Indirect NOx emission monitoring in natural gas fired boilers

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

    Research output: Contribution to journalArticleScientificpeer-review

    11 Citations (Scopus)
    18 Downloads (Pure)

    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 languageEnglish
    Pages (from-to)11-25
    Number of pages15
    JournalControl Engineering Practice
    Volume65
    DOIs
    Publication statusPublished - 1 Aug 2017
    Publication typeA1 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

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