Optimization of desulphurization control system based on model predictive control algorithm

Abstract

In order to improve the automatic control level of wet desulphurization system in thermal power plant， aiming at the problems of poor control effect， low automation degree， and inability to control the SO2 concentration of the original automatic control system of No.6 desulphurization unit in Zhejiang Wenzhou Power Plant， an advanced control scheme based on multivariable model predictive control algorithm is designed. The concentration of SO2 and pH value of absorber slurry are both listed as controlled variables， and a linear variable parameter model of desulphurization system with boiler load as scheduling variable is established. The desulphurization control scheme is preliminarily verified in Simulink simulation， and then applied in the desulphurization control optimization of No.6 unit. The actual operation effects show that the pH value can also be stably controlled within the allowable range by this advanced desulphurization control system， and the deviation between the hourly mean value of SO2 concentration and the set value is within ±2 mg/m³， which ensures the safe and efficient operation of the desulphurization equipment.

Keywords

• automatic control of flue gas wet desulphurization system
• model predictive control
• linear variable parameter model
• so2 concentration control
• ph value control of absorber slurry