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NOx emission prediction of coal-gas hybrid combustion plant based on the combination of attention mechanism model
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Hong QIAN1, 2, Jun ZHANG1, Bangzhi XU1
Thermal Power Generation | 2023, 52(8) : 137 - 145
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Thermal Power Generation | 2023, 52(8): 137-145
• Power generation technology forum •
NOx emission prediction of coal-gas hybrid combustion plant based on the combination of attention mechanism model
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Hong QIAN1, 2, Jun ZHANG1, Bangzhi XU1
Affiliations
  • 1.School of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China
  • 2.Shanghai Key Laboratory of Power Station Automation Technology, Shanghai 200072, China
Published: 2023-08-25 doi: 10.19666/j.rlfd.202212226
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Aiming at the problem of inaccurate prediction of NOx emission concentration when the current coal-gas boiler gas mixture is uncertain and changing, a combined online prediction method based on attention mechanism is proposed. First, the characteristic variables of the model are determined by combining the maximum information coefficient method with the Pearson correlation coefficient method; Secondly, vector autoregressive(VAR) model is constructed online with sliding time window for linearly correlated characteristic variables to realize the prediction of NOx emission concentration under the input of multi-dimensional time series linear correlation variables For non-linear-related feature variables, the relationship between NOx emission concentration is predicted by constructing an online Recurrent extreme learning machine(OR-ELM) model online learning. Finally, Attention Mechanism(AM) is used to dynamically weight the two forecasting models to achieve trend forecasting. Through field data verification, it shows that the VAR-OR-ELM combined online prediction model constructed in this paper can accurately predict the variation trend of NOx emission concentration after 10 minutes. Combining prediction accuracy and prediction time, the combined prediction model is better than other single prediction models.

maximal information coefficient  /  attention mechanism  /  combined prediction  /  online learning  /  NOx emission
Hong QIAN, Jun ZHANG, Bangzhi XU. NOx emission prediction of coal-gas hybrid combustion plant based on the combination of attention mechanism model[J]. Thermal Power Generation, 2023 , 52 (8) : 137 -145 . DOI: 10.19666/j.rlfd.202212226
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  • Natural Science Foundation of Shanghai(19ZR1420700)
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Year 2023 volume 52 Issue 8
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66
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Article Info
doi: 10.19666/j.rlfd.202212226
  • Online Date：2026-01-26
  • Published：2023-08-25
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  • Revised：2022-12-12
Funding
Natural Science Foundation of Shanghai(19ZR1420700)
Affiliations
    1.School of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China
    2.Shanghai Key Laboratory of Power Station Automation Technology, Shanghai 200072, China
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https://castjournals.cast.org.cn/joweb/rlfd/EN/10.19666/j.rlfd.202212226
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