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Title: Wave tank and bench-top control testing of a wave energy converter

Abstract

An increasing number of experiments are being conducted to study the design and performance of wave energy converters. Often in these tests, a real-time realization of prospective control algorithms is applied in order to assess and optimize energy absorption as well as other factors. This paper details the design and execution of an experiment for evaluating the capability of a model-scale WEC to execute basic control algorithms. Model-scale hardware, system, and experimental design are considered, with a focus on providing an experimental setup capable of meeting the dynamic requirements of a control system. To more efficiently execute such tests, a dry bench testing method is proposed and utilized to allow for controller tuning and to give an initial assessment of controller performance; this is followed by wave tank testing. The trends from the dry bench test and wave tank test results show good agreement with theory and confirm the ability of a relatively simple feedback controller to substantially improve energy absorption. Additionally, the dry bench testing approach is shown to be an effective and efficient means of designing and testing both controllers and actuator systems for wave energy converters.

Authors:
 [1]; ORCiD logo [1];  [1];  [1]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
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:
1507402
Report Number(s):
SAND2019-3344J
Journal ID: ISSN 0141-1187; 673788
Grant/Contract Number:  
AC04-94AL85000
Resource Type:
Accepted Manuscript
Journal Name:
Applied Ocean Research
Additional Journal Information:
Journal Volume: 86; Journal Issue: C; Journal ID: ISSN 0141-1187
Country of Publication:
United States
Language:
English
Subject:
16 TIDAL AND WAVE POWER

Citation Formats

Bacelli, Giorgio, Spencer, Steven J., Patterson, David C., and Coe, Ryan G.. Wave tank and bench-top control testing of a wave energy converter. United States: N. p., 2019. Web. doi:10.1016/j.apor.2018.09.009.
Bacelli, Giorgio, Spencer, Steven J., Patterson, David C., & Coe, Ryan G.. Wave tank and bench-top control testing of a wave energy converter. United States. doi:10.1016/j.apor.2018.09.009.
Bacelli, Giorgio, Spencer, Steven J., Patterson, David C., and Coe, Ryan G.. Wed . "Wave tank and bench-top control testing of a wave energy converter". United States. doi:10.1016/j.apor.2018.09.009.
@article{osti_1507402,
title = {Wave tank and bench-top control testing of a wave energy converter},
author = {Bacelli, Giorgio and Spencer, Steven J. and Patterson, David C. and Coe, Ryan G.},
abstractNote = {An increasing number of experiments are being conducted to study the design and performance of wave energy converters. Often in these tests, a real-time realization of prospective control algorithms is applied in order to assess and optimize energy absorption as well as other factors. This paper details the design and execution of an experiment for evaluating the capability of a model-scale WEC to execute basic control algorithms. Model-scale hardware, system, and experimental design are considered, with a focus on providing an experimental setup capable of meeting the dynamic requirements of a control system. To more efficiently execute such tests, a dry bench testing method is proposed and utilized to allow for controller tuning and to give an initial assessment of controller performance; this is followed by wave tank testing. The trends from the dry bench test and wave tank test results show good agreement with theory and confirm the ability of a relatively simple feedback controller to substantially improve energy absorption. Additionally, the dry bench testing approach is shown to be an effective and efficient means of designing and testing both controllers and actuator systems for wave energy converters.},
doi = {10.1016/j.apor.2018.09.009},
journal = {Applied Ocean Research},
number = C,
volume = 86,
place = {United States},
year = {2019},
month = {3}
}

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This content will become publicly available on March 13, 2020
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