The Application of Association Rules in Boiler Operation Optimization based on Organizational Evolutionary

Author

Gu Junjie ; Sun Qunli ; Gao Daming

Author_Institution

Sch. of Energy & Power Eng., North China Electr. Power Univ., Baoding

fYear

2009

fDate

27-31 March 2009

Firstpage

1

Lastpage

4

Abstract

Complicated on linear relationships exist among many data in the real-time control-process of large power plant. And data-mining technology could And knowledge, analyze parameters and adjust them. This paper ascertained target-value by means of data mining, which supported energy-loss analysis. The paper introduced relative theory on data mining, studied and applied target-value model of thermal supervised parameters in the way of Organizational Evolutionary Algorithm. Across analyze real-time operating data of thermal units, and mined the target-value models for main supervised parameters of boiler. The results supply a new idea and effective method for target-value models.

Keywords

boilers; control engineering computing; data mining; evolutionary computation; optimisation; association rules; boiler operation optimization; data-mining technology; energy-loss analysis; organizational evolutionary algorithm; real-time control-process; relative theory; target-value model; thermal supervised parameters; Association rules; Boilers; Data analysis; Data mining; Databases; Flowcharts; Itemsets; Power engineering and energy; Power generation; Sun;

fLanguage

English

Publisher

ieee

Conference_Titel

Power and Energy Engineering Conference, 2009. APPEEC 2009. Asia-Pacific

Conference_Location

Wuhan

Print_ISBN

978-1-4244-2486-3

Electronic_ISBN

978-1-4244-2487-0

Type

conf

DOI

10.1109/APPEEC.2009.4918866

Filename

4918866