A Hybrid Technique for the Performance Optimization in the Combustion Process of a Power Plant Boiler: An Efficient ANNSSA Technique
In this paper presents a hybrid method for optimization process of combustion in power plant boiler. ANSSA scheme will be joint implementation of Artificial Neural Network (ANN) as well as Salp Swarm Optimization Algorithm (SSA) known ANNSSA. Here, ANN training process will be enhanced by using the SSA calculating. The optimization of economic parameters reduces excess air level and performs combustion efficiency at boiler system. Due to the operation of service boiler, oxygen content of flue gases is one of the significant factors which influence the efficiency of boiler, and influence each other to other thermal parameters of economic like temperature of flue gases combustion, unburned carbon at fly ash slag and consumption of coal power supply. The combustion performance denotes a saving at operating costs of boiler. ANNSSA method evolved for process of combustion to enhance the implementation and efficiency of the power plant boiler. At that time, ANNSSA technique is implemented at MATLAB/Simulink work platform as well as implementation is evaluated using existing techniques.
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