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Intelligent transformation architecture and key technologies of wet flue gas desulfurization system
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Ruilian LI1, Deliang ZENG1, Jizhen LIU1, Yong HU1, Yaokui GAO2, Boyu PING1, Yan XIE1
Thermal Power Generation | 2023, 52(7) : 74 - 86
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Thermal Power Generation | 2023, 52(7): 74-86
Intelligent management technologies for coal-fired power plants
Intelligent transformation architecture and key technologies of wet flue gas desulfurization system
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Ruilian LI1, Deliang ZENG1, Jizhen LIU1, Yong HU1, Yaokui GAO2, Boyu PING1, Yan XIE1
Affiliations
  • 1.School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
  • 2.Xi'an Thermal Power Research Institute Co., Ltd., Xi'an 710054, China
Published: 2023-07-25 doi: 10.19666/j.rlfd.202305060
Outline
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The intelligent retrofit of coal-fired power generation units is an inevitable choice for improving energy efficiency and promoting green industrial transformation. Based on practical requirements and engineering perspectives, this article designs the overall framework and key technologies for the intelligent retrofitting of wet flue gas desulfurization systems. First, the structural components of the intelligent control system (ICS) network framework are discussed. Next, based on the ICS framework, an optimized control strategy combining information-physical fusion models and advanced control algorithms is designed, as well as an optimized control strategy for the absorption tower pH value based on the direct energy balance (DEB) approach. Simultaneously, the information-physical fusion optimization results guide the analysis of the intelligent evaluation system. Using data twin technology and mechanism models, intelligent early warning and fault diagnosis for the system are achieved. By analyzing typical faults, an expert system is established, combined with data-driven techniques for real-time fault tracking. Finally, the article points out that a visualization-based human-machine interaction system is used for real-time display of desulfurization system indicators, constructing an integrated desulfurization system that combines ICS, digital twins, machine learning and visualization. This provides a basis for realizing a self-optimizing, self-learning, self-recovering, self-organizing and self-adaptive intelligent desulfurization system.

intelligent desulfurization  /  ICS  /  DEB control strategy  /  information-physical fusion  /  digital twin  /  visual human-machine interaction
Ruilian LI, Deliang ZENG, Jizhen LIU, Yong HU, Yaokui GAO, Boyu PING, Yan XIE. Intelligent transformation architecture and key technologies of wet flue gas desulfurization system[J]. Thermal Power Generation, 2023 , 52 (7) : 74 -86 . DOI: 10.19666/j.rlfd.202305060
  • Major Project of National Natural Science Foundation of China(61833011)
Year 2023 volume 52 Issue 7
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Article Info
doi: 10.19666/j.rlfd.202305060
  • Receive Date:2023-05-09
  • Online Date:2026-01-26
  • Published:2023-07-25
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  • Received:2023-05-09
Funding
Major Project of National Natural Science Foundation of China(61833011)
Affiliations
    1.School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
    2.Xi'an Thermal Power Research Institute Co., Ltd., Xi'an 710054, 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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