The Reasrch Of Combustion Optimization Algorithm Application On The Circulating Fluidized Bed Boiler

With the sharp increase of the national economy in electricity demand, people payedattention to energy saving and environmental protection. As a large consumption of energy,thermal power enterprises face with the dual demands of reducing operating costs andpollutant emissions, therefore, the high efficiency and low pollution of combustionoptimization technology have become an important research direction of the thermalprocess in power station.In recent years, domestic and foreign scholars have been dedicating to the study ofthe above problems, and have achieved certain results. In order to improve the combustionefficiency and reduce pollutant emissions of the boiler in power station, for the study of a300MW Circulating Fluidized Bed Boiler(CFBB), whose combustion system have manycomplex characteristics, such as multi-variable, Time-varying, strong couplinginterference, lag large and so on, an integrated model of the combustion characteristics ofCFBB is established based on least squares support vector machine (LSSVM), the inputsof the model are the operating parameters of CFBB, the outputs of model are efficiencyand NOx emissions of the boiler. The Gravitation Search Algorithm(GSA) is applied to theprocess of the model parameters optimization to get the optimal model of CFBB becausethe accuracy and generalization ability of the model depend on the parameters. Then usingGSA again to find out the best input parameters combination of the optimal model in orderto reduce emissions and improve the efficiency. Finally,the respective input variables areadjustde to the optimum parameters to accomplish the purpose of CFBB combustionoptimizationUsing above theories, a combustion optimal model of the boiler is built andexperiment simulation is carried out. The results show that the system of boilercombustion optimization realizes both high-efficiency and low-pollution emissions.