基于神经网络的燃烧优化建模

Modeling of the combustion optimizion based on neural networks

建立了基于RBF神经网络的燃烧优化模型,实现了最佳给煤量和实发功率的寻优。同时利用MATLAB建立仿真模型,并进行了仿真研究,仿真结果表明:在稳定运行时,当锅炉负荷、电厂用的煤质(即煤发热量的不同)、燃烧所给的送风量和引风量变化时,基于RBF神经网络的锅炉燃烧系统非线性模型能够很好地实现给煤量和实发功率的寻优,所得的结果对锅炉的燃烧优化控制奠定了基础。

The combustion optimizion model based on RBF neural networks is set up, actualizing to find the best providing coal quantity and real generating electricity power. At the same time, this paper establishes simulating model by MATLAB, processing simulation researching, and simulating result indicates： when the system is in the stabilization state ,with the diversification of the boiler charge,electricity plant coal character （the distinctness of coal heat quantity） ,combustion supplying air quantity and combus- tion inducing air quantity, nonlinear modeling of the boiler combustion system in the power plant based on RBF neural networks can response the best providing coal quantity and the best real generating electricity power ,and the result also builds a strong base for optimal control and on - line prediction of the boiler.