Research on optimization model of gangue combustion based on chemical reaction kinetics

doi:10.11949/0438-1157.20250318

Abstract

Abstract:

This paper investigates the combustion characteristics of gangue and low-calorific-value coalbed methane. By using the co-combustion mode of gangue and coalbed methane in a circulating fluidized bed (CFB) boiler, and using chemical reaction kinetics, we optimize the pyrolysis reaction of the co-combustion of gangue and coalbed methane in the fluidized bed and derive a chemical reaction kinetics optimization combustion model. The simulation results are compared with experimental data to verify the correctness and reliability of the model. The key parameters of the chemical reaction rate of gangue and coal bed methane in the efficient mixing and burning in circulating fluidized bed boiler are analyzed and discussed; the changes and effects of different chemical reaction kinetics parameters on the chemical reaction rate are simulated. The results show that the optimized model can reduce the error of chemical reaction rate in the combustion region of the furnace, and the optimized simulation is especially critical for the combustion/reaction conditions and emission control; and the optimized group has significant advantages in the main reaction region, which can help to further improve the combustion efficiency, accurately predict the product concentration, and reduce the waste of energy and pollutant generation. Reflecting the fact that the internal conditions of the furnace are more sensitive to the optimization model, it is demonstrated that the applicability and accuracy of the model over the full height range can be further improved through optimization.

Key words: coal gangue, chemical reaction kinetics, optimization simulation, numerical simulation

摘要：

本文针对煤矸石及低热值煤层气燃烧特性，利用煤矸石和煤层气在循环流化床锅炉中混燃方式，基于化学反应动力学方法，对煤矸石与煤层气在流化床内混燃中的热解反应进行优化模拟，得出化学反应动力学优化燃烧模型，将模拟结果与实验数据进行对比验证了模型的正确性和可靠性。对煤矸石和煤层气在循环流化床锅炉中高效混燃的化学反应速率关键参数进行了分析与讨论；模拟得到了不同化学反应动力学参数对化学反应速率的影响。结果表明，优化模型能降低炉膛燃烧区域的化学反应速率误差，优化模拟对于掌握燃烧/反应状况和排放控制尤为关键；且优化组在主反应区具备显著优势，能够帮助进一步提升燃烧效率、准确预测产物浓度、减少能量浪费和污染物生成。反映了炉膛内部工况对优化模型敏感性更高的事实，证明通过优化可进一步提升模型在全高度范围内的适用性和准确度。

关键词: 煤矸石, 化学反应动力学, 优化模拟, 数值模拟

CLC Number:

TK 229

Dan LI, Xiuheng YU, Juhui CHEN, Tong SU, Michael ZHURAVKOV, Siarhel LAPATSIN, Wenrui JIANG. Research on optimization model of gangue combustion based on chemical reaction kinetics[J]. CIESC Journal, 2025, 76(12): 6410-6422.

李丹, 于秀恒, 陈巨辉, 苏潼, ZHURAVKOV Michael, LAPATSIN Siarhel, 姜文锐. 基于化学反应动力学煤矸石燃烧优化模型研究[J]. 化工学报, 2025, 76(12): 6410-6422.

Figures/Tables 14

References 32

[1]	郭彦霞, 张圆圆, 程芳琴. 煤矸石综合利用的产业化及其展望[J]. 化工学报, 2014, 65(7): 2443-2453.
	Guo Y X, Zhang Y Y, Cheng F Q. Industrial development and prospect about comprehensive utilization of coal gangue[J]. CIESC Journal, 2014, 65(7): 2443-2453.
[2]	Varol M, Symonds R, Anthony E J, et al. Emissions from co-firing lignite and biomass in an oxy-fired CFBC[J]. Fuel Processing Technology, 2018, 173: 126-133.
[3]	廖新杰. 煤泥流化床混烧机理及氮硫污染物排放特性研究[D]. 武汉: 华中科技大学, 2024.
	Liao X J. Study on the mechanism of coal slurry fluidized bed co firing and the emission characteristics of nitrogen and sulfur pollutants[D]. Wuhan: Huazhong University of Science and Technology, 2024.
[4]	黄顺进, 张丽, 颜井冲, 等. 高碱煤与煤矸石掺烧SO₂和NO减排及结渣抑制研究[J]. 化工学报, 2022, 73(12): 5581-5591.
	Huang S J, Zhang L, Yan J C, et al. Investigation on cofiring high-alkali coal with coal gangues: SO₂, NO reduction and ash slagging inhibition[J]. CIESC Journal, 2022, 73(12): 5581-5591.
[5]	Chen Y R, Li H J, Yang Z Q, et al. Co-utilization of two coal mine residues: non-catalytic co-combustion of coal bed methane and coal gangue in a circulating fluidized bed[J]. Advances in Mechanical Engineering, 2015, 7(9): 1687814015606380.
[6]	Wang S J, Lu J D, Li W J, et al. Modeling of pulverized coal combustion in cement rotary kiln[J]. Energy & Fuels, 2006, 20(6): 2350-2356.
[7]	周英贵. 大型电站锅炉SNCR/SCR脱硝工艺试验研究、数值模拟及工程验证[D]. 南京: 东南大学, 2016.
	Zhou Y G. Hybrid SNCR/SCR denitration technology in large thermal power plant boiler: experimental study, numerical simulation and egneering validation[D]. Nanjing: Southeast University, 2016.
[8]	Zhang J W, Zhang Y, He G, et al. Wind speed effect on infrared-image-based coal and gangue recognition with liquid intervention in LTCC[J]. Journal of Cleaner Production, 2024, 478: 143925.
[9]	Wang H P, Jin H Z, Yang Z, et al. CFD modeling of flow, combustion and NO _x emission in a wall-fired boiler at different low-load operating conditions[J]. Applied Thermal Engineering, 2024, 236: 121824.
[10]	Singh R I, Brink A, Hupa M. CFD modeling to study fluidized bed combustion and gasification[J]. Applied Thermal Engineering, 2013, 52(2): 585-614.
[11]	赵立正. 煤矸混烧超临界CFB锅炉气固流动及污染物生成特性研究[D]. 北京: 华北电力大学, 2020.
	Zhao L Z. Research on gas-solid flow and pollutants generation characteristics of a coal-gangue-fired supercritical CFB boiler[D]. Beijing: North China Electric Power University, 2020.
[12]	Chejne F, Hernandez J P. Modelling and simulation of coal gasification process in fluidised bed[J]. Fuel, 2002, 81(13): 1687-1702.
[13]	李林, 段伦博, 武万强, 等. 煤颗粒流化床增压富氧燃烧脱挥发分模型[J]. 煤炭学报, 2022, 47(11): 3906-3913.
	Li L, Duan L B, Wu W Q, et al. Model on devolatilization of coal particle in fluidized bed under pressurized oxy-fuel combustion[J]. Journal of China Coal Society, 2022, 47(11): 3906-3913.
[14]	马芯蕊. 高密度循环流化床煤气化过程数值模拟[D]. 北京: 华北电力大学, 2023.
	Ma X R. Numerical simulation of high-density circulating fluidized bed gasification process [D]. Beijing: North China Electric Power University, 2023.
[15]	景旭亮, 王志青, 张乾, 等. 流化床气化炉半焦细粉的燃烧特性及其动力学研究[J]. 燃料化学学报, 2014, 42(1): 13-19.
	Jing X L, Wang Z Q, Zhang Q, et al. Combustion property and kinetics of fine chars derived from fluidized bed gasifier[J]. Journal of Fuel Chemistry and Technology, 2014, 42(1): 13-19.
[16]	Matthews L R, Niziolek A M, Onel O, et al. Biomass to liquid transportation fuels via biological and thermochemical conversion: process synthesis and global optimization strategies[J]. Industrial & Engineering Chemistry Research, 2016, 55(12): 3203-3225.
[17]	Wen C M, Foster C, van Winden W, et al. Toward net-zero greenhouse gas emission: techno–economic and life cycle analyses of routes for triacetic acid lactone (TAL) bioproduction[J]. ACS Sustainable Chemistry & Engineering, 2024, 12(33): 12430-12445.
[18]	郭啸峰. 基于详细化学反应简化机理的燃烧污染物生成数值模拟与实验验证[D]. 北京. 中国科学院力学研究所, 2014.
	Guo X F. Numerical simulation of combustion pollutant formation based on reduced mechanism of detailed chemical reactions and experimental validation[D]. Beijing: Institute of Mechanics, Chinese Academy of Sciences, 2014.
[19]	李振山, 陈登高, 张志, 等. 煤粉燃烧中NO _x 的预测: 参数数据库及CFD实践[J]. 煤炭学报, 2016, 41(12): 3142-3150.
	Li Z S, Chen D G, Zhang Z, et al. Prediction of NO _x during pulverized coal combustion: parameter database and CFD application[J]. Journal of China Coal Society, 2016, 41(12): 3142-3150.
[20]	贺坤, 王刚, 邹忠平, 等. 富氢低碳高炉炉内动力学模型及其应用[C]//第十二届中国金属学会青年学术年会. 赣州, 2024: 111-119.
	He K, Wang G, Zhou Z P . et al . Dynamic model and application of rich hydrogen low carbon blast furnace [C]// The 12th Youth Academic Conference of the Chinese Society of Metals. Ganzhou, 2024: 111-119
[21]	王敬. 乙酸苯酚酯热解的实验与动力学模型研究[D]. 南宁: 广西大学, 2023: 25-54.
	Wang J. Experimental and kinetic model study on pyrolysis of phenol acetate [D]. Nanning: Guangxi University, 2023: 25-54.
[22]	周俊杰, 徐国权, 张华俊. FLUENT工程技术与实例分析[M]. 北京: 中国水利水电出版社, 2010.
	Zhou J J, Xu G Q, Zhang H J. FLUENT Engineering Technology and Case Analysis[M]. Beijing: China Water & Power Press, 2010.
[23]	李进良, 李承曦, 胡仁喜, 等. 精通FLUENT6.3流场分析[M]. 北京: 化学工业出版社, 2009.
	Li J L, Li C X, Hu R X. Proficient in FLUENT6.3 Flow Field Analysis[M]. Beijing: Chemical Industry Press, 2009.
[24]	唐家鹏. ANSYS FLUENT 16.0超级学习手册[M]. 北京: 人民邮电出版社, 2016.
	Tang J P. ANSYS FLUENT 16.0 Super Learning Manual[M]. Beijing: Posts & Telecom Press, 2016.
[25]	毛晓飞, 陈念祖. 煤燃烧反应活化能计算方法的研究[J]. 电站系统工程, 2007, 23(3): 15-17.
	Mao X F, Chen N Z. Improving the Flynn-Wall-Ozawa method in calculating the activation energy in combustion reactions of the coal[J]. Power System Engineering, 2007, 23(3): 15-17.
[26]	罗勇军, 李建波, 郭子鹏. 基于热重分析的低热值煤/生物质耦合燃烧动力学特性研究[J]. 煤炭技术, 2025, 44(2): 228-233.
	Luo Y J, Li J B, Guo Z P. Study on kinetic characteristics of low heat value coal and biomass co-combustion based on thermogravimetric analysis[J]. Coal Technology, 2025, 44(2): 228-233.
[27]	Namkung H, Lee Y J, Park J H, et al. Blending effect of sewage sludge and woody biomass into coal on combustion and ash agglomeration behavior[J]. Fuel, 2018, 225: 266-276.
[28]	Wang Y L, Jia L, Guo J R, et al. Thermogravimetric analysis of co-combustion between municipal sewage sludge and coal slime: combustion characteristics, interaction and kinetics[J]. Thermochimica Acta, 2021, 706: 179056.
[29]	曹妙妙, 张冬朋, 刘飞. 煤矸石的热重分析: 以淮北某煤矿为例[J]. 科技风, 2024(2): 160-163.
	Cao M M, Zhang D P, Liu F. Thermogravimetric analysis of coal gangue: taking a coal mine in Huaibei as an example[J]. Technology Wind, 2024(2): 160-163.
[30]	刘成龙. 含油污泥与煤矸石共热解特性研究与机理分析[D]. 北京: 北京化工大学, 2024.
	Liu C L. Co-pyrolysis characteristics and mechanism analysis of oily sludge with coal gangue [D]. Beijing: Beijing University of Chemical Technology, 2024.
[31]	Narula S C, Wellington J F. Prediction, linear regression and the minimum sum of relative errors[J]. Technometrics, 1977, 19(2): 185.
[32]	Dong Z H, Dong C Q, Zhang J J, et al. Modeling the combustion of coal in a 300MW circulating fluidized bed boiler with aspen plus[C]//2010 Asia-Pacific Power and Energy Engineering Conference. Chengdu: IEEE, 2010: 1-4.

温度/K	活化能/(kJ/mol)
温度/K	PE1	PE2	PE3	PE4	PE5
800	70.94	71.02	71.87	72.64	73.20
900	78.98	79.10	79.85	80.62	81.23
1000	87.52	87.63	88.20	88.90	89.30
1100	96.30	97.01	97.96	98.60	99.10
1200	107.20	107.90	108.52	109.1	109.96
1300	115.52	116.10	117.22	118.13	119.20

温度/K	活化能/(kJ/mol)
温度/K	PE1	PE2	PE3	PE4	PE5
800	70.94	71.02	71.87	72.64	73.20
900	78.98	79.10	79.85	80.62	81.23
1000	87.52	87.63	88.20	88.90	89.30
1100	96.30	97.01	97.96	98.60	99.10
1200	107.20	107.90	108.52	109.1	109.96
1300	115.52	116.10	117.22	118.13	119.20

温度/K	频率因子/s^-1
温度/K	PA1	PA2	PA3	PA4	PA5
800	1.00×10⁷	1.00×10⁷	7.13×10⁷	7.93×10⁷	8.30×10⁷
900	1.00×10⁷	1.07×10⁷	8.01×10⁷	8.57×10⁷	9.12×10⁸
1000	1.01×10⁷	1.11×10⁷	2.65×10⁷	1.23×10⁸	9.85×10⁸
1100	1.15×10⁷	3.74×10⁷	6.26×10⁷	1.96×10⁸	7.32×10⁹
1200	2.85×10⁷	9.85×10⁷	1.63×10⁸	7.41×10⁸	8.02×10⁹
1300	9.65×10⁷	1.45×10⁸	7.62×10⁹	2.03×10¹⁰	9.02×10¹⁰

温度/K	频率因子/s^-1
温度/K	PA1	PA2	PA3	PA4	PA5
800	1.00×10⁷	1.00×10⁷	7.13×10⁷	7.93×10⁷	8.30×10⁷
900	1.00×10⁷	1.07×10⁷	8.01×10⁷	8.57×10⁷	9.12×10⁸
1000	1.01×10⁷	1.11×10⁷	2.65×10⁷	1.23×10⁸	9.85×10⁸
1100	1.15×10⁷	3.74×10⁷	6.26×10⁷	1.96×10⁸	7.32×10⁹
1200	2.85×10⁷	9.85×10⁷	1.63×10⁸	7.41×10⁸	8.02×10⁹
1300	9.65×10⁷	1.45×10⁸	7.62×10⁹	2.03×10¹⁰	9.02×10¹⁰

温度/K	活化能/(kJ/mol)
温度/K	CE1	CE2	CE3	CE4	CE54
800	83.83	84.62	85.20	85.91	86.62
900	84.41	86.32	85.67	86.25	87.83
1000	85.00	85.70	86.80	87.30	88.90
1100	85.63	86.53	87.20	88.10	89.23
1200	86.52	87.63	87.21	87.95	89.65
1300	86.85	87.36	88.52	89.62	90.32