DocumentCode
2846760
Title
Optimization on Seawater Desulfurization Efficiency Based on LSSVM-GA
Author
Ding-ping, Liu ; Xiao-wei, Li
Author_Institution
Coll. of Electr. Power, South China Univ. of Technol., Guangzhou, China
Volume
2
fYear
2010
fDate
13-14 Oct. 2010
Firstpage
29
Lastpage
32
Abstract
Seawater flue gas Desulfurization (SFGD) was adopted in many coal-fired power plants of littoral for its low cost and high desulfurization efficiency. Operating Parameters would seriously affect SFGD efficiency, the desulfurization efficiency can be improved by adjusting reasonable parameters. this paper applied Least Square Support Machine (LSSVM) to build the studying model of seawater desulfurization efficiency With a seawater desulfurization system of a 1000MW thermal power plant, through analyzing the influencing factors. The input parameters of the model were sulfur dioxide concentration at flue gas inlet, net flue gas flow & temperature, electric current of water booster pump, seawater flow & temperature of the absorption tower inlet. Seawater flue gas desulfurization efficiency was used as output of the model. Then through using the method of genetic algorithm (GA) to optimize the seawater desulfurization efficiency, the research obtained the optimizing and adjusting tactics, which can be used to guide power plant desulfurization operation adjustment. It was proved in the field, that the desulfurization efficiency had been improved for using the value of adjustment.
Keywords
flue gas desulphurisation; genetic algorithms; least squares approximations; power engineering computing; steam power stations; support vector machines; LSSVM-GA; SFGD efficiency; coal-fired power plants; genetic algorithm; least square support machine; optimization; power 1000 MW; power plant desulfurization operation adjustment; seawater desulfurization efficiency; seawater flue gas desulfurization; sulfur dioxide concentration; water booster pump; Analytical models; Gallium; Genetic algorithms; Mathematical model; Optimization; Power generation; Support vector machines; GA; LSSVM; SFGD; desulfurization efficiency; optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent System Design and Engineering Application (ISDEA), 2010 International Conference on
Conference_Location
Changsha
Print_ISBN
978-1-4244-8333-4
Type
conf
DOI
10.1109/ISDEA.2010.345
Filename
5743374
Link To Document