基于㶲分析的陈化稻谷全粉碎发酵工艺节能优化

doi:10.3969/j.issn.1673-5854.2023.03.004

摘要/Abstract

摘要：

基于Aspen Plus设计并建立了处理量为40万吨/年的陈化稻谷全粉碎发酵工艺流程。采用分析法对工艺的热力学性能进行了研究, 明确㶲损失来源并进行了优化改造, 研究结果表明: 优化前工艺㶲损失为106 477.62 kW, 优化后损失为79 108.84 kW, 经优化㶲损失减少27 368.78 kW, 㶲效率提高了5.97%。生产1 t燃料乙醇总能耗为1 424.69 MJ, 消耗原料4.25 t, 耗水量和废水量分别为2.99和0.37 t, 在满足生产过程中蒸汽用量需求的基础上产生电力15.03 MW, 系统消耗1.29 MW。通过对优化前后工艺进行经济性分析发现, 优化后的工艺经济性较好, 工艺优化后公用工程的费用减少了52.76%, 总成本降低了49.73元/吨, 每年的净利润升高了2.85%。

关键词: 陈化稻谷, 燃料乙醇, 流程模拟, 能耗, 㶲分析

Abstract:

Based on Aspen Plus, a total comminution fermentation process of aged rice with a capacity of 4 hundred thousand tons per year was designed and established. Exergy analysis method was used to study the thermodynamic properties of the process, and the source of exergy loss was clarified and optimized. The results showed that exergy loss was 106 477.62 kW before optimization, and the exergy loss was 79 108.84 kW after optimization. Meanwhile, the exergy loss was reduced by 27 368.78 kW and the exergy efficiency increased by 5.97% after optimization. The total energy consumption of 1 ton fuel ethanol production was 1 424.69 MJ, the raw material consumption was 4.25 ton, and the consumptions of water and wastewater were 2.9 and 0.37 ton, respectively. On the basis of meeting the demand of steam consumption in the production process, the power generation was 15.03 MW, and the system consumption was 12.9 MW. Through the economic analysis of the processes before and after optimization, the optimized process had better economy. The cost of public works decreased by 52.76%, the total cost decreased by 49.73 yuan per ton and the annual net profit increased by 2.85% after process optimization.

Key words: aged rice, fuel ethonal, simulation, energy consumption, exergy analysis

中图分类号:

TQ35
TQ920.6

刘梦婷, 陈圆圆, 刘红, 李一馨, 张青瑞. 基于㶲分析的陈化稻谷全粉碎发酵工艺节能优化[J]. 生物质化学工程, 2023, 57(3): 23-30.

Mengting LIU, Yuanyuan CHEN, Hong LIU, Yixin LI, Qingrui ZHANG. Energy Saving Optimization of Total Comminution Fermentation Process of Aged Rice Based on Exergy Analysis[J]. Biomass Chemical Engineering, 2023, 57(3): 23-30.

图/表 8

图1

图2

表1

表2

图3

表3

表4

表5

参考文献 21

1	姜新春, 区镜深, 李凡, 等. 玉米燃料乙醇低能耗工业生产新工艺[J]. 生物质化学工程, 2021, 55 (4): 7- 13. doi: 10.3969/j.issn.1673-5854.2021.04.002
2	YUAN X C , CHEN X X , SHEN G G , et al. Densifying lignocellulosic biomass with sulfuric acid provides a durable feedstock with high digestibility and high fermentability for cellulosic ethanol production[J]. Renewable Energy, 2022, 182, 377- 389. doi: 10.1016/j.renene.2021.10.015
3	LI J , ZHAO R Y , XU Y J , et al. Fuel ethanol production from starchy grain and other crops: An overview on feedstocks, affecting factors and technical advances[J]. Renewable Energy, 2022, 188, 223- 239. doi: 10.1016/j.renene.2022.02.038
4	赵霞, 陶亚萍, 胡迪. 粮食安全视角下我国粮食产业国际竞争力的提升路径[J]. 农业经济问题, 2021, 497 (5): 107- 119.
5	苗春雨, 张茂芬, 陈光伟. 陈化水稻掺混生产燃料乙醇的工艺[J]. 化工管理, 2021, (4): 169- 170.
6	HUMBIRD D, DAVIS R, TAO L, et al. Process design and economics for conversion of lignocellulosic biomass to ethanol[R]. Golden, Colorado: National Renewable Energy Laboraltory, 2011.
7	AKPOMIEMIE M O , SMITH R . Cost-effective strategy for heat exchanger network retrofit[J]. Energy, 2018, 146, 82- 97. doi: 10.1016/j.energy.2017.09.005
8	晁彬. 基于Aspen Plus平台的酵母发酵工艺流程模拟[D]. 北京: 北京化工大学, 2018.
9	王丽, 李美书, 李坚, 等. 以木薯为原料制无水乙醇精馏工段节能优化[J]. 广东石油化工学院学报, 2016, 26 (1): 12- 16.
10	RENON H . Local composition in thermodynamic excess functions for liquid mixtures[J]. Aiche Journal, 1968, 14 (1): 135- 144. doi: 10.1002/aic.690140124
11	王灿, 潘忠, 许克家, 等. 陈稻谷全粉碎技术加工燃料乙醇的现状与展望[J]. 当代化工, 2019, 48 (1): 193- 195.193-195, 201
12	KANG Q , BAEYENS J , TAN T , et al. A novel sintered metal fiber microfiltration of bio-ethanol fermentation broth[J]. Korean Journal of Chemical Engineering, 2015, 32 (8): 1625- 1633.
13	武国庆, 吴德旺, 沈乃东, 等. 超贮稻谷半连续浓醪发酵生产燃料乙醇工艺研究[J]. 中国酿造, 2021, 40 (6): 97- 101.
14	XIAO F . Energy Saving Principle and Technology in Chemical Engineering, Version 1[M]. Beijing: Chemical Industry Press, 2009.
15	HAN X Q , LIU M , WU K L , et al. Exergy analysis of the flue gas pre-dried lignite-fired power system based on the boiler with open pulverizing system[J]. Energy, 2016, 106, 285- 300.
16	KOTAS T J . Exergy concepts for thermal plant: first of two papers on exergy techniques in thermal plant analysis[J]. International Jourmal of Heat and Fluid Flow, 1980, 2 (3): 105- 114.
17	QUEROL E , GONZALEZREGUERAL B , PEREZBENEDITO J L . Exergy Concept and Determination[M]. Berlin: Springer, 2013.
18	WALL G . Exergy, Ecology, Democracy[M]. Bucaramanga: Exergetics, 2009.
19	HEPBASLI A . A key review on exergetic analysis and assessment of renewable energy resources for a sustainable future[J]. Renewable and Sustainable Energy Reviews, 2008, 12, 593- 661.
20	王康, 潘忠, 李永恒, 等. 陈化水稻燃料乙醇全生命周期净能量分析[J]. 生物加工过程, 2019, 17 (4): 359- 364.
21	KANG Q , HUYBRECHTS J , BART V D B , et al. Hydrophilic membranes to replace molecular sieves in dewatering the bio-ethanol/water azeotropic mixture[J]. Separation and Purification Technology, 2014, 136, 144- 149.

模块 modules	设备 unit	名称 name	模块 modules	设备 unit	名称 name
Sep	MILL MOLCSIVE	粉碎机 crusher 分子筛 molecular sieve	RadFrac	CRUDE	粗馏塔 crude distillation column
Flash2	B4，B9	闪蒸罐 flash tank	RadFrac	RECTIFY	精馏塔 rectifying column
	DRYER	醪液干燥器 mash solution dryer	Mixer	B2，B3	混合器 mixer
	B19	气液分离器 gas-liquid separator	Mixer	B30	蒸汽喷射器 steam ejector
	B7	锅炉 boiler	Rstoic	FERMENT	糖化发酵罐 saccharifying fermenter
SSplit	B8，B17，B22	压滤机 filter press		ANAEROBI	厌氧消化罐 anaerobic digestion tank
Heater	B5，B24，B10	冷却器 cooler		AEROBIC	好氧消化罐 aerobic digestion tank
	B26，B28，B29	预热器 preheater		COMBUSTO	燃烧室 combustion chamber
	B14	冷凝器 condenser	FSplit	B11	热量分配器 heat separator
	B1	调浆水预热器 mixing water preheater	Compr	B16	蒸汽涡轮机 steam turbines

共沸物 azeotrope	质量分布 mass distribution/%		共沸点 azeotropy point/℃
共沸物 azeotrope	模拟值 simulation value	实验值 experiment value	模拟值 simulation value	实验值 experiment value
乙醇 ethanol	95.56	95.57	78.19	78.13
水 water	4.44	4.43	78.19	78.13

工段 section	设备 unit	㶲损失/kW exergy destruction
A100	MILL	551.39
A200	B1	2 853.65
	B28	3 028.49
	B5	756.38
	FERMENT	1 119.27
A300	DRYER	1 258.44
	B9	4 953.48
	CRUDE	10 974.9
	RECTIFY	6 485.51
	MOLCSIVE	2 794.82
A400	B24	1 431.26
	ANAEROBI	3 401.65
	AEROBIC	6 587.48
A500	B26	904.23
	B11	42 520.85
	B10	1 126.13
	B16	3 452.83
	B14	2 928.85

项目 items	输入㶲/kW input exergy	输出㶲/kW output exergy	㶲损失/kW exergy destruction	㶲效率/% exergy efficiency
优化前工艺 process before optimization	258 335.21	151 857.60	106 477.62	58.78
优化后工艺 process after optimization	224 411.88	145 303.04	79 108.84	64.75

工段 section	能量消耗 energy consumption/(MJ·t^-1)		能量产出 energy output/(MJ·t^-1)
工段 section	优化前 before optimization	优化后 after optimization	优化前 before optimization	优化后 after optimization
A100	169.05	169.06
A200	3 075.64	136.46
A300	10 889.12	1 042.11
A400	3.58	3.58
A500	75.65	73.48	6 198.26	4 599.20