Prediction of NOx Concentration from Coal Combustion Using LS-SVR
Nitrogen oxide (NOx) is one of main pollutants emitted from coal fired power plants and is a significant pollutant source in the environment. Therefore, the monitoring or prediction of NOx emissions is an indispensable process in coal-fired power plant so as to control NOx emissions. In this paper, NOx emissions modeling for real-time operation and control of a 300MWe coal-fired power generation plant is studied. A least square support vector regression (LS-SVR) model was proposed to establish a non-linear model between the parameters of the boiler and the NOx emissions. The results show that the LS-SVR model predicted NOx emissions with good accuracy. LS-SVR model is much more accurate than the GRNN model previously reported by the authors. LS-SVR model will be a good alternative to a neural network based model which is commonly used to implement the predictive emission monitoring system (PEMS).
Ligang Zheng Hailin Jia Shuijun Yu Minggao Yu
School of Safety Science and Engineering and Key Lab of Gas Geology and Gas Control, Henan Polytechn School of Safety Science and Engineering and Key Lab of Gas Geology and Gas Control, Henan Polytechn
国际会议
成都
英文
1-4
2010-06-18（万方平台首次上网日期，不代表论文的发表时间）