Indirect NOx emission monitoring in natural gas fired boilers

Timo Korpela; Pekka Kumpulainen; Yrjö Majanne; Anna Häyrinen; Pentti Lautala

doi:10.1016/j.conengprac.2017.04.013

Indirect NO_x emission monitoring in natural gas fired boilers

Timo Korpela, Pekka Kumpulainen, Yrjö Majanne, Anna Häyrinen, Pentti Lautala

Research output: Contribution to journal › Article › Scientific › peer-review

12 Citations (Scopus)

20 Downloads (Pure)

Abstract

New emission regulations will increase the need for inexpensive NO_x 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 NO_x 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
Pages (from-to)	11-25
Number of pages	15
Journal	Control Engineering Practice
Volume	65
DOIs	https://doi.org/10.1016/j.conengprac.2017.04.013
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

Access to Document

10.1016/j.conengprac.2017.04.013

Indirect NOx Emission Monitoring in Natural Gas Fired Boilers
© 2017. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Accepted author manuscript, 3.31 MB

http://urn.fi/URN:NBN:fi:tty-201708021643

Cite this

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title = "Indirect NOx emission monitoring in natural gas fired boilers",

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.",

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AU - Lautala, Pentti

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AB - 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.

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KW - Estimation

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KW - Monitoring

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