Capture Mechanism and Optimal Design of Micro-Particle Traps in HVAC/HVDC Gas Insulated Equipment
Yanan Chang, Zhipeng Liu, Qingmin Li, Naifan Xue, Jian Wang, Manu Hadad
Abstract
Gas-insulated equipment such as GIS (Gas-Insulated Substation) and GIL (Gas-Insulated transmission lines) faces critical insulation failure challenges caused by particles inside. However, the particle traps, as key devices available to inhibit the movement of particles, lack theoretical basis and quantitative methodology for trap design especially with high voltage ratings. In this paper, a particle motion excitation and observation platform is established to physically simulate the actual online operating conditions of HVAC/HVDC GIS/GIL and study the capture mechanism of particle traps. Experimental results illustrate that, the collision motion style is a principal factor to affect the particle capturing capability, and the capture behavior of AC and DC particle traps can be classified into three separate modes, depending on variation of the collision process which can be characterized by random probability and the lognormal distribution rebound angle. A particle trajectory simulation model incorporating motion randomness is thereby presented to realize quantitative analysis and further optimize the trap parameters. A hazard index and minimum collision times are defined and calculated to quantitatively evaluate the particle collision effect on trapping capability. Further, a novel trap design topology is proposed to enhance the anti-motion efficiency of the particle traps. Targeted at high objective capture probability, the particle trap parameters are optimized to reduce the hazard index and improve the minimum collision times by the Monte Carlo scheme. The obtained results indicated that, the capture probability of AC traps can reach 86.5% at a gap spacing of 5 mm, while that of DC traps can reach 74.1% with an 8 mm-width slot and a 50-degree inclination angle. Verification of the novel article trap is implemented on a test rig, which gives an increased capture probability by 30% compared with the traditional trap design. The proposed new trap topology and corresponding methodology present quantitative guidance for particle traps optimization and render application potential for different voltage levels.