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Title: System Identification of a Heaving Point Absorber: Design of Experiment and Device Modeling

Abstract

Empirically based modeling is an essential aspect of design for a wave energy converter. These models are used in structural, mechanical and control design processes, as well as for performance prediction. The design of experiments and methods used to produce models from collected data have a strong impact on the quality of the model. This study considers the system identification and model validation process based on data collected from a wave tank test of a model-scale wave energy converter. Experimental design and data processing techniques based on general system identification procedures are discussed and compared with the practices often followed for wave tank testing. The general system identification processes are shown to have a number of advantages. The experimental data is then used to produce multiple models for the dynamics of the device. These models are validated and their performance is compared against one and other. Furthermore, while most models of wave energy converters use a formulation with wave elevation as an input, this study shows that a model using a hull pressure sensor to incorporate the wave excitation phenomenon has better accuracy.

Authors:
; ; ;
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
OSTI Identifier:
1411883
Alternate Identifier(s):
OSTI ID: 1411882
Report Number(s):
SAND2017-1386J; SAND2017-3272J
Journal ID: ISSN 1996-1073; ENERGA; 656111
Grant/Contract Number:  
AC04-94AL85000
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Energies (Basel)
Additional Journal Information:
Journal Name: Energies (Basel); Journal Volume: 10; Journal Issue: 4; Journal ID: ISSN 1996-1073
Publisher:
MDPI AG
Country of Publication:
United States
Language:
English
Subject:
13 HYDRO ENERGY

Citation Formats

Bacelli, Giorgio, Coe, Ryan, Patterson, David, and Wilson, David. System Identification of a Heaving Point Absorber: Design of Experiment and Device Modeling. United States: N. p., 2017. Web. doi:10.3390/en10040472.
Bacelli, Giorgio, Coe, Ryan, Patterson, David, & Wilson, David. System Identification of a Heaving Point Absorber: Design of Experiment and Device Modeling. United States. doi:10.3390/en10040472.
Bacelli, Giorgio, Coe, Ryan, Patterson, David, and Wilson, David. Sat . "System Identification of a Heaving Point Absorber: Design of Experiment and Device Modeling". United States. doi:10.3390/en10040472. https://www.osti.gov/servlets/purl/1411883.
@article{osti_1411883,
title = {System Identification of a Heaving Point Absorber: Design of Experiment and Device Modeling},
author = {Bacelli, Giorgio and Coe, Ryan and Patterson, David and Wilson, David},
abstractNote = {Empirically based modeling is an essential aspect of design for a wave energy converter. These models are used in structural, mechanical and control design processes, as well as for performance prediction. The design of experiments and methods used to produce models from collected data have a strong impact on the quality of the model. This study considers the system identification and model validation process based on data collected from a wave tank test of a model-scale wave energy converter. Experimental design and data processing techniques based on general system identification procedures are discussed and compared with the practices often followed for wave tank testing. The general system identification processes are shown to have a number of advantages. The experimental data is then used to produce multiple models for the dynamics of the device. These models are validated and their performance is compared against one and other. Furthermore, while most models of wave energy converters use a formulation with wave elevation as an input, this study shows that a model using a hull pressure sensor to incorporate the wave excitation phenomenon has better accuracy.},
doi = {10.3390/en10040472},
journal = {Energies (Basel)},
number = 4,
volume = 10,
place = {United States},
year = {Sat Apr 01 00:00:00 EDT 2017},
month = {Sat Apr 01 00:00:00 EDT 2017}
}

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