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燃煤电站锅炉高效低污染燃烧对于节约能源和环境保护都有重要意义。借助正交实验获取数据,基于人工神经网络建立反映锅炉效率和排放特性的模型。通过引入成本系数,将NOx排放特性和反映锅炉效率的特征量统一起来。应用基于实数编码的遗传算法对锅炉高效低NOx运行进行寻优。理论分析和实验结果表明:该方法可获得锅炉的最佳运行参数,典型工况下NOx排放降低50m g.m-3,锅炉效率提高0.4%,为锅炉的经济与环保运行提供了可靠决策依据。
The high efficiency and low pollution combustion of coal-fired power plant boilers is of great significance for energy conservation and environmental protection. Obtained data with orthogonal experiment and established a model reflecting the boiler efficiency and emission characteristics based on artificial neural network. By introducing a cost coefficient, the NOx emission characteristics and the characteristic quantities reflecting the efficiency of the boiler are unified. Application of genetic algorithm based on real number code to optimize the operation of boiler with high efficiency and low NOx. The theoretical analysis and experimental results show that this method can obtain the best operating parameters of boilers, NOx emission reduction of 50m g.m-3 under typical conditions and boiler efficiency of 0.4%, providing a reliable basis for the economic and environmental operation of the boiler.