Combustion Optimization of Pulverized Coal-Fired Boiler in Thermal Power Plant Using Artificial Neural Network and Genetic Algorithm

2021 ◽  
Author(s):  
Muhammad Kamal Wisyaldin ◽  
Henry Pariaman ◽  
Andik Kurniawan
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Artificial Neural Network ◽  
Power Plant ◽  
Thermal Power Plant ◽  
Thermal Power ◽  
Pulverized Coal ◽  
Artificial Neural ◽  
Combustion Optimization

Modeling and Optimization of Unburned Carbon in Coal-Fired Boiler Using Artificial Neural Network and Genetic Algorithm

2013 ◽  
Vol 135 (3) ◽  
Author(s):  
P. Ilamathi ◽  
V. Selladurai ◽  
K. Balamurugan
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Artificial Neural Network ◽  
Field Experiments ◽  
Thermal Power ◽  
Bottom Ash ◽  
Unburned Carbon ◽  
Optimum Level ◽  
Boiler Load ◽  
Artificial Neural

An approach to model coal combustion process to predict and minimize unburned carbon in bottom ash of a large-capacity pulverized coal-fired boiler used in thermal power plant is proposed. The unburned carbon characteristic is investigated by parametric field experiments. The effects of excess air, coal properties, boiler load, air distribution scheme, and nozzle tilt are studied. An artificial neural network (ANN) is used to model the unburned carbon in bottom ash. A genetic algorithm (GA) is employed to perform a search to determine the optimum level process parameters in ANN model which decreases the unburned carbon in bottom ash.

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