Non-linear model building and optimizing of SRG in wave power generation system

Author

Wen-ping, Xiao ; Jia-wei, Ye ; Xiao-gang, Hu

Author_Institution

South China Univ. of Technol., Guangzhou

fYear

2009

fDate

25-27 May 2009

Firstpage

535

Lastpage

537

Abstract

Wave power generation is a prospective technology to provide clean and renewable energy. In the wave power generation system, switched reluctance generator (SRG) is a leading technology for energy conversion devices. A novel nonlinear BP neural network model is given to ensure that the SRG can response to the wave change more quickly and more efficiently. During the training course, several algorithm performances were compared. And the generalization of the SRG model has been verified.

Keywords

direct energy conversion; neural nets; power engineering computing; reluctance generators; wave power generation; energy conversion devices; nonlinear BP neural network model; nonlinear model building; renewable energy; switched reluctance generator; wave power generation system; Batteries; Marine technology; Ocean temperature; Ocean waves; Power generation; Power generation economics; Power system dynamics; Power system modeling; Reluctance generators; Renewable energy resources; BP neural network; nolinear model; switched reluctance generator; wave power;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on

Conference_Location

Xi´an

Print_ISBN

978-1-4244-2799-4

Electronic_ISBN

978-1-4244-2800-7

Type

conf

DOI

10.1109/ICIEA.2009.5138263

Filename

5138263