence mechanism of Ni modification on SF6 decomposition components detection. In summary, the Ni-CNT gas sensor prepared in this study can be an effective way to evaluate and diagnose the insulation status of SF6-insulated equipment online.

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Section: Resultsmentioning

confidence: 99%

Ni-CNT Chemical Sensor for SF6 Decomposition Components Detection: A Combined Experimental and Theoretical Study

Tao

Zhang

et al. 2018

Sensors

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“…The sequence of electron avalanches that started at the cathode is crucial in spark discharge to create the gas breakdown [39]. Spark discharge is originated from higher field strength than that the dielectric breakdown field strength of GIE, which is caused due to braking actions of disconnectors, fast transient overvoltage caused by ground faults, insulation defects inducing high local electric field strength, and continuous rising of equipment voltage [17]. Following a spark discharge, the organic insulation becomes carbonised by the high temperature spark, resulting in a decline in the overall dielectric strength and may pose a threat to the safety and stability of the power system operation, in addition in extreme cases, the metal electrodes may be eradicated [38][40].…”

Section: B Spark Dischargesmentioning

confidence: 99%

“…In addition, it is also desired to be able to evaluate the degree of PD severity because this critical information can help in overall equipment condition monitoring. Previous research reported that the number of decomposed by-product gases and their concentration could reflect the severity of PD activities in GIS [16] [17]. However, a specific guide for the PD severity evaluation is yet to be established [18].…”

Section: Introductionmentioning

confidence: 99%

SF₆Decomposed Component Analysis for Partial Discharge Diagnosis in GIS: A Review

2022

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This paper compiles, summarizes, and deliberates over one hundred important works on the different approaches and advances in the surveillance and diagnosis of the internal status of SF6 gas-insulated equipment (GIE), particularly partial discharge (PD) diagnosis in gas-insulated switchgear (GIS), and the proposed diagnosis techniques used. This review focused on four research aspects on PD diagnosis related to the developments in PD detection techniques, PD sources identification, and PD severity evaluation. Besides, the effect of various factors such as gas pressure, applied voltage, and impurities on the deterioration of insulation gas and its influence on the diagnosis process has been reviewed. Currently, some reviews on PD diagnosis in SF6-insulated switchgear have been presented and analysed; however, to date, most of them tend to focus on various PD detection techniques in GIS, while others are not extensive and comprehensive reviews. Unlike the available review publications, this paper highlighted various aspects of PD diagnosis in GIS and created a base for further development. The research trend in this field is expected to be directed toward a comprehensive assessment. This review provided a position of the current PD diagnosis in GIS studies and developments that can be a guideline for researchers for further research on the topic's actual impact in the field.

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“…Figure 8 shows the influence curves of H 2 O content on the effective generation rates (R RMS ) of SOF 2 , SO 2 F 2 and SOF 4 under spark discharge. R RMS is defined as formula (3∼4) in reference [52].…”

Section: Progress In Sf6 Decomposition Characteristics and Mechanismmentioning

confidence: 99%

SF ₆ decomposition and insulation condition monitoring of GIE: A review

Zeng

Cheng

et al. 2021

High Voltage

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The statistics of the Conference International des Grands Reseaux Electriques (CIGRE) indicate that the operational reliability of SF 6 gas-insulated equipment (GIE) is very high; however, the failure rate of the GIE in operation is much higher than that of the IEC standard, and the fault occurs frequently in the GIE at a high voltage level. The reason is due to the complex and strong on-site electromagnetic interference environment and fully enclosed structure of GIE. The key method and technology for effective on-line monitoring and fault diagnosis of GIE are still lacking. Given the partial strong electromagnetic energy and high temperature induced by early latent insulation faults in the equipment, SF 6 gas insulation presents different degrees of decomposition. The decomposition products mainly include SO 2 F 2 , SOF 2 , SO 2 , HF, and H 2 S. The decomposition characteristics of SF 6 are closely related to the property of insulation faults. At present, this area is attracting attention from the power industry and research institutes. This study summarises the current research on SF 6 decomposition component analysis (DCA). The content mainly includes the latest progress of SF 6 decomposition characteristics and mechanism under fault conditions, and fault diagnosis methods based on decomposition components.

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Influence Mechanisms of Trace H2O on the Generating Process of SF6 Spark Discharge Decomposition Components

Cited by 21 publications

References 27 publications

Ni-CNT Chemical Sensor for SF6 Decomposition Components Detection: A Combined Experimental and Theoretical Study

Ni-CNT Chemical Sensor for SF6 Decomposition Components Detection: A Combined Experimental and Theoretical Study

SF₆Decomposed Component Analysis for Partial Discharge Diagnosis in GIS: A Review

SF ₆ decomposition and insulation condition monitoring of GIE: A review

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Influence Mechanisms of Trace H2O on the Generating Process of SF6 Spark Discharge Decomposition Components

Cited by 21 publications

References 27 publications

Ni-CNT Chemical Sensor for SF6 Decomposition Components Detection: A Combined Experimental and Theoretical Study

Ni-CNT Chemical Sensor for SF6 Decomposition Components Detection: A Combined Experimental and Theoretical Study

SF6Decomposed Component Analysis for Partial Discharge Diagnosis in GIS: A Review

SF 6 decomposition and insulation condition monitoring of GIE: A review

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Product

Resources

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SF₆Decomposed Component Analysis for Partial Discharge Diagnosis in GIS: A Review

SF ₆ decomposition and insulation condition monitoring of GIE: A review