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基于PLS-SVR的电站锅炉NOx排放特性建模

51    2019-11-28

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作者:马宁1,2, 董泽1

作者单位:1. 华北电力大学河北省发电过程仿真与优化控制工程技术研究中心, 河北 保定 071003;
2. 华北电力大学控制与计算机工程学院, 北京 102206


关键词:NOx排放;燃煤锅炉;偏最小二乘;支持向量回归


摘要:

针对影响电站燃煤锅炉NOx排放的热工变量数量较多,且存在较强的耦合相关性的问题,提出一种基于偏最小二乘(PLS)和支持向量回归(SVR)相结合的PLS-SVR建模方法用以建立燃煤锅炉NOx排放模型。PLS-SVR模型首先利用PLS提取输入变量的特征信息消除变量之间的耦合特性并降低输入变量维度,然后将提取的特征信息作为SVR模型的输入。以某超超临界1 000 MW机组锅炉为对象,选取23个相关变量作为模型的输入建立电站锅炉NOx排放模型(PLS-SVR模型),该模型对测试样本的预测误差指标MRSE为4.072。将PLS-SVR模型的预测结果和建模时间与ANN模型和未经特征提取的SVR模型对比,结果表明PLS-SCR模型具有更好高的预测精度和更快的建模速度。


Modeling of NOx emission characteristics of coal-fired boiler based on PLS-SVR
MA Ning1,2, DONG Ze1
1. Hebei Engineering Research Center of Simulation & Optimized Control for Power Generation, North China Electric Power University, Baoding 071003, China;
2. School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
Abstract: In order to solve the problem that the number of thermal variables affecting the NOx emission of coal-fired boilers in power plants is large and there is strong coupling correlation, a PLS-SVR modeling method based on partial least squares (PLS) and support vector regression (SVR) is proposed. PLS-SVR model firstly uses PLS method to extract the feature information of input variables, eliminating the coupling between variables and reducing the dimension of input variables, and then the extracted the feature information is used as the input of SVR model. Taking a 1 000 MW ultra-supercritical unit boiler as an object, a PLS-SVR model of NOx emission from utility boiler is established by selecting 23 relevant variables as input of the model. The prediction error index MRSE of the model is 4.072. The prediction results and modeling time of PLS-SVR model are compared with ANN model and SVR model without feature extraction. The results show that PLS-SCR model has better prediction accuracy and faster modeling speed.
Keywords: NOx emission;coal-fired boiler;partial least squares;support vector regression
2019, 45(11):138-142  收稿日期: 2018-09-18;收到修改稿日期: 2018-11-29
基金项目: 国家自然科学基金(71471060)
作者简介: 马宁(1992-),男,河北迁安市人,博士研究生,研究方向为热工系统建模
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