Intelligent combustion control model for utility boilers based on asymmetric artificial neural networks

WU Hengyun; GAO Lin; TIAN Jianyong; ZHOU Junbo; GAO Haidong; WANG Lin; WANG Mingkun

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Intelligent combustion control model for utility boilers based on asymmetric artificial neural networks

Thermal Power Generation Issue 11, (2017)

更新时间：2025-09-28

- Intelligent combustion control model for utility boilers based on asymmetric artificial neural networks
- 作者机构：
  
  1. 西安热工研究院有限公司,陕西,西安,710054
  2. 国家电投集团河南电力有限公司开封发电分公司,河南,开封,475000
- 作者简介：
- 基金信息：
- DOI：
  CLC： TK32
- Published Online：27 November 2017，
  
  Published：2017
- 稿件说明：
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WU Hengyun, GAO Lin, TIAN Jianyong, et al. Intelligent combustion control model for utility boilers based on asymmetric artificial neural networks[J]. Thermal Power Generation, 2017, (11).
DOI：

WU Hengyun, GAO Lin, TIAN Jianyong, et al. Intelligent combustion control model for utility boilers based on asymmetric artificial neural networks[J]. Thermal Power Generation, 2017, (11). DOI：

摘要

针对目前国内电站锅炉燃烧建模存在煤质与负荷波动频繁、测点精度有限、设备运行组合多变等产生的问题，提出了电站锅炉燃烧的非对称神经网络建模方法。将锅炉模型的输入按照实际物理规律的关联关系设计网络结构组合，去掉关联性较弱的联系，从而使模型天然体现一定的锅炉燃烧规律，实现了不同燃烧器出力分配下的单一网络建模，提高了学习训练效率，并大幅降低了模型所需样本数量。将经典对称神经网络模型和非对称神经网络模型进行对比训练，结果表明本文提出的非对称神经网络建模方法检验正确率高。将其应用于某超临界660 MW机组的燃烧优化控制，锅炉效率平均可提高0.25%。

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