摘要
针对锅炉燃烧控制系统的研究和试验,确定锅炉燃烧调节优化控制方案,使发电机组安全经济稳定运行,提高锅炉燃烧效率的问题,是电厂锅炉优化的主要目标.基于大庆某热电厂锅炉的运行数据,针对其优化的控制回路,采用径向基神经网络的方法建立了以蒸汽压力、烟气含氧量和炉膛负压为输出的预测模型,实现了上述3个参数的预测,结果表明建立的模型能够反映锅炉的特性,为下面的优化工作奠定了基础.
The research and test of boiler combustion control system determine the optimal control of boiler combustion adjustment scheme, make economic stability operation of the generator set, improve the efficiency of boiler combustion, and are one of the main targets of the power plant boiler optimization. Based on Daqing thermal power plant boiler operation data, aiming at the optimization of control circuit, by RBF neural network established steam pressure, flue gas oxygen content and furnace negative pressure for the output prediction model, we impvove the above three parameters prediction. The results show that the model established can reflect the characteristics of the boiler, and the foundation for the following optimal work.
出处
《哈尔滨理工大学学报》
CAS
北大核心
2016年第1期89-92,共4页
Journal of Harbin University of Science and Technology
关键词
径向基神经网络
锅炉模型
预测
优化控制
燃烧效率
radial basis function neural network
modeling of the boiler
prediction
optimal control
combustion efficiency
