Title :
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
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;
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
DOI :
10.1109/ICIEA.2009.5138263
