Research on Excitation Estimation for Ocean Wave Energy Generators Based on Extended Kalman Filtering

Wave energy generation methods have significant energy costs. The implementation of sophisticated control techniques in wave energy generators can lower the cost of power generation by optimizing the energy recovered from wave energy converters (WECs). To determine control inputs, most control syste...

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Main Authors: Yuchen Zhang, Zhenquan Zhang, Jun Wang, Jian Qin, Shuting Huang, Gang Xue, Yanjun Liu
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/17/3/704
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author Yuchen Zhang
Zhenquan Zhang
Jun Wang
Jian Qin
Shuting Huang
Gang Xue
Yanjun Liu
author_facet Yuchen Zhang
Zhenquan Zhang
Jun Wang
Jian Qin
Shuting Huang
Gang Xue
Yanjun Liu
author_sort Yuchen Zhang
collection DOAJ
description Wave energy generation methods have significant energy costs. The implementation of sophisticated control techniques in wave energy generators can lower the cost of power generation by optimizing the energy recovered from wave energy converters (WECs). To determine control inputs, most control systems rely on knowledge of the wave excitation force, including information on past, present, and future excitation forces. For the excitation of WEC devices, wave excitation force can only be inferred and predicted because it is an unmeasurable quantity. One of the more widely used observers in wave excitation estimates at the moment is the Kalman filter, but its use is primarily restricted to linear Kalman filtering. The mooring system is an integral component of floating wave energy producers. The mooring force of the device is actually nonlinear; however, the majority of current studies on excitation estimates for wave energy producers based on Kalman filter methods employ an ideal motion model based on the linearization of the mooring force. This paper, in an attempt to make things more realistic, creates a WEC system with highly nonlinear mooring forces, suggests a way to build a wave excitation force estimator for a nonlinear WEC system using the extended Kalman filtering method, and assesses the impact of various factors, such as measurement noise, random phase, and the number of equal-energy methods dividing the frequency, on the accuracy of the wave excitation force estimate.
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spelling doaj.art-224a35574e104375a57d0a6b123c0d082024-02-09T15:11:40ZengMDPI AGEnergies1996-10732024-02-0117370410.3390/en17030704Research on Excitation Estimation for Ocean Wave Energy Generators Based on Extended Kalman FilteringYuchen Zhang0Zhenquan Zhang1Jun Wang2Jian Qin3Shuting Huang4Gang Xue5Yanjun Liu6Key Laboratory of High-Efficiency and Clean Mechanical Manufacture of Ministry of Education, Shandong University, Jinan 250061, ChinaInstitute of Marine Science and Technology, Shandong University, Qingdao 266237, ChinaInstitute of Marine Science and Technology, Shandong University, Qingdao 266237, ChinaInstitute of Marine Science and Technology, Shandong University, Qingdao 266237, ChinaInstitute of Marine Science and Technology, Shandong University, Qingdao 266237, ChinaKey Laboratory of High-Efficiency and Clean Mechanical Manufacture of Ministry of Education, Shandong University, Jinan 250061, ChinaKey Laboratory of High-Efficiency and Clean Mechanical Manufacture of Ministry of Education, Shandong University, Jinan 250061, ChinaWave energy generation methods have significant energy costs. The implementation of sophisticated control techniques in wave energy generators can lower the cost of power generation by optimizing the energy recovered from wave energy converters (WECs). To determine control inputs, most control systems rely on knowledge of the wave excitation force, including information on past, present, and future excitation forces. For the excitation of WEC devices, wave excitation force can only be inferred and predicted because it is an unmeasurable quantity. One of the more widely used observers in wave excitation estimates at the moment is the Kalman filter, but its use is primarily restricted to linear Kalman filtering. The mooring system is an integral component of floating wave energy producers. The mooring force of the device is actually nonlinear; however, the majority of current studies on excitation estimates for wave energy producers based on Kalman filter methods employ an ideal motion model based on the linearization of the mooring force. This paper, in an attempt to make things more realistic, creates a WEC system with highly nonlinear mooring forces, suggests a way to build a wave excitation force estimator for a nonlinear WEC system using the extended Kalman filtering method, and assesses the impact of various factors, such as measurement noise, random phase, and the number of equal-energy methods dividing the frequency, on the accuracy of the wave excitation force estimate.https://www.mdpi.com/1996-1073/17/3/704wave excitation forceestimationwave energy converterextended Kalman filter
spellingShingle Yuchen Zhang
Zhenquan Zhang
Jun Wang
Jian Qin
Shuting Huang
Gang Xue
Yanjun Liu
Research on Excitation Estimation for Ocean Wave Energy Generators Based on Extended Kalman Filtering
Energies
wave excitation force
estimation
wave energy converter
extended Kalman filter
title Research on Excitation Estimation for Ocean Wave Energy Generators Based on Extended Kalman Filtering
title_full Research on Excitation Estimation for Ocean Wave Energy Generators Based on Extended Kalman Filtering
title_fullStr Research on Excitation Estimation for Ocean Wave Energy Generators Based on Extended Kalman Filtering
title_full_unstemmed Research on Excitation Estimation for Ocean Wave Energy Generators Based on Extended Kalman Filtering
title_short Research on Excitation Estimation for Ocean Wave Energy Generators Based on Extended Kalman Filtering
title_sort research on excitation estimation for ocean wave energy generators based on extended kalman filtering
topic wave excitation force
estimation
wave energy converter
extended Kalman filter
url https://www.mdpi.com/1996-1073/17/3/704
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