Research On Modeling And Optimal Control Of Desulfurization Absorption Tower

With the rapid development of the national economy,the social demand for electricity is increasing day by day.At the same time,the renewable energy power generation has the advantages of energy conservation and environmental protection,and has been vigorously developed.However,due to its own output uncertainty brings challenges to the stable operation of the power grid.Therefore,in the process of the construction of new power system,coal-fired generating units are still dominant in the power generation market.But pollution from coal-fired power generation is one of the main causes of air pollution.To that end,the country has issued the latest standards for pollutant emissions from coal-fired power plants.In order to respond to the national policy and achieve ultra-low emission of pollutants,various coal-fired power plants have carried out ultra-clean emission technology transformation.As SO2 is the main component of pollutants,how to control the emission concentration of SO2 stably and make the desulfurization system run efficiently and economically has become an urgent problem for the desulfurization control system of thermal power units.In order to achieve stable control of SO2 emission,the control aspects of the desulfurization system need to be optimized,and the establishment of an accurate system model is a prerequisite for achieving control optimization.This paper takes limestone-gypsum wet flue gas desulfurization system as the research object,and on the basis of introducing the process flow and desulfurization principle of the desulfurization system,the main control demands of the current desulfurization system are clarified.According to the control requirements,starting from the mechanism of desulfurization,the model structure is established according to the main factors affecting the controlled object and the operation characteristics of the controlled object.A particle swarm algorithm incorporating the cuckoo algorithm is used to identify the model,and a model with slurry pH and outlet SO2 concentration as output variables is obtained respectively.The precision of the model obtained from the identification is good,which verifies the effectiveness of the improved algorithm and the applicability of the model.The desulfurization system is a complex control system with large inertia,pure latency,nonlinearity and time variability,and it is difficult to achieve optimal operation by relying only on traditional single-loop PID control.In this paper,an improved control strategy is proposed by adding a flow-regulated subloop,using the generalized predictive control algorithm as the main controller algorithm,while using the flue gas side disturbance as a feedforward and adding a differential term of the feedback value in the feedback channel to form a cascaded feedforward-feedback composite control system.The proposed improved control strategy is simulated and compared with the conventional PID control.The results show that the generalized predictive control has better control performance than the conventional PID control,improves the dynamic performance and steady-state performance of the system,and provides a feasible solution for the optimal control of the wet desulfurization system of coal-fired power plants.