Development and implementation of Intelligent Soot Blowing Optimization System for TNB Janamanjung
Backpropagation; Boilers; Coal; Computational fluid dynamics; Fossil fuel power plants; Neural networks; Soot; Coal-fired power plant; Combination of neural-network; Data preparation; Energy demands; Optimization system; Predictive tools; Training algorithms; Training function; Dust
Saved in:
| Main Authors: | , , , |
|---|---|
| Other Authors: | |
| Format: | Conference Paper |
| Published: |
EDP Sciences
2023
|
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| id |
my.uniten.dspace-23083 |
|---|---|
| record_format |
dspace |
| spelling |
my.uniten.dspace-230832023-05-29T14:37:43Z Development and implementation of Intelligent Soot Blowing Optimization System for TNB Janamanjung Sundaram T. Basim Ismail F. Gunnasegaran P. Gurusingam P. 57196438069 58027086700 35778031300 57196439549 Backpropagation; Boilers; Coal; Computational fluid dynamics; Fossil fuel power plants; Neural networks; Soot; Coal-fired power plant; Combination of neural-network; Data preparation; Energy demands; Optimization system; Predictive tools; Training algorithms; Training function; Dust With an ever increasing demand for energy, Malaysia has become a nation that thrives on solid power generation sector to meet the energy demand and supply market. In a coal fired power plant, soot blowing operation is commonly used as a cleaning mechanism inside the boiler. There are many types of sequence available for this soot blowing operation. Hence, there is no efficient ways in utilizing the soot blowing operation to enhance the efficiency of boiler. Soot blowing optimization requires specific set of data preparation and simulation in order to achieve the best modal. Computational Fluid Dynamics (CFD) is used to model a 700MW super-critical boiler, whereby parameters with effect to soot blowing operation is studied. Two different boiler condition is studied to analyze parameters in a clean and faulty boiler. Artificial Neural Network (ANN) is used to train neural network modal with back propagation method to determine the best modal that will be used to predict soot blowing operation. Combination of neural network different number of neurons, hidden layers, training algorithm, and training functions is trained to find the modal with lowest error. By improving soot blowing sequence, efficiency of boiler can be improved by providing best parameter and model. This model is then used as a reference for advisory tool whereby a Neural Network Predictive Tool is suggested to the station to predict the soot blowing operation that occurs. � The authors, published by EDP Sciences, 2017. Final 2023-05-29T06:37:42Z 2023-05-29T06:37:42Z 2017 Conference Paper 10.1051/matecconf/201713101006 2-s2.0-85033217584 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85033217584&doi=10.1051%2fmatecconf%2f201713101006&partnerID=40&md5=cf7b9760696e31fe0c5782c73a75a6e9 https://irepository.uniten.edu.my/handle/123456789/23083 131 1006 All Open Access, Gold, Green EDP Sciences Scopus |
| institution |
Universiti Tenaga Nasional |
| building |
UNITEN Library |
| collection |
Institutional Repository |
| continent |
Asia |
| country |
Malaysia |
| content_provider |
Universiti Tenaga Nasional |
| content_source |
UNITEN Institutional Repository |
| url_provider |
http://dspace.uniten.edu.my/ |
| description |
Backpropagation; Boilers; Coal; Computational fluid dynamics; Fossil fuel power plants; Neural networks; Soot; Coal-fired power plant; Combination of neural-network; Data preparation; Energy demands; Optimization system; Predictive tools; Training algorithms; Training function; Dust |
| author2 |
57196438069 |
| author_facet |
57196438069 Sundaram T. Basim Ismail F. Gunnasegaran P. Gurusingam P. |
| format |
Conference Paper |
| author |
Sundaram T. Basim Ismail F. Gunnasegaran P. Gurusingam P. |
| spellingShingle |
Sundaram T. Basim Ismail F. Gunnasegaran P. Gurusingam P. Development and implementation of Intelligent Soot Blowing Optimization System for TNB Janamanjung |
| author_sort |
Sundaram T. |
| title |
Development and implementation of Intelligent Soot Blowing Optimization System for TNB Janamanjung |
| title_short |
Development and implementation of Intelligent Soot Blowing Optimization System for TNB Janamanjung |
| title_full |
Development and implementation of Intelligent Soot Blowing Optimization System for TNB Janamanjung |
| title_fullStr |
Development and implementation of Intelligent Soot Blowing Optimization System for TNB Janamanjung |
| title_full_unstemmed |
Development and implementation of Intelligent Soot Blowing Optimization System for TNB Janamanjung |
| title_sort |
development and implementation of intelligent soot blowing optimization system for tnb janamanjung |
| publisher |
EDP Sciences |
| publishDate |
2023 |
| _version_ |
1806426245521473536 |
| score |
13.19449 |