NO<sub>x</sub> emission prediction of coal-fired power plants based on PSO and Bi-GRU

XIE Ruibiao; LI Xinli; WANG Yingnan; YANG Guotian

doi:10.19666/j.rlfd.202103042

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NO_x emission prediction of coal-fired power plants based on PSO and Bi-GRU

更新时间：2025-09-28

- NO_x emission prediction of coal-fired power plants based on PSO and Bi-GRU
- Thermal Power Generation Vol. 50, Issue 10, Pages: 87-94(2021)
- 作者机构：
  
  华北电力大学控制与计算机工程学院
- 作者简介：
- 基金信息：
- DOI：10.19666/j.rlfd.202103042
  CLC： TP18;X773
- Published：2021
- 稿件说明：
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XIE Ruibiao, LI Xinli, WANG Yingnan, et al. NO_x emission prediction of coal-fired power plants based on PSO and Bi-GRU[J]. Thermal power generation, 2021, 50(10): 87-94.
DOI：

XIE Ruibiao, LI Xinli, WANG Yingnan, et al. NO_x emission prediction of coal-fired power plants based on PSO and Bi-GRU[J]. Thermal power generation, 2021, 50(10): 87-94. DOI： 10.19666/j.rlfd.202103042.

摘要

针对燃煤电厂NO_x排放的预测问题

提出了基于粒子群优化算法和双向门控循环(PSO-BiGRU)神经网络的NO_x排放预测模型。通过主成分分析对影响NO_x排放的运行参数进行降维

消除变量间的耦合;基于双向门控循环神经网络学习NO_x排放的非线性特性和前后时序信息

提高特征提取能力;采用粒子群算法对Bi-GRU神经网络模型进行超参数寻优

使网络结构最大程度匹配影响NO_x排放的变量特征

克服依靠经验选取或手动调节参数而导致预测精度低的问题。最后基于某电厂660 MW机组燃煤锅炉运行参数

建立NO_x排放预测模型

并与单向门控循环神经网络、传统Bi-GRU神经网络预测模型进行对比。仿真结果表明

PSO-Bi-GRU神经网络模型预测效果最好

其平均绝对误差、平均绝对百分误差、均方根误差均最小

验证了本文所提PSO-Bi-GRU神经网络NO_x排放预测模型的有效性。

Abstract

In view of the prediction of NO_x emissions from coal-fired power plants

the NO_x prediction model is proposed based on particle swarm optimization (PSO) algorithm and bidirectional gate recurrent unit (Bi-GRU).Principal component analysis (PCA) is used to reduce the dimension and eliminate coupling of operating parameters which affecting the NO_x emission.The nonlinear characteristics and time sequence information of NO_x emission are achieved through the Bi-GRU neural network

which is helpful to improve the ability of feature extraction.The PSO algorithm is applied to optimize the parameters of the Bi-GRU network model

so that the network structure can match the feature of NO_x data to the greatest extent

and the problem of low prediction accuracy caused by selecting parameters according to experience or manual adjustment can be overcome.Finally

based on the operation parameters of a 660 MW coal-fired boiler

the NO_x emission prediction model is established and compared with the single direction GRU model and Bi-GRU model.The simulation results show that

the PSO-Bi-GRU model has the best prediction performance

and the mean absolute error

mean absolute percentage error and root mean square error are the minimum

which verifies the effectiveness of the proposed algorithm.

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NOx emission prediction of coal-fired power plants based on PSO and Bi-GRU

DOI：10.19666/j.rlfd.202103042

摘要

Abstract

关键词

Keywords

references

NO_x emission prediction of coal-fired power plants based on PSO and Bi-GRU