Journal
FUEL
Volume 274, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.fuel.2020.117811
Keywords
Coal-fired boilers; NOx emission; Real-time dynamic prediction model; Variable load conditions; Least square support vector machine
Categories
Funding
- National Natural Science Foundation of China [51706066, 51606063]
- Fundamental Research Funds for the Central Universities [2018MS026]
Ask authors/readers for more resources
This study focuses on the problem of predicting nitrogen oxide (NOx) concentration at the inlet of selective catalytic reduction (SCR) reactors under variable load conditions of thermal power units. Some variables with strong correlation with NOx concentration at the SCR inlet were selected as auxiliary variables and the delay time between NOx concentration and auxiliary variables was determined by the mutual information method. Taking the delay time, dynamic time and prediction error into account, a real-time dynamic prediction model of NOx concentration based on the least square support vector machine was proposed. The model was tested using the actual historical data under variable load operating conditions of two thermal power units. Test results show that the proposed dynamic prediction model has high real-time prediction accuracy and satisfactory generalization ability.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available