Modeling and simulation of wet desulfurization system dynamic process

doi:10.11949/0438-1157.20200149

Abstract

Abstract:

The chemical mechanism model of the desulfurization tower in limestone-gypsum flue gas desulfurization was established, and the chemical process of flue gas desulfurization in the tower was dynamically simulated. Based on the material balance and chemical balance in the desulfurization tower, the model is described as a differential equation and solved by the special calculation software. Based on the actual operation data of the desulfurization system of a power plant, the changes of various indexes of the desulfurization system, such as pH, desulfurization rate, etc., and the axial spatial distributions of some important chemical substances, such as H ⁺, SO₂, are predicted. According to the calculation results, the influence of pH on the desulfurization rate is analyzed, and the boundary conditions of the operating parameters are explored and found. The results of this study put forward optimization suggestions for the design and operation of the actual desulfurization tower, and strengthen the anticorrosive performance at the flue gas inlet. The pH of the power plant slurry should be controlled at 4.2—5.3.

Key words: wet flue gas desulfurization, kinetic modeling, mathematical modeling, dynamic simulation, model correction

摘要：

针对石灰石-石膏法烟气脱硫建立脱硫塔的化学机理模型，对塔内烟气脱硫的化学过程进行动态模拟与仿真。基于脱硫塔内物料平衡和化学平衡，将模型描述为微分方程，并通过计算软件求解。基于某电厂脱硫系统实际运行数据，预测一定时间内脱硫系统各项指标的变化，如pH、脱硫率等，以及一些重要化学物质的轴向空间分布情况，如H⁺、SO₂。根据计算结果，分析pH对脱硫率的影响规律，探究和寻找运行参数的边界条件。研究结果对实际脱硫塔的设计和运行提出了优化建议，比如在烟气入口处加强防腐措施，控制浆液pH在4.2~5.3。

关键词: 湿法烟气脱硫, 动力学模型, 数学模拟, 动态仿真, 模型修正

CLC Number:

TQ 03-39

Shuangchen MA, Quan ZHOU, Jianzong CAO, Qi LIU, Wentong CHEN, Shuaijun FAN, Yakun YAO, Chenyu LIN, Caini MA. Modeling and simulation of wet desulfurization system dynamic process[J]. CIESC Journal, 2020, 71(8): 3741-3751.

马双忱, 周权, 曹建宗, 刘琦, 陈文通, 樊帅军, 要亚坤, 林宸雨, 马彩妮. 湿法脱硫系统动态过程建模与仿真[J]. 化工学报, 2020, 71(8): 3741-3751.

Figures/Tables 16

Fig.1 Coupling model of distributed gas-liquid-solid three-phase reaction

Fig.2 Main mass transfer processes and chemical reaction history

Table 1 Basic parameters of desulfurization tower

项目	内容	单位
吸收塔塔形	喷淋空塔
流向	逆向
浆液池高度	13.7	m
浆液池直径	13.2	m
吸收区高度	23.0	m
吸收区直径	13.2	m

Table 2 Chemical reaction parameters

变量名	化学反应速率	数值	单位	来源文献
k₂	反应(2)正	6.27×10⁵	mol/m³	[14]
k₃	反应(2)逆	2.00×10⁴	(mol/m³)^-1	[14]
k₄	反应(3)正	3.11×10⁵	mol/m³	[15]
k₅	反应(3)逆	5.00×10⁴	(mol/m³)^-1	[15]
k₈	反应(5)正	4.52×10⁴	mol/m³	[16]
k₉	反应(5)逆	2.11×10⁴	(mol/m³)^-1	[16]
k₁₀	反应(6)正	8.21×10⁴	(mol/m³)^-1	[14]
k₁₁	反应(6)逆	4.53×10⁴	mol/m³	[14]
k₁₂	反应(7)正	2.30×10⁵	(mol/m³)^-1	[14]
k₁₃	反应(7)逆	7.21×10⁴	mol/m³	[14]
k₁₄	反应(8)单向	2.31×10⁴		[4]
k₁₅	反应(9)单向	1.30×10^-3		[4]
k₁₆	反应(10)单向	2.50×10²		[4]
k₁₇	反应(11)单向	2.50×10²		[4]
k₁₈	反应(12)正	1.52×10⁴	(mol/m³)^-1	[18]
k₁₉	反应(12)逆	6.37×10⁴	mol/m³	[18]
k₂₂	反应(14)正	2.70×10⁴	(mol/m³)^-1	[16]
k₂₃	反应(14)逆	5.38×10⁵	mol/m³	[16]
$H S O 2$	SO₂的亨利系数	5.52×10^-3	kPa	[5]
$k d, C a C O 3$	CaCO₃溶解常数	6.32×10^-12	mol/(kg·s)	[5]
$K S P, C a C O 3$	CaCO₃溶度积	2.80×10^-3	(mol/m³)²	[5]

Table 2 Chemical reaction parameters

变量名	化学反应速率	数值	单位	来源文献
k₂	反应(2)正	6.27×10⁵	mol/m³	[14]
k₃	反应(2)逆	2.00×10⁴	(mol/m³)^-1	[14]
k₄	反应(3)正	3.11×10⁵	mol/m³	[15]
k₅	反应(3)逆	5.00×10⁴	(mol/m³)^-1	[15]
k₈	反应(5)正	4.52×10⁴	mol/m³	[16]
k₉	反应(5)逆	2.11×10⁴	(mol/m³)^-1	[16]
k₁₀	反应(6)正	8.21×10⁴	(mol/m³)^-1	[14]
k₁₁	反应(6)逆	4.53×10⁴	mol/m³	[14]
k₁₂	反应(7)正	2.30×10⁵	(mol/m³)^-1	[14]
k₁₃	反应(7)逆	7.21×10⁴	mol/m³	[14]
k₁₄	反应(8)单向	2.31×10⁴		[4]
k₁₅	反应(9)单向	1.30×10^-3		[4]
k₁₆	反应(10)单向	2.50×10²		[4]
k₁₇	反应(11)单向	2.50×10²		[4]
k₁₈	反应(12)正	1.52×10⁴	(mol/m³)^-1	[18]
k₁₉	反应(12)逆	6.37×10⁴	mol/m³	[18]
k₂₂	反应(14)正	2.70×10⁴	(mol/m³)^-1	[16]
k₂₃	反应(14)逆	5.38×10⁵	mol/m³	[16]
$H S O 2$	SO₂的亨利系数	5.52×10^-3	kPa	[5]
$k d, C a C O 3$	CaCO₃溶解常数	6.32×10^-12	mol/(kg·s)	[5]
$K S P, C a C O 3$	CaCO₃溶度积	2.80×10^-3	(mol/m³)²	[5]

Table 3 External parameters

变量名	含义	取值	单位	参数类型
G_gas,f	原烟气体积流量	323.95	m³/s	不可调
$C S O 2, g, f$	原烟气中SO₂浓度	0.0212	mol/m³	不可调
$C C O 2, g, f$	原烟气中CO₂浓度	0.5451	mol/m³	不可调
$C O 2, g, f$	原烟气中O₂浓度	2.3161	mol/m³	不可调
$G O 2$	氧化风体积流量	1.4722	m³/s	不可调
$C O 2, g, o x$	氧化风中O₂浓度	9.375	mol/m³	不可调
$S C a C O 3$	输入固相CaCO₃体积流量	2.2820	m³/s	可调
$C C a C O 3, s, f$	单位体积输入固相CaCO₃物质的量	22319	mol/m³	可调
$S C a S O 4$	输出固相CaSO₄体积流量	2.2820	m³/s	可调
$C C a S O 4, s, f$	单位体积输出固相CaCO₃物质的量	计算值	mol/m³	不可调
L_out	排出脱硫废水的体积流量	0.01	m³/s	可调
pH	浆液区的pH	4.98	无量纲	不可调

Table 3 External parameters

变量名	含义	取值	单位	参数类型
G_gas,f	原烟气体积流量	323.95	m³/s	不可调
$C S O 2, g, f$	原烟气中SO₂浓度	0.0212	mol/m³	不可调
$C C O 2, g, f$	原烟气中CO₂浓度	0.5451	mol/m³	不可调
$C O 2, g, f$	原烟气中O₂浓度	2.3161	mol/m³	不可调
$G O 2$	氧化风体积流量	1.4722	m³/s	不可调
$C O 2, g, o x$	氧化风中O₂浓度	9.375	mol/m³	不可调
$S C a C O 3$	输入固相CaCO₃体积流量	2.2820	m³/s	可调
$C C a C O 3, s, f$	单位体积输入固相CaCO₃物质的量	22319	mol/m³	可调
$S C a S O 4$	输出固相CaSO₄体积流量	2.2820	m³/s	可调
$C C a S O 4, s, f$	单位体积输出固相CaCO₃物质的量	计算值	mol/m³	不可调
L_out	排出脱硫废水的体积流量	0.01	m³/s	可调
pH	浆液区的pH	4.98	无量纲	不可调

Table 4 Internal parameters

变量名	含义	取值	单位
G	气相体积流量	363.3869	m³/s
L	液相体积流量	5.2649	m³/s
S	固相体积流量	0.7320	m³/s
V_g_,i	第i层气相体积(i=1~5)	619.2799	m³
V_l,i	第i层液相体积(i=1~5)	8.9724	m³
V_s_,i	第i层固相体积(i=1~5)	1.2475	m³
V_g_,6	氧化区气相体积	7.6265	m³
V_l,i	氧化区液相体积	1852.7	m³
V_s_,i	氧化区固相体积	14.51	m³

Fig.3 pH changing with time

Fig.4 pH distribution toward axial space

Fig.5 Desulfurization efficiency changing with time

Fig.6 Distribution of SO2 concentration toward axial space

Fig.7 CaCO3 consumption and gypsum production changing with time

Fig.8 Relationship between desulfurization rate and pH

Fig.9 Comparison of theoretical and actual values of desulfurization rate under actual conditions

Fig.10 Relationship between standardized residual and calculated value of desulfurization rate

Fig.11 Comparison of theoretical and actual values of desulfurization rate after correction

Fig.12 Frequency distribution of error between theoretical calculation and actual value of desulfurization rate

References 29

30	余胜威. MATLAB优化算法案例分析与应用: 进阶篇[M]. 北京: 清华大学出版社, 2015: 225-228.
	Yu S W. Case Study and Application of MATLAB Optimization Algorithm: Advanced[M]. Beijing: Tsinghua University Press, 2015: 225-228.
31	张德丰. MATLAB R2015b数值计算方法[M]. 北京: 清华大学出版社, 2017: 142-146.
	Zhang D F. MATLAB R2015b Numerical Calculation Method[M]. Beijing: Tsinghua University Press, 2017: 142-146.
32	吴国华, 朴香兰, 王玉军, 等. 添加剂强化石灰/石灰石烟气脱硫过程的应用及研究进展[J]. 环境科学动态, 2004, (3): 12-14.
	Wu G H, Piao X L, Wang Y J, et al. Application and research progress of additive-enhanced lime / limestone flue gas desulfurization process[J]. Environmental Science News, 2004, (3): 12-14.
1	武春锦, 吕武华, 梅毅, 等. 湿法烟气脱硫技术及运行经济性分析[J]. 化工进展, 2015, 34(12): 4368-4374.
	Wu C J, Lyu W H, Mei Y, et al. Wet flue gas desulfurization technology and economic analysis of operation[J]. Chemical Industry and Engineering Progress, 2015, 34(12): 4368-4374.
2	吴记保. 湿法烟气脱硫系统数学建模与仿真分析[D]. 重庆: 重庆大学, 2006.
	Wu J B. Mathematical modeling and simulation analysis of wet flue gas desulfurization system[D]. Chongqing: Chongqing University, 2006.
3	于明华, 李弘. 仿真技术的应用和发展[J].内蒙古科技与经济, 2007, (1): 67-69.
	Yu M H, Li H. Application and development of simulation technology[J]. Inner Mongolia Science Technology and Economy, 2007, (1): 67-69.
4	陈尔鲁. 湿法烟气脱硫过程建模与优化[D]. 杭州: 浙江大学, 2016.
	Chen E L. Modeling and optimization of wet flue gas desulfurization process[D]. Hangzhou: Zhejiang University, 2016.
5	展锦程, 冉景煜, 孙图星. 烟气脱硫吸收塔反应过程的数值模拟及试验研究[J].动力工程, 2008, (3): 433-437+446.
	Zhan J C, Ran J Y, Sun T X. Numerical simulation and experimental study of reaction process of flue gas desulfurization absorption tower[J]. Power Engineering, 2008, (3): 433-437+446.
6	石旻昊. 烟气脱硫过程净烟二氧化硫含量的动态仿真软件的研发[D]. 沈阳: 东北大学, 2017.
	Shi M H. Development of dynamic simulation software for net sulfur dioxide content in flue gas desulfurization process[D]. Shenyang: Northeastern University, 2017.
7	尚慧. 300 MW机组湿式石灰石/石膏烟气脱硫实时仿真系统研究[D]. 保定: 华北电力大学(河北), 2010.
	Shang H. Research on wet limestone/gypsum flue gas desulfurization real-time simulation system for 300 MW unit[D]. Baoding: North China Electric Power University (Hebei), 2010.
8	钟秦, 王娟, 陈迁乔, 等. 化工原理[M]. 北京: 国防工业出版社, 2001: 121.
	Zhong Q, Wang J, Chen Q Q, et al. Principles of Chemical Engineering[M]. Beijing: National Defense Industry Press, 2001: 121.
9	邓飞其, 刘洪伟, 冯昭枢, 等. 大型分布式迭代随机系统的均方渐近收敛性[J]. 华南理工大学学报(自然科版), 1998, (5): 130-135.
	Deng F Q, Liu H W, Feng Z S, et al. Mean square asymptotic convergence of large distributed iterative stochastic system[J]. Journal of South China University of Technology (Natural Science Edition), 1998, (5): 130-135.
10	鲍卫锋, 黄介生, 闫华, 等. 基于分布式参数模型的地下水数值模拟[J]. 农业工程学报, 2005, (5): 25-28.
	Bao W F, Huang J S, Yan H, et al. Numerical simulation of groundwater based on distributed parameter model [J]. Journal of Agricultural Engineering, 2005, (5): 25-28.
11	林永明. 大型石灰石-石膏湿法喷淋脱硫技术研究及工程应用[D]. 杭州: 浙江大学, 2006.
	Lin Y M. Research and engineering application of large-scale limestone-gypsum wet spray desulfurization technology[D]. Hangzhou: Zhejiang University, 2006.
12	吴文强, 李国敏, 陈求稳. 地下水数值模拟中分布式水文模型的耦合应用[J]. 勘察科学技术, 2009, (5): 48-51.
	Wu W Q, Li G M, Chen Q W. Coupling application of distributed hydrological model in groundwater numerical simulation[J]. Prospecting Science and Technology, 2009, (5): 48-51.
13	冯昭枢, 刘永清, 刘洪伟. 分布式迭代随机大系统的收敛性与稳定性[J]. 华南理工大学学报(自然科学版), 1994, (1): 23-26.
	Feng Z S, Liu Y Q, Liu H W. Convergence and stability of distributed iterative stochastic large-scale systems [J]. Journal of South China University of Technology (Natural Science Edition), 1994, (1): 23-26.
14	Gutiérrez O F J. A simple realistic modeling of full-scale wet limestone FGD units[J]. Chemical Engineering Journal, 2010, 165(2): 426-439.
15	张想. 湿法烟气脱硫吸收塔理论建模[D]. 北京: 华北电力大学, 2018.
	Zhang X. Theoretical modeling of wet flue gas desulfurization absorption tower[D]. Beijing: North China Electric Power University, 2018.
16	Neveux T, Hagi H, Moullec Y L. Performance simulation of full-scale wet flue gas desulfurization for oxy-coal combustion [J]. Energy Procedia, 2014, (63): 463-470.
17	王颖聪. 湿法脱硫烟气石膏雨成因分析及处理方案综述[J]. 华北电力技术, 2012, (10): 68-71+75.
	Wang Y C. Genesis analysis and treatment of wet desulfurization flue gas gypsum rain[J]. North China Electric Power Technology, 2012, (10): 68-71 + 75.
18	朱天乐, 李曜, 凌炫, 等. 湿式烟气脱硫中石灰石反应活性[J]. 环境科学, 2005, (6): 17-20.
	Zhu T L, Li Y, Ling X, et al. Reactive activity of limestone in wet flue gas desulfurization[J]. Environmental Science, 2005, (6): 17-20.
19	Jia Y, Zhong Q, Fan X, et al. Modeling of ammonia-based wet flue gas desulfurization in the spray scrubber[J]. Korean Journal of Chemical Engineering, 2011, 28(4): 1058-1064.
20	卓小芳. 石灰石/石膏湿法烟气脱硫系统仿真研究[D]. 重庆: 重庆大学, 2007.
	Zhuo X F. Simulation study of limestone/gypsum wet flue gas desulfurization system[D]. Chongqing: Chongqing University, 2007.
21	郎春雷. 湿式石灰石-石膏法烟气脱硫系统优化控制的仿真研究[D]. 保定: 华北电力大学(河北), 2007.
	Lang C L. Simulation study on optimal control of wet limestone-gypsum flue gas desulfurization system[D]. Baoding: North China Electric Power University (Hebei), 2007.
22	肖刚, 金保升, 刘继驰, 等. 烟气湿法脱硫用石灰石溶解速率定量分析[J]. 东南大学学报(自然科学版), 2008, 38(6): 1029-1033.
	Xiao G, Jin B S, Liu J C, et al. Quantitative analysis of limestone dissolution rate for flue gas wet desulfurization[J]. Journal of Southeast University (Natural Science Edition), 2008, 38(6): 1029-1033.
23	王坤. 逆流洗涤过程模型软件的研发[D]. 沈阳: 东北大学, 2011.
	Wang K. Development of countercurrent washing process model software [D]. Shenyang: Northeastern University, 2011.
24	钟秦. 燃煤烟气脱硫脱硝技术及工程实例[M]. 2版. 北京: 化学工业出版社, 2007: 85-86.
	Zhong Q. Desulfurization and Denitrification Technology and Engineering Example of Coal-fired Flue Gas[M]. 2nd ed. Beijing: Chemical Industry Press, 2007: 85-86.
25	Zhao Z. Particle trajectory model desulfurization spray tower used in numerical simulation of flue gas [J]. Journal of Sol-Gel Science and Technology, 2005, (33): 19-24.
26	严宣申, 王长富. 水溶液中离子平衡与化学反应[M]. 北京: 高等教育出版社, 1993: 63-66.
	Yan X S, Wang C F. Ion Balance and Chemical Reaction in Aqueous Solution[M]. Beijing: Higher Education Press, 1993: 63-66.
27	李振寰. 元素性质手册[M]. 石家庄: 河北人民出版社, 1984: 108+136.
	Li Z H. Element Nature Manual[M]. Shijiazhuang: Hebei People s Publishing House, 1984: 108+136.
28	周至祥, 段建中, 薛建明. 火电厂湿法烟气脱硫技术手册[M]. 北京: 中国电力出版社, 2006: 74-76.
	Zhou Z X, Duan J Z, Xue J M. Technical Manual for Wet Flue Gas Desulfurization in Thermal Power Plants[M]. Beijing: China Electric Power Press, 2006: 74-76.
29	王俊. 火力发电厂石灰石-石膏湿法脱硫系统优化运行研究[D]. 北京: 北京交通大学, 2010.
	Wang J. Research on optimal operation of limestone-gypsum wet desulfurization system in thermal power plant[D]. Beijing: Beijing Jiaotong University, 2010.

[1]	Xin YANG, Wen WANG, Kai XU, Fanhua MA. Simulation analysis of temperature characteristics of the high-pressure hydrogen refueling process [J]. CIESC Journal, 2023, 74(S1): 280-286.
[2]	Jiahao SONG, Wen WANG. Study on coupling operation characteristics of Stirling engine and high temperature heat pipe [J]. CIESC Journal, 2023, 74(S1): 287-294.
[3]	Siyu ZHANG, Yonggao YIN, Pengqi JIA, Wei YE. Study on seasonal thermal energy storage characteristics of double U-shaped buried pipe group [J]. CIESC Journal, 2023, 74(S1): 295-301.
[4]	Zhenghao JIN, Lijie FENG, Shuhong LI. Energy and exergy analysis of a solution cross-type absorption-resorption heat pump using NH₃/H₂O as working fluid [J]. CIESC Journal, 2023, 74(S1): 53-63.
[5]	Guoze CHEN, Dong WEI, Qian GUO, Zhiping XIANG. Optimal power point optimization method for aluminum-air batteries under load tracking condition [J]. CIESC Journal, 2023, 74(8): 3533-3542.
[6]	Zhaoguang CHEN, Yuxiang JIA, Meng WANG. Modeling neutralization dialysis desalination driven by low concentration waste acid and its validation [J]. CIESC Journal, 2023, 74(6): 2486-2494.
[7]	Chengze WANG, Kaili GU, Jinhua ZHANG, Jianxuan SHI, Yiwei LIU, Jinxiang LI. Sulfidation couples with aging to enhance the reactivity of zerovalent iron toward Cr(Ⅵ) in water [J]. CIESC Journal, 2023, 74(5): 2197-2206.
[8]	Laiming LUO, Jin ZHANG, Zhibin GUO, Haining WANG, Shanfu LU, Yan XIANG. Simulation and experiment of high temperature polymer electrolyte membrane fuel cells stack in the 1—5 kW range [J]. CIESC Journal, 2023, 74(4): 1724-1734.
[9]	Jieyuan ZHENG, Xianwei ZHANG, Jintao WAN, Hong FAN. Synthesis and curing kinetic analysis of eugenol-based siloxane epoxy resin [J]. CIESC Journal, 2023, 74(2): 924-932.
[10]	Huan ZHOU, Mengli ZHANG, Qing HAO, Si WU, Jie LI, Cunbing XU. Process mechanism and dynamic behaviors of magnesium sulfate type carnallite converting into kainite [J]. CIESC Journal, 2022, 73(9): 3841-3850.
[11]	Yujun MA, Xiangjun LIU. Theoretical studies of water recovery from flue gas by using ceramic membrane [J]. CIESC Journal, 2022, 73(9): 4103-4112.
[12]	Yifang DONG, Yingying YU, Xuegong HU, Gang PEI. Electric field effect on wetting and capillary flow characteristics in vertical microgrooves [J]. CIESC Journal, 2022, 73(7): 2952-2961.
[13]	Zihao QI, Wenqi ZHONG, Xi CHEN, Guanwen ZHOU, Xiaoliang ZHAO, Meijing XIN, Yi CHEN, Yongchang ZHU. Research on dynamic characteristics of cement raw meal decomposition process based on hybrid modeling [J]. CIESC Journal, 2022, 73(5): 2039-2051.
[14]	Cheng ZHANG, Lizhi PAN, Yuan LI. Fault detection and diagnosis method based on weighted statistical feature KICA [J]. CIESC Journal, 2022, 73(2): 827-837.
[15]	Ziyi CHI, Chengwei LIU, Yuling ZHANG, Xuegang LI, Wende XIAO. Reactor simulation and optimization for CO oxidative coupling to dimethyl oxalate reactions [J]. CIESC Journal, 2022, 73(11): 4974-4986.