基于遗传算法-综合计算法的生物质热解气化优化分析

doi:10.11949/0438-1157.20210030

化工学报 ›› 2021, Vol. 72 ›› Issue (9): 4910-4920.DOI: 10.11949/0438-1157.20210030

基于遗传算法-综合计算法的生物质热解气化优化分析

朱轶林^1,²(),张新敬^1,²,徐玉杰^1,^2,³,丁捷^1,²,郭欢^1,²,陈海生^1,^2,³()

^1.中国科学院工程热物理研究所，北京 100190
^2.中国科学院大学工程科学学院，北京 100049
^3.国家能源大规模物理储能技术（毕节）研发中心，贵州毕节 551712

收稿日期:2021-01-08 修回日期:2021-04-06 出版日期:2021-09-05 发布日期:2021-09-05
通讯作者: 陈海生
作者简介:朱轶林(1989—)，男，博士，助理研究员，zhuyilin@iet.cn
基金资助:
国家重点研发计划项目(2018YFE0117300);贵州省大规模物理储能技术研发平台能力建设项目(黔科合服企[2019]4011);分布式冷热电联供系统北京市重点实验室项目;中国科学院大学工程科学高精尖学科建设博士后资助项目

Analysis and optimization of biomass pyrolysis and gasification based on genetic algorithm-comprehensive calculation method

Yilin ZHU^1,²(),Xinjing ZHANG^1,²,Yujie XU^1,^2,³,Jie DING^1,²,Huan GUO^1,²,Haisheng CHEN^1,^2,³()

^1.Institute of Engineering Thermophysic, Chinese Academy of Sciences, Beijing 100190, China
^2.Institute of Engineering Science, University of Chinese Academy of Sciences, Beijing 100049, China
^3.National Energy Large Scale Energy Storage Technologies R&D Center (Bijie), Bijie 551712, Guizhou, China

Received:2021-01-08 Revised:2021-04-06 Online:2021-09-05 Published:2021-09-05
Contact: Haisheng CHEN

摘要/Abstract

摘要：

生物质热解气化可实现碳基可再生能源的高效清洁利用。为准确预测生物质热解气化产率分布，贴合生物质热解气化真实转化过程，由生物质热解气化实测数据通过遗传算法（genetic algorithm， GA）对综合计算法模型进行改进，按照综合计算法中热解段和固定碳气化反应段建立Aspen Plus模型。结果表明：在GA-综合计算法中，稻壳在热解段CO₂的氧为干基氧含量的32.02%，焦油产率为挥发分的8.32%，平均热解组分误差为8.53%，平均合成气组分误差为5.37%；基于GA-综合计算法的Aspen Plus模型，热解过程组分和气化段固定碳转化率由GA-综合计算法得出，实现了GA-综合计算法和流程模拟的复合，其合成气模拟值与实验值接近，较好地反映生物质热解气化流程，为生物质热解气化产率分布及流程参数优化提供指导。

关键词: 生物质, 热解, 气化, 遗传算法, 综合计算法, Aspen Plus

Abstract:

Biomass pyrolysis and gasification can realize the efficient and clean utilization of carbon-based renewable energy. In order to predict yield distribution of compositions and achieve the closest of biomass pyrolysis and gasification, the comprehensive calculation method has been improved through genetic algorithm (GA) method with tested data of biomass pyrolysis and gasification. Aspen Plus model has been established consisting of pyrolysis stage and gasification reactions of fixed carbon according to GA-comprehensive calculation method. The results show that the optimum ratio coefficient of O for husk (dry basis) transferring to CO₂ equals 32.02% in the GA-comprehensive calculation method, and the optimized yield ratio for tar (R_tar) is 8.32% of the volatile with the mean pyrolysis component error of 8.53%, while the mean gasification component error of 5.37%. As for Aspen Plus model based on GA-comprehensive calculation method, the yield distribution of gasification components and conversion rate of fixed carbon in gasification process are calculated by GA-comprehensive calculation method, enhancing the computing reliability through the combination of theoretical calculation and process simulation. The simulation values of gasification gas compositions have good agreement with experimental values, which reveals pyrolysis stage and gasification process clearly. Generally, the proposed innovative model contributes to the prediction of component distribution of biomass pyrolysis and gasification, along with parameters optimization of gasification system.

Key words: biomass, pyrolysis, gasification, genetic algorithm, comprehensive calculation method, Aspen Plus

中图分类号:

TK 6

朱轶林, 张新敬, 徐玉杰, 丁捷, 郭欢, 陈海生. 基于遗传算法-综合计算法的生物质热解气化优化分析[J]. 化工学报, 2021, 72(9): 4910-4920.

Yilin ZHU, Xinjing ZHANG, Yujie XU, Jie DING, Huan GUO, Haisheng CHEN. Analysis and optimization of biomass pyrolysis and gasification based on genetic algorithm-comprehensive calculation method[J]. CIESC Journal, 2021, 72(9): 4910-4920.

图/表 10

表1 两种模型热解段产物产率输入条件对比

Table 1 Comparison of input values of pyrolysis composition yields in different models

No.	综合计算法	GA-综合计算法
1	燃料中约CR₁=0.45的O与当量的H生成热解水	CR₁=0.2~0.45
2	燃料中约CR₂=0.3的O转变为CO₂	CR₂=0.2~0.5
3	燃料中约CR₃=0.2的H转变为CH₄	CR₃=0.15~0.25
4	3%的H与当量的C生成C₂H₄	不变
5	焦油产率约为挥发分的R_tar=0.1,且焦油含量中的C、H、O和N的物质的量之比为66∶78∶7.5∶1	焦油分子组成为CH_1.12O_0.19，R_tar=0.05~0.1
6	燃料中所有的N都转入生物质干馏气中	不变
7	燃料中20%的S进入灰渣，80%的S与当量的H以H₂S形式进入生物质气中	不变
8	剩余的H都以游离状态转入生物质干馏气中	不变
9	剩余的O与当量的C以CO的形式转入生物质干馏气中	不变

图1 生物质热解气化GA-综合计算法流程

Fig.1 Flowchart of GA-comprehensive calculation model for biomass pyrolysis and gasification

图2 生物质热解气化基于综合计算法的Aspen Plus模型

Fig.2 Aspen Plus model of biomass pyrolysis and gasification

表2 生物质原料的工业分析和元素分析

Table 2 Proximate and ultimate analysis of biomass samples

原料	工业分析/%(收到基)				热值Q_ar,net/(MJ/kg)	元素分析/%(干燥基)
原料	挥发分V_ar	固定碳Fc_ar	灰含量Ash_ar	水分M_ar	热值Q_ar,net/(MJ/kg)	N_d	C_d	S_d	H_d	O_d
稻壳	63.7	12.6	16.9	6.8	14.35	0.54	40.34	0.107	5.26	35.62
白杨木	77.1	9.5	3	10.4	19.18	0.67	55.58	0.33	6.47	33.59

图3 稻壳热解模型值与实验值对比

Fig.3 Comparison of simulated results and experimental values for husk pyrolysis

图4 生物质气化模型与实验值对比

Fig.4 Comparison of simulated results and experimental values for husk and poplar gasification

图5 综合平衡常数对稻壳干合成气组分、固定碳转化成CO摩尔系数和C/N特征值的影响

Fig.5 Effect of comprehensive equivalent constant on gasification compositions, transferring coefficient of fixed carbon for CO and characteristic value C/N

图6 综合平衡常数对生物质合成气评价指标的影响

Fig.6 Effect of comprehensive equivalent constant on gasification evaluating values

图7 固定碳转化率对干合成气组分、固定碳转化成CO摩尔系数和C/N特征值的影响

Fig.7 Effect of conversion ratio of fixed carbon on gasification compositions, transferring coefficient of fixed carbon for CO and characteristic value C/N

图8 固定碳转化率对生物质合成气评价指标的影响

Fig.8 Effect of conversion ratio of fixed carbon on gasification evaluating values

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基于遗传算法-综合计算法的生物质热解气化优化分析

Analysis and optimization of biomass pyrolysis and gasification based on genetic algorithm-comprehensive calculation method

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