Combustion system model based prediction of boiler efficiency and NO<sub>x</sub> emission

HE Yongchao Hebei Huadian Shijiazhuang Yuhua Thermal Power Plant Co.

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Combustion system model based prediction of boiler efficiency and NO_x emission

更新时间：2025-09-28

- Combustion system model based prediction of boiler efficiency and NO_x emission
- Thermal Power Generation Vol. 42, Issue 4, Pages: 65-69(2013)
- 作者机构：
  
  河北华电石家庄裕华热电有限公司
- 作者简介：
- 基金信息：
- DOI：
  CLC： TK227.6
- Published：2013
- 稿件说明：
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HE Yongchao Hebei Huadian Shijiazhuang Yuhua Thermal Power Plant Co.. Combustion system model based prediction of boiler efficiency and NO_x emission[J]. Thermal power generation, 2013, 42(4): 65-69.
DOI：

HE Yongchao Hebei Huadian Shijiazhuang Yuhua Thermal Power Plant Co.. Combustion system model based prediction of boiler efficiency and NO_x emission[J]. Thermal power generation, 2013, 42(4): 65-69. DOI：

摘要

以某电厂燃煤锅炉燃烧调整试验数据为基础

运用BP神经网络建立锅炉效率与NOx排放浓度的双目标锅炉燃烧系统模型

并用遗传算法优化BP神经网络的权值和阈值产生优化型GA-BP神经网络模型。通过对2种模型预测误差的比较表明

GA-BP神经网络模型的锅炉效率平均预测误差由6%降至3.4%

NOx排放浓度平均预测误差由0.1%降至0.04%

泛化能力相对于BP神经网络模型大大增强

可适用于建立锅炉燃烧优化系统。

Abstract

On the basis of test data of coal-fired boiler combustion adjustment in a power plant

a hybrid model of the boiler combustion system was established by using the BP neural network

targeting at predicting the boiler efficiency and NOx emission.Moreover

by the genetic algorithms

the weights and thresholds of the BP neural network model were optimized to obtain the improved GA-BP neural network model.Finally

comparison of the prediction error between above two models was conducted.The results showed that

compared with the BP neural network model

by the GA-BP neutral network model

the average prediction error declines from 6% to 3.4% for boiler efficiency and from 0.1% to 0.04% for NOx emission concentration.The generalization ability of the GA-BP neural network model was greatly enhanced

and this model was suitable to build the boiler combustion optimization system.

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Related Institution

Xi'an Thermal Power Research Institute Co., Ltd

Xi'an Thermal Power Research Institute Co.,Ltd.,Suzhou Branch

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School of Electric Power, North China University of Water Resources and Electric Power

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Combustion system model based prediction of boiler efficiency and NOx emission

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Combustion system model based prediction of boiler efficiency and NO_x emission