摘要
采用径向基神经网络建立了锅炉燃烧输入与输出参数的智能优化模型,分析了不同径向基函数分布密度对模型预测精度的影响,应用基于实数编码方式的遗传算法实现了运行操作参数的实时寻优。通过某电厂600MW机组的实际应用,燃烧调整过程中实际运行参数的获得可用于指导锅炉运行人员的操作,使优化操作后的锅炉效率得到了提高。
Adopting radial radical neural network, an intelligent optimizing model for input and output parameters of combustion has been established, the influence of distribution density in different radial radical functin upon prediction accuracy of the model being analysed. By using genelic algorithm based on real - number coding method, the real - time optimization of manipulating parameters in operation has been realized. Through practical application on 600 MW unit in one power plant, the obtained actual operation parameters in the process of combustion regulation have guiding significance for manipulation of boiler operations, the boiler efficiency after optimization of manipulation heing enhanced, the optimization of Combustion in the boiler being realized.
出处
《热力发电》
CAS
北大核心
2008年第9期23-27,31,共6页
Thermal Power Generation
关键词
电站
锅炉
燃烧优化
神经网络
遗传算法
Power Plant
boiler
optimization of combustion
neural network
genetic algorithm
