The Preparation and Current Situation of Ce and Mn Catalyst

2013 ◽  
Vol 864-867 ◽  
pp. 1612-1615
Author(s):  
Wen Long Zhen ◽  
Rui Tang Guo ◽  
Wei Guo Pan ◽  
Yan Wu Gao ◽  
Chao Lin Shi
Keyword(s):  
Flue Gas ◽  
Power Plants ◽  
Catalytic Reduction ◽  
Reduction Process ◽  
Air Pollutant ◽  
Photochemical Smog ◽  
Environmental Friendly ◽  
Secondary Pollution ◽  
Temperature Window ◽  
Low Temperature Scr

NOx is the main air pollutant of coal-fired power plants, which is one of the important reasons to cause pollution such as acid rain, photochemical smog and so on. Selective catalytic reduction process is the major technology for reducing NOx emissions from coal-fired power plants. However, the commercial vanaidia-based catalyst is active within a narrow temperature window of 300-400°C, easily to be deacticed by SO2 in the flue gas. And the formation of N2O and toxicity of vanaidia cause secondary pollution. Therefore, it is of more importance to develop a new environmental-friendly catalyst for low temperature SCR with high activity.

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.

Preparation and Performance of Several Non-Precious Metal Oxides Catalysts for the Low Temperature SCR of NOx with NH3

2011 ◽  
Vol 356-360 ◽  
pp. 1528-1534
Author(s):  
Wei Fang Dong
Keyword(s):  
Low Temperature ◽  
Metal Oxides ◽  
Flue Gas ◽  
Precious Metal ◽  
Catalytic Reduction ◽  
Fixed Bed ◽  
Catalytic Performance ◽  
Fixed Bed Reactor ◽  
Low Temperature Scr ◽  
Scr Of Nox

A series of non-precious metal oxides catalysts were prepared for low-temperature selective catalytic reduction (SCR) of NOx with NH3 in a fixed bed reactor. The catalytic performance was evaluated by the removal efficiency of NOx and N2selectivity which were respectively detected by flue gas analyzer and flue gas chromatograph. Furthermore, the components of gas products from the above experiments were analysed with 2010 GC-MS. The results illustrated that the MnO2exhibited the highest NOx conversion to 95.46% and the highest selectivity of N2to 100% at temperature of 393K, then followed ZrO2, Al2O3and Fe2O3.

scholarly journals Investigation and Control Technology on Excessive Ammonia-Slipping in Coal-Fired Plants

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4249
Author(s):  
Xuan Yao ◽  
Man Zhang ◽  
Hao Kong ◽  
Junfu Lyu ◽  
Hairui Yang
Keyword(s):  
Flue Gas ◽  
Power Plants ◽  
Catalytic Reduction ◽  
Flue Gas Desulfurization ◽  
Ammonia Emission ◽  
Dust Collector ◽  
Neural Network Algorithm ◽  
Injection Technology ◽  
And Control ◽  
The Relationship

After the implementation of the ultra-low emissions regulation on the coal-fired power plants in China, the problem of the excessive ammonia-slipping from selective catalytic reduction (SCR) seems to be more severe. This paper analyzes the operating statistics of the coal-fired plants including 300 MW/600 MW/1000-MW units. Statistics data show that the phenomenon of the excessive ammonia-slipping is widespread. The average excessive rate is over 110%, while in the small units the value is even higher. A field test data of nine power plants showed that excessive ammonia-slipping at the outlet of SCR decreased following the flue-gas process. After most ammonia reduced by the dust collector and the wet flue-gas desulfurization (FGD), the ammonia emission at the stack was extremely low. At same time, a method based on probability distribution is proposed in this paper to describe the relationship between the NH3/NOX distribution deviation and the De–NOX efficiency/ammonia-slipping. This paper also did some original work to solve the ammonia-slipping problem. A real-time self-feedback ammonia injection technology using neural network algorithm to predict and moderate the ammonia distribution is proposed to decrease the NH3/NOX deviation and excessive ammonia-slipping. The technology is demonstrated in a 600-MW unit and works successfully. The excessive ammonia-slipping problem is well controlled after the implementation of the technology.

The Feasibility Analysis of Applying SCR Technology to Regenerative Combustion System

2012 ◽  
Vol 610-613 ◽  
pp. 1747-1750
Author(s):  
Zhong Jun Tian ◽  
Shi Ping Jin ◽  
Tan Li ◽  
Zhen Biao Hao ◽  
Wu Qi Wen
Keyword(s):  
Flue Gas ◽  
Waste Heat ◽  
Catalytic Reduction ◽  
Catalytic Reactions ◽  
Feasibility Analysis ◽  
Combustion System ◽  
Combustion Technology ◽  
Temperature Window ◽  
Regenerative Cells ◽  
Industrial Heating

The regenerative combustion technology has been widely used in the recovery of flue gas waste heat, but the denitration is not considered. This article is based on the comprehensive application of the Selective Catalytic Reduction(SCR) technology and the regenerative combustion technology to recycling waste heat and removing NOx from flue gas. In many industrial heating processes, the temperature of flue gas falls from above 1000°C to the ambient temperature (50°C-100°C) along regenerators, while the temperature window of most catalysts ranges from 200°C to 450°C, meanwhile catalysts and regenerative cells are porous mediums, so the regenerative cells that hold a temperature range for catalytic reactions can be replaced by catalysts, and the waste heat of flue gas can be recovered and the nitrogen oxides can be removed simultaneously.

scholarly journals Research Progress on Control and Removal Technology of SO3 of Coal-fired Power Plants

2019 ◽  
Vol 118 ◽  
pp. 01036
Author(s):  
Xiuru Liu ◽  
Yiqing Sun ◽  
Fangming Xue ◽  
Jingcheng Su ◽  
jiangjiang Qu ◽  
...  
Keyword(s):  
Flue Gas ◽  
Coal Combustion ◽  
Power Plants ◽  
Catalytic Reduction ◽  
Research Progress ◽  
Combustion Mode ◽  
High Concentration ◽  
Safe Operation ◽  
Removal Technology ◽  
Coal Power Plants

SO3 is one of pollutants in flue gas of coal power plants. It mainly derived from coal combustion in boiler and selective catalytic reduction denitrification system. The content of SO3 in flue gas were influenced by the combustion mode, sulfur content in fuel, composition of denitrification catalyst and fly ash. SO3 and water vapour generated H2SO4 droplets. Sulfate secondary particles in atmosphere could cause haze, acid rain and other disastrous weather. High concentration of SO3 could cause blockage and corrosion and affect the safe operation of the units. The generation mechanism of SO3 was discussed. The latest research progress on control and removal technology of SO3 was summarized. The study in this paper provides a reference for pollutant treatment in coal-fired power plants.

scholarly journals Experiment and simulation study of the effect of ethanol and compound additives on the urea-based selective non-catalytic reduction process under moderate temperature conditions

2018 ◽  
Vol 5 (10) ◽  
pp. 180969
Author(s):  
Bang Wu ◽  
Ge Pu ◽  
Jiantai Du
Keyword(s):  
Simulation Study ◽  
No Reduction ◽  
Flow Reactor ◽  
Catalytic Reduction ◽  
Reduction Process ◽  
Inhibitory Effect ◽  
Ethanol Decomposition ◽  
Entrained Flow Reactor ◽  
Temperature Window ◽  
Experiment And Simulation

An experiment and simulation study of the effect of using liquid additives on the selective non-catalytic reduction (SNCR) process is presented, providing a novel way for plants reducing NO X emissions. An experimental study is conducted in an entrained flow reactor, and CHEMKIN is applied for simulation study. Ethanol additive can effectively shift the temperature window of the NO X OUT process to a lower range and the NO X OUT efficiency ranges from 29 to 56% at 700–800°C. Furthermore, ethanol additive has a significant inhibitory effect on ammonia slip. Na 2 SO 4 and C 2 H 5 OH can be combined into a compound additive, which has a synergistic effect on NO reduction. The addition of methanol can greatly promote denitrification efficiency from 650°C to 725°C, indicating the potential of compound additives in NO reduction. The HNCO + OH = H 2 O + NCO pathway is also proven to be enhanced for ethanol decomposition, thereby providing OH•, which is active in NO reduction. Finally, the reaction routes for ethanol on the urea-based SNCR process at the proper temperature are proposed.

scholarly journals Multimodel Anomaly Identification and Control in Wet Limestone-Gypsum Flue Gas Desulphurization System

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Xiaoli Li ◽  
Quanbo Liu ◽  
Kang Wang ◽  
Fuqiang Wang ◽  
Guimei Cui ◽  
...  
Keyword(s):  
Flue Gas ◽  
Sulphur Dioxide ◽  
High Performance ◽  
Power Plants ◽  
Control Method ◽  
Control Strategies ◽  
Air Pollutant ◽  
Process Data ◽  
Whole Process ◽  
Flue Gas Desulphurization

Sulphur dioxide, as one of the most common air pollutant gases, brings considerable numbers of hazards on human health and environment. For the purpose of reducing the detrimental effect it brings, it is of urgent necessity to control emissions of flue gas in power plants, since a substantial proportion of sulphur dioxide in the atmosphere stems from flue gas generated in the whole process of electricity generation. However, the complexity and nondeterminism of the environment increase the occurrences of anomalies in practical flue gas desulphurization system. Anomalies in industrial desulphurization system would induce severe consequences and pose challenges for high-performance control with classical control strategies. In this article, based on process data sampled from 1000 MW unit flue gas desulphurization system in a coal-fired power plant, a multimodel control strategy with multilayer parallel dynamic neural network (MPDNN) is utilized to address the control problem in the context of different anomalies. In addition, simulation results indicate the applicability and effectiveness of the proposed control method by comparing with different cases.

Environmental Study of the Design and Operation of the SCR Flue Gas Denitration Project

2014 ◽  
Vol 977 ◽  
pp. 285-289 ◽  
Author(s):  
Yan Kun Cheng ◽  
Li Xuan Wang ◽  
Peng Huo
Keyword(s):  
Selective Catalytic Reduction ◽  
Flue Gas ◽  
Catalytic Reduction ◽  
Environmental Study ◽  
Technology Application ◽  
Secondary Pollution ◽  
Flue Gas Denitrification

Describes the principle and process of application of (Selective catalytic reduction) SCR flue gas denitration technology application and process, boiler flue gas generated NOx and NH3reduction in the role of a catalyst, generating no secondary pollution N2 and H2O, this paper layout and operation of the equipment on the SCR reactor, and the effect of flue gas denitrification were discussed deeply。

Sign in / Sign up

Export Citation Format

Share Document