Gas-insulated Metal-enclosed Transmission Line Research Articles

Gas Insulated Metal Enclosed Transmission Line (GIL) Seismic Response Analysis

The seismic response analysis of a 550 kV gas-insulated metal-enclosed transmission line (GIL) is carried out to address the seismic performance issues in the design of the GIL. Firstly, the GIL is modeled in three dimensions, and the pre-stressed modal analysis is conducted to obtain the vibration characteristics of the GIL structure. Secondly, the seismic response spectrum analysis is conducted according to the national standard, and the seismic characteristics are obtained to meet the requirement of resisting an earthquake of magnitude 9, but there are problems of relatively large stress distribution and small safety coefficient of the brace. Finally, it is proposed to change the cross-section of the bracket to strengthen the stiffness of the bracket to improve the seismic performance of the GIL equipment, and simulations are carried out to verify the results, which show that increasing the cross-section of the bracket can improve the seismic performance of the equipment.

Stories From China

Compared with traditional transmission technology such as cable and overhead line, gas-insulated, metal-enclosed transmission line (GIL) has advantages: high voltage level, large capacity, and small floor area. In addition, affected by structural characteristics of GIL, the operation is not sensitive to the surrounding environment. Therefore, it can be used in power transmission under complex conditions.

Finite Element Analysis and Experimental Study of Metal Shell of GIL

Mathematical modeling, finite element numerical simulation and experimental measurement of the stress-deformation distribution of the gas-insulated metal-enclosed transmission line shell were carried out. Also, Stress linearization analysis was used to analyze the maximum stress. The results show that the stress is linearly dependent on water pressure and the shell occurs elastic deformation without plastic deformation. The simulated maximum stress of 76.2MPa is fairly in good agreement with the measured one (69.9MPa). The stress linearization analysis results show that the shell well satisfies the environmental safety requirements. The experimental results are consistent with the finite element results.

Reliability Prediction for GIL Equipment Based on Multilayer Directed and Weighted Network and Failure Propagation

As an effective alternative to the power cables and overhead lines in the electrical transmission networks, the gas-insulated metal enclosed transmission line (GIL) has been receiving ever-increasing usage worldwide. The GIL reliability, as one of the important characteristics of GIL equipment, is greatly determined by the processing technologies used in manufacturing, transportation, and installation stages, and failures caused by poor processing technologies can cause great damage to GIL equipment, which can further result in great losses to the electrified wire netting. Thus, it is necessary to study and accurately predict the reliability of GIL equipment to discover potential failure modes and take precautions before GIL equipment goes into operation. In this paper, a new reliability prediction model called the multilayer directed and weighted network (M-LDAWN) reliability prediction model is proposed to analyze and predict the GIL equipment reliability by concerning failure propagation and practical processing technologies. In the reliability prediction process, the reliability minimum cut sets triggered by substandard processing technologies are searched by the M-LDAWN model, and the increased failure rate of GIL equipment under each reliability minimum cut set is calculated considering the amplification and concatenation effects of failure propagation. Using the proposed reliability prediction model, the effects of substandard processing technologies on the GIL equipment reliability can be quantified, and the reliability fluctuation caused by them can be calculated. The effectiveness of the proposed framework is demonstrated on a practical GIL reliability prediction example.