Abstract：Selection of catalytic reduction SCR denitrification system is the most important denitrification technology in thermal power plants. Because of its large time delay, large inertia, system interference and model variability, it is of great significance to design an optimization strategy that can meet the system control index. This paper draws on the research results of predecessors in the application of predictive control in SCR denitrification system and combines PSO optimization algorithm to overcome the disadvantage of difficult parameter tuning of predictive controller in the use process, so that the predictive controller can achieve optimal control. Finally, the simulation analysis of a 600MW unit's SCR denitrification system object verifies the adaptability and superiority of the algorithm.
崔海东. 基于粒子群预测优化算法的选择性催化还原脱硝系统仿真研究[J]. 电气技术, 2019, 20(3): 37-41.
Cui Haidong. Simulation of SCR denitrification system based on PSO predictive optimization. Electrical Engineering, 2019, 20(3): 37-41.
2019, Vol. 20 
