基于神经网络的火电厂脱硫控制系统研究

Research on Desulfurization Control System of Thermal Power Plant Based on Neural Network

以某火电厂2×300 MW机组为研究对象,设计了以石灰石-石膏湿法为工艺基础的烟气脱硫控制系统。对脱硫控制系统中吸收塔的浆液pH值的控制进行了改进,设计了基于神经网络自适应控制器。该控制器能有效提高浆液pH值的控制精度与稳定性。

Taking a 2×300 MW unit of a thermal power plant as the research object,a FGD control system based on limestone-gypsum wet process is designed.The control of slurry pH value in absorption tower of desulfurization control system is improved,and an adaptive controller based on neural network is designed.The controller can effectively improve the control accuracy and stability of slurry pH value,which provides a new approach for the design of desulfurization control system in thermal power plants at this stage.