Abstract
New emission regulations will increase the need for inexpensive NOx emission monitoring solutions also in smaller power plants. The objective in this study is to find easily maintainable and transparent but still valid models to predict NOx emissions in natural gas fired hot water boilers utilizing existing process instrumentation. With a focus on long-term applicability in practical installations, the performance of linear regression is compared in two municipal 43 MW boilers with three widely used nonlinear methods: multilayer perceptron, support vector regression, and fuzzy inference system. The linear models were the most applicable providing the best estimation results (relative error of 1 applications in practise. However, each boiler model should be identified individually.
Original language | English |
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Pages (from-to) | 11-25 |
Number of pages | 15 |
Journal | Control Engineering Practice |
Volume | 65 |
DOIs | |
Publication status | Published - 1 Aug 2017 |
Publication type | A1 Journal article-refereed |
Keywords
- Combustion
- Estimation
- Modelling
- Monitoring
- Natural gas
- NO
- Soft sensor
Publication forum classification
- Publication forum level 2
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications
- Applied Mathematics
- Electrical and Electronic Engineering