Prediction For NO_x Emission Characteristic Of Opposed Wall Supercritical Boiler-firing Blended Coals

The boiler NO_x emission is an important index to reflect the boiler combustion state and the environmental protection of power plant operation. Accurate prediction of NO_x emissions not only helps guide the optimal adjustment of the boiler to reduce environmental pollution,but also improves the economicality of the boiler operation. The power plant is often mixed with inferior coal due to the limitation of the origin of the coal and the policy which the country has demanded to the usage of the coal to produce power, while the full burnout of inferior coal needs higher boiler temperature and longer residence time. The opposed wall firing supercritical boiler's features easily lead to the phenomenon of high NO_x emission.Therefore, by deeply analyzing of boiler NO_x emission characteristics and influence factors and predict methods of NO_x emissions, the boiler operating parameters that influence NO_x emissions can be optimistically adjusted, which shows important significance to reduce the influence of NO_x emission to the environmental pollution.The thesis analyzes the characteristics of NO_x emission of the opposed wall firing supercritical boiler and the influential factors based of the NO_x formation mechanism. With the research object of a 660 MW opposed wall firing supercritical boiler, the thesis has conducted the experimental study on NO_x emission characteristics and studied the influence of NO_x emission through the change of the single operational factor. The NO_x emission prediction model has been founded on the basis of different influential factors according to the characteristics of BP nerve network, then the NO_x emission prediction of the boiler has also been conducted and finally the field thermal state test has been validated. Thus, it provides the theoretical basis for the generation of NO_x calculation model, the experimental study on NO_x emission characteristic, the establishment of BP neural network model and the reduce of NO_x emissions.According to the research results, fuel NO_x and thermal NO_x are the major products in the process of the coal burning. The form of the opposed wall firing of the boiler, the temperature of the inside of the boiler, the characteristics of the fuel and the structure of the burner have great effects on NO_x emission. The volume fraction of O2 and over-fired air opening of boiler's operational factors shows pretty obvious influence on NO_x emission.NO_x emission will obviously increase with the increase of the volume fraction of O2 while NO_x emission will decrease as over-fired air opening increases. By building the BP nerve network and practicing it, the BP nerve network of the opposed wall firing supercritical boiler's NO_xemission has been obtained. Besides, the maximum error between the untrained sample forecasted and standard values value is less than 5%, which completely meets the needs of accuracy.