The Optimizing Control of the Operation Voltage for Electrostatic Precipitator Based on Intellective Method

Author

Li, Da-Zhong ; Tian, Li ; Liu, Shu-ping

Author_Institution

Dept. of Autom., North China Electr. Power Univ., Baoding

fYear

2006

fDate

13-16 Aug. 2006

Firstpage

247

Lastpage

251

Abstract

For the problems of dust discharging concentration and power consumption in power plants, a new optimizing control method on the whole was presented to improve the performance of the electrostatic precipitator. The corona power model was identified by least-squares method and dust concentration of the outlet was represented by the neural network model. Based on this, the operation voltage optimization was realized by GA. Simulation results show that this control method can not only ensure the collection efficiency but also save energy

Keywords

electrostatic precipitators; genetic algorithms; least squares approximations; neural nets; power consumption; power engineering computing; power generation control; power plants; voltage control; corona power model; dust discharge concentration; electrostatic precipitator; genetic algorithms; intellective method; least-square method; neural network model; operation voltage optimization; optimizing control; power consumption; power plant; Automatic voltage control; Control systems; Corona; Cybernetics; Electrodes; Electrostatic precipitators; Energy consumption; Equations; Fluid flow; Machine learning; Optimization methods; Power generation; Power supplies; Voltage control; Electrostatic precipitator; Intellective method; Operation voltage; Optimizing control;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2006 International Conference on

Conference_Location

Dalian, China

Print_ISBN

1-4244-0061-9

Type

conf

DOI

10.1109/ICMLC.2006.258962

Filename

4028067