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Prediction and optimization of back pressure of direct air-cooled unit based on data mining
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Yuhang LIU1, Yujiong GU1, 2, Qingshuai ZHENG1, Zihao LI1, Jiwei MA1, Guangxiong SONG1
Thermal Power Generation | 2023, 52(5) : 127 - 135
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Thermal Power Generation | 2023, 52(5): 127-135
• Thermal energy and science research •
Prediction and optimization of back pressure of direct air-cooled unit based on data mining
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Yuhang LIU1, Yujiong GU1, 2, Qingshuai ZHENG1, Zihao LI1, Jiwei MA1, Guangxiong SONG1
Affiliations
  • 1.School of Energy, Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China
  • 2.National Thermal Power Engineering Technology Research Center, North China Electric Power University, Beijing 102206, China
Published: 2023-05-25 doi: 10.19666/j.rlfd.202212181
Outline
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In order to realize the cold end optimization of direct air-cooled units, a cold end operation optimization method of air-cooled units is proposed based on the historical operation data of units and combined with data mining and deep learning algorithm. Firstly, the obtained historical operation data are screened in steady state and divided into working conditions. Combined with the Gaussian mixture model algorithm, the back pressure reference interval of the unit under multiple working conditions is determined. Then, the Spearman coefficient method is used to select the characteristic variables, and the back pressure prediction model of the direct air cooling unit is constructed in combination with the gated circulation unit. The back pressure optimization suggestions and early warning information are given by comparing the back pressure reference interval with the back pressure prediction value. Finally, the method is applied to a subcritical 300 MW air-cooled condensing steam unit. The results show that the back pressure optimization method proposed in this paper can give effective back pressure early warning information and realize optimal operation of cold end of the air-cooled unit.

direct air cooling unit  /  back pressure optimization  /  data mining  /  reference interval  /  neural network of GRU
刘宇航, 顾煜炯, 郑庆帅, 李子浩, 马吉伟, 宋光雄. 基于数据挖掘的直接空冷机组背压预测及优化. 热力发电, 2023 , 52 (5) : 127 -135 . DOI: 10.19666/j.rlfd.202212181
Yuhang LIU, Yujiong GU, Qingshuai ZHENG, Zihao LI, Jiwei MA, Guangxiong SONG. Prediction and optimization of back pressure of direct air-cooled unit based on data mining[J]. Thermal Power Generation, 2023 , 52 (5) : 127 -135 . DOI: 10.19666/j.rlfd.202212181
Funding
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  • National Key Research and Development Program(2017YFB0603904-4)
Appendix
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Year 2023 volume 52 Issue 5
424
142
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Article Info
doi: 10.19666/j.rlfd.202212181
  • Receive Date：2022-12-05
  • Online Date：2026-01-23
  • Published：2023-05-25
Article Data
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History
  • Received：2022-12-05
Funding
National Key Research and Development Program(2017YFB0603904-4)
Affiliations
    1.School of Energy, Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China
    2.National Thermal Power Engineering Technology Research Center, North China Electric Power University, Beijing 102206, China
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https://castjournals.cast.org.cn/joweb/rlfd/EN/10.19666/j.rlfd.202212181
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