Deactivation Mechanism of Multipoisons in Cement Furnace Flue Gas on Selective Catalytic Reduction Catalysts

2019 ◽  
Vol 53 (12) ◽  
pp. 6937-6944 ◽  
Author(s):  
Dong Wang ◽  
Jinming Luo ◽  
Qilei Yang ◽  
Junchen Yan ◽  
Kaihang Zhang ◽  
...  
Keyword(s):  
Selective Catalytic Reduction ◽  
Flue Gas ◽  
Catalytic Reduction ◽  
Cement Furnace ◽  
Reduction Catalysts ◽  
Deactivation Mechanism

A review on oxidation of elemental mercury from coal-fired flue gas with selective catalytic reduction catalysts

2015 ◽  
Vol 5 (7) ◽  
pp. 3459-3472 ◽  
Author(s):  
Lingkui Zhao ◽  
Caiting Li ◽  
Xunan Zhang ◽  
Guangming Zeng ◽  
Jie Zhang ◽  
...  
Keyword(s):  
Selective Catalytic Reduction ◽  
Flue Gas ◽  
Catalytic Reduction ◽  
Elemental Mercury ◽  
P Transformation ◽  
Scr Catalysts ◽  
Mechanism And Kinetics ◽  
Reduction Catalysts

Transformation and speciation of Hg in coal-fired flue gas, mechanism and kinetics for oxidizing Hg0 with SCR catalysts were discussed.

Deactivation of Mn/TiO2 catalyst for NH3-SCR reaction: effect of phosphorous

RSC Advances ◽  
2016 ◽  
Vol 6 (14) ◽  
pp. 11226-11232 ◽  
Author(s):  
Ning-zhi Yang ◽  
Rui-tang Guo ◽  
Qing-shan Wang ◽  
Wei-guo Pan ◽  
Qi-lin Chen ◽  
...  
Keyword(s):  
Selective Catalytic Reduction ◽  
Catalytic Reduction ◽  
Reduction Of No ◽  
Tio2 Catalyst ◽  
Nh3 Scr ◽  
Deactivation Mechanism

The deactivation mechanism of phosphorous on a Mn/TiO2 catalyst for selective catalytic reduction of NO with NH3 was investigated in this study.

Experimental and kinetic analysis of hydrothermal aging effects on ammonia adsorption capacity over a commercial Cu-zeolite selective catalytic reduction catalyst

2018 ◽  
Vol 233 (12) ◽  
pp. 3030-3042
Author(s):  
Tae Joong Wang ◽  
In Hyuk Im
Keyword(s):  
Adsorption Capacity ◽  
Selective Catalytic Reduction ◽  
Catalytic Reduction ◽  
Adsorption Site ◽  
Selective Catalytic Reduction Catalyst ◽  
Aging Effects ◽  
Hydrothermal Aging ◽  
Ammonia Adsorption ◽  
Fresh Catalyst ◽  
Reduction Catalysts

Ammonia/urea selective catalytic reduction is an efficient technology to control NOx emission from diesel engines. One of its critical challenges is the performance degradation of selective catalytic reduction catalysts due to the hydrothermal aging experienced in real-world operations during the lifetime. In this study, hydrothermal aging effects on the reduction of ammonia adsorption capacity over a commercial Cu-zeolite selective catalytic reduction catalyst were investigated under actual engine exhaust conditions. Ammonia adsorption site densities of the selective catalytic reduction catalysts aged at two different temperatures of 750°C and 850°C for 25 h with 10% H2O were experimentally measured and compared to that of fresh catalyst on a dynamometer test bench with a heavy-duty diesel engine. The test results revealed that hydrothermal aging significantly decreased the ammonia adsorption capacity of the current commercial Cu-zeolite selective catalytic reduction catalyst. Hydrothermal treatment at 750°C reduced the ammonia adsorption site to 62.5% level of that of fresh catalyst, while hydrothermal treatment at 850°C lowered the adsorption site to 37.0% level of that of fresh catalyst. Also, in this study, numerical simulation and kinetic analysis were carried out to quantify the impact of hydrothermal aging on the reduction of ammonia adsorption capacity by introducing an aging coefficient. The kinetic parameter calibrations based on actual diesel engine tests with a commercial monolith Cu-zeolite selective catalytic reduction catalyst provided a highly realistic kinetic parameter set of ammonia adsorption/desorption and enabled a mathematical description of hydrothermal aging effect.

scholarly journals Selective Catalytic Reduction System Ammonia Injection Control Based on Deep Deterministic Policy Reinforcement Learning

2021 ◽  
Vol 9 ◽  
Author(s):  
Peiran Xie ◽  
Guangming Zhang ◽  
Yuguang Niu ◽  
Tianshu Sun
Keyword(s):  
Reinforcement Learning ◽  
Selective Catalytic Reduction ◽  
Virtual Environment ◽  
Flue Gas ◽  
Catalytic Reduction ◽  
Thermal Power ◽  
Gas Treatment ◽  
Intelligent Controller ◽  
Secondary Pollution ◽  
Ammonia Injection

The control of flue gas emission in thermal power plants has been a topic of concern. Selective catalytic reduction technology has been widely used as an effective flue gas treatment technology. However, precisely controlling the amount of ammonia injected remains a challenge. Too much ammonia not only causes secondary pollution but also corrodes the reactor equipment, while too little ammonia does not effectively reduce the NOx content. In recent years, deep reinforcement learning has achieved better results than traditional methods in decision making and control, which provides new methods for better control of selective catalytic reduction systems. The purpose of this research is to design an intelligent controller using reinforcement learning technology, which can accurately control ammonia injection, and achieve higher denitrification effect and less secondary pollution. To train the deep reinforcement learning controller, a high-precision virtual denitration environment is first constructed. In order to make the virtual environment more realistic, this virtual environment was designed as a special structure with two decoders and a unique approach was used in fitting the virtual environment. A deep deterministic policy agent is used as an intelligent controller to control the amount of injected ammonia. To make the intelligent controller more stable, the actor-critic framework and the experience pool approach were adopted. The results show that the intelligent controller can control the emissions of nitrogen oxides and ammonia at the outlet of the reactor after training in virtual environment.

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