Process design and performance evaluation for carbon dioxide hydrogenation to methanol

MENG Wenliang; LI Yuhao; TIAN Haifeng; TANG Xiaohua; GUO Xiaojun; WANG Yuanyuan; ZHA Fei

doi:10.11949/0438-1157.20260063

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Process design and performance evaluation for carbon dioxide hydrogenation to methanol

更新时间：2026-06-03

- Process design and performance evaluation for carbon dioxide hydrogenation to methanol
- CIESC Journal Pages: 1-12(2026)
- 作者机构：
  
  1.西北师范大学化学化工学院，甘肃兰州 730070
  2.中国石油天然气股份有限公司兰州石化分公司，甘肃兰州 730060
- 作者简介：
- 基金信息：
- DOI：10.11949/0438-1157.20260063
  CLC： TQ 09
- Received：15 January 2026，
  
  Revised：2026-05-31，
  
  Online First：03 June 2026，
- 稿件说明：
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孟文亮, 李宇豪, 田海锋, 唐小华, 郭效军, 王园园, 查飞. 二氧化碳加氢合成甲醇工艺设计与性能评价[J]. 化工学报,

MENG Wenliang, LI Yuhao, TIAN Haifeng, TANG Xiaohua, GUO Xiaojun, WANG Yuanyuan, ZHA Fei. Process design and performance evaluation for carbon dioxide hydrogenation to methanol[J]. CIESC Journal,
孟文亮, 李宇豪, 田海锋, 唐小华, 郭效军, 王园园, 查飞. 二氧化碳加氢合成甲醇工艺设计与性能评价[J]. 化工学报, DOI： 10.11949/0438-1157.20260063

MENG Wenliang, LI Yuhao, TIAN Haifeng, TANG Xiaohua, GUO Xiaojun, WANG Yuanyuan, ZHA Fei. Process design and performance evaluation for carbon dioxide hydrogenation to methanol[J]. CIESC Journal, DOI： 10.11949/0438-1157.20260063

摘要

加氢合成甲醇工艺既能实现CO

的资源化利用，还可将波动性、间歇性的风光电转化为易于储运的甲醇，实现长周期储能。该工艺通常包括CO

捕集、电解水制氢和甲醇合成三个子系统，为了研究三系统耦合特性与工艺性能间的构效关系，采用多参数协同调控实现CO

加氢合成甲醇工艺的优化设计。首先，在Aspen Plus软件中建立各子系统的模型，并进行模型准确性验证；然后，采用最优拉丁超立方抽样方法，批量计算得到不同决策变量组合下工艺能量消耗和甲醇产量模拟数据。利用响应面方法构建目标函数与决策变量之间的对应关系。运用非支配排序遗传算法（NSGA-II）对甲醇产量和工艺能耗进行多目标优化；最后，以能量效率和年总成本（TAC）为指标对CO

加氢合成甲醇工艺进行技术经济性能评价。结果表明：经多目标优化权衡，甲醇产量为1477.03 kg/h，工艺能耗为40.44 MW，全局能量集成后工艺能量效率从40.17%提升至51.98%；当电价低至0.1元/kWh时，项目投资回收期缩短至3.25年，TAC为1743.54元/吨。该研究对于CO

加氢合成甲醇工艺设计和优化具有重要的指导意义。

Abstract

The process of CO

hydrogenation to methanol not only enables the resource utilization of CO

but also converts fluctuating and intermittent wind and solar power into easily storable methanol

thereby achieving long‑cycle energy storage. This process typically consists of three subsystems: CO

capture

water electrolysis for hydrogen production

and methanol synthesis. To investigate the structure‑performance relationship between the coupling characteristics of the three systems and the process performance

this study employs multi‑parameter collaborative regulation for the optimal design of the CO

‑to‑methanol process. First

simulation models for each subsystem were developed in Aspen Plus software and model validation. Then

using the optimal Latin hypercube sampling method

batch generate simulation data of process energy consumption and methanol yield under different combinations of decision variables based on computational and simulation software. The response surface methodology was employed to establish the functional correspondence between target variables and decision variables. A multi‑objective optimization of methanol production and process energy consumption was performed using the Non‑dominated Sorting Genetic Algorithm II (NSGA‑II). Finally

the techno‑economic performance of the

‑to‑methanol process was evaluated in terms of energy efficiency and total annual cost (TAC). The results show that after optimization

the methanol production reached 1477.03 kg/h and the process energy consumption was 40.44 MW. Following global heat integration

the process energy efficiency reached 51.98%. When the electricity price is 0.1 CNY/kWh

the payback period is shortened to 3.25 years

and the TAC is 1743.54 CNY/t. This research provides important guidance for the design and optimization of CO

‑to‑methanol processes.

关键词

Keywords

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