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Dynamic modeling and control of liquid ammonia gasification system based on mechanism and data
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Yuan LIU1, Liming CUI2, Wei CHU3, Mo ZHOU3, Zijian CUI3, Yinsong WANG1
Thermal Power Generation | 2025, 54(8) : 72 - 83
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Thermal Power Generation | 2025, 54(8): 72-83
Multi-energy collaborative optimization of green hydrogen and green ammonia
Dynamic modeling and control of liquid ammonia gasification system based on mechanism and data
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Yuan LIU1, Liming CUI2, Wei CHU3, Mo ZHOU3, Zijian CUI3, Yinsong WANG1
Affiliations
  • 1.Department of Automation, North China Electric Power University, Baoding 071003, China
  • 2.Shenhua Group Co., Ltd., Beijing 100011, China
  • 3.Yantai Longyuan Power Technology Co., Ltd., Yantai 264006, China
Published: 2025-08-25 doi: 10.19666/j.rlfd.202505091
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Ammonia, as a low-carbon fuel, has important application prospects in the field of industrial combustion. However, the dynamic characteristics of liquid ammonia gasification process are complex, and conventional mechanism models are difficult to meet high-precision control requirements. To address the problem of unstable control caused by insufficient modeling accuracy in the liquid ammonia gasification process in ammonia combustion systems, a dynamic modeling method that combines mechanism with data fusion is proposed. By establishing a nonlinear mechanism model based on thermodynamic laws, and combining with a data-driven model based on recursive fuzzy C-means (RFCM) clustering and recursive least square (RLS) algorithm, a hybrid dynamic model with adaptive weight optimization is constructed. On this basis, decoupling control strategies are developed to achieve precise control of the gasification systems. Experimental verification shows that, the proposed model significantly improves the prediction accuracy of the gasification process, and the decoupling control scheme based on this dynamic model achieves stable ammonia supply, verifying the effectiveness and engineering practicality of the dynamic model that integrates mechanism and data for the control system. This method provides an effective solution for intelligent control of ammonia fuel combustion systems and has promotional value for the engineering application of clean energy technology.

coal-ammonia coupled combustion  /  liquid ammonia gasification  /  dynamic modeling  /  RFCM-RLS algorithm  /  decoupling control  /  simulation analysis
Yuan LIU, Liming CUI, Wei CHU, Mo ZHOU, Zijian CUI, Yinsong WANG. Dynamic modeling and control of liquid ammonia gasification system based on mechanism and data[J]. Thermal Power Generation, 2025 , 54 (8) : 72 -83 . DOI: 10.19666/j.rlfd.202505091
  • National Science and Technology Infrastructure Project(GJNY-2023-9)
Year 2025 volume 54 Issue 8
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Article Info
doi: 10.19666/j.rlfd.202505091
  • Receive Date:2025-05-23
  • Online Date:2026-03-05
  • Published:2025-08-25
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History
  • Received:2025-05-23
Funding
National Science and Technology Infrastructure Project(GJNY-2023-9)
Affiliations
    1.Department of Automation, North China Electric Power University, Baoding 071003, China
    2.Shenhua Group Co., Ltd., Beijing 100011, China
    3.Yantai Longyuan Power Technology Co., Ltd., Yantai 264006, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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