Optimal Combustion Control Method Based On Visualization Of Temperature Distribution In Furnace

Advanced combustion monitor and control technology can realize the high stability, high efficiency and low pollution of combustion process in the coal-fired boiler. Current research achievements on visualization of 3-D temperature distributions in pc-fired furnaces can provide the practical basis for the application of a new combustion optimal control strategy. Against the delay, parameter-distributed characteristic of the traditional combustion control, a new combustion control strategy with the 3-D temperature distribution in a furnace as an intermediate goal to control the multi-burner boiler is presented. Concerning the combustion efficiency and pollution emission of utility boilers, the integrated optimization of a combustion process is studied. In this paper, a linear model is set up to relate the features of the temperature distributions with the input of the combustion processes, such as the mass flow rates of fuel and air fed into the furnaces through all the burners. A furnace combustion control strategy based on an adaptive genetic algorithm, using a group of new characteristic parameters featuring the 3-D temperature distribution inside the furnaces, is studied by simulation. The results show that the control method could provide suitable control signals for the fuel and air mass flow rates to change the load level, estimate the failure of individual burner and give correct control signals to deal with it. The temperature distribution optimal control strategy based on the adaptive genetic algorithm can be applied into the combustion of tangentially pc-fired utility boilers. An experimental study based on combustion adjustment was conducted on a 300MW coal fired boiler, where a 3-D temperature distribution visualization monitoring system was installed. The results show that the correctly furnace temperature distribution can be obtained by the system, and the combustion adjustment has great influence on the 3-D temperature distribution,NOx emission, furnace radiant energy, and unburned carbon in fly ash. Furthermore, NOx emission has high correlation with the 3-D temperature distribution, especially the temperatures in the main combustion zone. The combustion monitoring system give support for control NOx emission through temperature distribution. On the basis of combustion experiment, a model based on ANN for the NOx emission and unburned carbon in fly ash is developed, and the model is verified well. The NOx emission ANN model give an improved prediction performance by using the furnace cross-section highest temperatures as part of input parameters. A optimal control strategy Based on adaptive genetic algorithm is proposed for the high efficiency and low NOx emission of boiler. The simulation results show that the combustion adjustment using parameters suggested by the model can reduce NOx emission and unburned carbon in fly ash, and raise the boiler efficiency. The correlation analysis of gray system theory is adopted to analyze the relationship between the inputs of the furnace and the pollution emission concentration, the main factors influencing the boiler efficiency and pollution emission is found, and the optimal operation mode can be gained under the current coal quality and unit load.