Title :
Constrained Optimization of Combustion at a Coal-Fired Utility Boiler Using Hybrid Particle Swarm Optimization with Invasive Weed
Author :
Zhao, Huan ; Wang, Pei-hong ; Peng, Xianyong ; Qian, Jin ; Wang, Quan
Author_Institution :
Sch. of Energy & Environ., Southeast Univ., Nanjing, China
Abstract :
In order to meet the requirement of high efficiency and low NOx emission combustion of coal-fired boiler, two constrained optimization objectives were designed based on the practical requirement, the one was that maximization of boiler efficiency under NOx emission constraint, and the other one was that minimization of NOx emission under a good boiler performance. Considering the complexity of response characteristics modeling about efficiency and NOx emission, a hybrid particle swarm optimization with invasive weed (IW-PSO) was proposed to optimize the constrained objective functions. In IW-PSO, particle swarm optimization (PSO) and invasive weed optimization (IWO) were integrated in parallel form, and after some iteration, IWO was considered to assist PSO. And in the process of optimizing, variational optimization objective values were tracked by inspection of the results conducted previously. The optimized results indicate that the proposed method can effectively control NOx emission and improve boiler efficiency for different constrained objectives.
Keywords :
air pollution; boilers; combustion; particle swarm optimisation; boiler efficiency maximization; coal-fired utility boiler; constrained optimization; emission minimization; hybrid particle swarm optimization; invasive weed optimization; low emission combustion; variational optimization; Boilers; Combustion; Constraint optimization; Design for experiments; Design optimization; Flue gases; Humans; Inspection; Particle swarm optimization; Production; IW-PSO; IWO; NOx; PSO; boiler efficiency; constraited optimization;
Conference_Titel :
Energy and Environment Technology, 2009. ICEET '09. International Conference on
Conference_Location :
Guilin, Guangxi
Print_ISBN :
978-0-7695-3819-8
DOI :
10.1109/ICEET.2009.143