【作者】 郑立刚；

【导师】 周昊； 岑可法；

【作者基本信息】 浙江大学 ， 热能工程， 2004， 硕士

【摘要】 锅炉的燃烧优化是通过锅炉的运行调整，达到最高的锅炉燃烧效率和最低的污染物排放量，从而降低电厂的煤耗和排污费用。我国能源人均占有率低，能源利用率低，“节能降耗”是我国目前主要的能源政策，同时工业造成了人类生存环境的恶化，保护环境更是一个世界性的问题，因此锅炉的燃烧优化具有很强的现实意义。 本文探讨了锅炉污染物NOx的生成机理和控制方法。重点探讨了NOx的生成机理、影响因素及其控制的一般原则。 锅炉NOx排放量、飞灰含碳量受锅炉煤种和运行参数影响很大，相互关系很难以常规的计算公式表达，本文引入BP网络(Back-Propagation)与广义回归神经网络，建立了锅炉的污染物NOx排放、飞灰含碳量神经网络模型。模型以影响目标值的因素为输入变量，以NOx产量及飞灰含碳量等为输出变量，用电厂采集的数据样本进行训练。此模型通过人工神经网络本身具有的强大的联想功能和记忆功能以及对于非线性变量的映射能力，来计算污染物排放与锅炉效率。 本文建立了锅炉燃烧优化算法模型。综合考虑锅炉效率和NOx排放两个方面的影响，建立了燃烧优化问题的目标函数；建立了机理模型和神经网络模型相结合的燃烧优化模型；研究了十进制遗传算法及其在数值优化中的应用，并将其用于该燃烧优化问题的寻优计算，优化结果对运行生产具有指导作用。 阐述了光学波动法测量气固多相流颗粒浓度的原理，并在实验条件下，利用此原理对多相射流的浓度与粒度分布进行了测量研究，对单弯头、组合弯头对多相流浓度粒度分布的影响进行了分析；对前置空间组合弯头及内置楔形体的直流燃烧器出口不同截面气固两相流颗粒浓度粒度分布作了测量研究，得出各截面浓度分布规律，扩散和衰减规律；对燃烧器出口射流和侧边风混合特性做了详细的研究，讨论了各截面浓度分布规律及两相流的混合特性。更多还原

【Abstract】 Boiler combustion optimization is to improve boiler efficiency and reduce nitrogen oxide emissions from boiler through adjustment of boiler operation parameters.In the paper, the NOx emission and carbon burnout characteristics were investigated through parametric field experiments. The effects of over-fire-air (OFA), flow rates, coal properties, boiler load, air temperature, air distribution scheme and nozzle tilt were studied.Because of the complexity of the NOx production mechanism, it is very difficult to establish an exact and simple mathematical model to estimate the production of NOx emission. On the basis of the experimental results, an ANN was used to model the NOx emission characteristics and the carbon burnout characteristics. The operation parameters that contribute to NOx emission and the boiler efficiency are used as the inputs of the neural network model, and economic parameters such as the boiler efficiency and NOx production are used as outputs. Data downloaded from DCS have been used to train the model. The completed trained NOx emission and unburned carbon model is used to predict the NOx emission and the unburned carbon in fly ash emitted from 300MW and 600MW boiler.In this paper, a Boiler Operation Optimizing model is built by combining Neural Network model and Genetic Algorithms. GA technique was employed to perform a search to determine the optimum solution of the ANN model, determining the optimal setpoints for the current operating conditions, which can suggest operators’ correct actions to decrease NOx emission.Chapter six describes the principle for determining the parameters of particles, such as the size, concentration and its velocity with light fluctuation based on the random theory and light scattering theory. The experiments were conducted to determine the particle concentrations and size distribution in the gas-solid jet flow from the burner with a former space combination elbow and an inner cuneiform. The characteristics of lateral mixing and diffusion of the burner with side-located air were studied.This method was also used to study the particle concentrations and size distribution in pulverized coal conveying lines, which was a rope in a vertical pipe, formed by a single elbow preceded by a long, straight, horizontal pipe section and a combination of two elbows.更多还原