Prediction of Pollution State of Heating Surface in Coal-Fired Utility Boilers

Qiang Li; Peigang Yan; Jinfu Liu; Yuanhao Shi; Daren Yu

doi:10.1109/ACCESS.2020.3036840

Prediction of Pollution State of Heating Surface in Coal-Fired Utility Boilers

Qiang Li
, Peigang Yan
, Jinfu Liu^*
, Yuanhao Shi
, Daren Yu

^*Corresponding author for this work

School of Energy Science and Engineering, Harbin Institute of Technology
North University of China

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

11 Scopus citations

Abstract

This paper presents a method to predict the cleaning state of the boiler heating surface. In this method, firstly, the historical fouling rate data is decomposed into two parts: fitting curve data and the difference between original data and the fitting curve. Then, combined with the real-time fouling rate data, the prediction model is established. Finally, the method is verified by the actual operation data of a 300 MW coal-fired power station boiler. The method does not need additional special instruments or a complex calculation system but can use the existing monitoring data to realize the dirt monitoring and soot blowing optimization of the economizer, which has a certain guiding role for the soot blowing operation of the coal-fired power plant.

Original language	English
Article number	9252897
Pages (from-to)	206132-206145
Number of pages	14
Journal	IEEE Access
Volume	8
DOIs	https://doi.org/10.1109/ACCESS.2020.3036840
State	Published - 2020
Externally published	Yes

Keywords

Boiler heating surface
difference
fitting
fouling rate
prediction

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10.1109/ACCESS.2020.3036840

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@article{22e8d89b14c84323a3f809fbee1c1105,

title = "Prediction of Pollution State of Heating Surface in Coal-Fired Utility Boilers",

abstract = "This paper presents a method to predict the cleaning state of the boiler heating surface. In this method, firstly, the historical fouling rate data is decomposed into two parts: fitting curve data and the difference between original data and the fitting curve. Then, combined with the real-time fouling rate data, the prediction model is established. Finally, the method is verified by the actual operation data of a 300 MW coal-fired power station boiler. The method does not need additional special instruments or a complex calculation system but can use the existing monitoring data to realize the dirt monitoring and soot blowing optimization of the economizer, which has a certain guiding role for the soot blowing operation of the coal-fired power plant.",

keywords = "Boiler heating surface, difference, fitting, fouling rate, prediction",

author = "Qiang Li and Peigang Yan and Jinfu Liu and Yuanhao Shi and Daren Yu",

note = "Publisher Copyright: {\textcopyright} 2013 IEEE.",

year = "2020",

doi = "10.1109/ACCESS.2020.3036840",

language = "英语",

volume = "8",

pages = "206132--206145",

journal = "IEEE Access",

issn = "2169-3536",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - JOUR

T1 - Prediction of Pollution State of Heating Surface in Coal-Fired Utility Boilers

AU - Li, Qiang

AU - Yan, Peigang

AU - Liu, Jinfu

AU - Shi, Yuanhao

AU - Yu, Daren

PY - 2020

Y1 - 2020

N2 - This paper presents a method to predict the cleaning state of the boiler heating surface. In this method, firstly, the historical fouling rate data is decomposed into two parts: fitting curve data and the difference between original data and the fitting curve. Then, combined with the real-time fouling rate data, the prediction model is established. Finally, the method is verified by the actual operation data of a 300 MW coal-fired power station boiler. The method does not need additional special instruments or a complex calculation system but can use the existing monitoring data to realize the dirt monitoring and soot blowing optimization of the economizer, which has a certain guiding role for the soot blowing operation of the coal-fired power plant.

AB - This paper presents a method to predict the cleaning state of the boiler heating surface. In this method, firstly, the historical fouling rate data is decomposed into two parts: fitting curve data and the difference between original data and the fitting curve. Then, combined with the real-time fouling rate data, the prediction model is established. Finally, the method is verified by the actual operation data of a 300 MW coal-fired power station boiler. The method does not need additional special instruments or a complex calculation system but can use the existing monitoring data to realize the dirt monitoring and soot blowing optimization of the economizer, which has a certain guiding role for the soot blowing operation of the coal-fired power plant.

KW - Boiler heating surface

KW - difference

KW - fitting

KW - fouling rate

KW - prediction

UR - https://www.scopus.com/pages/publications/85097336195

U2 - 10.1109/ACCESS.2020.3036840

DO - 10.1109/ACCESS.2020.3036840

M3 - 文章

AN - SCOPUS:85097336195

SN - 2169-3536

VL - 8

SP - 206132

EP - 206145

JO - IEEE Access

JF - IEEE Access

M1 - 9252897

ER -

Prediction of Pollution State of Heating Surface in Coal-Fired Utility Boilers

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Keywords

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