| Helium is an important rare gas resource which is the guarantee of our national defense security and economic development, because of its unique properties has been widely used in various fields. Currently, the extraction of helium from natural gas is the main source for industry. Helium in China is very poor, how to extract helium from natural gas efficiently and energy saving becomes an important research subject. Cryogenic is the main method of helium gas lift. In actual operation, due to the influence of operating parameters on main equipment such as the device of towers and helium compressor, the production apparatus consume large energy. Aiming at the analysis of the helium unit, the process to optimize the parameters analysis of helium gas device makes it effectively reduce the energy consumption and meet the device in the actual production.Using Aspen-HYSYS process simulation of the helium gas lift device, we analysis the energy consumption of the equipment. Then, through single factor analysis of device parameters, explore the effect of device controllable parameters on the energy consumption and the crude helium concentration and testify the degree of the effects of parameters on the total energy consumption and the crude helium concentration, which concluded four optimization factors and constraints. On the basis of the regression equation between optimizes parameters and energy consumption, secondary crude helium concentration by the response surface optimization method, on the interaction of multiple factors analysis, the results showed:tower Ⅰ feed pressure and tower Ⅰ bottom logistics distribution ratio, tower Ⅰ feed temperature and tower Ⅰ bottom logistics distribution ratio, tower Ⅰ feed temperature and tower Ⅰ feed pressure have a significant interaction and the interaction relationship between the size of for:the interaction between tower Ⅰ feed pressure and tower Ⅰ bottom logistics distribution> the interaction between tower Ⅰ feed temperature and tower Ⅰ bottom logistics distribution> the interaction between tower Ⅰ feed temperature and tower Ⅰ feed pressureIn response surface regression equation based on the analysis of variance, the use of the Design-Expert of response surface method on the original fitting the polynomial model was simplified reasonably, manual optimization response surface equation, the energy consumption optimization of simplified equation. The results showed that the optimized temperature of feed gas into tower Ⅰ is-116.93℃, the optimized pressure of feed gas into tower Ⅰ is2205.56kPa, the optimized bottom logistics distribution ratio of tower Ⅰ is0.09, the optimized reflux ratio of tower Ⅱ is4.74, and the optimized total energy consumption by31.6%. |
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