CFB锅炉燃烧优化技术的研究

Study on Optimization Technology of CFB Boiler Combustion

分析了影响CFB锅炉燃烧效率的各种因素,分别建立了以模型输出为锅炉燃烧效率及NOx排放量的BP神经网络预测模型,并采用了遗传算法实现对模型参数进行全局优化。通过调整燃烧工况参数使锅炉燃烧效率和NOx排放最优,利用锅炉真实运行数据对神经网络经行训练。通过Matlab仿真,结果表明:该模型和算法对锅炉燃烧的优化是有效的。

Various factors affecting the CFB boiler combustion efficiency are analyzed. The BP neural network prediction model is established, which is based on the model output for the boiler combustion efficiency and NOx emissions amount respectively. The genetic algorithm is used to optimize the parameters of the model. The boiler efficiency and NOx emission are optimized by adjusting combustion parameters. Neural network can be trained, which is based on real operation data of boiler.The result with Matlab simulation shows the proposed model and algorithm are effective for optimization of boiler combustion.