Probability-Based Binary Particle Swarm Optimization Algorithm and Its Application to WFGD Control

Sulfur dioxide is an air pollutant and an acid rain precursor. Coal-fired power generating plants are major sources of sulfur dioxide, so the limestone-gypsum wet flues gas desulphurization (WFGD) technology has been widely used in thermal power plant in China nowadays to reduce the emission of sulfur dioxide and protect the environment. The absorber slurry pH value control is very important for limestone-gypsum WFGD technique since it directly determine the desulphurization performance and the quality of product. However, it is hard to achieve the satisfactory adjustment performance for the traditional PID controller because of the complexity of the absorber slurry pH control. To tackle this problem, a novel probability-based binary particle swarm optimization (PBPSO) is proposed to tuning the PID parameters. The simulation results show PBPSO is valid and outperform the traditional binary PSO algorithm in terms of easy implementation and global optimal search ability. And it also presents that the proposed PBPSO algorithm can search the optimal PID parameters and achieves the expected control performance with PID controller by constructing the proper fitness function of PID tuning.