Feedwater Control System Of Supercritical Power Unit Based On Identification By Using Genetic Algorithms

Supercritical boilers will be the country's future development direction and water supply system is one of the important parts. Ultra-supercritical plants using once-through boiler, from the feed water pump to the steam machine, steam and water being directly related to each other, making each parameter between the boiler and steam turbine and boiler with strong coupling characteristics increase the difficulty of feedwater control. In the analysis and design of thermal power plant's thermal process control system, model-based control method is widely used. This article taking the State Power Tongling 600MW supercritical once-through boiler for example, through on-site data analysis and pre-processing, dynamic model of the 100% and 70% boiler operating conditions is established using adaptive genetic identification method. According to multi-variable control, the article proposes a neural network decoupling control method that is used to decouple the built model, and is apllyed to the mid-point enthalpy correction coal-water ratio of the feedwater control system.Through the simulation, we can see that the control system can overcome disturbances to ensure the mid-point enthalpy value, to achieve an coarse regulation of the overheated temperature.