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Medium voltage (MV) switchgear is a vital part of modern power systems, responsible for regulating the flow of electrical power and ensuring the safety of equipment and personnel. However, switchgear can experience various types of faults that can compromise its reliability and safety. Common faults in switchgear include arcing, tracking, corona, normal cases, and mechanical faults. Accurate detection of these faults is essential for maintaining the safety of MV switchgear. In this paper, we propose a novel approach for fault detection using a hybrid model (1D-CNN-LSTM) in both the time domain (TD) and frequency domain (FD). The proposed approach involves gathering a dataset of switchgear operation data and pre-processing it to prepare it for training. The hybrid model is then trained on this dataset, and its performance is evaluated in the testing phase. The results of the testing phase demonstrate the effectiveness of the hybrid model in detecting faults. The model achieved 100% accuracy in both the time and frequency domains for classifying faults in Switchgear, including arcing, tracking, and mechanical faults. Additionally, the model achieved 98.4% accuracy in detecting corona faults in the TD. The hybrid model proposed in this study provides an effective and efficient approach for fault detection in MV switchgear. By learning spatial and temporal features simultaneously, this model can accurately classify faults in both the TD and FD. This approach has significant potential to improve the safety of MV switchgear as well as other industrial applications.

Regarding the use of SF6 in medium voltage switchgear (MVS), a review of alternatives was encouraged by the European Parliament in Regulation No 517/2014. This is aimed at a new regulatory change, that is expected soon, which will include its prohibition, similar to what has happened with other fluorinated greenhouse gases in other fields, like refrigeration. Therefore, there is an urgent need to study the physical and chemical properties of alternative gas mixtures to determine if they are suitable to replace SF6. In this context, this work addresses the difusional analysis of new gases. Binary and ternary mixtures made of 1,3,3,3-tetrafluoropropene (C3F4H2) and heptafluoroisopropyl trifluoromethyl ketone (C5F10O), using dry air as a carrier gas, were studied. The mixtures were analyzed using original equipment, composed of UV-Vis spectroscopy technology in a sealed gas chamber, which is similar to MVS. Consequently, an experimental equipment that monitors the concentration of a gas mixture online and a model that predicts the mixing process were designed and tested. The concentration profiles were obtained concerning both the time and position in the gas chamber, and the diffusional and convectional parameters were numerically calculated and optimized in an algorithm created in Scilab. [ABSTRACT FROM AUTHOR]

Copyright of e & i Elektrotechnik und Informationstechnik is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Regarding the use of SF6 in medium voltage switchgear (MVS), a review of alternatives was encouraged by the European Parliament in Regulation No 517/2014. This is aimed at a new regulatory change, that is expected soon, which will include its prohibition, similar to what has happened with other fluorinated greenhouse gases in other fields, like refrigeration. Therefore, there is an urgent need to study the physical and chemical properties of alternative gas mixtures to determine if they are suitable to replace SF6. In this context, this work addresses the difusional analysis of new gases. Binary and ternary mixtures made of 1,3,3,3-tetrafluoropropene (C3F4H2) and heptafluoroisopropyl trifluoromethyl ketone (C5F10O), using dry air as a carrier gas, were studied. The mixtures were analyzed using original equipment, composed of UV-Vis spectroscopy technology in a sealed gas chamber, which is similar to MVS. Consequently, an experimental equipment that monitors the concentration of a gas mixture online and a model that predicts the mixing process were designed and tested. The concentration profiles were obtained concerning both the time and position in the gas chamber, and the diffusional and convectional parameters were numerically calculated and optimized in an algorithm created in Scilab.

Numerical analysis has been applied to estimate the electric and electromagnetic fields in a medium voltage compact switchgear. The electric field evaluation enables to establish proper dimensions of the switchgear inner devices, e.g. bushing insulators. The electromagnetic field estimation with proposed (by the authors) models of main circuit connections leads to more accurate identification of Joule heating sources. These heat sources can be applied in the further thermo‐ventilation analysis. [ABSTRACT FROM AUTHOR]

Recent studies suggest that fluoronitriles compound Novec 4710 possesses a dielectric strength two times higher than that of SF6, while with a low global warming potential of only 2400. Mixed with CO2 buffer gas, the Novec 4710 mixtures offer excellent dielectric properties and the possibility to be used as an eco-friendly alternative to SF6 for medium voltage switchgears. This paper focuses on the comparative study of the breakdown strength and partial discharge (PD) characteristics between the fluoronitrile/CO2 mixtures and SF6 under AC voltages. Breakdown tests are conducted under different electrode configurations, i.e., planeplane, sphere-plane, rod-plane, and needle-plane, at different pressures and electrode gaps. In the uniform field, equivalent dielectric strength to SF6 at 100 kPa can be reached by a mixture containing 15% fluoronitrile at identical total pressure; while in non-uniform and highly non-uniform fields, SF6 exhibits higher dielectric strength than 20% mixture. The PD analysis suggests that SF6 has much more PDs with lower magnitude and the 20% fluoronitrile/CO2 mixture has less PDs but with higher magnitude. Due to the different PD characteristics, the corona stabilization effect may be responsible for the higher breakdown strength of SF6 under highly non-uniform field. [ABSTRACT FROM AUTHOR]

Copyright of e & i Elektrotechnik und Informationstechnik is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The partial discharge (PD) leads to catastrophic failure of the medium voltage (MV) switchgear insulation. Determination of the PD source (defect) location in high voltage (HV) equipment is very important in the maintenance procedures and in isolating the root cause of PD generation. In this paper, the transient earth voltage (TEV) detection method was used to acquire defect-initiated PD signals in a simulated MV switchgear model. An array of four TEV sensors were placed on the surface walls outside an MV switchgear tank to acquire the PD signals generated from the known location(s)/coordinates of sharp needle type defect inside the tank. The time difference of arrival (TDOA) between signals that are captured by the TEV sensors array was critically analyzed. Estimating the TDOA between PD signals generated by PD source at a known location with high accuracy is of great importance for accurate defect localization. The cumulative energy method (CEM) is used to estimate the onset time point of each TEV signal. The estimated TDOA by the cumulative energy method is compared with actual and expected TDOA based on known coordinates of PD source and TEV sensors. Experimental data are used as a basis for determining the TEV method accuracy for PD source localization. Experimental results show the average error of time difference is about 1.34 ns, which is equivalent to the propagation distance of 0.4 m. [ABSTRACT FROM AUTHOR]