GIS insulation co-ordination: on-site tests and dielectric diagnostic techniques. A utility point of view

Sabot, A.; Petit, Alain; Taillebois, J.P.

doi:10.1109/61.517485

Cited by 59 publications

(8 citation statements)

References 4 publications

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“…The insulation material gradually deteriorates, eventually leading to equipment insulation breakdown, indirectly destroying the relevant equipment and endangering the operators on site. Therefore, long-term online monitoring of partial discharges in power equipment plays an essential role in maintaining high-voltage equipment [4,5].…”

Section: Introductionmentioning

confidence: 99%

Exploring the Impact of Parallel Architecture on Improving Adaptable Neuro-Fuzzy Inference Systems for Gas-Insulated Switch Defect Recognition

Chung¹,

Lin

2022

Energies

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Gas-insulated switchgear malfunctions during power system operation may occur due to electrical, thermal, or human errors in the manufacturing process. The leading causes of insulation deterioration of gas-insulated switchgear are discharging along the surface caused by dirt on the insulating material, internal discharge caused by impurities and cavities in the insulating material, corona discharge caused by poor assembly or construction at the site, and electric tree channel discharge caused by the intense internal discharge. Since different defects produce different partial discharge characteristics, the operating power equipment can be analyzed using measurement instruments to detect partial discharge for preventive equipment fault diagnosis, avoiding unnecessary power outages and losses; therefore, evaluating the defects in gas-insulated switchgear is essential. In this study, three gas-insulated switchgears were prefabricated with different defects before encapsulation, and the partial discharge data of each defect were measured by applying different test voltages. The adaptive neuro-fuzzy inference system (ANFIS) input data were used to evaluate the recognition effect, showing that the average recognition rate of the core for all defects was over 90%. The proposed system architecture can continuously accumulate the defect measurement database of gas-insulated switchgear and be used as a reference for constructing electrical equipment defect recognition systems.

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Section: Introductionmentioning

confidence: 99%

Exploring the Impact of Parallel Architecture on Improving Adaptable Neuro-Fuzzy Inference Systems for Gas-Insulated Switch Defect Recognition

Chung¹,

Lin

2022

Energies

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“…Gas-insulated switchgears (GISs) are widely used in modern power system due to the advantages of high reliability, environmental friendliness, and compact structure [1,2]. Nevertheless, some unavoidable insulation defects may occur inside the GIS during manufacturing, assembling and operation.…”

Section: Introductionmentioning

confidence: 99%

Study on the combined characteristics of UHF and optical signals induced by partial discharge at spacer surface in GIS

Han

Guo

Shen

et al. 2020

IET Generation, Transmission & Distribution

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“…Many GISs are getting aged nowadays and the need to mitigate failure has recently become of paramount importance for researchers. Maintenance facilities have shifted from time based monitoring to condition based monitoring, where different diagnostic techniques for the detection of different defects such as PDs are used [11], [12]. Around 85% of the failures of HV and MV equipment are mainly attributed to PDs [15].…”

Section: Introductionmentioning

confidence: 99%

On the Electromagnetic Wave Behavior Due to Partial Discharge in Gas Insulated Switchgears: State-of-Art Review

et al. 2019

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The rapid growth of gas insulated switchgears as a compact, efficient, and reliable device has recently been given great attention. Albeit gas insulated switchgears can seldom suffer from failure due to the high resiliency and robustness, some severe damages have been experienced by such devices particularly in the event of partial discharge. Thus, monitoring such accidents has become a vital part of power systems reliability. The ultra-high frequency techniques have recently shown superior performance in the detection and classification of electromagnetic waves produced by partial discharge. This is mainly due to the great immunity to the noise of the ultra-high frequency detection techniques compared with the veryhigh-frequency counterparts. This review paper highlights the mathematical aspects of the electromagnetic waves generated by partial discharge. It also delivers an overview of the electromagnetic wave behavior in the complex structure of gas insulated switchgears, and outlines the important characteristics of the internal and external partial discharge detection using ultra-high frequency methods. INDEX TERMS Electromagnetic waves behavior, finite difference time domain, gas insulated switchgears, partial discharge, sensors, ultra-high frequency measurements.

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GIS insulation co-ordination: on-site tests and dielectric diagnostic techniques. A utility point of view

Cited by 59 publications

References 4 publications

Exploring the Impact of Parallel Architecture on Improving Adaptable Neuro-Fuzzy Inference Systems for Gas-Insulated Switch Defect Recognition

Exploring the Impact of Parallel Architecture on Improving Adaptable Neuro-Fuzzy Inference Systems for Gas-Insulated Switch Defect Recognition

Study on the combined characteristics of UHF and optical signals induced by partial discharge at spacer surface in GIS

On the Electromagnetic Wave Behavior Due to Partial Discharge in Gas Insulated Switchgears: State-of-Art Review

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