title: [The utility boiler low NOx combustion optimization based on ANN and simulated annealing algorithm].
abstract: With the developing restrict environmental protection demand, more attention was paid on the low NOx combustion optimizing technology for its cheap and easy property. In this work, field experiments on the NOx emissions characteristics of a 600 MW coal-fired boiler were carried out, on the base of the artificial neural network (ANN) modeling, the simulated annealing (SA) algorithm was employed to optimize the boiler combustion to achieve a low NOx emissions concentration, and the combustion scheme was obtained. Two sets of SA parameters were adopted to find a better SA scheme, the result show that the parameters of T0 = 50 K, alpha = 0.6 can lead to a better optimizing process. This work can give the foundation of the boiler low NOx combustion on-line control technology.
authors.affiliation: Clean Energy and Environment Engineering Key Lab of MOE, Institute for Thermal Power Engineering, Zhejiang University, Hangzhou 310027, China. zhouhao@cmee.zju.edu.cn
authors.forename: Hao
authors.initials: H
authors.lastname: Zhou
authors.forename: Xinping
authors.initials: X
authors.lastname: Qian
authors.forename: Ligang
authors.initials: L
authors.lastname: Zheng
authors.forename: Anxin
authors.initials: A
authors.lastname: Weng
authors.forename: Kefa
authors.initials: K
authors.lastname: Cen
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006361:Heating; D016571:Neural Networks, Computer; D009589:Nitrogen Oxides / Q000737:chemistry*
chemical_list: D009589:Nitrogen Oxides