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Operation optimization of dry-wet joint cooling system of generator set based on MLP-MINLP
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Yao MA, Yue CAO, Ranjing CHEN, Fengqi SI
Thermal Power Generation | 2025, 54(3) : 121 - 130
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Thermal Power Generation | 2025, 54(3): 121-130
Thermal energy science research
Operation optimization of dry-wet joint cooling system of generator set based on MLP-MINLP
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Yao MA, Yue CAO, Ranjing CHEN, Fengqi SI
Affiliations
  • Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, Southeast University, Nanjing 210096, China
Published: 2025-03-25 doi: 10.19666/j.rlfd.202407154
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In the context of achieving “dual-carbon” goals, power units function as adaptable power sources for integrating new energy sources, posing significant challenges to their power generation flexibility. The dry-wet joint cooling system plays a pivotal role in ensuring the safe and stable operation of power units. Therefore, there is an urgent need to optimize the operational strategy of the dry-wet joint cooling system to enhance its flexibility and economic efficiency. Focusing on the dry-wet joint cooling system of a 660 MW generator set, a multi-layer perceptron (MLP) neural network model has been established to predict the outlet temperature of the cooling water. A mixed integer nonlinear programming (MINLP) model is formulated and linearized based on actual operating condition constraints. By solving the MLP-MINLP optimization model, the optimal operation strategy for variable-frequency fans in each operating condition of dry-wet joint cooling system is determined, successfully reducing its power consumption. The results indicate that, after optimizing the configuration of variable-frequency fans, there is a significant reduction in total power by approximately 11.16%, and implementing different frequency operations for variable-frequency fans can reduce total power by about 3.62%~5.38% in a limited manner. The MLP-MINLP optimization model can achieve precise and low-power operation of dry-wet joint cooling system, offering a viable solution for optimizing dry-wet joint cooling systems.

dry-wet joint cooling system  /  variable-frequency fan  /  multilayer perceptron  /  mixed integer nonlinear planning
Yao MA, Yue CAO, Ranjing CHEN, Fengqi SI. Operation optimization of dry-wet joint cooling system of generator set based on MLP-MINLP[J]. Thermal Power Generation, 2025 , 54 (3) : 121 -130 . DOI: 10.19666/j.rlfd.202407154
  • National Key Research and Development Program(2022YFB4100700)
Year 2025 volume 54 Issue 3
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doi: 10.19666/j.rlfd.202407154
  • Receive Date:2024-07-04
  • Online Date:2026-03-06
  • Published:2025-03-25
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  • Received:2024-07-04
Funding
National Key Research and Development Program(2022YFB4100700)
Affiliations
    Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, Southeast University, Nanjing 210096, 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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