Effects of SF6 decomposition components and concentrations on the discharge faults and insulation defects in GIS equipment

Abstract

Gas-insulated switchgear (GIS) is widely used across multiple electric stages and different power grid levels. However, the threat from several inevitable faults in the GIS system surrounds us for the safety of electricity use. In order to improve the evaluation ability of GIS system safety, we propose an efficient strategy by using machine learning to conduct SF6 decomposed components analysis (DCA) for further diagnosing discharge fault types in GIS. Note that the empirical probability function of different faults fitted by the Arrhenius chemical reaction model has been investigated into the robust feature engineering for machine learning based GIS diagnosing model. Six machine learning algorithms were used to establish models for the severity of discharge fault and main insulation defects, where identification algorithms were trained by learning the collection dataset composing the concentration of the different gas types (SO2, SOF2, SO2F2, CF4, and CO2, etc.) in the system and their ratios. Notably, multiple discharge fault types coexisting in GIS can be effectively identified based on a probability model. This work would provide a great insight into the development of evaluation and optimization on solving discharge fault in GIS.

Digital colorimetric sensing for real‐time gas monitoring for smart green energy system

“…Previously, we explained the mechanism of SO 2 gas generation in detail using the concepts of PD and arc 23–25 . To confirm the findings, we created an artificial GIS chamber replicating a real GIS system.…”

“…Previously, we explained the mechanism of SO 2 gas generation in detail using the concepts of PD and arc. [23][24][25] To confirm the findings, we created an artificial GIS chamber replicating a real GIS system. Figure 5B shows the GIS-mimicking chamber and the PD activated and deactivated states inside the chamber.…”

“…23,24 In general, gases generated by PD in the presence of moisture and oxygen in the GIS include CO 2 , CF 4 , SOF 2 , SO 2 F 2 , SOF 4 , S 2 F 10 O, SO 2 , and HF. 25 It is crucial to identify the closely correlated factors that are related to the deterioration of the insulation of GIS. Several studies have indicated that SOF 2 or SO 2 is the most suitable gas for GIS diagnosis because of its relative stability inside the GIS.…”

“…However, chemical diagnosis and analysis by decomposition products of SF 6 gas are more common 23,24 . In general, gases generated by PD in the presence of moisture and oxygen in the GIS include CO 2 , CF 4 , SOF 2 , SO 2 F 2 , SOF 4 , S 2 F 10 O, SO 2 , and HF 25 . It is crucial to identify the closely correlated factors that are related to the deterioration of the insulation of GIS.…”

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

“…The results of existing research show that, under the partial strong electromagnetic energy instantly released by the spark discharge, SF 6 molecules will be divided into low-fluorine sulphides SF x (x = 1, 2, …, 5) [45,46]. SF x easily reacts with trace H 2 O and other impurities in the gas chamber, thereby resulting in a series of complex and irreversible chemical reactions, which generate decomposition characteristic products, such as SOF 2 , SOF 4 , SO 2 F 2 , SO 2 , S 2 F 10 , S 2 OF 10 , HF, and CO 2 .…”