Research and application on combustion optimization of coal-fired boiler in thermal power plant based on artificial intelligence technology

Peifeng NIU; Yunpeng MA; Xinxin ZHANG; Xiaobin HU

doi:10.11959/j.issn.2096-6652.201925

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Research and application on combustion optimization of coal-fired boiler in thermal power plant based on artificial intelligence technology

Regular Papers | 更新时间：2024-06-05

- Research and application on combustion optimization of coal-fired boiler in thermal power plant based on artificial intelligence technology
- Chinese Journal of Intelligent Science and Technology Vol. 1, Issue 2, Pages: 163-170(2019)
- 作者机构：
  
  1. 燕山大学电气工程学院，河北秦皇岛 066004
  2. 天津商业大学信息工程学院，天津300134
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-6652.201925
  CLC： TP323
- Published Online：2019-06，
  
  Published：20 June 2019
- 稿件说明：
移动端阅览
Peifeng NIU, Yunpeng MA, Xinxin ZHANG, et al. Research and application on combustion optimization of coal-fired boiler in thermal power plant based on artificial intelligence technology[J]. Chinese journal of intelligent science and technology, 2019, 1(2): 163-170.
DOI：

Peifeng NIU, Yunpeng MA, Xinxin ZHANG, et al. Research and application on combustion optimization of coal-fired boiler in thermal power plant based on artificial intelligence technology[J]. Chinese journal of intelligent science and technology, 2019, 1(2): 163-170. DOI： 10.11959/j.issn.2096-6652.201925.

摘要

为了降低火电厂燃煤锅炉的氮氧化合物排放浓度和锅炉煤耗，提出了样本增量量子神经网络和改进型量子蜂群算法。样本增量量子神经网络可以动态建立燃煤锅炉的氮氧化合物排放浓度和锅炉煤耗的综合模型，并且可实现模型滚动优化。基于建立的综合模型，通过应用改进型量子蜂群算法优化一二次风量、燃煤量和各二次风门开度来实现锅炉燃烧优化。基于上述两种方法，开发了一套燃煤锅炉智能燃烧优化软件，并应用于某热电厂330 MW锅炉上，测试结果表明，氮氧化合物排放浓度和锅炉煤耗均有不同程度的降低，说明建模方法和优化算法是有效的。

Abstract

In order to reduce the NO

emission concentration and coal consumption of coal-fired boilers in thermal power plants

the sample increment quantum neural network and an improved quantum bee colony algorithm were proposed.The quantum sample incremental feed-forward neural network can dynamically establish a comprehensive model of Nitrogen and Oxygen emission concentration and boiler coal consumption of coal-fired boiler

and can realize rolling optimization of the model.Based on the established comprehensive model

the optimization of the primary and secondary air volume and coal and the opening degree of each secondary air valve were realized by using the improved quantum bee colony algorithm.Based on the above two methods

a set of intelligent combustion optimization software for coal-fired boiler was developed and applied to the 330 MW boiler of a thermal power plant.The test results show that the Nitrogen and Oxygen emission concentration and the coal consumption of the boiler have been reduced in varying degrees.It is shown that the modeling method and the optimization algorithm are effective.

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references

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