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- Title
ASH FOULING MONITORING AND KEY VARIABLES ANALYSIS FOR COAL FIRED POWER PLANT BOILER.
- Authors
Yuanhao SHI; Jingcheng WANG
- Abstract
Ash deposition on heat transfer surfaces is still a significant problem in coal-fired power plant utility boilers. The effective ways to deal with this problem are accurate on-line monitoring of ash fouling and soot-blowing. In this paper, anonline ash fouling monitoring model based on dynamic mass and energy balancemethod is developed and key variables analysis technique is introduced to studythe internal behavior of soot-blowing system. In this process, artificial neuralnetworks are used to optimize the boiler soot-blowing model and mean impactvalues method is utilized to determine a set of key variables. The validity of themodels has been illustrated in a real case-study boiler, a 300 MW Chinese power station. The results on same real plant data show that both models have goodprediction accuracy, while the artificial neural networks model II has less input parameters. This work will be the basis of a future development in order to control and optimize the soot-blowing of the coal-fired power plant utility boilers.
- Subjects
BOILERS; COAL-fired power plant equipment; THERMAL efficiency; HEAT engineering; ARTIFICIAL neural networks; HEAT transfer
- Publication
Thermal Science, 2015, Vol 19, Issue 1, p253
- ISSN
0354-9836
- Publication type
Article
- DOI
10.2298/TSCI120428118S