DocumentCode
669540
Title
Estimation of incident wave of AWS-based wave energy converter using extended Kalman filter
Author
Jae Seung Kim ; Jung Yoon Kim ; Jin Bae Park
Author_Institution
Dept. of Electr. & Electron. Eng., Yonsei Univ., Seoul, South Korea
fYear
2013
fDate
20-23 Oct. 2013
Firstpage
1411
Lastpage
1416
Abstract
This paper presents a novel method of estimating ocean waves by measuring current outputs from the Archimedes Wave Swing (AWS) wave energy converter (WEC). The wave period and height are crucial information to maximize the power output from the AWS. However, since the AWS is installed on the seabed, additional sensors and buoys are required to obtain the ocean wave information. The extended Kalman filter (EKF) is applied to obtain the states of the ocean wave by measuring the generator current in the α - β domain. As the EKF requires the Jacobian matrix of the system dynamic equations for the system matrix, simplified hydrodynamics of the floater including the Froude-Krylov excitation force and the domain α - β voltage equation of the generator is derived to develop the mathematical model of the AWS. In order to verify the performance of the estimator, a numerical simulation is performed and presented and it shows great agreement with the actual motion.
Keywords
Kalman filters; numerical analysis; ocean waves; wave power generation; Archimedes Wave Swing; Froude-Krylov excitation force; Jacobian matrix; buoys; extended Kalman filter; incident wave estimation; mathematical model; numerical simulation; ocean wave information; ocean waves; seabed; sensors; wave energy converter; Jacobian matrices; AWS; Extended Kalman Filter; Ocean Wave; WEC; Wave Energy Converter;
fLanguage
English
Publisher
ieee
Conference_Titel
Control, Automation and Systems (ICCAS), 2013 13th International Conference on
Conference_Location
Gwangju
ISSN
2093-7121
Print_ISBN
978-89-93215-05-2
Type
conf
DOI
10.1109/ICCAS.2013.6704106
Filename
6704106
Link To Document