The detection and analysis of SF6 decomposition components are of great significance in online condition assessment and fault diagnosis of GIS. Considering the shortcomings of general detection methods, carbon nanotubes (CNTs) gas sensor was studied to detect the SF6 decomposition components because of its advantages in large surface activity and abundant pore structure, et al. The large surface area has a strong adsorption and desorption capacity. In this chapter, SF6 decomposed gases, namely SO2F2, SOF2, SO2, H2S and CF4 are chosen as probe gases because they are the main by-products in the decomposition of SF6 under partial density (PD). First, the properties and preparation methods of CNTs are introduced to verify the advantages of CNTs for SF6 decomposition components detection. Then, both theoretical calculation and sensing experiment were adopted to study the microadsorption mechanism and macrogas-sensing properties. Based on the intrinsic CNTs, study for SF6 decomposition components adsorption, Pd, Ni, Al, Pt and Au metal doping CNTs and plasma-modified CNTs are discussed in order to enhance the gas sensing and selectivity of CNTs.
Titanium dioxide nanotube arrays (TNTAs) are a typical three-dimensional nanomaterial. TNTA has rich chemical and physical properties and low manufacturing costs. Thus, TNTA has broad application prospects. In recent years, research has shown that because of its large specific surface area and nanosize effect, the TNTAs have an enormous potential for development compared with other nanostructure forms in fields such as light catalysis, sensor, and solar batteries. TNTAs have become the hotspot of international nanometer material research. The tiny gas sensor made from TNTA has several advantages, such as fast response, high sensitivity, and small size. Several scholars in this field have achieved significant progress. As a sensitive material, TNTA is used to test O2, NO2, H2, ethanol, and other gases. In this chapter, three SF6 decomposed gases, namely SO2, SOF2 and SO2F2, are chosen as probe gases because they are the main by-products in the decomposition of SF6 under PD. Then, the adsorption behaviors of these gases on different anatase (101) surfaces including intrinsic, Pt-doped and Au-doped, are studied using the first principles density functional theory (DFT) calculations. The simulation results can be used as supplement for gas-sensing experiments of TNTA gas sensors. This work is expected to add insights into the fundamental understanding of interactions between gases and TNTA surfaces for better sensor design.
Gas Insulated Switchgear (GIS) has been widely used in substations. The insulating medium used in GIS is sulfur hexafluoride (SF6) gas. However, the internal insulation defect existed in GIS would inevitably lead to partial discharge (PD), and cause the composition of SF6 to SOF2, SO2F2 and SO2 and other characteristic component gases. The decomposition phenomenon would greatly reduce the insulation performance of SF6 insulated equipment, and even paralyze the whole power supply system. In this chapter, we first discuss the objective existence, decomposition mechanism and harmness of insulation defects. Then the methods for insulation defects detection used to avoid the insulation accidents are introduced. Comparing all of the detection methods, diagnosing the insulation defect through analyzing the decomposed gases of SF6 by chemical gas sensors is the optimal method due to its advantages, such as high detection accuracy and stability, signifying the importance of developing chemical gas sensor used in SF6 insulated equipment. In conclusion, there kinds of gas sensor material, carbon nanotubes, graphene, are chosen as the gas sensing materials to build specific gas sensors for detecting each kind of SF6 decomposed gases, and then enhance the gas sensitivity and selectivity by material modification.
In order to judge the inside insulation fault of SF6 insulated equipment, the gas-sensing properties to a series of characteristic SF6 decomposition components, SOF2, SO2F2, SO2, H2S, CF4, HF, and SF6, have been studied. In this study, a comparative study of these gas-sensing materials has been made in theoretical and experimental fields to find the optimal gas-sensing material, and put forward the effective approaches to improve the gas-sensing properties of materials.
As a significant equipment in power system, the operation condition of transformers directly determines the safety of power system. Therefore, it has been an indispensable measure to detect and analyze the dissolved gases in transformers, aiming to estimate the early potential faults in oil‐insulated transformers. In this chapter, the adsorption processes between modified carbon nanotubes (CNTs) (CNTs‐OH, Ni‐CNTs) and dissolved gases in transformers oil including C2H2, C2H4, C2H6, CH4, CO, and H2 have been simulated based on the first principle theory. Meanwhile, the density of states (DOS), adsorption energy, charge transfer amount, and adsorption distance of adsorption process between CNTs and dissolved gases were calculated. Moreover, two kinds of sensors, mixed acid‐modified CNTs and NiCl2‐modified CNTs, are prepared to conduct the dissolved gases response experiment. Then, the gas response mechanisms were investigated. Finally, the results between response experiment and theoretical calculation were compared, reflecting a good coherence with each other. The CNTs gas sensors possess a relatively high sensitivity and fine linearity, and could be employed in dissolved gas analysis equipment in transformer.
Part of the book: Electrochemical Sensors Technology
Graphene is an allotrope of carbon apart from graphite, diamond, fullerene and carbon nanotubes. Because graphene has unique mechanical, structural, thermal and electrochemical properties and can present the stability characteristics of these features, it becomes two‐dimensional (2‐d) materials which can alter three‐dimensional (3‐d) carbon nanotubes composite materials and has important research value. Pristine graphene and graphene films doped with Au nanoparticles were synthesized by the chemical reduction method. Their corresponding gas sensors were both fabricated by the traditional drop coating method and then used as an adsorbent for the detection of H2S, SO2, SOF2 and SO2F2 at room temperature. Theoretical simulation was also investigated when the decomposed gaseous components of sulfur hexafluoride (SF6), namely, H2S, SO2, SOF2 and SO2F2, were adsorbed on pristine and Au‐embedded graphene based on DFT. In order to interpret the adsorption processes between Au‐doped graphene and gas molecules, this chapter discussed the charge transfer mechanism on the adsorption surface for further investigation.
Partial discharge (PD), a type of low-temperature plasma, indicates a discharge event that does not bridge the electrodes of an electrical insulation system under high voltage stress. It is common in power equipment, such as transformers, cables, gas-insulated switchgears, and so on. The occurrence of PD could deteriorate the insulation performance of the equipment, but, meanwhile, it is often used to diagnose the insulation status. Therefore, it is very necessary to clarify the PD mechanism, and through modeling the PD process, a better understanding of the phenomenon could be attained. Although PD is essentially a gas discharge phenomenon, it possesses some distinctive features, for example, very narrow discharge channel, short time duration, and stochastic behavior, which determine the simulation method of PD different from that for the other types of plasmas. This chapter seeks to propose a simulation method that could reflect the physical processes of PD development after introducing some background knowledge about PD and analyzing the shortcomings of existent models.
Part of the book: Plasma Science and Technology
Gas-insulated switchgear (GIS) is a common electrical equipment, which uses sulfur hexafluoride (SF6) as insulating medium instead of traditional air. It has good reliability and flexibility. However, GIS may have internal defects and partial discharge (PD) is then induced. PD will cause great harm to GIS and power system. Therefore, it is of great importance to study the intrinsic characteristics and detection of PD for online monitoring. In this chapter, typical internal defects of GIS and the PD characteristics are discussed. Several detection methods are also presented in this chapter including electromagnetic method, chemical method, and optical method.