University of Oulu

M. Neuvonen, I. Selek, E. Ikonen and L. Aho, "Heat exchanger fouling estimation for combustion–thermal power plants including load level dynamics," 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Prague, Czech Republic, 2022, pp. 2987-2992, doi: 10.1109/SMC53654.2022.9945541.

Heat exchanger fouling estimation for combustion–thermal power plants including load level dynamics

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Author: Neuvonen, Markus1; Selek, István1; Ikonen, Enso1;
Organizations: 1Intelligent Machines and Systems, University of Oulu Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.5 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe202301317784
Language: English
Published: Institute of Electrical and Electronics Engineers, 2022
Publish Date: 2023-01-31
Description:

Abstract

This paper presents a robust soft sensor for estimating heat exchanger fouling in combustion–thermal power plant context. The approach is data–driven and focuses on identifying the effect of plant load changes to fouling estimation. Proposed method is applied to real process measurements and results are presented. The method consists of two blocks; a static energy balance calculation block for “traditional” fouling indicator calculation and a dynamic subspace identification block for finding sootblowing– and load level dynamics components of the static fouling indicator signal. Results from applying the proposed method to real plant data show that load level dynamics can be decoupled from static fouling estimate.

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Series: IEEE International Conference on Systems, Man, and Cybernetics
ISSN: 1062-922X
ISSN-E: 2577-1655
ISSN-L: 1062-922X
ISBN: 978-1-6654-5258-8 978-1-6654-5257-1
ISBN Print: 978-1-6654-5259-5
Pages: 2987 - 2992
DOI: 10.1109/SMC53654.2022.9945541
OADOI: https://oadoi.org/10.1109/SMC53654.2022.9945541
Host publication: 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC), October 9-12, 2022, Prague, Czech Republic : proceedings
Conference: IEEE International Conference on Systems, Man, and Cybernetics
Type of Publication: A4 Article in conference proceedings
Field of Science: 222 Other engineering and technologies
Subjects:
Funding: This work was conducted in the H2020 project COGNITWIN (grant number 870130).
EU Grant Number: (870130) COGNITWIN - COGNITIVE PLANTS THROUGH PROACTIVE SELF-LEARNING HYBRID DIGITAL TWINS
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