660 MW火电机组全工况下凝结水节流动态模型的研究OA

In order to solve the problem that it is difficult to combine accuracy,rapidity and generalization of condensate throttling models in thermal power units,a hybrid modeling method that combines mechanism modeling and data-driven modeling is proposed.The dynamic effect of condensate throttling on the internal pressure of the deaerator is deeply analyzed,and the parameter identification technology is introduced.A complex mechanism model with high accuracy is established based on the dynamic and static characteristics of the condensate throttling system.Under the premise of ensuring the accuracy of the model,with the help of data-driven methods,the relationship between a certain complex variables in the complex module is found,which reduces the complexity of the model and improves the rapidity of the model.The particle swarm optimization(PSO)algorithm is used to identify the unknown parameters in the model under different operating conditions and improve the generalization of the model according to the proposed fitness function about load,deaerator volume and pressure deviation.The simulation results show that the evaluation indexes such as root mean square error(RMSE)and Pearson correlation coefficient of the present model can perform well under 260 MW and 450 MW operating conditions.It proves that the present model has high accuracy,rapidity and generalization.