Abstract
As the boiler characteristics are affected by load change, the traditional control method cannot realize load tracking to control the main steam temperature MST in real time. In this paper a system is designed to control the midpoint temperature to adjust the fuel-water ratio as the major control, and secondary superheating water spray cooling adjustment as minor control. Firstly, in order to meet the coordinated of the power grid and the power plant, the boiler steam turbine coordination control system is established to track load change control the boiler input and steam turbine output signals.And take the outlet water temperature of the water wall as the intermediate point temperature (MPT), obtain the oil-water ratio, load, MPT relationship from the actual equipment data, and establish the MPT nonlinear discrete controller, to reduce the spray water and quickly adjust the main steam temperature. Use the Sailfish algorithm (SFO) to optimizes PID parameters. At the same time, in order to further improve the SFO optimization ability, an initialization method based on chaotic mapping and reverse learning is proposed, to improve the population diversity and global search ability. Finally, to verify the model accuracy, the actual data input to the model, and compared with the actual data. The error between THE MPT and the actual value is 0℃~3℃, and the error between the MST and the target value is -1.7℃~0.3℃. Compared with the traditional PID, the ISFO-PID controller can reduce the steady-state error by 60%, adjust time by 68%, and spray volume by 40%. The self-adaptive tracking control of main steam temperature load is realized, which can significantly reduce the coal consumption rate and improve the power generation efficiency. It has great application value in energy conversion control
Keywords Main steam temperature,Load tracking,Fuel-water ratio,Water spray cooling,Improved sailfish optimization,ISFO-PID
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Energy Proceedings