To reduce NO_(x) emissions of coal-fired power plant boilers,this study introduced particle swarm optimization employing opposition-based learning(OBLPSO)and particle swarm optimization employing generalized oppositio...To reduce NO_(x) emissions of coal-fired power plant boilers,this study introduced particle swarm optimization employing opposition-based learning(OBLPSO)and particle swarm optimization employing generalized opposition-based learning(GOBLPSO)to a low NO_(x) combustion optimization area.Thermal adjustment tests under different ground conditions,variable oxygen conditions,variable operation modes of coal pulverizer conditions,and variable first air pressure conditions were carried out on a 660 MW boiler to obtain samples of combustion optimization.The adaptability of PSO,differential evolution algorithm(DE),OBLPSO,and GOBLPSO was compared and analyzed.Results of 51 times independently optimized experiments show that PSO is better than DE,while the performance of the GOBLPSO algorithm is generally better than that of the PSO and OBLPSO.The median-optimized NO_(x) emission by GOBLPSO is up to 15.8 mg/m^(3) lower than that obtained by PSO.The generalized opposition-based learning can effectively utilize the information of the current search space and enhance the adaptability of PSO to the low NO_(x) combustion optimization of the studied boiler.展开更多
The radiant tube burner was modeled and analyzed by the numerical simulation method to investigate the influence factors and rules of NO_(x) emissions in a W-type radiant tube.These factors,which include air preheatin...The radiant tube burner was modeled and analyzed by the numerical simulation method to investigate the influence factors and rules of NO_(x) emissions in a W-type radiant tube.These factors,which include air preheating temperature,excess air coefficient,and fuel gas composition,were modified to study their effects on NO_(x) emissions under varying working conditions.Simulation results were compared with the theoretical calculation value based on chemical reaction equilibrium theory and the onsite experimental value to verify the simulation accuracy.The results show that NO_(x) emissions rise with increasing air preheating temperatures.NO_(x) production increases to an extreme value and then decreases during the oxygen-poor to oxygen-enriched process with the rise of the excess air coefficient.Enhancing the proportion of coke oven gas in the fuel gas raises the combustion temperature as well as the NO_(x) discharge.Both the thermal efficiency and NO_(x) emissions should be balanced.Therefore,the recommended values based on the simulation results are as follows:the air preheating temperature should not exceed 400℃,the excess air coefficient should be between 1.1 and 1.2,and the volume fraction of the coke oven gas should not exceed 30%.展开更多
Nitrogen oxide(NO_(x))pollutants emitted from coal combustion are attracting growing public concern.While the traditional technologies of reducing NO_(x) were mainly focused on terminal treatment,and the research on s...Nitrogen oxide(NO_(x))pollutants emitted from coal combustion are attracting growing public concern.While the traditional technologies of reducing NO_(x) were mainly focused on terminal treatment,and the research on source treatment is limited.This paper proposes a new coal combustion strategy that significantly reduces NO_(x) emissions during coal combustion.This strategy has two important advantages in reducing NO_(x) emissions.First,by introducing iron-based catalyst at the source,which will catalyze the conversion of coke nitrogen to volatile nitrogen during the pyrolysis process,thereby greatly reducing the coke nitrogen content.The second is de-NO_(x) process by a redox reaction between NO_(x) and reducing agents(coke,HCN,NH_(3),etc.)that occurred during coke combustion.Compared to direct combustion of coal,coke prepared by adding iron-based catalyst has 46.1% reduction in NO_(x) emissions.To determine the effect of iron-based additives on de-NO_(x) performance,demineralized coal(de-coal)was prepared to eliminate the effect of iron-based minerals in coal ash.The effects of iron compounds,additive dosages,and combustion temperatures on de-NO_(x) efficiency are systematically studied.The results revealed that the NO_(x) emission of the coke generated by pyrolysis of de-coal loaded with 3%(mass)Fe_(2)O_(3) decreases to 27.3% at combustion temperature of 900℃.Two main reasons for lower NO_(x) emissions were deduced:(1)During the catalytic coal pyrolysis stage,the nitrogen content in the coke decreases with the release of volatile nitrogen.(2)Part of the NO_(x) emitted during the coke combustion was converted into N_(2) for the catalytic effect of the Fe-based catalysts.It is of great practical value and scientific significance to the comprehensive treatment and the clean utilization process of coal.展开更多
文摘To reduce NO_(x) emissions of coal-fired power plant boilers,this study introduced particle swarm optimization employing opposition-based learning(OBLPSO)and particle swarm optimization employing generalized opposition-based learning(GOBLPSO)to a low NO_(x) combustion optimization area.Thermal adjustment tests under different ground conditions,variable oxygen conditions,variable operation modes of coal pulverizer conditions,and variable first air pressure conditions were carried out on a 660 MW boiler to obtain samples of combustion optimization.The adaptability of PSO,differential evolution algorithm(DE),OBLPSO,and GOBLPSO was compared and analyzed.Results of 51 times independently optimized experiments show that PSO is better than DE,while the performance of the GOBLPSO algorithm is generally better than that of the PSO and OBLPSO.The median-optimized NO_(x) emission by GOBLPSO is up to 15.8 mg/m^(3) lower than that obtained by PSO.The generalized opposition-based learning can effectively utilize the information of the current search space and enhance the adaptability of PSO to the low NO_(x) combustion optimization of the studied boiler.
文摘The radiant tube burner was modeled and analyzed by the numerical simulation method to investigate the influence factors and rules of NO_(x) emissions in a W-type radiant tube.These factors,which include air preheating temperature,excess air coefficient,and fuel gas composition,were modified to study their effects on NO_(x) emissions under varying working conditions.Simulation results were compared with the theoretical calculation value based on chemical reaction equilibrium theory and the onsite experimental value to verify the simulation accuracy.The results show that NO_(x) emissions rise with increasing air preheating temperatures.NO_(x) production increases to an extreme value and then decreases during the oxygen-poor to oxygen-enriched process with the rise of the excess air coefficient.Enhancing the proportion of coke oven gas in the fuel gas raises the combustion temperature as well as the NO_(x) discharge.Both the thermal efficiency and NO_(x) emissions should be balanced.Therefore,the recommended values based on the simulation results are as follows:the air preheating temperature should not exceed 400℃,the excess air coefficient should be between 1.1 and 1.2,and the volume fraction of the coke oven gas should not exceed 30%.
基金supported by National Natural Science Foundation of China(21878210)Shanxi Provincial Science and Technology Achievement Transformation Guidance Special Program of China(202104021301052)Shanxi Province Patent Transformation Special Program Project(202202054).
文摘Nitrogen oxide(NO_(x))pollutants emitted from coal combustion are attracting growing public concern.While the traditional technologies of reducing NO_(x) were mainly focused on terminal treatment,and the research on source treatment is limited.This paper proposes a new coal combustion strategy that significantly reduces NO_(x) emissions during coal combustion.This strategy has two important advantages in reducing NO_(x) emissions.First,by introducing iron-based catalyst at the source,which will catalyze the conversion of coke nitrogen to volatile nitrogen during the pyrolysis process,thereby greatly reducing the coke nitrogen content.The second is de-NO_(x) process by a redox reaction between NO_(x) and reducing agents(coke,HCN,NH_(3),etc.)that occurred during coke combustion.Compared to direct combustion of coal,coke prepared by adding iron-based catalyst has 46.1% reduction in NO_(x) emissions.To determine the effect of iron-based additives on de-NO_(x) performance,demineralized coal(de-coal)was prepared to eliminate the effect of iron-based minerals in coal ash.The effects of iron compounds,additive dosages,and combustion temperatures on de-NO_(x) efficiency are systematically studied.The results revealed that the NO_(x) emission of the coke generated by pyrolysis of de-coal loaded with 3%(mass)Fe_(2)O_(3) decreases to 27.3% at combustion temperature of 900℃.Two main reasons for lower NO_(x) emissions were deduced:(1)During the catalytic coal pyrolysis stage,the nitrogen content in the coke decreases with the release of volatile nitrogen.(2)Part of the NO_(x) emitted during the coke combustion was converted into N_(2) for the catalytic effect of the Fe-based catalysts.It is of great practical value and scientific significance to the comprehensive treatment and the clean utilization process of coal.
