Optimization Control Research Considering Energy-saving And Pro-environment Of Combined Desulfurization System For Circulating Fluidized Bed Unit

With the implementation of the ultra-low emission policy in our country,SO2 removal process for Circulating Fluidized Bed(CFB)unit is forced to change from the single furnace desulfurization mode to a two-stage joint mode.The new complex desulfurization system increases the control difficulty and the operation cost.This subject has introduced S02 removal process principles of the furnace desulfurization system and the outside furnace desulfurization system,analyzed its main factors affecting the desulfurization efficiency,and then determined its characteristics and input-output of control.On this basis,the paper studies the parameters identification of the control model,the design of the control system and the economy operating adjustment of the combined system.The concrete research content is as follows:1.Designing a model parameter identification algorithm based on Particle swarm optimization(PSO)algorithm with the adaptive weighting factor.The control models of the furnace desulfurization system and the outside furnace desulfurization system are established based on this algorithm using the field experimental data.The results show PSO algorithm has very good effect in the model parameter identification.2.Raising the incremental adaptive compensation control strategy and its improved algorithm.The simulation control system using the desulfurization system model is built to prove the control effect of the strategy compared with the traditional PID control method and the fuzzy control method.The simulation results show the strategy not only has a good dynamic and steady-state performance,but also has a strong anti-interference and adaptability model ability.3.The energy and material consumption models of the furnace desulfurization system and the outside furnace desulfurization system are made by using field operating data.And then the operating cost mathematical model in an hour of the combined desulfurization system can be got.Boundary conditions are set up based on the actual operation data and design parameters.4.Designing a constrained function optimization algorithm based on improved particle swarm optimization algorithm.It is used to solve the the operating cost mathematical model.Then the optimization parameters,such as the S02 concentration of the absorber inlet and the removing share between the two desulfuration Systems,can be obtained as the operating cost is minimum in two cases of the different load and the different coal sulfur content.It can be used to adjust the setting point of the combined desulfurization control system dynamically,witch makes the combined desulfurization system more economical.In the new stage of the ultra low emission,the research findings of this project provide a theoretical basis for automation,intelligence and economical operation of the combined desulfurization system.