经济—碳排放权衡下绿氢耦合煤制甲醇系统的两阶段随机优化

刘雨洁; 郑俊杰; 张玉婷; 周文晋; 赵志仝; 张玮

doi:10.11949/0438-1157.20260697

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经济—碳排放权衡下绿氢耦合煤制甲醇系统的两阶段随机优化

智能过程工程 | 更新时间：2026-08-12

- 经济—碳排放权衡下绿氢耦合煤制甲醇系统的两阶段随机优化
- Two-stage stochastic optimization of a green-hydrogen-coupled coal-to-methanol system under economic–carbon emission trade-offs
- 化工学报 2026年
- 作者机构：
  
  太原理工大学化学与化工学院，山西太原 030024
- 作者简介：
  
  刘雨洁（2005-），女，本科生，13509739210@163.com
  郑俊杰（2003-），男，本科生，zhengjunjie3025@link.tyut.edu.cn
  周文晋（1994-），男，博士，讲师，zhouwenjin@tyut.edu.cn
- 基金信息：
  
  国家自然科学基金项目(22178241;22508279);山西省基础研究计划(202503021211012;202503021212047)
- DOI：10.11949/0438-1157.20260697
  中图分类号： TQ 021.8
- 收稿：2026-05-20，
  
  修回：2026-08-11，
  
  录用：2026-08-12，
- 稿件说明：
移动端阅览
刘雨洁, 郑俊杰, 张玉婷, 等. 经济—碳排放权衡下绿氢耦合煤制甲醇系统的两阶段随机优化[J/OL]. 化工学报, 2026.

LIU Yujie, ZHENG Junjie, ZHANG Yuting, et al. Two-stage stochastic optimization of a green-hydrogen-coupled coal-to-methanol system under economic–carbon emission trade-offs[J/OL]. CIESC Journal, 2026.
刘雨洁, 郑俊杰, 张玉婷, 等. 经济—碳排放权衡下绿氢耦合煤制甲醇系统的两阶段随机优化[J/OL]. 化工学报, 2026. DOI： 10.11949/0438-1157.20260697.

LIU Yujie, ZHENG Junjie, ZHANG Yuting, et al. Two-stage stochastic optimization of a green-hydrogen-coupled coal-to-methanol system under economic–carbon emission trade-offs[J/OL]. CIESC Journal, 2026. DOI： 10.11949/0438-1157.20260697.

摘要

煤制甲醇是煤化工碳排放的重要来源，将绿氢注入合成环节替代水气变换灰氢是其深度脱碳的关键路径。然而，风光出力的随机波动与化工稳态连续进料的刚性需求存在天然矛盾，实现绿氢耦合煤制甲醇（green hydrogen coupled with coal-to-methanol，GH-CTM）的经济性与碳减排的权衡尚缺乏定量优化框架。在此背景下，本文构建了GH-CTM系统的两阶段随机优化模型，通过数据驱动的方法确定典型周场景并建立煤制甲醇关键变量的代理模型，同步优化绿氢设备容量配置与系统逐时运行调度。案例研究表明，年产98.25万吨甲醇的经济最优解为非绿氢耦合模式，年化净利润为7.44亿元，直接碳排放强度为0.79 tCO

/tMeOH，系统切换为绿氢耦合模式的直接碳排放强度为0.7 tCO

/tMeOH。此外，在甲醇售价提升、风光及电解槽设备投资成本下降等市场与技术条件改善下，GH-CTM系统展现出兼顾经济性与深度碳减排的潜力。

Abstract

Coal-to-methanol (CTM) processes are major contributors to carbon emissions in the coal chemical industry. Injecting green hydrogen into the synthesis stage to replace gray hydrogen derived from the water-gas shift process is a key pathway for deep decarbonization. However

an inherent contradiction exists between the stochastic fluctuations of wind and solar power and the rigid demand for steady-state continuous feeding in chemical production. Currently

a quantitative optimization framework to balance the economic viability and carbon reduction of the green-hydrogen-coupled coal-to-methanol (GH-CTM) system is still lacking. In this context

a two-stage stochastic optimization model for the GH-CTM system was developed. A data-driven method was employed to determine typical weekly scenarios

and surrogate models for key variables in the CTM process were established to simultaneously optimize the capacity configuration of green hydrogen equipment and the hourly operational scheduling of the system. Case studies indicate that

for a plant with an annual methanol production capacity of 982.5 kt

the economically optimal solution does not integrate green hydrogen

yielding an annualized net profit of CNY 744 million and a direct CO₂ emission intensity of 0.79 t CO₂/t MeOH. The system begins to integrate green hydrogen when the direct CO₂ emission intensity limit is tightened to 0.70 t CO₂/t MeOH. Furthermore

under improved market and technical conditions—such as increased methanol prices and decreased investment costs for wind

solar

and electrolyzer equipment—the GH-CTM system demonstrates significant potential for achieving both economic efficiency and deep carbon emission reduction.

关键词

Keywords

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